Integrated system for safe intracranial administration of cells

Abstract

To provide an integrated system for safe intracranial administration of cells.SOLUTION: The present disclosure provides a method for identifying a site for administering cells in cell therapy for central nervous system damage in a subject, the method comprising: A) a step for acquiring image data of at least part of the subject's brain, with an imaging device; B) a step for obtaining information on the subject's brain, with a computer device in communication with the imaging device; C) a step for using the image data and data pertaining to the subject's brain acquired by the computer device to depict motor fibers; D) a step for identifying a damaged location where motor fibers have suffered damage, with the computer device, the step involving identifying a portion where motor fiber run-data is lower than another portion and identifying the lower portion as being motor fibers that have suffered damage; E) a step for using the computer device to select, as a site of administration, a safe region near the damaged location; and F) a step for outputting the selected site of administration.SELECTED DRAWING: Figure 1A

Description

[Technical Field]

[0001] The present disclosure relates to a technique useful in cell therapy for central nervous system disorders (such as cerebral infarction and cerebral hemorrhage). [Background technology]

[0002] Cell therapy is expected to be a treatment for central nervous system disorders (such as cerebral infarction and cerebral hemorrhage). One possible administration method is intracerebral administration, which has the advantage of being able to clear the blood-brain barrier and deliver a larger amount of cells to the affected area compared to intravascular (venous or arterial) administration. However, a problem with intracerebral administration is the risk of creating new brain damage. To avoid this, it is necessary to (1) determine the cell administration site (avoiding critical areas), (2) determine the area through which the administration needle passes (avoiding cerebral sulci and blood vessels), and (3) prevent migration of cells into the brain due to cerebrospinal fluid leakage. There are no existing technologies disclosed for these integrated systems related to cell therapy. Summary of the Invention [Means for solving the problem]

[0003] In this disclosure, the present inventors provide a new surgical and administration method, which is mainly characterized by the following:

[0004] (1) Deciding the injection site: To determine the injection site, motor fibers are visualized in advance using brain MRI. The damaged areas of the visualized motor fibers are identified (if the brain is severely damaged and the motor fibers cannot be visualized, healthy motor fibers on the contralateral side are used as a reference). The injection site is selected as close as possible to the damaged area (within a 1.5 cm radius) and is not thought to play an important role in neurological function.

[0005] (2) Determining the area through which the injection needle will pass: A brain MRI is used in advance to identify the large veins on the brain surface, and the needle is then passed through the area to avoid penetrating the area. Furthermore, once the needle has been inserted into the brain, a path is selected that will not enter the cerebral sulci (entering the cerebral sulci could damage the small veins and arteries running along the surface of the brain). This method can be described as a surgical method, and can also be described as a program invention.

[0006] (3) Methods for preventing cerebrospinal fluid leakage: When the arachnoid membrane on the surface of the brain is incised, cerebrospinal fluid leaks out. Because the brain appears to float in the cerebrospinal fluid, brain shift (sinking) occurs over time. To prevent this, before incising the arachnoid membrane, an electrosurgical instrument such as bipolar coagulating forceps can be used to coagulate and adhere the arachnoid membrane and pia mater on the surface of the brain at the planned puncture site. This prevents the brain from shifting when inserting the needle. This is particularly important when multiple punctures are required.

[0007] The present invention provides the following items. (Item 1) A method for identifying a site to administer cells in cell therapy for a central nervous system disorder in a subject, the method comprising: A) acquiring image data of at least a portion of the subject's brain with an imaging device; B) obtaining information about the subject's brain by a computer device in communication with the imaging device; C) using the computer device to delineate motor fibers using the acquired image data and data related to the subject's brain; D) a step of identifying a location of the motor fiber where the motor fiber is damaged by the computer device, in which a portion where the running data of the motor fiber is lower than other portions is identified, and the lower portion is identified as the motor fiber that is damaged; E) selecting, by the computing device, a safe zone near the lesion location as an administration site; F) outputting the selected administration site as a graphical representation; The method includes: (Item 2) 10. The method of any of the preceding items, wherein the imaging device comprises an MRI, CT, ultrasound, or angiography device. (Item 3) Item 2. The method according to item 1, wherein the motor fiber running data is represented in a DTI image. (Item 4) The method according to any of the preceding items, wherein the running data is represented by a fractional anisotropy value (FA value) in a DTI image. (Item 5) The method according to any of the preceding items, wherein the decrease in running data in the area where the running data of the motor fibers is lower than in other areas is a decrease of at least 50% or more. (Item 6) 10. The method of claim 1, wherein the safety zone includes a location within a radius of about 1.5 cm from the obstacle location. (Item 7) A method according to any of the preceding items, wherein the safe zone is selected to be within a radius of approximately 1.5 cm from the lesion location and is a region that is not considered to play a significant role in neural function. (Item 8) 10. The method of any of the preceding items, wherein the administration site is positioned caudal to the brain relative to the location of the lesion. (Item 9) 10. The method of any of the preceding items, wherein the administration site is determined for each lesion location. (Item 10) The method of any of the preceding items, wherein the administration site is one or more relative to the lesion location. (Item 11) A method according to any of the preceding items, characterized in that, when data on the course of the motor fiber cannot be obtained, the damaged area is identified by referring to healthy motor fibers on the contralateral side. (Item 12) The selection may be By comparing the DWI image and the T2 image, the area damaged by the current cerebral infarction is identified and excluded from selection. Areas that were negative on DWI but showed significant edema on T2 and FLAIR images were also excluded from the selection. Depicting motor fibers in the DTI region and deselecting the region of the depicted motor fibers; 10. The method of any of the preceding items. (Item 13) In the T2 weighted image and FLAIR image of the MRI, a) Areas of high signal intensity in FLAIR images plotted with signal intensity, and b) A method according to any of the preceding items, wherein an area that satisfies both of the high signal areas in a T2-weighted image plotted by signal intensity is identified as edema. (Item 14) [1] When tractography is depicted in the DTI image, (a) Normal brain tissue located as close as possible to the area where the tractography is torn or weakened in the DTI image (usually a white area on DWI in the case of acute cerebral infarction, a high signal on T2 / FLAIR in the case of chronic cerebral infarction, a high signal on CT in the case of acute trauma or cerebral hemorrhage, and a high signal on T2 / FLAIR in the case of chronic trauma or cerebral hemorrhage), and (b) It is a safe location (a location that will cause minimal damage even if bleeding or an allergic reaction occurs: a location other than the area generally referred to as the eloquent area* of an AVM). It satisfies the condition that (c) If necessary, avoid high signal areas on the T2 / FLAIR images and examine the area as close to them as possible. Select a site as the administration site that satisfies the following conditions, or [2] If tractography is not visualized in the DTI image, (aa) The ROI for tractography (usually nerve fibers passing through three points: the precentral gyrus, the posterior limb of the internal capsule, and the pons) is set by referring to the tractography obtained by performing the precentral gyrus, the posterior limb of the internal capsule, and the pons separately, and selecting motor fibers that are normally expected in humans, or If (bb) or (aa) does not work, estimate the course of the motor fibers by referring to the contralateral tractography, and estimate the area where the motor fibers are torn at the point where the damaged area shown as high signal intensity on the DWI image in the acute phase or the damaged area shown as low signal intensity on the T2 / FLAIR image in the chronic phase overlaps with the estimated tractography pass point, and perform [1]. 10. The method according to any of the preceding items, characterized in that (Item 15) A method for identifying a passage area of ​​an administration needle for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: (A) acquiring image data of at least a portion of the brain of the subject using an imaging device; (B) obtaining information about the subject's brain by a computer device in communication with the imaging device; (C) depicting blood vessels from the acquired image data and information about the subject's brain by the computer device; (D) identifying, by the computing device, a path extent that does not penetrate the blood vessel; (E) using the computer device to identify a non-invasive sulcal area that does not extend beyond the sulcus after inserting a needle into the brain; (F) setting a route within the overlapping range of the route ranges calculated in (D) and (E) by the computer device; (G) outputting the set route as a graphic display; A method that encompasses (Item 16) Item 17. The method according to Item 15, wherein the blood vessels include large veins draining from the surface of the brain into the superior sagittal sinus. The method according to any of the preceding items, wherein the identification is performed by determining that a high signal intensity area on a gadolinium-enhanced T1 image is a blood vessel. (Item 18) The method of any of the preceding items, wherein the identification is achieved based on an MRI image by measuring at least one of DWI, T2, fluid-attenuated inversion-recovery (FLAIR), and DTI on the MRI image. (Item 19) 10. The method of any of the preceding items, wherein the identification is determined based on MRI images, with respect to the MRI images, in a sequence of (1) FLAIR images, (2) T2 images, and (3) gadolinium-enhanced T1 images. (Item 20) 10. The method of any of the preceding items, wherein the identification of the non-invasive sulcal pathway is achieved by reviewing T2-weighted and FLAIR images in MRI. (Item 21) In (E), 1) In FLAIR images plotting signal intensity, areas with low signal intensity, and 2) High signal intensity areas in T2-weighted images plotted by signal intensity The method according to any of the preceding items, wherein a region that satisfies both of the above is identified as a sulcus. (Item 22) 1. A method for preventing a cerebrospinal fluid leak in the brain of a subject, comprising: A) The step of cutting the dura mater on the surface of the brain. B) A step of coagulating and adhering the arachnoid membrane and pia mater on the surface of the brain at the planned puncture start site using an electrosurgical instrument, (a) until the arachnoid membrane becomes cloudy, or (b) until microvessels on the surface of the brain can no longer be identified by visual inspection of the arachnoid membrane or in an image displaying the arachnoid membrane, or (c) under conditions where the output power is set to an output power that has been confirmed to cause the arachnoid membrane to become cloudy, and adhering the arachnoid membrane to the pia mater. A method comprising: (Item 23) The method according to any of the preceding items, wherein the prevention of cerebrospinal fluid leakage in the brain is in cell therapy for a central nervous system disorder in the subject. (Item 24) The method of any of the preceding items, further comprising the step of C) administering to said subject cells in need thereof. (Item 25) 1. A system for preventing cerebrospinal fluid leak in the brain of a subject, comprising: A) A cutting tool for cutting the dura mater on the surface of the brain; B) An electrosurgical instrument configured to coagulate and adhere the arachnoid membrane and pia mater on the surface of the brain at the intended puncture start site, which is operated to coagulate and adhere the arachnoid membrane and pia mater (a) until the arachnoid membrane becomes opaque, or (b) until microvessels on the surface of the brain can no longer be identified by visual inspection of the arachnoid membrane or in an image displaying the arachnoid membrane, or (c) under conditions in which the output power is set to an output power that has been confirmed to cause the arachnoid membrane to become opaque; C) a sensor capable of detecting the opacity of the arachnoid membrane; A system including: (Item 26) A method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: i) acquiring image data of at least a portion of the subject's brain with an imaging device; ii) obtaining, by a computer device in communication with said imaging device, information about the subject's brain; iii) providing potential routes for administering the cells by the following steps: aa) selecting, by the computing device, a safe zone near the lesion location as an administration site; bb) identifying a route of administration to the selected administration site; cc) optionally selecting, by said computer device, an ablation location for passing an administration device for administering cells in the scalp; and iv) outputting the selected administration site as a graphical representation; The method includes: (Item 27) aa) is C) using the computer device to delineate motor fibers using the acquired image data and data related to the subject's brain; D) A step of identifying the location of the motor fiber injury by the computer device, in which a portion of the running data of the motor fiber where the amount of motor fiber is lower than other portions is identified, and the lower portion is identified as the motor fiber that is injured. E) selecting, by the computing device, a safe zone near the lesion location as an administration site; The method of any of the preceding items, including: (Item 28) The above bb) is (C) depicting blood vessels from the acquired image data and information about the subject's brain by the computer device; (D) identifying, by the computing device, a path extent that does not penetrate the blood vessel; (E) using the computer device to identify a non-invasive sulcal area that does not extend beyond the sulcus after inserting a needle into the brain; (F) setting a route within the overlapping range of the route ranges calculated in (D) and (E) by the computer device; The method of any of the preceding items, including: (Item 29) 10. The method of any of the preceding items, wherein the imaging device comprises an MRI, CT, ultrasound, or angiography device. (Item 30) 10. The method of any one of the preceding items, wherein the motor fiber trajectory data is represented in a DTI image. (Item 31) The method according to any of the preceding items, wherein the running data is represented by a fractional anisotropy value (FA value) in a DTI image. (Item 32) The method according to any of the preceding items, wherein the decrease in running data in the area where the running data of the motor fibers is lower than in other areas is a decrease of at least 50% or more. (Item 33) 10. The method of claim 1, wherein the safety zone includes a location within a radius of about 1.5 cm from the obstacle location. (Item 34) A method according to any of the preceding items, wherein the safe zone is selected to be within a radius of approximately 1.5 cm from the lesion location and is a region that is not considered to play a significant role in neural function. (Item 35) 10. The method of any of the preceding items, wherein the administration site is positioned caudal to the brain relative to the location of the lesion. (Item 36) 10. The method of any of the preceding items, wherein the administration site is determined for each lesion location. (Item 37) The method of any of the preceding items, wherein the administration site is one or more relative to the lesion location. (Item 38) A method according to any of the preceding items, characterized in that, when data on the course of the motor fiber cannot be obtained, the damaged area is identified by referring to healthy motor fibers on the contralateral side. (Item 39) The selection may be By comparing the DWI image and the T2 image, the area damaged by the current cerebral infarction is identified and excluded from selection. Areas that were negative on DWI but showed significant edema on T2 and FLAIR images were also excluded from the selection. Depicting motor fibers in the DTI region and deselecting the region of the depicted motor fibers; 10. The method of any of the preceding items. (Item 40) In the T2 weighted image and FLAIR image of the MRI, a) Areas of high signal intensity in FLAIR images plotted with signal intensity, and b) High signal intensity areas in T2-weighted images plotted with signal intensity The method of any of the preceding items, wherein a site that satisfies both of the above is identified as edema. (Item 41) [1] When tractography is depicted in the DTI image, (a) Normal brain tissue located as close as possible to the area where the tractography is torn or weakened in the DTI image (usually a white area on DWI in the case of acute cerebral infarction, a high signal on T2 / FLAIR in the case of chronic cerebral infarction, a high signal on CT in the case of acute trauma or cerebral hemorrhage, and a high signal on T2 / FLAIR in the case of chronic trauma or cerebral hemorrhage), and (b) It is a safe location (a location that will cause minimal damage even if bleeding or an allergic reaction occurs: a location other than the area generally referred to as the eloquent area* of an AVM). It satisfies the condition that (c) If necessary, avoid high signal areas on the T2 / FLAIR images and examine the area as close to them as possible. Select a site as the administration site that satisfies the following conditions, or [2] If tractography is not visualized in the DTI image, (aa) The ROI for tractography (usually nerve fibers passing through three points: the precentral gyrus, the posterior limb of the internal capsule, and the pons) is set by referring to the tractography obtained by performing the precentral gyrus, the posterior limb of the internal capsule, and the pons separately, and selecting motor fibers that are normally expected in humans, or If (bb) or (aa) does not work, estimate the course of the motor fibers by referring to the contralateral tractography, and estimate the area where the motor fibers are torn at the point where the estimated tractography passes through, overlaps with the damaged area shown as high signal intensity on the DWI image in the acute phase or the damaged area shown as low signal intensity on the T2 / FLAIR image in the chronic phase, and then perform [1]. 10. The method according to any of the preceding items, characterized in that (Item 42) 10. The method of any preceding item, wherein the blood vessels include large veins that drain from the surface of the brain into the superior sagittal sinus. (Item 43) The method according to any of the preceding items, wherein the identification is performed by determining that a high signal intensity area on a gadolinium-enhanced T1 image is a blood vessel. (Item 44) The method of any of the preceding items, wherein the identification is achieved based on an MRI image by measuring at least one of DWI, T2, fluid-attenuated inversion-recovery (FLAIR), and DTI on the MRI image. (Item 45) 10. The method of any of the preceding items, wherein the identification is determined based on MRI images, with respect to the MRI images, in a sequence of (1) FLAIR images, (2) T2 images, and (3) gadolinium-enhanced T1 images. (Item 46) 10. The method of any of the preceding items, wherein the identification of the non-invasive sulcal pathway is achieved by reviewing T2-weighted and FLAIR images in MRI. (Item 47) In (E), 1) In FLAIR images plotting signal intensity, areas with low signal intensity, and 2) High signal intensity areas in T2-weighted images plotted by signal intensity The method according to any of the preceding items, wherein a region that satisfies both of the above is identified as a sulcus. (Item 48) A method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: i) acquiring image data of at least a portion of the subject's brain with an imaging device; ii) obtaining, by a computer device in communication with said imaging device, information about the subject's brain; iii) providing potential routes for administering the cells by the following steps: a) optionally selecting, by the computer device, an ablation location for passing an administration device to administer cells in the scalp; b) selecting, with the computing device, an opening in the skull for passing the administration device to administer the cell therapy; c) using the computer device, identifying at least one brain pathway exclusion region selected from the group consisting of motor fibers, cerebral blood vessels, cerebral sulci, and functional areas using the acquired image data and data related to the subject's brain; d) selecting, by the computing device, a safe zone near the lesion location as an administration site; e) delineating an administration route between the opening and the administration site, the administration route being delineated including information about the brain pathway exclusion region, and optionally providing suitability information for the administration route from the information about the brain pathway exclusion region; and iv) outputting the selected administration site as a graphical representation; The method includes: (Item 49) 10. The method of any of the preceding items, wherein the imaging device comprises an MRI, CT, ultrasound, or angiography device. (Item 50) The above d) is C) using the computer device to delineate motor fibers using the acquired image data and data related to the subject's brain; D) a step of identifying a location of the motor fiber where the motor fiber is damaged by the computer device, in which a portion where the running data of the motor fiber is lower than other portions is identified, and the lower portion is identified as the motor fiber that is damaged; E) selecting, by the computing device, a safe zone near the lesion location as an administration site; The method of any of the preceding items, including: (Item 51) The method according to any of the preceding items, wherein in c), high signal intensity areas on gadolinium-enhanced T1 images are determined to be the cerebral blood vessels. (Item 52) In the above c), 1) In FLAIR images plotting signal intensity, areas with low signal intensity, and 2) High signal intensity areas in T2-weighted images plotted by signal intensity The method of any of the preceding items, wherein the areas filling both the sacs are identified as sulci. (Item 53) A method for predicting the probability of occurrence of an adverse effect of cell therapy on a central nervous system disorder in a subject, comprising: 1) inputting a data group indicating the administration position of cells and data on the occurrence of adverse effects of cell therapy for each administration position of the cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; 2) acquiring a data set indicative of the location of cell administration; 3) inputting the data set indicating the administration position of the cells obtained in 2) into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; A method that encompasses (Item 54) Item 54. The method according to Item 53, wherein the group of data indicating the administration position of the cells includes at least one of data on the distance between the administration position and the brain surface, the distance between the administration position and the lesion position, the distance between the administration position and the edema area, and whether the administration position is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 55) 56. The method according to Item 54 or 55, wherein the group of data indicating the administration position of the cells includes a combination of the distance between the administration position and the brain surface, the distance between the administration position and the lesion position, the distance between the administration position and the edema area, and whether the administration position is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 56) 56. The method according to any one of items 53 to 55, wherein the location of administration of the cells is identified by one or more methods of items 1 to 14. (Item 57) A method for predicting the probability of occurrence of an adverse effect of cell therapy on a central nervous system disorder in a subject, comprising: 1) inputting a data group indicating the area through which an injection needle for administering cells passes and data on adverse effects of cell therapy for each area through which the injection needle for administering cells passes into an artificial intelligence model as learning data, and allowing the artificial intelligence model to learn; 2) acquiring a data set indicating a passage area of ​​an injection needle for injecting cells; 3) inputting the data set obtained in 2) indicating the area through which the injection needle for injecting the cells passes into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; A method that encompasses (Item 58) Item 58. The method according to Item 57, wherein the group of data indicating the area through which the administration needle for administering the cells passes includes at least one of the distance between the brain surface just below the skin through which the administration needle passes and the skull, whether the area just below the insertion point of the administration needle is an eloquent area, whether there is a large vein just below the insertion point of the administration needle, whether the administration needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate, the distance between the cerebral sulcus and the administration needle, and the distance between the administration needle and a large blood vessel in the brain. (Item 59) Item 59. The method according to Item 57 or 58, wherein the group of data indicating the area through which the injection needle for administering the cells passes includes a combination of the distance between the skull and the brain surface just below the skin through which the injection needle passes, whether the area just below the injection point of the injection needle is an eloquent area, whether there is a large vein just below the injection point of the injection needle, whether the injection needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate, the distance between the cerebral sulcus and the injection needle, and the distance between the injection needle and a large blood vessel in the brain. (Item 60) 60. The method according to any one of items 57 to 59, wherein the location of administration of the cells is identified by one or more methods of items 15 to 25. (Item 61) A method for predicting the probability of occurrence of an adverse effect of cell therapy on a central nervous system disorder in a subject, comprising: 1) inputting a data group indicating the administration position of cells, a data group indicating the passage area of ​​an administration needle for administering cells to the administration position of cells, and data on adverse effects of cell therapy for each data group indicating the administration position of cells and the passage area of ​​an administration needle for administering cells to the administration position of cells, into an artificial intelligence model as learning data, and allowing the artificial intelligence model to learn; 2) acquiring a data group indicating a cell administration position and a data group indicating a passage area of ​​an administration needle for administering cells to the cell administration position; 3) inputting the data set indicating the administration position of the cells acquired in 2) and the data set indicating the passage area of ​​an administration needle for administering the cells to the administration position into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; A method that encompasses (Item 62) Item 62. The method according to Item 61, wherein the group of data indicating the administration position of the cells includes a combination of the distance between the administration position and the brain surface, the distance between the administration position and the lesion position, the distance between the administration position and the edema area, and whether the administration position is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 63) The data group showing the area through which the injection needle passes to inject the cells into the injection site of the cells includes the distance between the brain surface and the skull just below the skin through which the injection needle passes, the area just below the injection point of the injection needle is eloquent, 63. The method according to any one of items 61 and 62, comprising a combination of: whether the area is a cerebral sulcus; whether there is a large vein directly below the injection point of the administration needle; whether the administration needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate; the distance between the administration needle and the cerebral sulcus; and the distance between the administration needle and a large blood vessel in the brain. (Item 64) the data group indicating the administration position of the cells includes at least one of the following: a distance between the administration position and the brain surface; a distance between the administration position and the lesion position; a distance between the administration position and the edema area; and whether the administration position is other than a site called an eloquent area in a cerebral arteriovenous malformation (AVM); 64. The method according to any one of Items 61 to 63, wherein the group of data indicating the area through which the injection needle passes to inject the cells into the injection site includes at least one of the following: the distance between the brain surface just below the skin through which the injection needle passes and the skull; whether the area just below the injection point of the injection needle is an eloquent area; whether there is a large vein just below the injection point of the injection needle; whether the injection needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate; the distance between the cerebral sulcus and the injection needle; and the distance between the injection needle and a large blood vessel in the brain. (Item 65) 65. The method according to any one of Items 61 to 64, wherein the administration position of the cells and the passage area of ​​an administration needle for administering the cells to the administration position of the cells are identified by one or more of the methods of Items 26 to 52. (Item 66) 66. The method according to any one of items 53 to 65, wherein the adverse effect is an adverse effect on motor function, sensory function, speech function or vision, or blood loss. (Item 67) A program for causing a computer to execute a method for predicting the probability of occurrence of an adverse effect of cell therapy on a central nervous system disorder in a subject, the method comprising: 1) inputting a data group indicating the administration position of cells and data on the occurrence of adverse effects of cell therapy for each administration position of the cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; 2) acquiring a data set indicative of the location of cell administration; 3) inputting the data set indicating the administration position of the cells obtained in 2) into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; encompassing,programs. (Item 68) Item 68. The program according to Item 67, wherein the group of data indicating the administration position of the cells includes at least one of data on the distance between the administration position and the brain surface, the distance between the administration position and the lesion position, the distance between the administration position and the edema area, and whether the administration position is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 69) Item 69. The program according to Item 67 or 68, wherein the group of data indicating the administration position of the cells includes a combination of the distance between the administration position and the brain surface, the distance between the administration position and the lesion position, the distance between the administration position and the edema area, and whether the administration position is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 70) 70. The program according to any one of Items 67 to 69, wherein the administration location of the cells is identified by one or more methods of Items 1 to 14. (Item 71) A program for causing a computer to execute a method for predicting the probability of occurrence of an adverse effect of cell therapy on a central nervous system disorder in a subject, the method comprising: 1) inputting a data group indicating the area through which an injection needle for administering cells passes and data on adverse effects of cell therapy for each area through which the injection needle for administering cells passes into an artificial intelligence model as learning data, and allowing the artificial intelligence model to learn; 2) acquiring a data set indicating a passage area of ​​an injection needle for injecting cells; 3) inputting the data set obtained in 2) indicating the area through which the injection needle for injecting the cells passes into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; A program that encompasses: (Item 72) Item 72. The program according to Item 71, wherein the group of data indicating the area through which the injection needle for administering the cells passes includes at least one of the distance between the brain surface just below the skin through which the injection needle passes and the skull, whether the area just below the injection point of the injection needle is an eloquent area, whether there is a large vein just below the injection point of the injection needle, whether the injection needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate, the distance between the cerebral sulcus and the injection needle, and the distance between the injection needle and a large blood vessel in the brain. (Item 73) Item 73. The program according to Item 71 or 72, wherein the group of data indicating the area through which the injection needle for administering the cells passes includes a combination of the distance between the skull and the brain surface just below the skin through which the injection needle passes, whether the area just below the injection point of the injection needle is an eloquent area, whether there is a large vein just below the injection point of the injection needle, whether the injection needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate, the distance between the cerebral sulcus and the injection needle, and the distance between the injection needle and a large blood vessel in the brain. (Item 74) 74. The program according to any one of Items 71 to 73, wherein the administration location of the cells is identified by one or more methods of Items 15 to 25. (Item 75) A program for causing a computer to execute a method for predicting the probability of occurrence of an adverse effect of cell therapy on a central nervous system disorder in a subject, the method comprising: 1) inputting a data group indicating the administration position of cells, a data group indicating the passage area of ​​an administration needle for administering cells to the administration position of cells, and data on adverse effects of cell therapy for each data group indicating the administration position of cells and the passage area of ​​an administration needle for administering cells to the administration position of cells, into an artificial intelligence model as learning data, and allowing the artificial intelligence model to learn; 2) acquiring a data group indicating a cell administration position and a data group indicating a passage area of ​​an administration needle for administering cells to the cell administration position; 3) inputting the data set indicating the administration position of the cells acquired in 2) and the data set indicating the passage area of ​​an administration needle for administering the cells to the administration position into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; encompassing,programs. (Item 76) Item 76. The program according to Item 75, wherein the data group indicating the administration position of the cells includes a combination of the distance between the administration position and the brain surface, the distance between the administration position and the lesion position, the distance between the administration position and the edema area, and whether the administration position is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 77) The data group showing the area through which the injection needle passes to inject the cells into the injection site of the cells includes the distance between the brain surface and the skull just below the skin through which the injection needle passes, the area just below the injection point of the injection needle is eloquent, 77. The program according to any one of items 75 and 76, which includes a combination of whether the area is a cerebral sulcus, whether there is a large vein directly below the insertion point of the administration needle, whether the administration needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate, and the distance between the administration needle and the cerebral sulcus, and the distance between the administration needle and a large blood vessel in the brain. (Item 78) the data group indicating the administration position of the cells includes at least one of the following: a distance between the administration position and the brain surface; a distance between the administration position and the lesion position; a distance between the administration position and the edema area; and whether the administration position is other than a site called an eloquent area in a cerebral arteriovenous malformation (AVM); 78. The program according to any one of items 75 to 77, wherein the group of data indicating the area through which the injection needle passes to inject the cells at the injection site includes at least one of the following: the distance between the brain surface just below the skin through which the injection needle passes and the skull; whether the area just below the injection point of the injection needle is an eloquent area; whether there is a large vein just below the injection point of the injection needle; whether the injection needle passes through an artificial object such as an artificial bone, artificial dura mater, or titanium plate; the distance between the cerebral sulcus and the injection needle; and the distance between the injection needle and a large blood vessel in the brain. (Item 79) The program according to any one of items 75 to 78, wherein the administration position of the cells and the passage area of ​​the administration needle for administering the cells to the administration position of the cells are identified by one or more methods of items 26 to 52. (Item 80) 80. The program according to any one of items 67 to 79, wherein the adverse effect is an adverse effect on motor function, sensory function, language function or vision, or blood loss. (Item 81) A recording medium storing a program for causing a computer to execute a method for predicting the occurrence probability of adverse effects of cell therapy on central nervous system disorders in a subject, the method comprising: 1) inputting a data group indicating the administration position of cells and data on the occurrence of adverse effects of cell therapy for each administration position of the cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; 2) acquiring a data set indicative of the location of cell administration; 3) inputting the data set indicating the administration position of the cells obtained in 2) into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; A recording medium including: (Item 82) Item 82. The recording medium according to Item 81, wherein the group of data indicating the administration position of the cells includes at least one of data on the distance between the administration position and the brain surface, the distance between the administration position and the lesion position, the distance between the administration position and the edema area, and whether the administration position is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 83) 83. The recording medium according to Item 67 or 82, wherein the group of data indicating the administration position of the cells includes a combination of the distance between the administration position and the brain surface, the distance between the administration position and the lesion position, the distance between the administration position and the edema area, and whether the administration position is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 84) 84. The recording medium according to any one of Items 81 to 83, wherein the administration location of the cells is identified by one or more methods of Items 1 to 14. (Item 85) A recording medium storing a program for causing a computer to execute a method for predicting the occurrence probability of adverse effects of cell therapy on central nervous system disorders in a subject, the method comprising: 1) inputting a data group indicating the area through which an injection needle for administering cells passes and data on adverse effects of cell therapy for each area through which the injection needle for administering cells passes into an artificial intelligence model as learning data, and allowing the artificial intelligence model to learn; 2) acquiring a data set indicating a passage area of ​​an injection needle for injecting cells; 3) inputting the data set obtained in 2) indicating the area through which the injection needle for injecting the cells passes into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; A recording medium comprising: (Item 86) Item 86. The recording medium according to Item 85, wherein the group of data indicating the area through which the injection needle for administering the cells passes includes at least one of the following: the distance between the brain surface just below the skin through which the injection needle passes and the skull; whether the area just below the injection point of the injection needle is an eloquent area; whether there is a large vein just below the injection point of the injection needle; whether the injection needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate; the distance between the cerebral sulcus and the injection needle; and the distance between the injection needle and a large blood vessel in the brain. (Item 87) Item 87. The recording medium according to Item 85 or 86, wherein the group of data indicating the area through which the injection needle for administering the cells passes includes a combination of the distance between the brain surface just below the skin through which the injection needle passes and the skull, whether the area just below the injection point of the injection needle is an eloquent area, whether there is a large vein just below the injection point of the injection needle, whether the injection needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate, the distance between the cerebral sulcus and the injection needle, and the distance between the injection needle and a large blood vessel in the brain. (Item 88) 88. The recording medium according to any one of Items 85 to 87, wherein the administration location of the cells is identified by one or more of the methods of Items 15 to 25. (Item 89) A recording medium storing a program for causing a computer to execute a method for predicting the occurrence probability of adverse effects of cell therapy on central nervous system disorders in a subject, the method comprising: 1) inputting a data group indicating the administration position of cells, a data group indicating the passage area of ​​an administration needle for administering cells to the administration position of cells, and data on adverse effects of cell therapy for each data group indicating the administration position of cells and the passage area of ​​an administration needle for administering cells to the administration position of cells, into an artificial intelligence model as learning data, and allowing the artificial intelligence model to learn; 2) acquiring a data group indicating a cell administration position and a data group indicating a passage area of ​​an administration needle for administering cells to the cell administration position; 3) inputting the data set indicating the administration position of the cells acquired in 2) and the data set indicating the passage area of ​​an administration needle for administering the cells to the administration position into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; A recording medium including: (Item 90) Item 90. The recording medium according to Item 89, wherein the data group indicating the administration position of the cells includes a combination of the distance between the administration position and the brain surface, the distance between the administration position and the lesion position, the distance between the administration position and the edema area, and whether the administration position is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 91) The data group showing the area through which the injection needle passes to inject the cells into the injection site of the cells includes the distance between the brain surface and the skull just below the skin through which the injection needle passes, the area just below the injection point of the injection needle is eloquent, 91. The recording medium according to any one of items 89 and 90, comprising a combination of: whether the area is a cerebral sulcus; whether there is a large vein directly below the injection point of the administration needle; whether the administration needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate; the distance between the administration needle and the cerebral sulcus; and the distance between the administration needle and a large blood vessel in the brain. (Item 92) the data group indicating the administration position of the cells includes at least one of the following: a distance between the administration position and the brain surface; a distance between the administration position and the lesion position; a distance between the administration position and the edema area; and whether the administration position is other than a site called an eloquent area in a cerebral arteriovenous malformation (AVM); 92. The recording medium according to any one of items 89 to 91, wherein the data group indicating the area through which the injection needle passes to inject the cells into the injection site includes at least one of the following: the distance between the brain surface just below the skin through which the injection needle passes and the skull; whether the area just below the injection point of the injection needle is an eloquent area; whether there is a large vein just below the injection point of the injection needle; whether the injection needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate; the distance between the cerebral sulcus and the injection needle; and the distance between the injection needle and a large blood vessel in the brain. (Item 93) The recording medium according to any one of items 89 to 92, wherein the administration position of the cells and the passage area of ​​an administration needle for administering the cells to the administration position of the cells are identified by one or more methods selected from items 26 to 52. (Item 94) 94. The recording medium according to any one of items 81 to 93, wherein the adverse effect is an adverse effect on motor function, sensory function, language function or vision, or blood loss. (Item 95) A system for predicting the probability of occurrence of an adverse effect of cell therapy on a central nervous system disorder in a subject, comprising: 1) a learning unit that inputs a group of data indicating the administration position of cells and data on the occurrence of adverse effects of cell therapy for each administration position of the cells into an artificial intelligence model as learning data and causes the artificial intelligence model to learn; 2) an acquisition unit that acquires a data group indicating the administration position of the cells; 3) an input unit that inputs a group of data indicating the administration position of the cells obtained in 2) to the trained artificial intelligence model; 4) A system comprising a calculation unit that causes the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy. (Item 96) Item 96. The system according to Item 95, wherein the group of data indicating the administration position of the cells includes at least one of data on the distance between the administration position and the brain surface, the distance between the administration position and the lesion position, the distance between the administration position and the edema area, and whether the administration position is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 97) Item 97. The system according to Item 95 or 96, wherein the group of data indicating the administration location of the cells includes a combination of the distance between the administration location and the brain surface, the distance between the administration location and the lesion location, the distance between the administration location and the edema area, and whether the administration location is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 98) 98. The system according to any one of items 95 to 97, wherein the location of administration of the cells is identified by one or more methods of items 1 to 14. (Item 99) A system for predicting the probability of occurrence of adverse effects of cell therapy on central nervous system disorders in a subject, comprising: 1) a learning unit that inputs a data group indicating the area through which an injection needle for administering cells passes and data on the adverse effects of cell therapy for each area through which the injection needle for administering cells passes into an artificial intelligence model as learning data, and causes the artificial intelligence model to learn; 2) acquiring a data set indicating a passage area of ​​an injection needle for injecting cells; 3) an input unit that inputs a group of data obtained in 2) indicating a passage area of ​​an injection needle for injecting the cells to the trained artificial intelligence model; and 4) A system comprising a calculation unit that causes the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy. (Item 100) Item 99. The system according to Item 99, wherein the group of data indicating the area through which the administration needle for administering the cells passes includes at least one of the distance between the brain surface just below the skin through which the administration needle passes and the skull, whether the area just below the insertion point of the administration needle is an eloquent area, whether there is a large vein just below the insertion point of the administration needle, whether the administration needle passes through an artificial object such as an artificial bone, artificial dura mater, or titanium plate, the distance between the cerebral sulcus and the administration needle, and the distance between the administration needle and a large blood vessel in the brain. (Item 101) The system described in Item 99 or 100, wherein the group of data indicating the area through which the administration needle for administering the cells passes includes a combination of the distance between the brain surface just below the skin through which the administration needle passes and the skull, whether the area just below the insertion point of the administration needle is an eloquent area, whether there is a large vein just below the insertion point of the administration needle, whether the administration needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate, the distance between the cerebral sulcus and the administration needle, and the distance between the administration needle and a large blood vessel in the brain. (Item 102) The system according to any one of Items 99 to 101, wherein the location of administration of the cells is identified by one or more methods of Items 15 to 25. (Item 103) A system for predicting the probability of occurrence of adverse effects of cell therapy on central nervous system disorders in a subject, comprising: 1) a learning unit that inputs a data group indicating the administration position of cells, a data group indicating the passage area of ​​an administration needle for administering cells to the administration position of cells, and data on adverse effects of cell therapy for each of the data group indicating the administration position of cells and the passage area of ​​an administration needle for administering cells to the administration position of cells, into an artificial intelligence model as learning data, and causes the artificial intelligence model to learn; 2) an acquisition unit that acquires a data group indicating a cell administration position and a data group indicating a passage area of ​​an administration needle for administering cells to the cell administration position; 3) an input unit that inputs, to the trained artificial intelligence model, a data group indicating the administration position of the cells acquired in 2) and a data group indicating the passage area of ​​an administration needle for administering the cells to the administration position of the cells; 4) A system comprising a calculation unit that causes the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy. (Item 104) Item 104. The system according to Item 103, wherein the group of data indicating the administration location of the cells includes a combination of the distance between the administration location and the brain surface, the distance between the administration location and the lesion location, the distance between the administration location and the edema area, and whether the administration location is other than a site called an eloquent area in cerebral arteriovenous malformation (AVM). (Item 105) The data group showing the area through which the injection needle passes to inject the cells into the injection site of the cells includes the distance between the brain surface and the skull just below the skin through which the injection needle passes, the area just below the injection point of the injection needle is eloquent, The system according to any one of items 103 or 104, which includes a combination of whether the area is a cerebral sulcus, whether there is a large vein directly below the insertion point of the administration needle, whether the administration needle passes through an artificial object such as an artificial bone, artificial dura mater or titanium plate, and the distance between the administration needle and the cerebral sulcus, and the distance between the administration needle and a large blood vessel in the brain. (Item 106) the data group indicating the administration position of the cells includes at least one of the following: a distance between the administration position and the brain surface; a distance between the administration position and the lesion position; a distance between the administration position and the edema area; and whether the administration position is other than a site called an eloquent area in a cerebral arteriovenous malformation (AVM); The system according to any one of Items 93 to 105, wherein the group of data indicating the area through which the administration needle passes to administer the cells to the administration site includes at least one of the following: the distance between the brain surface just below the skin through which the administration needle passes and the skull; whether the area just below the insertion point of the administration needle is an eloquent area; whether there is a large vein just below the insertion point of the administration needle; whether the administration needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate; the distance between the cerebral sulcus and the administration needle; and the distance between the administration needle and a large blood vessel in the brain. (Item 107) The system described in any one of items 93 to 106, wherein the administration position of the cells and the passage area of ​​the administration needle for administering the cells to the administration position of the cells are identified by one or more methods of items 26 to 52. (Item 108) 108. The system of any one of items 95 to 107, wherein the adverse effect is an adverse effect on motor function, sensory function, language function or vision, or blood loss. (Item A1) A method for identifying a site to administer cells in cell therapy for a central nervous system disorder in a subject, the method comprising: X) inputting a group of image data of at least a part of the brain of the subject and a group of data of the site to which the cells are to be administered into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; A) acquiring image data of at least a portion of the subject's brain with an imaging device; Y) inputting image data of at least a part of the subject's brain acquired in A) into the trained artificial intelligence model; Z) A step of having the trained artificial intelligence model calculate data on the site to which cells are to be administered; A method that encompasses (Item A2) B) obtaining information about the subject's brain by a computer device in communication with the imaging device; C) using the computer device to delineate motor fibers using the acquired image data and data related to the subject's brain; D) A step of identifying the location of the motor fiber that is damaged by the computer device, in which the running data of the motor fiber is identified as being lower than other parts, and the lower part is identified as the motor fiber that is damaged; F) outputting the calculated administration site as a graphical representation; The method according to item A1, further comprising: (Item A3) The method described in item A1 or A2, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a site called an eloquent area in the subject's cerebral arteriovenous malformation (AVM). (Item A4) The method according to any one of items A1 to A3, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the motor fibers of the subject, data on the location of damage to the motor fibers, data on the location of the brain surface of the subject, data on the edema area of ​​the subject, and data on a site called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject. (Item A5) The method according to any one of items A1 to A4, further comprising one or more features of items 1 to 14. (Item A6) A program for causing a computer to execute a method for specifying a site to administer cells in cell therapy for a central nervous system disorder in a subject, the method comprising: X) inputting a group of image data of at least a part of the brain of the subject and a group of data of the site to which the cells are to be administered into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; A) acquiring image data of at least a part of the brain of the subject using an imaging device; Y) inputting image data of at least a part of the subject's brain acquired in A) into the trained artificial intelligence model; Z) A step of having the trained artificial intelligence model calculate data on the site to which cells are to be administered; encompassing,programs. (Item A7) The method comprises: B) obtaining information about the subject's brain by a computer device in communication with the imaging device; C) using the computer device to delineate motor fibers using the acquired image data and data related to the subject's brain; D) A step of identifying the location of the motor fiber that is damaged by the computer device, in which the running data of the motor fiber is identified as being lower than other parts, and the lower part is identified as the motor fiber that is damaged; F) outputting the calculated administration site as a graphical representation; The program according to item A6, further comprising: (Item A8) The program described in item A6 or A7, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a region of the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item A9) The program described in any one of items A6 to A8, wherein the image data of at least a portion of the subject's brain includes a combination of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a region of the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item A10) The program according to any one of Items A6 to A9, further including one or more features of Items 1 to 14. (Item A11) A recording medium storing a program for causing a computer to execute a method for identifying a site to administer cells in cell therapy for a central nervous system disorder in a subject, the method comprising: X) inputting a group of image data of at least a part of the brain of the subject and a group of data of the site to which the cells are to be administered into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; A) acquiring image data of at least a part of the brain of the subject using an imaging device; Y) inputting image data of at least a part of the subject's brain acquired in A) into the trained artificial intelligence model; Z) A step of having the trained artificial intelligence model calculate data on the site to which cells are to be administered; A recording medium including: (Item A12) The method comprises: B) obtaining information about the subject's brain by a computer device in communication with the imaging device; C) using the computer device to delineate motor fibers using the acquired image data and data related to the subject's brain; D) A step of identifying the location of the motor fiber that is damaged by the computer device, in which the running data of the motor fiber is identified as being lower than other parts, and the lower part is identified as the motor fiber that is damaged; F) outputting the calculated administration site as a graphical representation; The recording medium according to Item A11, further comprising: (Item A13) The recording medium described in item A11 or A12, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM). (Item A14) The recording medium described in any one of items A11 to A13, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the motor fibers of the subject, data on the location of damage to the motor fibers, data on the position of the brain surface of the subject, data on the edema area of ​​the subject, and data on a region called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject. (Item A15) The recording medium according to any one of Items A11 to A14, further comprising one or more features of Items 1 to 14. (Item A16) A system for identifying a site to administer cells in cell therapy for a central nervous system disorder in a subject, the system comprising: X) a learning unit that inputs a group of image data of at least a part of the brain of the subject and a group of data of the site to which the cells are to be administered into an artificial intelligence model as learning data and causes the artificial intelligence model to learn; A) an acquisition unit that acquires image data of at least a part of the brain of the subject using an imaging device; Y) an input unit that inputs image data of at least a part of the subject's brain obtained in A) into the trained artificial intelligence model; Z) A system comprising a calculation unit that causes the trained artificial intelligence model to calculate data on the site to which cells are to be administered. (Item A17) B) an acquisition unit that acquires information about the subject's brain by a computer device in communication with the imaging device; C) a depiction unit that depicts motor fibers using the acquired image data and data related to the subject's brain by the computer device; D) A part that identifies the location of the motor fiber that is damaged by the computer device, and identifies the part where the running data of the motor fiber is lower than other parts, and identifies the lower part as the motor fiber that is damaged; F) an output unit that outputs the calculated administration site as a graphic display; The system of item A16 further comprises: (Item A18) The system described in item A16 or A17, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on the area of ​​the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item A19) The system described in any one of items A16 to A18, wherein the image data of at least a portion of the subject's brain includes a combination of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a region of the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item A20) The system according to any one of items A16 to A19, further including one or more features of items 1 to 14. (Item B1) A method for identifying a passage area of ​​an administration needle for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: (X) inputting a group of image data of at least a portion of the brain of the subject and a group of data of a passage area of ​​an injection needle for injecting cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; (A) acquiring image data of at least a portion of the brain of the subject using an imaging device; (Y) inputting image data of at least a part of the subject's brain obtained in (A) into the trained artificial intelligence model; (Z) causing the trained artificial intelligence model to calculate data on the area through which an injection needle passes for injecting cells; A method that encompasses (Item B2) (B) obtaining information about the subject's brain by a computer device in communication with the imaging device; (C) depicting blood vessels from the acquired image data and information about the subject's brain by the computer device; (D) identifying, by the computing device, a path extent that does not penetrate the blood vessel; (E) using the computer device to identify a non-invasive sulcal area that does not extend beyond the sulcus after inserting a needle into the brain; (G) outputting the calculated route as a graphical representation; The method according to item B1, further comprising: (Item B3) The method according to item B1 or B2, wherein the image data of at least a portion of the brain of the subject includes at least one of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the brain surface and the skull of the subject, data on a site called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate, data on the position of a large artery just below the skin, and data on the position of a large blood vessel in the brain. (Item B4) The method according to any one of items B1 to B3, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the motor fibers of the subject, data on the position of the cerebral sulci of the subject, data on the distance between the brain surface and the skull of the subject, data on a site called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject, data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item B5) The method according to any one of items B1 to B4, further comprising one or more features of items 15 to 25. (Item B6) A program for causing a computer to execute a method for specifying a passage area of ​​an administration needle for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: (X) inputting a group of image data of at least a portion of the brain of the subject and a group of data of a passage area of ​​an injection needle for injecting cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; (A) acquiring image data of at least a portion of the brain of the subject using an imaging device; (Y) inputting image data of at least a part of the subject's brain obtained in (A) into the trained artificial intelligence model; (Z) causing the trained artificial intelligence model to calculate data on the area through which an injection needle passes for injecting cells; encompassing,programs. (Item B7) The method comprises: (B) obtaining information about the subject's brain by a computer device in communication with the imaging device; (C) depicting blood vessels from the acquired image data and information about the subject's brain by the computer device; (D) identifying, by the computing device, a path extent that does not penetrate the blood vessel; (E) using the computer device to identify a non-invasive sulcal area that does not extend beyond the sulcus after inserting a needle into the brain; (G) outputting the calculated route as a graphical representation; The program according to item B6, further comprising: (Item B8) The program described in item B6 or B7, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the subject's brain surface and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item B9) The program according to any one of items B6 to B8, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the brain surface and the skull of the subject, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item B10) The program according to any one of Items B6 to B9, further comprising one or more features of Items 15 to 25. (Item B11) A recording medium storing a program for causing a computer to execute a method for identifying a passage area of ​​an administration needle for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: (X) inputting a group of image data of at least a portion of the brain of the subject and a group of data of a passage area of ​​an injection needle for injecting cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; (A) acquiring image data of at least a portion of the brain of the subject using an imaging device; (Y) inputting image data of at least a part of the subject's brain obtained in (A) into the trained artificial intelligence model; (Z) causing the trained artificial intelligence model to calculate data on the area through which an injection needle passes for injecting cells; A recording medium including: (Item B12) The method comprises: (B) obtaining information about the subject's brain by a computer device in communication with the imaging device; (C) depicting blood vessels from the acquired image data and information about the subject's brain by the computer device; (D) identifying, by the computing device, a path extent that does not penetrate the blood vessel; (E) using the computer device to identify a non-invasive sulcal area that does not extend beyond the sulcus after inserting a needle into the brain; (G) outputting the calculated route as a graphical representation; The recording medium according to item B11, further comprising: (Item B13) The recording medium described in item B11 or B12, wherein the image data of at least a portion of the brain of the subject includes at least one of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the brain surface of the subject and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item B14) The recording medium according to any one of items B11 to B13, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the motor fibers of the subject, data on the position of the cerebral sulci of the subject, data on the distance between the brain surface of the subject and the skull, data on the area called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject, data on the position of artificial objects such as artificial bones, artificial dura mater or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item B15) The recording medium according to any one of Items B11 to B14, further comprising one or more features of Items 15 to 25. (Item B16) A system for identifying a passage area of ​​an administration needle for administering cells in cell therapy for a central nervous system disorder in a subject, the system comprising: (X) a learning unit that inputs a group of image data of at least a portion of the brain of the subject and a group of data of a passage area of ​​an injection needle for injecting cells into an artificial intelligence model as learning data and causes the artificial intelligence model to learn; (A) an acquisition unit that acquires image data of at least a portion of the brain of the subject using an imaging device; (Y) an input unit that inputs image data of at least a part of the subject's brain acquired in (A) into the trained artificial intelligence model; (Z) a calculation unit that causes the trained artificial intelligence model to calculate data on the passing area of ​​an injection needle for injecting cells; A system that encompasses: (Item B17) (B) an acquiring unit that acquires information about the subject's brain by a computer device in communication with the imaging device; (C) a depiction unit that depicts blood vessels using the computer device based on the acquired image data and information about the subject's brain; (D) a route range determination unit that determines, by the computer device, a route range that does not penetrate the blood vessel; (E) a non-invasive sulcus range identifying unit that identifies a non-invasive sulcus range that does not appear in the sulcus after inserting a needle into the brain using the computer device; (G) an output unit that outputs the calculated route as a graphic display; The system according to item B16, further comprising: (Item B18) The system described in item B16 or B17, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the subject's brain surface and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item B19) The system according to any one of items B16 to B18, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the brain surface and the skull of the subject, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item B20) The system of any one of items B16 to B19, further including one or more features of items 15 to 25. (Item C1) A method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: x) inputting a group of image data of at least a part of the brain of the subject and a group of data of the route of administration of the cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; i) acquiring image data of at least a part of the brain of the subject using an imaging device; y) inputting image data of at least a part of the brain of the subject acquired in i) into the trained artificial intelligence model; z) causing the trained artificial intelligence model to calculate data on the route for administering cells; A method that encompasses (Item C2) ii) obtaining information about the subject's brain by a computer device in communication with the imaging device; iii) providing potential routes for administering the cells by the following steps: aa) selecting, by the computing device, a safe zone near the lesion location as an administration site; bb) identifying a route of administration to the selected administration site; cc) optionally selecting, by said computer device, an ablation location for passing an administration device for administering cells in the scalp; and iv) outputting the calculated administration site as a graphical representation; The method according to item C1, further comprising: (Item C3) The method according to item C1 or C2, wherein the image data of at least a portion of the brain of the subject includes at least one of data on the course of the motor fibers of the subject, data on the location of damage to the motor fibers, data on the location of the brain surface of the subject, data on the edema area of ​​the subject, and data on a site called an eloquent area in the cerebral arteriovenous malformation (AVM) of the subject. (Item C4) The method according to any one of items C1 to C3, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the motor fibers of the subject, data on the location of damage to the motor fibers, data on the location of the brain surface of the subject, data on the edema area of ​​the subject, and data on a site called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject. (Item C5) The method according to any one of items C1 to C4, wherein the image data of at least a portion of the brain of the subject includes at least one of data on the course of the motor fibers of the subject, data on the position of the cerebral sulci of the subject, data on the distance between the brain surface and the skull of the subject, data on a site called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject, data on the position of an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate, data on the position of a large artery just below the skin, and data on the position of a large blood vessel in the brain. (Item C6) The method according to any one of items C1 to C5, wherein the image data of at least a part of the brain of the subject includes a combination of data on the course of the motor fibers of the subject, data on the position of the cerebral sulci of the subject, data on the distance between the brain surface and the skull of the subject, data on a site called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject, data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item C7) The method of any one of items C1 to C6, further comprising one or more features of items 26 to 47. (Item C8) A program for causing a computer to execute a method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: x) inputting a group of image data of at least a part of the brain of the subject and a group of data of the route of administration of the cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; i) acquiring image data of at least a part of the brain of the subject using an imaging device; y) inputting image data of at least a part of the brain of the subject acquired in i) into the trained artificial intelligence model; z) causing the trained artificial intelligence model to calculate data on the route for administering cells; encompassing,programs. (Item C9) The method comprises: ii) obtaining information about the subject's brain by a computer device in communication with the imaging device; iii) providing potential routes for administering the cells by the following steps: aa) selecting, by the computing device, a safe zone near the lesion location as an administration site; bb) identifying a route of administration to the selected administration site; cc) optionally selecting, by said computer device, an ablation location for passing an administration device for administering cells in the scalp; and iv) outputting the calculated administration site as a graphical representation; The program according to item C8, further comprising: (Item C10) The program described in item C8 or C9, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a region of the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item C11) The program described in any one of items C8 to C10, wherein the image data of at least a portion of the subject's brain includes a combination of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a region of the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item C12) The program described in any one of items C8 to 11, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the subject's brain surface and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item C13) The program according to any one of items C8 to C12, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the brain surface and the skull of the subject, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item C14) The program according to any one of items C8 to C13, further comprising one or more features of items 26 to 47. (Item C15) A recording medium storing a program for causing a computer to execute a method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: x) inputting a group of image data of at least a part of the brain of the subject and a group of data of the route of administration of the cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; i) acquiring image data of at least a part of the brain of the subject using an imaging device; y) inputting image data of at least a part of the brain of the subject acquired in i) into the trained artificial intelligence model; z) causing the trained artificial intelligence model to calculate data on the route for administering cells; A recording medium including: (Item C16) The method comprises: ii) obtaining information about the subject's brain by a computer device in communication with the imaging device; iii) providing potential routes for administering the cells by the following steps: aa) selecting, by the computing device, a safe zone near the lesion location as an administration site; bb) identifying a route of administration to the selected administration site; cc) optionally selecting, by said computer device, an ablation location for passing an administration device for administering cells in the scalp; and iv) outputting the calculated administration site as a graphical representation; The recording medium according to item C15, further comprising: (Item C17) The recording medium described in item C15 or C16, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM). (Item C18) The recording medium described in any one of items C15 to C17, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the motor fibers of the subject, data on the location of damage to the motor fibers, data on the position of the brain surface of the subject, data on the edema area of ​​the subject, and data on a region called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject. (Item C19) The recording medium according to any one of items C15 to C18, wherein the image data of at least a portion of the brain of the subject includes at least one of data on the course of the motor fibers of the subject, data on the position of the cerebral sulci of the subject, data on the distance between the brain surface of the subject and the skull, data on the area called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject, data on the position of artificial objects such as artificial bones, artificial dura mater or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item C20) The recording medium according to any one of items C15 to C19, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the motor fibers of the subject, data on the position of the cerebral sulci of the subject, data on the distance between the brain surface of the subject and the skull, data on the area called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject, data on the position of artificial objects such as artificial bones, artificial dura mater or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item C21) The recording medium according to any one of Items C15 to C20, further comprising one or more features of Items 26 to 47. (Item C22) A system for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the system comprising: x) a learning unit that inputs a group of image data of at least a part of the brain of the subject and a group of data on the route of administration of the cells into an artificial intelligence model as learning data and causes the artificial intelligence model to learn; i) an acquisition unit that acquires image data of at least a part of the brain of the subject using an imaging device; y) an input unit that inputs image data of at least a part of the brain of the subject acquired in i) into the trained artificial intelligence model; z) A system comprising a calculation unit that causes the trained artificial intelligence model to calculate data on the route for administering cells. (Item C23) ii) an acquiring unit that acquires information about the subject's brain by a computer device in communication with the imaging device; iii) a provider that provides candidate routes for administering the cells by the following steps, wherein the provider: aa) a selection unit that selects, by the computing device, a safe area near the lesion location as an administration site; bb) an identification unit that identifies an administration route to the selected administration site; cc) if necessary, a selection unit for selecting an incision position for passing an administration device for administering cells on the scalp by the computer device; a providing unit including: iv) an output unit that outputs the calculated administration site as a graphic display; The system according to item C22, further comprising: (Item C24) The system described in item C22 or C23, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on the area of ​​the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item C25) The system described in any one of items C22 to C24, wherein the image data of at least a portion of the subject's brain includes a combination of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a region of the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item C26) The system of any one of items C22 to C25, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the subject's brain surface and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item C27) The system described in any one of items C22 to C26, wherein the image data of at least a portion of the subject's brain includes a combination of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the subject's brain surface and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item C28) The system of any one of items C22 to C27, further including one or more features of items 26 to 47. (Item D1) A method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: x) inputting a group of image data of at least a part of the brain of the subject and a group of data of the route of administration of the cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; i) acquiring image data of at least a part of the brain of the subject using an imaging device; y) inputting image data of at least a part of the brain of the subject acquired in i) into the trained artificial intelligence model; z) causing the trained artificial intelligence model to calculate data on the route for administering cells; A method that encompasses (Item D2) ii) obtaining, by a computer device in communication with said imaging device, information about the subject's brain; iii) providing potential routes for administering the cells by the following steps: a) optionally selecting, by the computer device, an ablation location for passing an administration device to administer cells in the scalp; b) selecting, with the computing device, an opening in the skull for passing the administration device to administer the cell therapy; c) using the computer device, identifying at least one brain pathway exclusion region selected from the group consisting of motor fibers, cerebral blood vessels, cerebral sulci, and functional areas using the acquired image data and data related to the subject's brain; d) selecting, by the computing device, a safe zone near the lesion location as an administration site; e) delineating an administration route between the opening and the administration site, the administration route being delineated including information about the brain pathway exclusion region, and optionally providing suitability information for the administration route from the information about the brain pathway exclusion region; and iv) outputting the calculated administration site as a graphical representation; The method according to item D1, further comprising: (Item D3) The method described in item D1 or D2, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a site called an eloquent area in the subject's cerebral arteriovenous malformation (AVM). (Item D4) The method according to any one of items D1 to D3, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the motor fibers of the subject, data on the location of damage to the motor fibers, data on the location of the brain surface of the subject, data on the edema area of ​​the subject, and data on a site called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject. (Item D5) The method according to any one of items D1 to D4, wherein the image data of at least a portion of the brain of the subject includes at least one of data on the course of the motor fibers of the subject, data on the position of the cerebral sulci of the subject, data on the distance between the brain surface and the skull of the subject, data on a site called the eloquent area in the cerebral arteriovenous malformation (AVM) of the subject, data on the position of an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate, data on the position of a large artery just below the skin, and data on the position of a large blood vessel in the brain. (Item D6) The method according to any one of Items D1 to D5, wherein the image data of at least a portion of the brain of the subject includes a combination of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the brain surface and the skull of the subject, data on a site called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item D7) The method of any one of items D1 to D6, further comprising one or more features of items 49 to 52. (Item D8) A program for causing a computer to execute a method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: x) inputting a group of image data of at least a part of the brain of the subject and a group of data of the route of administration of the cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; i) acquiring image data of at least a part of the brain of the subject using an imaging device; y) inputting image data of at least a part of the brain of the subject acquired in i) into the trained artificial intelligence model; z) A program comprising a step of causing the trained artificial intelligence model to calculate data on the route for administering cells. (Item D9) The method comprises: ii) obtaining, by a computer device in communication with said imaging device, information about the subject's brain; iii) providing potential routes for administering the cells by the following steps: a) optionally selecting, by the computer device, an ablation location for passing an administration device to administer cells in the scalp; b) selecting, with the computing device, an opening in the skull for passing the administration device to administer the cell therapy; c) using the computer device, identifying at least one brain pathway exclusion region selected from the group consisting of motor fibers, cerebral blood vessels, cerebral sulci, and functional areas using the acquired image data and data related to the subject's brain; d) selecting, by the computing device, a safe zone near the lesion location as an administration site; e) delineating an administration route between the opening and the administration site, the administration route being delineated including information about the brain pathway exclusion region, and optionally providing suitability information for the administration route from the information about the brain pathway exclusion region; and iv) outputting the calculated administration site as a graphical representation; The program according to item D8, further comprising: (Item D10) The program described in item D8 or D9, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a region of the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item D11) The program described in any one of items D8 to 10, wherein the image data of at least a portion of the subject's brain includes a combination of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a region of the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item D12) The program described in any one of items D8 to D11, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the subject's brain surface and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item D13) The program described in any one of items D8 to D12, wherein the image data of at least a portion of the subject's brain includes a combination of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the subject's brain surface and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item D14) The program according to any one of Items D8 to D13, further comprising one or more features of Items 49 to 52. (Item D15) A recording medium storing a program for causing a computer to execute a method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: x) inputting a group of image data of at least a part of the brain of the subject and a group of data of the route of administration of the cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; i) acquiring image data of at least a part of the brain of the subject using an imaging device; y) inputting image data of at least a part of the brain of the subject acquired in i) into the trained artificial intelligence model; z) causing the trained artificial intelligence model to calculate data on the route for administering cells; A recording medium including: (Item D16) The method comprises: ii) obtaining, by a computer device in communication with said imaging device, information about the subject's brain; iii) providing potential routes for administering the cells by the following steps: a) optionally selecting, by the computer device, an ablation location for passing an administration device to administer cells in the scalp; b) selecting, with the computing device, an opening in the skull for passing the administration device to administer the cell therapy; c) using the computer device, identifying at least one brain pathway exclusion region selected from the group consisting of motor fibers, cerebral blood vessels, cerebral sulci, and functional areas using the acquired image data and data related to the subject's brain; d) selecting, by the computing device, a safe zone near the lesion location as an administration site; e) delineating an administration route between the opening and the administration site, the administration route being delineated including information about the brain pathway exclusion region, and optionally providing suitability information for the administration route from the information about the brain pathway exclusion region; and iv) outputting the calculated administration site as a graphical representation; The recording medium according to item D15, further comprising: (Item D17) A recording medium described in item D15 or D16, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a region of the subject's cerebral arteriovenous malformation (AVM) called an eloquent area. (Item D18) The recording medium described in any one of items D15 to 17, wherein the image data of at least a portion of the subject's brain includes a combination of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a region of the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item D19) A recording medium described in any one of items D15 to D18, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the subject's brain surface and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item D20) A recording medium described in any one of items D15 to D19, wherein the image data of at least a portion of the subject's brain includes a combination of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the subject's brain surface and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item D21) The recording medium according to any one of Items D15 to D20, further comprising one or more features of Items 49 to 52. (Item D22) A system for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the system comprising: x) a learning unit that inputs a group of image data of at least a part of the brain of the subject and a group of data on the route of administration of the cells into an artificial intelligence model as learning data and causes the artificial intelligence model to learn; i) an acquisition unit that acquires image data of at least a part of the brain of the subject using an imaging device; y) an input unit that inputs image data of at least a part of the brain of the subject acquired in i) into the trained artificial intelligence model; z) A system comprising a calculation unit that causes the trained artificial intelligence model to calculate data on the route for administering cells. (Item D23) ii) an acquiring unit that acquires information about the subject's brain by a computer device in communication with the imaging device; iii) a provider that provides candidate routes for administering the cells by the following steps, wherein the provider: a) optionally, an ablation position selection unit that selects, by the computer device, an ablation position for passing an administration device that administers cells on the scalp; b) an opening selector that selects, by the computing device, an opening in the skull through which the administration device is passed to administer the cell therapy; c) an identification unit that identifies, by the computer device, at least one brain pathway exclusion region selected from the group consisting of motor fibers, cerebral blood vessels, cerebral sulci, and functional areas using the acquired image data and data related to the brain of the subject; d) a selection unit that selects, by the computing device, a safe area near the lesion location as an administration site; e) delineating an administration route between the opening and the administration site, the administration route being delineated including information about the brain pathway exclusion region, and optionally, an information providing unit that provides suitability information about the administration route from the information about the brain pathway exclusion region; iv) an output unit that outputs the calculated administration site as a graphic display; The system of item D22 further comprises: (Item D24) The system described in item D22 or D23, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on the area of ​​the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item D25) The system described in any one of items D22 to D24, wherein the image data of at least a portion of the subject's brain includes a combination of data on the course of the subject's motor fibers, data on the location of damage to the motor fibers, data on the location of the subject's brain surface, data on the subject's edema area, and data on a region of the subject's cerebral arteriovenous malformation (AVM) called the eloquent area. (Item D26) The system described in any one of items D22 to D25, wherein the image data of at least a portion of the subject's brain includes at least one of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the subject's brain surface and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item D27) The system described in any one of items D22 to D26, wherein the image data of at least a portion of the subject's brain includes a combination of data on the course of the subject's motor fibers, data on the position of the subject's cerebral sulci, data on the distance between the subject's brain surface and the skull, data on the area called the eloquent area in the subject's cerebral arteriovenous malformation (AVM), data on the position of artificial objects such as artificial bones, artificial dura mater, or titanium plates, data on the position of large arteries just below the skin, and data on the position of large blood vessels in the brain. (Item D28) The system of any one of items D22 to D27, further comprising one or more features of items 49 to 52.

[0008] It is contemplated that the present disclosure may provide one or more of the above-described features in combinations other than those explicitly stated. Still further embodiments and advantages of the present disclosure will be recognized by those skilled in the art upon reading and understanding the following detailed description, if necessary. [Effects of the Invention]

[0009] Examples of the effects achieved by each invention are described below. (1) Determining the administration site By providing an objective method as disclosed herein, accurate administration can be performed, significantly increasing the success rate of cell therapy for the brain. Furthermore, by programming the method using a computer, surgeons can be provided with a choice of administration sites that are likely to be successful, allowing for surgery with a certain degree of objectivity rather than surgery that relies on experience and intuition, contributing to increased reproducibility and success rate. (2) Determining the needle path By providing an objective method as disclosed herein, accurate administration can be performed, significantly increasing the success rate of cell therapy for the brain. Furthermore, by programming the method into a computer, surgeons are provided with options for administration routes that are likely to be successful, allowing surgeries to be performed with a certain degree of objectivity rather than relying on experience and intuition, contributing to increased reproducibility and success rates. (3) How to prevent cerebrospinal fluid leakage By providing an objective method for treating cerebrospinal fluid leaks as disclosed herein, cell therapy can be performed with a significantly reduced probability of failure, dramatically increasing the success rate of cell therapy for the brain. Furthermore, by programming the method into a computer, surgeons are provided with a selection of methods for treating cerebrospinal fluid leaks that can be successful, allowing surgeons to perform surgery with a certain degree of objectivity rather than surgery that relies on experience and intuition, contributing to increased reproducibility and success rates. [Brief explanation of the drawings]

[0010] [Figure 1A] Figure 1 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. A: DWI image. [Figure 1B] Figure 1 shows an MRI image of a patient in which the location of cell administration was determined according to the present disclosure. B: DTI image. [Figure 1C] 1 shows an MRI image of a patient in which the location of cell administration was determined in accordance with the present disclosure. C: FLAIR image. In C, the location of cell administration is circled. [Figure 2A] Figure 2 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. A: DWI image. [Figure 2B] Figure 2 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. B: DTI image. [Figure 2C] 2 shows MRI images of a patient in which the location of cell administration was determined in accordance with the present disclosure. C: FLAIR image. In C, the location of cell administration is circled. [Figure 3A] Figure 3 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure: A: DWI image. [Figure 3B] Figure 3 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. B: DTI image. [Figure 3C] 3 shows an MRI image of a patient in which the location of cell administration was determined in accordance with the present disclosure. C: FLAIR image. In C, the location of cell administration is circled. [Figure 4A] Figure 4 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. A: DWI image. [Figure 4B] Figure 4 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. B: DTI image. [Figure 4C] 4 shows an MRI image of a patient in which the location of cell administration was determined in accordance with the present disclosure. C: FLAIR image. In C, the location of cell administration is circled. [Figure 5A]Figure 5 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. A: DWI image. [Figure 5B] Figure 5 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. B: DTI image. [Figure 5C] 5 shows an MRI image of a patient in which the location for cell administration was determined according to the present disclosure. C: FLAIR image. In C, the location for cell administration is circled. [Figure 6A] 6 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. A: DWI image. [Figure 6B] Figure 6 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. B: DTI image. [Figure 6C] 6 shows an MRI image of a patient in which the location for cell administration was determined in accordance with the present disclosure. C: FLAIR image. In C, the location for cell administration is circled. [Figure 7A] 7 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. A: DWI image. [Figure 7B] Figure 7 shows MRI images of a patient in which the location of cell administration was determined according to the present disclosure. B: DTI image. [Figure 7C] 7 shows an MRI image of a patient in which the location for cell administration was determined in accordance with the present disclosure. C: FLAIR image. In C, the location for cell administration is circled. DETAILED DESCRIPTION OF THE INVENTION

[0011] Specific embodiments of the present disclosure will be described in detail below, but the present disclosure is not limited to the following embodiments and can be implemented with appropriate modifications within the scope of the purpose of the present disclosure. Note that duplicated explanations may be omitted as appropriate, but this does not limit the gist of the invention.

[0012] Throughout this specification, singular expressions should be understood to include the plural concept unless otherwise specified. Thus, singular articles (e.g., "a," "an," "the," etc. in English) should be understood to include the plural concept unless otherwise specified. Furthermore, it should be understood that terms used in this specification are used in the sense commonly used in the art unless otherwise specified. Therefore, unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. In case of conflict, the present specification (including definitions) will control.

[0013] <Definition> As used herein, the terms "subject" or "test subject" or "subject" are used synonymously with "patient" and refer to any living organism or animal that is the subject of the techniques of the present disclosure, such as cell therapy, and are sometimes referred to as "object," but these have the same meaning. The subject is preferably, but is not limited to, a human.

[0014] As used herein, the term "central nervous system disorder" refers to any disorder of the central nervous system.

[0015] As used herein, "cell therapy" (also referred to in English as "cellular therapy" or "cytotherapy") refers to the transplantation of human or animal cells to prevent, treat, or ameliorate one or more symptoms associated with a disease or disorder, including, but not limited to, replacing or repairing damaged tissues or organs, modulating immune responses, and reducing inflammatory symptoms and cancer.

[0016] As used herein, the term "imaging device" refers to any device for capturing cross-sectional images of the body. Examples of imaging devices include magnetic resonance imaging (MRI) devices, computed tomography (CT) devices, angiography devices, and ultrasound devices, with MRI devices being preferred. Images can be presented or displayed using optical imaging techniques, also referred to as graphic displays, and can be displayed for viewing by a subject, particularly on a computer monitor, plasma screen, LCD screen, CRT, projection screen, fog screen, water screen, VR goggles, a head-mounted helmet or glasses having an image display screen, or any other structure capable of displaying images.

[0017] As used herein, "motor fibers" refer to nerve fibers that transmit signals to command muscle movement in the body and internal organs of a subject. They pass through the precentral gyrus, the posterior limb of the internal capsule, and the pons. They are used interchangeably with "motor nerves."

[0018] As used herein, "motor fiber trajectory data" refers to a method for estimating the trajectory of nerve fiber bundles in white matter, etc., from imaging data such as MRI images, and data depicting the trajectories of nerve fibers estimated by this method. In this specification, the term "motor fiber trajectory data" is sometimes used interchangeably with "tractography."

[0019] As used herein, the term "electrosurgical instrument" refers to any instrument that is attached to a suitable source of electrosurgical energy and has an active electrode capable of cauterizing, coagulating, and / or cutting tissue. The active electrode is any form of conductive element, elongated, and may be in the form of a thin, flat blade with a pointed or rounded distal end. Any electrosurgical instrument capable of coagulating the arachnoid membrane and mucosa may be utilized, including, but not limited to, electrosurgical instruments such as bipolar coagulating forceps.

[0020] As used herein, the term "brain shift" refers to brain movement caused by cerebrospinal fluid leakage or air intrusion during burr hole surgery, which can hinder the identification of the target position during stereotactic brain surgery.

[0021] As used herein, the term "eloquent area" refers to an area responsible for important brain functions such as motor function, sensory function, language function, and vision.

[0022] As used herein, the term "cerebral surface" refers to the surface of the cerebrum. For example, the arachnoid mater or pia mater of a specific region of the cerebral surface refers to the arachnoid mater or pia mater covering the cerebral surface of that specific region.

[0023] As used herein, "cerebrospinal fluid" refers to the clear, colorless fluid that fills the ventricular system and subarachnoid space. It is found in the area between the arachnoid mater and the pia mater. It is a waste fluid produced by the choroid plexus of the ventricular system and is responsible for buffering the brain's water content and maintaining its shape and position. It is used interchangeably with "cerebrospinal fluid."

[0024] As used herein, the term "cerebral sulci" refers to grooves on the surface of the brain, which are areas filled with cerebrospinal fluid.

[0025] As used herein, the term "gyrus" refers to a raised area in the cerebral cortex that is surrounded by sulci.

[0026] As used herein, the term "apex of the gyrus" refers to the part of the gyrus that is closest to the skull and the surrounding area, and does not include the area around the cerebral sulci.

[0027] As used herein, the term "National Institute of Health Stroke Scale (NIHSS)" refers to a stroke severity assessment scale. It includes items for assessing consciousness, gaze, visual field, facial paralysis, quadriplegia, ataxia, sensory impairment, aphasia, dysarthria, diminished extinction, and neglect. The higher the score for each item, the higher the severity, with a maximum score of 42.

[0028] As used herein, the term "modified Rankin Scale (mRS)" refers to an assessment criterion that is frequently used as a general prognostic assessment scale for stroke. Assessment can be made on a 7-point scale ranging from 0 to 6. The higher the score, the greater the severity.

[0029] In this specification, the "Functional Independence Measure (FIM)" is an index that quantifies and evaluates the degree of independence in activities of daily living. It is also called the Functional Independence Measure. In addition to motor items, it also includes cognitive items such as communication and social cognition, making it possible to evaluate actual activities of daily living. There are 13 motor items and 5 cognitive items. Each item is rated on a 7-point scale, with higher scores indicating greater independence.

[0030] In this specification, the "Barthel Index (BI)" is an evaluation scale used in rehabilitation for cerebrovascular disorders. It has 10 evaluation items: eating, transferring, grooming, toileting, bathing, walking (wheelchair), climbing stairs, getting dressed, defecation, and urination, and a higher score indicates greater independence.

[0031] In this specification, "Fugl-Meyer Assessment (FMA)" refers to a comprehensive physical function assessment method for stroke patients that evaluates upper and lower limb motor function, balance, sensation, range of motion, and pain. A higher score indicates better physical function. (MRI image) In this specification, MRI (magnetic resonance imaging) is also referred to as nuclear magnetic resonance imaging (NMRI). Two-thirds of the human body is composed of water. Furthermore, the structural formulas of various fatty acids and amino acids contain hydrogen (H). Therefore, medical MRI uses the signal from this hydrogen atom (H). Hydrogen consists of one proton and one electron, with the electron spinning around the proton. This spin gives each hydrogen atom a slight magnetization. Normally, these spins are random, resulting in no overall magnetization. When a strong external magnetic field is applied, the spin orientation of each hydrogen atom is forced to align. When radio waves of a specific frequency (e.g., 42.58 MHz) are applied to this state, the hydrogen nuclei resonate with the radio waves and emit their own radio waves. This phenomenon is called nuclear magnetic resonance. Adding positional information to this phenomenon creates a map showing the signal intensity distribution, which becomes a nuclear magnetic resonance image, or MRI. By applying pulses of these specific frequencies and varying the conditions, different types of images can be produced (T1-weighted images, T2-weighted images, etc.).

[0032] In this specification, T1WI is used as an abbreviation for T1 weighted image (T1WI). In T1WI, water is depicted as black with a low signal intensity (ventricles are black), producing images similar to those of CT, and is characterized by its ability to easily capture anatomical structures such as the cerebral cortex and white matter.

[0033] Substances that exhibit high signals on T1-weighted images include fat, subacute hematomas (methemoglobin), cerebral white matter (compared to gray matter) (myelination is not advanced in infants, so the contrast between white and gray matter is reversed), water with a high concentration of dissolved protein, areas of cortical necrosis that may exhibit high signals, prominent calcifications that may exhibit high signals, normal posterior pituitary gland, anterior pituitary gland in newborns and pregnant women (late pregnancy), areas of manganese deposition (the globus pallidus may exhibit high signals, particularly in association with liver dysfunction), areas enhanced by Gd (gadolinium) (in the central nervous system, areas of blood-brain barrier disruption or defect are enhanced, and the enhancement effect does not necessarily reflect vascularity), and paramagnetic substances: the above-mentioned methemoglobin, manganese, and gadolinium are also paramagnetic substances. Other magnetic materials include melanin (melanoma can exhibit high signal intensity on T1-weighted images even without hemorrhage). Substances that exhibit low signal intensity on T1-weighted images include water (cerebrospinal fluid), cerebral gray matter (compared to white matter), many lesions (reflecting increased water content, such as infarctions and tumors), hyperacute and acute hematomas (before methemoglobin formation), cortical bone, calcification, and air, all of which do not contain signal-generating substances.

[0034] In this specification, T2WI is an abbreviation for T2 weighted image (T2WI). In T2WI, water appears white with a high signal intensity (ventricles appear white), and many lesions appear with a high signal intensity, making it useful for detecting lesions.

[0035] Substances that exhibit high signal intensity on T2-weighted images include water (cerebrospinal fluid), many lesions (reflecting increased water content, such as tumors, infarctions, edema, and demyelination), cerebral gray matter (compared to white matter) (in infants, the contrast between white matter and gray matter is reversed), subacute hematomas (after red blood cells are broken down), and hyperacute hematomas (before oxyhemoglobin is converted to deoxyhemoglobin). Substances that exhibit low signal intensity on T2-weighted images include acute hematomas (before red blood cells are broken down, with deoxyhemoglobin inside). These include areas containing hemoglobin or methemoglobin), old bleeding foci (hemosiderin), areas with a high iron (ferritin) content (especially the globus pallidus, red nucleus of the midbrain, substantia nigra, and dentate nucleus of the cerebellum), cerebral white matter (compared to gray matter), areas that do not contain signal-generating substances such as bone cortex, dense calcification, and air, tissues with little water such as water with a very high amount of dissolved protein, fibrosis, and dense tissue, and paramagnetic materials with an uneven distribution (such as the above-mentioned acute hematoma, old bleeding, areas of iron deposition, and melanin).

[0036] In this specification, FLAIR is an abbreviation for "FLAIR image: Fluid Attenuated Inversion Recovery (water-suppressed image)." FLAIR images are essentially T2-weighted images (T2WI-like images in which the ventricles appear black) that suppress water signals, clearly depicting lesions adjacent to the ventricles. They are useful for identifying areas of cerebral infarction (appearing white) in the chronic stage of cerebral infarction, such as hidden cerebral infarctions typified by lacunar infarctions and Binswanger leukoencephalopathy seen in vascular dementia. Simply put, they are T2-weighted images (with some T1-weighted elements) taken under conditions designed to make cerebrospinal fluid appear black. They are often used to reduce the risk of overlooking lesions close to cerebrospinal fluid, such as those in the periventricular and near-cortical areas. They can sometimes depict small subacute subarachnoid hemorrhages that cannot be detected by CT. In acute cerebral infarction, occluded blood vessels can appear as high-intensity signals. There are strong artifacts due to cerebrospinal fluid pulsation and magnetic materials, and the detection rate of posterior fossa lesions is said to be slightly lower, but this does not pose a problem in practical use.

[0037] In this specification, T2*WI refers to a T2* weighted image (T2 star weighted image) or T2 star weighted image (T2*WI). T2* weighted images have an extremely high ability to detect hemorrhagic lesions (they appear in black), and are excellent for identifying previously occurring hemorrhagic lesions and detecting asymptomatic microbleeds.

[0038] In this specification, DWI is an abbreviation for diffusion weighted image, which is an image of the diffusive movement (free mobility) of water molecules. Areas with reduced diffusion are depicted as high signals. Since diffusion decreases in acute cerebral infarction, DWI is useful for determining the location of hyperacute cerebral infarction (depicted as white).

[0039] As used herein, the term "prognosis" refers to predicting the likelihood of death or progression due to a disease or disorder, such as cancer. Prognostic factors are variables related to the natural history of a disease or disorder, and they affect the recurrence rate, etc., of patients who have developed the disease or disorder. Clinical indicators associated with worsening prognosis include, for example, any cellular indicator used in the present disclosure. Prognostic factors are often used to classify patients into subgroups with different pathological conditions. By using the technology of the present disclosure to associate genetic information with diagnostically useful trait information, it may be possible to provide prognostic factors based on the genetic information of controls.

[0040] In this specification, the term "program" is used in the ordinary sense of the term in this field, and refers to a sequence of processes to be performed by a computer. In Japan, this term is treated as a "product" under the Patent Act. All computers operate according to a program. In modern computers, programs are expressed as data in a broad sense and are stored on recording media or storage devices.

[0041] In this specification, the term "recording medium" refers to a recording medium that stores a program for executing the method of the present disclosure, and the recording medium may be any type of recording medium as long as it can store the program. For example, the recording medium may be an internally stored ROM, an HDD, a magnetic disk, or an external storage device such as a flash memory such as a USB memory, but is not limited to these.

[0042] In this specification, the term "system" refers to a configuration that executes the method or program disclosed herein, and originally means a system or organization for accomplishing a purpose, in which multiple elements are systematically configured and interact with each other. In the computer field, it refers to the overall configuration, including hardware, software, an OS, and a network.

[0043] In this specification, "machine learning" refers to a technology that gives computers the ability to learn without explicit programming. It is the process by which functional units improve their performance by acquiring new knowledge and skills or by reconstructing existing knowledge and skills. Programming computers to learn from experience can greatly reduce the effort required for detailed programming. The field of machine learning discusses how to build computer programs that can automatically improve through experience. Along with algorithms, data analysis and machine learning are fundamental technologies for intelligent processing. They are typically used in conjunction with other technologies and require knowledge of the relevant field (domain-specific knowledge; for example, medicine). Applications include prediction (collecting data and predicting future events), exploration (finding distinctive features from the collected data), and testing and description (examining the relationships between various elements in the data). Machine learning is based on metrics that indicate the degree of achievement of real-world goals, and machine learning users must understand those goals. Furthermore, it is necessary to formulate metrics that improve when the goal is achieved. Machine learning is an inverse problem, an ill-posed problem where it is unclear whether a solution has been found. The behavior of learned rules is not deterministic but probabilistic. Operational ingenuity is required, assuming that some uncontrollable aspects will remain, and the tailor-made method of the present invention can be said to be a means of solving this problem. It is also useful for machine learning users to sequentially select and discard data and information in accordance with real-world goals while observing performance indicators during training and operation.

[0044] For machine learning, linear regression, logistic regression, support vector machine, etc. can be used, and cross validation (CV) can be performed to calculate the discrimination accuracy of each model. After ranking, feature amounts are added one by one, and machine learning (linear regression, logistic regression, support vector machine, etc.) and cross validation are performed to calculate the discrimination accuracy of each model. This makes it possible to select the model with the highest accuracy. In the present invention, any machine learning method can be used, and linear, logistic, support vector machine (SVM), etc. can be used as supervised machine learning.

[0045] Logical inference is used in machine learning. There are roughly three types of logical inference: deduction, induction, abduction, and analogy. Deduction is a specific conclusion, as it derives the conclusion that Socrates is mortal when given the hypotheses that Socrates is human and all humans are mortal. Induction is a general rule, as it derives the conclusion that all humans are mortal when given the hypotheses that Socrates is mortal and Socrates is human. Abduction is a hypothesis / explanation, as it derives the conclusion that Socrates is human when given the hypotheses that Socrates is mortal and all humans are mortal. However, it should be noted that even with induction, how it generalizes depends on the assumptions, so it may not be objective. Analogy is a probabilistic logical reasoning method in which, if object A and object B have four characteristics and object A has three of those characteristics in common, object B will also have the remaining characteristic, and object A and object B are of the same species or have a similar close relationship.

[0046] There are three basic types of impossibility: impossible, very difficult, and unsolved. Impossibility also includes generalization error, the no-free-lunch theorem, and the ugly duckling theorem, and it is important to note that ill-posed problems, which mean that a model cannot be verified because it is impossible to observe the true model, are also ill-posed.

[0047] In machine learning, features and attributes describe the state of a target when viewed from a certain aspect. A feature vector and attribute vector are a collection of features (attributes) that describe the target in the form of a vector.

[0048] As used herein, the terms "model" and "hypothesis" are used interchangeably and refer to a mapping or a set of candidates that describes the correspondence between an input prediction target and a prediction result, expressed using a mathematical function or logical formula. In machine learning, the model that is thought to best approximate the true model is selected from the set of models by referring to the training data.

[0049] Examples of models include generative models, discriminative models, and functional models. These show the differences in approaches to expressing classification models of the mapping relationship between input (target to be predicted) x and output (prediction result) y. Generative models express the conditional distribution of output y when input x is given. Discriminative models express the joint distribution of input x and output y. In discriminative and generative models, the mapping relationship is probabilistic. In functional models, the mapping relationship is deterministic, and expresses a deterministic functional relationship between input x and output y. Between discriminative and generative models, discriminative models are sometimes said to be slightly more accurate, but due to the no-free-lunch theorem, there is basically no superiority or inferiority between them.

[0050] Model complexity: The degree to which the mapping relationship between the target and the predicted outcome can be described in more detail and complexity. The more complex the model set, the more training data is generally required.

[0051] When expressing a mapping relationship as a polynomial, a higher-order polynomial can express a more complex mapping relationship. A higher-order polynomial can be said to be a more complex model than a linear polynomial.

[0052] When mapping relationships are represented by decision trees, deeper decision trees with more levels can express more complex mapping relationships. Therefore, decision trees with more levels can be said to be more complex models than decision trees with fewer levels.

[0053] Classification is also possible based on the policy for expressing the correspondence between input and output. In parametric models, the shape of the distribution or function is completely determined by the parameters, while in non-parametric models, the shape is basically determined by the data, and the parameters are limited to determining smoothness.

[0054] Parameter: An input that specifies one of a set of distributions or functions in a model. To distinguish it from other inputs, it is also written as Pr[y|x;θ] or y=f(x;θ).

[0055] In the parametric case, the shape of the Gaussian distribution is determined by the mean and variance parameters, regardless of the number of training data, while in the nonparametric case, only the smoothness of the histogram is determined by the number of bins parameter, which is considered to be more complex than the parametric case.

[0056] In machine learning, training data is referenced and the model that is thought to best approximate the true model is selected from a set of models. There are various learning methods depending on the type of "approximation." A typical example is maximum likelihood estimation, a learning criterion for selecting the model with the highest probability of occurrence of the training data from a set of probabilistic models. Maximum likelihood estimation allows the selection of the model that most closely approximates the true model. KL divergence, as the likelihood increases, decreases. There are various types of estimation, depending on the type of method used to calculate the estimated predicted value or parameters. Point estimation, which calculates the single most certain value, is most commonly used in maximum likelihood estimation and MAP estimation, which use the most frequent value of a distribution or function. On the other hand, interval estimation is often used in statistics to calculate a range within which an estimated value lies, with a 95% probability that the estimated value lies within this range. Distribution estimation is used in Bayesian estimation and other methods in combination with a generative model that incorporates a prior distribution to determine the distribution within which the estimated value lies.

[0057] (Preferred embodiment) Preferred embodiments of the present disclosure are described below. The embodiments provided herein, including the following, are provided for a better understanding of the present disclosure, and it is understood that the scope of the present disclosure should not be limited to the following description. Therefore, it is clear that those skilled in the art can make appropriate modifications within the scope of the present disclosure in light of the description herein. It is also understood that the following embodiments of the present disclosure can be used alone or in combination.

[0058] (Cell administration method for brain cell therapy) In one aspect, the present disclosure provides a method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject.

[0059] The method includes at least one of the following steps or procedures: i) acquiring image data of at least a portion of the subject's brain with an imaging device; ii) obtaining, by a computer device in communication with said imaging device, information about the subject's brain; iii) providing potential routes for administering the cells by the following steps: a) identifying, by the computer device, an ablation location on the scalp for passing an administration device that administers cells; b) identifying, with the computing device, an opening in the skull through which to pass the administration device for administering the cell therapy; c) using the computer device, identifying at least one brain pathway exclusion region selected from the group consisting of motor fibers, cerebral blood vessels, cerebral sulci, and functional areas using the acquired image data and data related to the subject's brain; d) selecting, by the computing device, a safe zone near the lesion location as an administration site; e) delineating an administration route between the opening and the administration site, the administration route being delineated including information about the brain pathway exclusion region, and optionally providing suitability information for the administration route from the information about the brain pathway exclusion region; iv) outputting the selected administration site as a graphical representation; Includes.

[0060] In another aspect, the present disclosure provides a method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: i) acquiring image data of at least a portion of the subject's brain with an imaging device; ii) obtaining, by a computer device in communication with said imaging device, information about the subject's brain; iii) providing potential routes for administering the cells by the following steps: aa) selecting, by the computing device, a safe zone near the lesion location as an administration site; bb) identifying a route of administration to the selected administration site; cc) optionally selecting, by said computer device, an ablation location for passing an administration device for administering cells in the scalp; and iv) outputting the selected administration site as a graphical representation; The present invention provides a method comprising:

[0061] In one embodiment, i) acquiring image data of at least a portion of the subject's brain using an imaging device can be achieved by using a conventional imaging procedure such as MRI, CT, etc. The acquired brain image data preferably substantially covers the region targeted for cell therapy, and more preferably, it is advantageous to obtain an image of the entire brain.

[0062] The image data may be in the form of DICOM, JPEG, or TIFF, with DICOM being preferred.

[0063] In one embodiment, ii) obtaining brain information of the subject by a computer device communicating with the imaging device can be achieved by any method commonly used in the art. Useful brain information includes, for example, past medical history of the brain, information on damage, information on motor fibers, functional information (language areas, higher brain function areas), etc.

[0064] In one embodiment, iii) providing candidate routes for administering the cells by the following steps includes, for example, a) using the computer device to identify an incision location in the scalp for passing an administration device for administering cells; b) using the computer device to identify an opening in the skull for passing the administration device for administering cell therapy; c) using the computer device to identify at least one brain pathway exclusion region selected from the group consisting of motor fibers, cerebral blood vessels, cerebral sulci, and functional regions using the acquired image data and data related to the subject's brain; d) using the computer device to select a safe region near the lesion location as an administration site; and e) drawing an administration route between the opening and the administration site, the administration route being drawn including information related to the brain pathway exclusion region, and, if necessary, providing suitability information for the administration route from the information related to the brain pathway exclusion region. Regarding safety areas, the locations of areas that play an important role in neural function have already been identified in humans with almost no individual differences, so it is possible to input these areas into a computer in advance, and while left-handed people generally have the same functions as right-handed people, in rare cases there are left-handed people who have the opposite function (mainly in the area of ​​language, and since both right-handed and left-handed people usually have the language area in the left hemisphere, in such cases ingenuity is required, but this modification can be made using methods known in the field, and there are rare left-handed people whose language area is in the right hemisphere), even in such cases, the language area can be confirmed in advance using other methods (MRI) and determined to be in the right hemisphere, and although care must be taken when setting up an administration route and administration site that passes through this area, this can be designed.

[0065] In this specification, a) the computer device can use techniques commonly used in the field of neurosurgery to identify the incision position in the scalp for passing the administration device to administer cells. For example, if there is a scar from skin excision, incision that crosses the scar at an angle should be avoided. For example, MRI images can be imported into Medtronic's navigation calculation system, FlameLink, and confirmed as a skin depression. If the skin has already been incised, the incision is basically used. If the intended burr hole is significantly off-center from the previous skin incision line, the skin can be incised longer and the Galea can be peeled off.

[0066] In this specification, b) the computer device can identify an opening in the skull through which to pass the administration device for administering cell therapy using techniques commonly used in the field of neurosurgery. For example, to prevent postoperative infection, areas containing artificial structures such as artificial bone, artificial dura, or titanium plates are excluded from the administration route, if possible. The burr hole should be selected so that the insertion point does not overlap with a functional site. If the brain is atrophied and significantly depressed (approximately 5 mm), incising the dura may result in a long distance to the brain, which could lead to an accident. Therefore, a site where the brain surface is directly beneath the bone (the apex of the gyrus) is selected as the administration route. If the burr hole is located near the midline, there may be a large vein (possibly forming a venous lake) that supplies the superior sagittal sinus (SSS). Therefore, FlameLink should be used to confirm in advance that there are no large veins around the dural incision site.

[0067] In the present specification, c) using the acquired image data and data related to the subject's brain, the computer device can identify at least one brain pathway exclusion region selected from the group consisting of motor fibers, cerebral blood vessels, cerebral sulci, and functional regions using any method used in the art. This can be done by using at least one, preferably two, three, or four, of DWI, T2, FLAIR, and DTI images to determine the administration site. The DWI image identifies the area damaged by cerebral infarction. Since the lack of blood flow in areas damaged by cerebral infarction will cause the administered cells to die, it is recommended that the drug not be administered. Next, T2 and FLAIR images are used to evaluate areas that are DWI-negative (avoiding cell death) but show significant edema (which may be recoverable but is not necessarily desirable for administration), and motor fibers are visualized using DTI images to assess where the motor fibers are severed, allowing the selection of candidate administration routes or areas. Next, a cell injection site can be selected that is close to the torn or weakened tractography (usually a white area on DWI) and highly safe (a location that would cause minimal damage even if bleeding or an allergic reaction were to occur; typically, this is outside the eloquent area of ​​AVM). When selecting the injection site, it may be useful to avoid areas with high signal intensity on T2 / FLAIR images and inject cells into the essentially normal side. In some cases, tractography cannot be visualized due to excessive damage. In such cases, the nerve fiber path can be estimated using the contralateral tractography to create an estimated tractography, allowing the cell injection site to be determined. To prevent cells from leaving the injection site, it is recommended to exclude areas close to the brain surface (within 1 cm, 1.5 cm, 2 cm, 2.5 cm, or 3 cm of the brain surface) from the candidate injection sites. It may be advantageous to exclude areas within 1 cm, 1.5 cm, 2 cm, 2.5 cm, or 3 cm of areas that appear white on DTI images but not on DWI images.

[0068] The administration site and route can be determined using MRI-guided navigation software, and the MRI images taken off-site can also be used.

[0069] In one embodiment, d) the computer device can select a safe area near the lesion location as the administration site using any method known in the art, or a combination thereof. For example, a location close to a torn or weakened area on tractography (usually a white area on DWI) and with high safety (a location with minimal damage even if bleeding or an allergic reaction occurs; generally, a location other than the eloquent area in AVM) is selected as the cell administration site. When selecting the cell administration site, high signal intensity areas on T2 / FLAIR images can also be avoided, and the cells can be administered as close to these areas as possible.

[0070] In one embodiment, e) delineating an administration route between the opening and the administration site, the administration route being delineated including information about the brain pathway exclusion region, can be performed using any technique known in the art and a combination thereof, where information about the brain pathway exclusion region can provide suitability information for the administration route, if necessary.

[0071] Herein, the selected administration site can be output as a graphic display using any method known in the art.

[0072] The present disclosure may be provided as a program for causing a computer to realize the above, or may be provided as a recording medium on which the program is recorded.

[0073] In another aspect, the present disclosure provides a system for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject.

[0074] The system includes at least one of the following components: i) an imaging device that acquires image data of at least a portion of the subject's brain; ii) a computer device in communication with the imaging device that obtains information about the subject's brain; and iii) a computing unit for providing candidate routes for administering the cells by the following steps, the steps comprising: a) identifying, by the computer device, an ablation location on the scalp for passing an administration device that administers cells; b) identifying, with the computing device, an opening in the skull through which to pass the administration device for administering the cell therapy; c) using the computer device, identifying at least one brain pathway exclusion region selected from the group consisting of motor fibers, cerebral blood vessels, cerebral sulci, and functional areas using the acquired image data and data related to the subject's brain; d) selecting, by the computing device, a safe zone near the lesion location as an administration site; e) delineating an administration route between the opening and the administration site, the administration route being delineated including information regarding the brain route exclusion region. and optionally a computing unit for providing suitability information for the administration route from information about the brain pathway excluded region. iv) a display unit that outputs the selected administration site as a graphic display.

[0075] In one embodiment, i) acquiring image data of at least a portion of the subject's brain using an imaging device can be achieved by using a conventional imaging procedure such as MRI, CT, etc. The acquired brain image data preferably substantially covers the region targeted for cell therapy, and more preferably, it is advantageous to obtain an image of the entire brain.

[0076] (Determining the administration location) In one embodiment, the present disclosure provides a method for identifying a site to administer cells in cell therapy for a central nervous system disorder in a subject, the method comprising the steps of: A) acquiring image data of at least a portion of the brain of the subject using an imaging device; B) acquiring information about the brain of the subject using a computer device connected to the imaging device; C) using the acquired image data and data about the brain of the subject using the computer device to depict motor fibers; D) identifying a location where the motor fibers are damaged using the computer device, wherein the computer device identifies a portion of the motor fiber trajectory data where the data is lower than other portions and identifies the lower portion as the damaged motor fiber; E) using the computer device to select a safe region around the location of the damage as an administration site; and F) outputting the selected administration site as a graphic display.

[0077] In one embodiment, A) obtaining image data of at least a portion of the subject's brain by an imaging device can be accomplished using any technique known in the art and described in detail elsewhere herein, and any of these techniques can be applied.

[0078] In one embodiment, B) obtaining information about the subject's brain by a computer device in communication with the imaging device can be accomplished using any technique known in the art and described in detail elsewhere herein, and any of these techniques can be applied.

[0079] In one embodiment, C) the computer device uses the acquired image data and data on the subject's brain to delineate motor fibers can be realized by any method known in the art, and is described in detail elsewhere in this specification, and any of these methods can be applied.Motor fibers can be delineated using at least one of DWI image, T2 image, FLAIR image, and DTI image.For example, T2 image and FLAIR image can be used to evaluate DWI-negative (avoided cell death) but highly edematous areas (which can be recovered but are not necessarily desirable for administration), and motor fibers can be delineated from DTI image to evaluate where motor fibers are severed.

[0080] In one embodiment, D) the computer device can identify the location of the motor fiber where the motor fiber is damaged by identifying a portion of the motor fiber's running data where the running data is lower than other portions, and identifying the lower portion as the motor fiber that is damaged.

[0081] In one embodiment, E) the computer device can select a safe area near the lesion location as the administration site using any method known in the art, as described in detail elsewhere in this specification. A location that is highly safe when administering cells and that will cause little damage even if bleeding or an allergic reaction occurs (other than the area generally called the eloquent area in cerebral arteriovenous malformation (AVM)) can be indicated as the cell administration safe area, or an area with a radius of 1.5 cm centered on the identified lesion location, excluding motor fiber locations, that is a cell administration safe area and excludes areas where cell administration is not possible, can be indicated as a candidate cell administration location.

[0082] In one embodiment, F) outputting the selected administration site as a graphical representation can be accomplished using any technique known in the art and described in detail elsewhere herein.

[0083] In one embodiment, the imaging device includes, but is not limited to, MRI, CT, angiography, and ultrasound. Preferably, MRI is used.

[0084] In one embodiment, the tractography data of the present disclosure is expressed as a fractional anisotropy value (FA value). For example, tractography can be visually inspected for torn or thinned areas, but this can also be done by computer programming, which can quantify the tractography (FA value). Areas where this value is significantly lower (e.g., 40%, 50%, 60%, etc.) than other areas can be extracted and evaluated as damaged areas. Therefore, the decrease in tractography data at areas where motor fiber trajectory data is lower than other areas may be at least 40%, 50%, 60%, or more. Alternatively, an administration site can be selected that is as close as possible (e.g., within 2 cm, 2.5 cm, 3 cm, 3.5 cm, or 4 cm) and that is not considered to play a significant role in neural function. Preferably, the safe zone is selected as a location within a radius of approximately 1.5 cm from the lesion location and that is not considered to play a significant role in neural function. Since the locations of areas that play an important role in neural function have already been identified in humans with almost no individual differences, it is possible to input these areas into a computer in advance. For example, left-handed people are generally the same as right-handed people, but there are very rare cases of left-handed people with the opposite function, mainly in the area of ​​language. Normally, both right-handed and left-handed people have a language area in the left hemisphere, but there are rare cases of left-handed people whose language area is in the right hemisphere, and this can be identified. In other words, in the case of left-handed people, the language area should be confirmed in advance by another method (MRI) to be in the right hemisphere, and although care must be taken when setting up an administration route or administration site that passes through that area, those skilled in the art can carry out this as appropriate, and these can also be designed as computer programs.

[0085] In one embodiment, the administration site can be positioned caudal to the brain relative to the lesion location, which is commonly referred to as hitting from below.

[0086] In one embodiment, the administration site is determined for each of the lesion locations.

[0087] In one embodiment, one or more administration sites are present at the lesion location. The number of administration sites can be appropriately determined by those skilled in the art depending on the case, and can be determined by those skilled in the art based on the relative relationship between the amount of cells to be administered and the brain region to be restored.

[0088] In one embodiment, when the motor fibers are not visualized due to severe brain damage, the damaged area is identified by referring to the healthy motor fibers on the contralateral side. This can be achieved simply by taking symmetry.

[0089] The present disclosure may be provided as a program for causing a computer to realize the above, or may be provided as a recording medium on which the program is recorded.

[0090] In another aspect, the present disclosure provides a system for identifying a site to administer cells in cell therapy for a central nervous system disorder in a subject, the system including: A) an imaging device that acquires image data of at least a portion of the brain of the subject; B) a computer device in communication with the imaging device that acquires information about the brain of the subject, the computer device using the acquired image data and data related to the brain of the subject to depict motor fibers, identify a lesion location where the motor fibers are damaged, identify a portion of the motor fiber trajectory data where the motor fiber trajectory data is lower than other portions, identify the lower portion as the damaged motor fiber, and select a safe region near the lesion location as the administration site; and D) a display unit that outputs a graphic representation of the administration site.

[0091] (Method for determining the passage area of ​​an injection needle for injecting cells) In one aspect, the present disclosure provides a method for determining a passage area of ​​an administration needle for administering cells.

[0092] In this aspect of the present disclosure, the present disclosure provides a method for identifying a passage area of ​​an administration needle for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: A) acquiring image data of at least a portion of the subject's brain using an imaging device; B) obtaining information about the subject's brain by a computer device in communication with the imaging device; C) using the computer device to delineate blood vessels from the acquired image data and information about the subject's brain; D) identifying, by the computing device, a path extent that does not penetrate the blood vessel; E) using the computer device to identify a non-invasive area of ​​the cerebral sulcus that does not extend beyond the cerebral sulcus after inserting a needle into the brain; F) setting a route within the overlapping range of the route ranges calculated in D) and E) by the computer device; G) outputting the set route as a graphic display; A method that encompasses

[0093] In one embodiment, A) obtaining image data of at least a portion of the subject's brain using an imaging device can be accomplished using any technique known in the art and described in detail elsewhere herein, and any of these techniques can be applied.

[0094] In one embodiment, B) obtaining information about the subject's brain by a computer device in communication with the imaging device can be accomplished using any technique known in the art and described in detail elsewhere herein, and any of these techniques can be applied.

[0095] In one embodiment, C) the computer device can use any method known in the art to visualize blood vessels based on the acquired image data and information on the subject's brain, and any of these methods can be applied. For example, blood vessels can be visualized using at least one of a DWI image, a T2 image, a FLAIR image, and a DTI image. For example, a gadolinium-enhanced T1 image can be used to identify strong signals, taking advantage of the fact that only blood vessels are visualized with a strong high signal. Alternatively, the original image of MRA (magnetic resonance angiography) can be used to visualize blood vessels.

[0096] In one embodiment, D) the computer device can identify a route range that does not penetrate the blood vessel using any method known in the art, and any of these methods can be applied. For example, the route range can be identified by depicting the blood vessel using at least one of a DWI image, a T2 image, a FLAIR image, and a DTI image, and then using the result to identify the route and range that does not penetrate the blood vessel. Alternatively, the original image of MRA (magnetic resonance angiography) can be used to depict the blood vessel.

[0097] In one embodiment, E) the computer device can also identify a non-invasive sulcal area that does not extend into the posterior sulcus after inserting a needle into the brain using any method known in the art, and any of these methods can be applied. For example, at least one of a DWI image, a T2 image, a FLAIR image, and a DTI image can be used to depict blood vessels, and the result can be used to identify a non-invasive sulcal area that does not extend into the posterior sulcus after inserting a needle into the brain. For example, this can be achieved by measuring at least DWI, T2, FLAIR, and DTI on the MRI image.

[0098] In one embodiment, F) the computer device sets a route within the overlapping range of the route ranges calculated in D) and E), which can also be achieved by any method known in the art, and any of these methods can be applied, such as a method of calculating and selecting the overlapping range as a suitable candidate route using the information obtained in steps D) and E).

[0099] In one embodiment, G) outputting the planned route as a graphical display can be accomplished using any technique known in the art and described in detail elsewhere herein, and any of these techniques can be applied.

[0100] In one embodiment, when tractography is visualized in a diffusion tensor (DTI) image, the administration site is selected from a location that satisfies the following conditions: (a) normal brain tissue located as close as possible to an area where the tractography is torn or weakened in the DTI image (usually a white area on DWI in the case of acute cerebral infarction, a high signal on T2 / FLAIR in the case of chronic cerebral infarction, a high signal on CT in the case of acute trauma or cerebral hemorrhage, and a high signal on T2 / FLAIR in the case of chronic trauma or cerebral hemorrhage), and (b) a highly safe location (a location that will cause little damage even if bleeding or an allergic reaction occurs: other than the area generally called the eloquent area* in AVM), and (c) if necessary, a location as close as possible to the high signal area on the T2 / FLAIR image, avoiding it. On the other hand, if tractography is not visualized in the diffusion tensor image, (aa) the ROI for tractography is set (usually nerve fibers passing through three points: the precentral gyrus, the posterior limb of the internal capsule, and the pons) by referring to the tractography that appears when the precentral gyrus, the posterior limb of the internal capsule, and the pons are examined separately, and from among these, motor fibers that are normally expected in humans are selected. (bb) If (aa) does not appear either, the course of the nerve fibers is estimated by referring to the tractography on the contralateral side, and the damaged area shown as a high signal in the acute phase DWI image or the damaged area shown as a low signal in the chronic phase T2 / FLAIR image and the area where the estimated tractography points overlap are estimated to be the location where the motor fibers are torn, and the procedure for when tractography is visualized in the diffusion tensor image is followed.

[0101] In one embodiment, the administration site is selected by identifying the area damaged by the current cerebral infarction in the DWI region and excluding that area from the selection. For example, T2 hyperintensity is useful for identifying areas that have been damaged over time. Areas that are DWI negative but show significant edema in the T2 and FLAIR images may also be excluded from the selection. It may also be advantageous to visualize motor nerves in the DTI region and exclude the areas of the visualized motor fibers from the selection.

[0102] In one embodiment, the blood vessels that the disclosed method avoids as pathways include large veins that drain from the surface of the brain into the superior sagittal sinus.

[0103] In one embodiment, blood vessels can be identified using gadolinium-enhanced T1 images, where only blood vessels are depicted with a strong high signal intensity. Specifically, when the signal intensity of the brain is quantified as a pixel image, two peaks are identified: the brain parenchyma (low signal intensity) and the blood vessels (high signal intensity). Blood vessels can be identified by the high signal intensity. Alternatively, a conventional T1-weighted image without gadolinium can be simultaneously acquired and subtracted from the gadolinium-enhanced T1 image to obtain a similar pixel image signal intensity, and the resulting single peak (blood vessel) can be evaluated. Blood vessels can also be depicted using an original MRA (magnetic resonance angiography) image, where the signal intensity is measured in the pixel image and the peak value is higher than that of other brain regions.

[0104] In one embodiment, blood vessel identification is achieved by measuring at least one, two, three, or four of DWI, T2, FLAIR, and DTI on MRI images. While not wishing to be bound by theory, FLAIR, GdT1, and DTI are preferred. DWI is a convenient method in which the area of ​​cerebral infarction appears white for only one week after onset. This is usually used to determine whether or not a patient has had a cerebral infarction. Since the exemplary clinical trial included patients in the acute phase, DWI is very useful for determining the location of injury and the cause of paralysis. However, in patients in the chronic phase after a certain period of time, DWI may not provide much useful information because the white image no longer appears white (the period has already passed). Furthermore, DWI may not be able to evaluate trauma or cerebral hemorrhage. Furthermore, T2 and FLAIR images provide very similar results, with FLAIR providing the most information. Therefore, when considering the minimum sequence required for calculating the optimal injection site and route in an app, including FLAIR, gadolinium-enhanced T1, and DTI may be advantageous. Alternatively, the preferred sequence could be described as (1) FLAIR, (2) T2, and (3) gadolinium-enhanced T1. This is exemplified by the three parameters customarily used to build part of navigation software (e.g., that provided by Medtronic). As mentioned above, one example of a minimum requirement is FLAIR, GdT1, and DTI. An illustrative example would be to create a navigation system using FLAIR / GdT1 / T2, and then determine the location by viewing DWI and DTI on a separate computer.

[0105] In one embodiment, regions in the brain can be classified as follows when plotting signal intensity on T2-weighted MRI images and fluid-attenuated inversion-recovery (FLAIR) images:

[0106] [Table 1]

[0107] When it is sometimes difficult to distinguish between the FLAIR low signal intensity of the sulci and the FLAIR medium signal intensity of the normal brain parenchyma, it is possible to determine the location more accurately by using the T2 high signal intensity of the sulci and the T2 medium signal intensity of the normal brain parenchyma.

[0108] In one embodiment, the non-invasive sulcal pathways are identified by confirming them using T2-weighted MRI images and fluid-attenuated inversion-recovery (FLAIR) images. In T2 images, normal brain parenchyma appears as a medium signal, while sulci and intracerebral edema appear as high signal signals. In FLAIR images, normal brain parenchyma appears as a medium signal, sulci appear as low signal signals, and intracerebral edema appears as high signal signals. This facilitates the identification of sulci. Specifically, A) when the signal intensity of a pixel image of the brain is plotted in FLAIR, two peaks are present, distinguishing between normal brain parenchyma (medium signal) and sulci (low signal). These low signal peaks are identified as sulci. B) When the signal intensity of a pixel image of the brain is plotted in T2-weighted images, two peaks are present, distinguishing between normal brain parenchyma (medium signal) and sulci (high signal). These high signal peaks are identified as sulci. Sulci identified in both images are identified as actual sulci. In one embodiment, confirmation is performed using T2-weighted MRI images and fluid-attenuated inversion-recovery (FLAIR) images as follows: A) When the signal intensity of a pixel image of the brain is plotted using FLAIR, two peaks are present, one representing normal brain parenchyma (medium signal intensity) and the other representing sulci (low signal intensity). The low signal intensity areas are identified as sulci.

[0109] B) In T2-weighted images, when the signal intensity of the brain is plotted as a pixel image, two peaks are present, representing normal brain parenchyma (medium signal) and cerebral sulci (high signal). The high signal areas are identified as cerebral sulci. Sulci identified in both of these are determined to be actual sulci.

[0110] The present disclosure may be provided as a program for causing a computer to realize the above, or may be provided as a recording medium on which the program is recorded.

[0111] In another aspect, the present disclosure provides a system for specifying a passage area of ​​an injection needle for administering cells in cell therapy for a central nervous system disorder in a subject, the system including: A) an imaging device for acquiring image data of at least a portion of the brain of the subject; B) a computer device in communication with the imaging device for acquiring information about the brain of the subject, the computer device using the acquired image data and the information about the brain of the subject to depict blood vessels, specify a route range that does not penetrate the blood vessels, specify a non-invasive range of the cerebral sulcus that does not extend into the posterior cerebral sulcus after the needle is inserted into the brain, and set a route within an overlapping range of the route ranges calculated in D) and E); and G) a display unit for outputting a graphic display of the set route.

[0112] (Prevention of cerebrospinal fluid leakage) In one aspect, a method for preventing cerebrospinal fluid leakage from the brain of a subject includes the steps of: A) incising the dura mater present on the surface of the brain; and B) coagulating and adhering the arachnoid mater and pia mater on the brain surface at the planned puncture start site using an electrosurgical device such as a bipolar coagulation forceps, wherein the image or output conditions are set until the arachnoid mater becomes opaque or are known to cause opacity. Here, the image conditions known to cause opacity can be specified, for example, by setting the image level of the arachnoid mater displayed visually or via a camera or the like until microvessels present on the brain surface can no longer be identified, or by setting the image level to a level known to cause opacity depending on the type of output device.

[0113] The present disclosure may be provided as a program for causing a computer to realize the above, or may be provided as a recording medium on which the program is recorded.

[0114] In one embodiment, the prevention of cerebrospinal fluid leakage in the brain is in cell therapy for a central nervous system disorder in the subject.

[0115] In a further embodiment, the disclosed method for preventing cerebrospinal fluid leakage includes the step of C) administering to the subject cells needed.

[0116] In another aspect, the present disclosure provides a system for preventing cerebrospinal fluid leakage in the brain of a subject, the system including: A) an incision tool for incising the dura mater present on the surface of the brain; B) an electrosurgical instrument such as an electrosurgical instrument such as bipolar coagulation forceps, the electroirradiation instrument configured to coagulate and adhere the arachnoid membrane and pia mater on the surface of the brain at the intended puncture start site, and which can be set to image conditions or output conditions that are understood to cause the arachnoid membrane to become cloudy or to become cloudy; and C) a sensor capable of detecting the clouding of the arachnoid membrane.

[0117] In one aspect, the present disclosure provides a method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: i) acquiring image data of at least a portion of the subject's brain with an imaging device; ii) obtaining, by a computer device in communication with said imaging device, information about the subject's brain; iii) providing potential routes for administering the cells by the following steps: aa) selecting, by the computing device, a safe zone near the lesion location as an administration site; bb) identifying a route of administration to the selected administration site; cc) optionally selecting, by said computer device, an ablation location for passing an administration device for administering cells in the scalp; and iv) outputting the selected administration site as a graphical representation; Includes.

[0118] In another aspect, the present disclosure provides a method for identifying a route for administering cells in cell therapy for a central nervous system disorder in a subject, the method comprising: i) acquiring image data of at least a portion of the subject's brain with an imaging device; ii) obtaining, by a computer device in communication with said imaging device, information about the subject's brain; iii) providing potential routes for administering the cells by the following steps: a) optionally selecting, by the computer device, an ablation location for passing an administration device to administer cells in the scalp; b) selecting, with the computing device, an opening in the skull for passing the administration device to administer the cell therapy; c) using the computer device, identifying at least one brain pathway exclusion region selected from the group consisting of motor fibers, cerebral blood vessels, cerebral sulci, and functional areas using the acquired image data and data related to the subject's brain; d) selecting, by the computing device, a safe zone near the lesion location as an administration site; e) delineating an administration route between the opening and the administration site, the administration route being delineated including information about the brain pathway exclusion region, and optionally providing suitability information for the administration route from the information about the brain pathway exclusion region; and iv) outputting the selected administration site as a graphical representation; Includes.

[0119] In one aspect, the present disclosure provides a method for predicting the probability of an adverse effect of a cell therapy on a central nervous system disorder in a subject, the method comprising: 1) inputting a data group indicating the administration position of cells and data on the occurrence of adverse effects of cell therapy for each administration position of the cells into an artificial intelligence model as learning data, and causing the artificial intelligence model to learn; 2) acquiring a data set indicative of the location of cell administration; 3) inputting the data set indicating the administration position of the cells obtained in 2) into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; Includes.

[0120] In one embodiment, the group of data indicating the administration location of the cells includes at least one of the following data: the distance between the administration location and the brain surface, the distance between the administration location and the lesion location, the distance between the administration location and the edema area, and whether the administration location is other than the area called the eloquent area in a cerebral arteriovenous malformation (AVM).

[0121] In some embodiments, the group of data indicating the administration location of the cells includes a combination of the distance between the administration location and the brain surface, the distance between the administration location and the lesion location, the distance between the administration location and the edema area, and whether the administration location is other than a site called an eloquent area in a cerebral arteriovenous malformation (AVM).

[0122] In another aspect, the present disclosure provides a method for predicting the probability of occurrence of an adverse effect of a cell therapy on a central nervous system disorder in a subject, the method comprising: 1) inputting a data group indicating the area through which an injection needle for administering cells passes and data on adverse effects of cell therapy for each area through which the injection needle for administering cells passes into an artificial intelligence model as learning data, and allowing the artificial intelligence model to learn; 2) acquiring a data set indicating a passage area of ​​an injection needle for injecting cells; 3) inputting the data set obtained in 2) indicating the area through which the injection needle for injecting the cells passes into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; Includes.

[0123] In one embodiment, the group of data indicating the area through which the injection needle for administering the cells passes includes at least one of the following: the distance between the brain surface just below the skin through which the injection needle passes and the skull; whether the area just below the injection point of the injection needle is an eloquent area; whether there is a large vein just below the injection point of the injection needle; whether the injection needle passes through an artificial object such as an artificial bone, artificial dura mater, or titanium plate; the distance between the cerebral sulcus and the injection needle; and the distance between the injection needle and a large blood vessel in the brain.

[0124] In another embodiment, the data group indicating the area through which the injection needle for administering the cells passes includes a combination of the distance between the skull and the brain surface just below the skin through which the injection needle passes, whether the area just below the injection point of the injection needle is an eloquent area, whether there is a large vein just below the injection point of the injection needle, whether the injection needle passes through an artificial object such as an artificial bone, artificial dura mater, or titanium plate, the distance between the cerebral sulcus and the injection needle, and the distance between the injection needle and a large blood vessel in the brain.

[0125] In one aspect, the present disclosure provides a method for predicting the probability of an adverse effect of a cell therapy on a central nervous system disorder in a subject, the method comprising: 1) inputting a data group indicating the administration position of cells, a data group indicating the passage area of ​​an administration needle for administering cells to the administration position of cells, and data on adverse effects of cell therapy for each data group indicating the administration position of cells and the passage area of ​​an administration needle for administering cells to the administration position of cells, into an artificial intelligence model as learning data, and allowing the artificial intelligence model to learn; 2) acquiring a data group indicating a cell administration position and a data group indicating a passage area of ​​an administration needle for administering cells to the cell administration position; 3) inputting the data set indicating the administration position of the cells acquired in 2) and the data set indicating the passage area of ​​an administration needle for administering the cells to the administration position into the trained artificial intelligence model; 4) causing the trained artificial intelligence model to calculate the probability of adverse effects of cell therapy; Includes.

[0126] In one embodiment, the data group indicating the administration location of the cells includes a combination of the distance between the administration location and the brain surface, the distance between the administration location and the lesion location, the distance between the administration location and the edema area, and whether the administration location is other than a site called the eloquent area in a cerebral arteriovenous malformation (AVM).

[0127] In some embodiments, the group of data indicating the area through which the injection needle passes to administer cells to the cell administration site includes a combination of the distance between the brain surface just below the skin through which the injection needle passes and the skull, whether the area just below the injection point of the injection needle is an eloquent area, whether there is a large vein just below the injection point of the injection needle, whether the injection needle passes through an artificial object such as an artificial bone, an artificial dura mater, or a titanium plate, the distance between the cerebral sulcus and the injection needle, and the distance between the injection needle and a large blood vessel in the brain.

[0128] In another embodiment, the group of data indicating the administration location of the cells includes at least one of the distance between the administration location and the brain surface, the distance between the administration location and the lesion location, the distance between the administration location and the edema area, and whether the administration location is other than a location called the eloquent area in cerebral arteriovenous malformation (AVM), and the group of data indicating the area through which the administration needle will pass to administer the cells to the administration location includes at least one of the distance between the brain surface just below the skin through which the administration needle passes and the skull, whether the area just below the injection point of the administration needle is an eloquent area, whether there is a large vein just below the injection point of the administration needle, whether the administration needle passes through an artificial object such as an artificial bone, artificial dura mater, or titanium plate, the distance between the cerebral sulcus and the administration needle, and the distance between the administration needle and a large blood vessel in the brain.

[0129] The present disclosure also provides a program for executing the above-described method, a recording medium storing the program, and an apparatus and system for performing the above-described method. This method can be run on the Internet, and the obtained data can be made available to an administrator (e.g., via Google or Facebook), allowing the accumulation of data for improving the method. Postoperative images and motor function recovery evaluation data can also be input to evaluate adverse effects of cell therapy.

[0130] (Program structure example) In one embodiment, the present disclosure can be provided as a program that acquires MRI images of the brain of a patient with cerebral infarction, measures DWI, T2, FLAIR, and DTI for the acquired MRI images, and imports the images obtained by the measurements into the program.

[0131] This program performs the following steps to determine the cell administration site: It indicates areas that have been pre-loaded and are highly safe for cell administration, and that are unlikely to cause damage even if bleeding or an allergic reaction occurs (other than areas generally referred to as eloquent areas in AVMs), as safe cell administration regions. If the patient is in the acute phase of trauma or cerebral hemorrhage, it indicates areas with high signal intensity (at least 50 Hounsfield units) on CT as areas where cell administration is prohibited. It also indicates areas within 2, 1, or 3 cm of the brain surface as areas where cell administration is prohibited. It also indicates areas within 0.5 cm of areas that appear white on DTI images but not on DWI images as areas where edema is evident on T2 and FLAIR images as areas where cell administration is prohibited. It also indicates areas of interest (Region of Interest) on DTI images. The precentral gyrus, posterior limb of the internal capsule, and pons are selected as ROIs to visualize the motor fibers, and the area where the motor fiber trajectory data is lower than other areas (areas where the FA value is at least 50% lower) is identified as the lesion location.The area excluding the motor fiber area, with a radius of 1.5 cm centered on the identified lesion location, which is also a safe area for cell administration and excludes areas where cell administration is not possible, can be displayed as a candidate cell administration location.

[0132] Alternatively, it can be realized by the following configuration: For example, an MRI image of the brain of a patient with cerebral infarction is taken, and DWI, T2, FLAIR, and DTI are measured for the taken MRI image. The images obtained by the measurement are imported into a computer, and an exemplary program of the present disclosure determines the cell administration site and indicates, as a cell administration safe area, a previously imported area that is highly safe for cell administration and will cause little damage even if bleeding or an allergic reaction occurs (other than the area generally called the eloquent area in AVM). If the patient is in the acute phase of trauma or cerebral hemorrhage, areas with high signal intensity on CT are indicated as cell administration unsafe areas, and areas within 2 cm of the brain surface are indicated as cell administration unsafe areas. Areas with severe edema on T2 images and FLAIR images are indicated as cell administration unsafe areas. If the brain is severely damaged and motor fibers cannot be visualized even when the precentral gyrus, posterior limb of the internal capsule, and pons are selected as ROIs, or when the precentral gyrus, posterior limb of the internal capsule, and pons are visualized individually, the course of nerve fibers is estimated by reference to the contralateral healthy motor nerve, and an area with a radius of 1.5 cm from the identified damaged location, excluding the motor fiber area, which is a cell administration safe area and excludes the cell administration unsafe area, is indicated as a candidate cell administration location.

[0133] The present disclosure can also be provided as a program for determining the cell administration site. This program captures MRI images of the brain of a patient with cerebral infarction and measures DWI, T2, FLAIR, and DTI on the captured MRI images. The images obtained by the measurements are imported into a computer, and the program of the present disclosure performs the following to determine the cell administration site: That is, a location that has been imported in advance and is highly safe for cell administration and that will cause minimal damage even if bleeding or an allergic reaction occurs (generally, an eloquent site in AVM) is selected. The area other than the area called the "cerebral sulcus" (called the "cerebral sulcus") is designated as a safe area for cell administration. If the patient is in the chronic stage of cerebral infarction or the chronic stage of trauma / cerebral hemorrhage, there will be high signal intensity on T2 / FLAIR. (A) When the signal intensity of a pixel image of the brain is plotted on FLAIR, there will be two peaks distinguishable between normal brain parenchyma (intermediate signal intensity) and cerebral sulci (low signal intensity). These low signal intensity areas are determined to be cerebral sulci. B) When the signal intensity of a pixel image of the brain is plotted on T2-weighted images, there will be two peaks distinguishable between normal brain parenchyma (intermediate signal intensity) and cerebral sulci (high signal intensity). These high signal intensity areas are determined to be cerebral sulci. Sulci confirmed in both of these are determined to be actual cerebral sulci. ) is shown as a cell administration unavailable region, the region within 2 cm from the brain surface is shown as a cell administration unavailable region, the region within 0.5 cm from the area that appears white in the DTI image but not in the DWI image is shown as a cell administration unavailable region, and the area where edema is strong in the T2 image and FLAIR image is shown as a cell administration unavailable region. The precentral gyrus, posterior limb of the internal capsule, and pons are selected as ROIs to visualize the motor fibers, and the area where the motor fiber trajectory data is lower than other areas (areas where the FA value is at least 50% lower) is identified as the lesion location.The area excluding the motor fiber area, with a radius of 1.5 cm centered on the identified lesion location, which is also a safe area for cell administration and excludes areas where cell administration is not possible, can be displayed as a candidate cell administration location.

[0134] As another configuration example, for example, the program of the present disclosure can also determine the cell administration site when the brain is severely damaged. In this case, an MRI image of the brain of a patient with cerebral infarction is taken, and DWI, T2, FLAIR, and DTI are measured for the taken MRI image. The images obtained by the measurements are imported into a computer, and the cell administration site can be determined. Here, the computer program selects a location that is highly safe for cell administration and that will cause minimal damage even if bleeding or an allergic reaction occurs (generally eloquent in AVM), which has been imported in advance. The area (excluding the area called the "cell administration area") is shown as a safe area for cell administration. If the patient is in the chronic stage of cerebral infarction or the chronic stage of trauma / cerebral hemorrhage, areas with high signal intensity on T2 / FLAIR are shown as a safe area for cell administration. Areas within 2 cm of the brain surface are shown as a safe area for cell administration. Areas within 0.5 cm of areas that appear white on DTI images but not on DWI images are shown as a safe area for cell administration. Areas with strong edema on T2 and FLAIR images are shown as a safe area for cell administration. If the brain is severely damaged and motor fibers cannot be visualized even when the precentral gyrus, posterior limb of the internal capsule, and pons are selected as ROIs, or when the precentral gyrus, posterior limb of the internal capsule, and pons are selected individually, the course of nerve fibers is estimated with reference to healthy nerve fibers on the contralateral side, and the area with a radius of 1.5 cm around the identified damaged location, excluding the motor fiber area, which is also a safe area for cell administration and excludes the safe area for cell administration, can be shown as a candidate site for cell administration.

[0135] An example of a program in the present disclosure is one that selects one of the candidate cell administration locations and then uses the program to determine the cell administration route. This exemplary program captures MRI images of the brain of a patient with cerebral infarction and imports gadolinium-enhanced T1, T2, FLAIR, and DTI images of the captured MRI images into a computer. The program then performs the following steps to determine the cell administration route. Specifically, the program can indicate the skin region where the distance between the brain surface and the skull directly below the skin is less than 10 mm and where the apex of the gyrus is directly below the skin as the recommended injection region. For example, the distance between the brain surface and the skull can be classified into three levels: safe (recommended) if less than 5 mm, possible (medium difficulty) if 5 mm to less than 10 mm, and impossible (high difficulty) if 10 mm or more. This allows the provision of software (application) that allows physicians to select various routes. The numerical values ​​used to classify the distance between the brain surface and the skull into safe (recommended), possible (medium difficulty), and impossible (high difficulty) can also be freely changed by physicians.

[0136] Additionally, the area of ​​skin directly beneath the eloquent area is designated as a no-penetration area, and the area of ​​skin directly beneath a large vein on a gadolinium-enhanced T1 image is designated as a no-penetration area. The thickness of veins can be determined as follows: Quantifying the signal intensity of a pixelated image of the brain reveals two peaks: one representing the brain parenchyma (low signal intensity) and the other representing the blood vessels (high signal intensity). Alternatively, a conventional T1-weighted image without gadolinium can be simultaneously acquired and subtracted from the gadolinium-enhanced T1 image to obtain a similar pixelated image signal intensity, and the resulting single peak (blood vessel) can be evaluated. Furthermore, the original MRA (magnetic resonance angiography) image can be used to visualize blood vessels. The signal intensity can be measured on the pixelated image, and the peak value can be confirmed as being higher than that of other brain regions. In addition, areas with artificial objects such as artificial bones, artificial dura mater, or titanium plates can be marked as non-administration areas, and sulcal regions can be marked as non-administration areas on FLAIR / T2 images. Sulcal regions can be identified as follows: A) When plotting signal intensity on a pixel image of the brain using FLAIR, two peaks are present, distinguishing between normal brain parenchyma (medium signal) and sulci (low signal). These low-signal areas are identified as sulci. B) When plotting signal intensity on a pixel image of the brain using T2-weighted images, two peaks are present, distinguishing between normal brain parenchyma (medium signal) and sulci (high signal). These high-signal areas are identified as sulci. Sulci identified in both A) and B are identified as actual sulci. Here, not only is a route that penetrates the sulci not a desirable option, but the proximity of the needle to the sulci also increases the risk of damaging blood vessels. Therefore, the safety of a route can be classified based on the distance between the sulci and the needle. For example, classification can be done as follows: ·Safety (recommended) range: The distance between the cerebral sulcus and the needle is 5 mm or more. - Administration range (medium difficulty): The distance between the cerebral sulcus and the needle is 5mm or more and less than 10mm. -Area where administration is not possible (high difficulty): The distance between the cerebral sulcus and the needle is less than 10 mm (including cases where the needle penetrates the cerebral sulcus).

[0137] The numerical values ​​used to classify the distance between the cerebral sulcus and the needle into the safe (recommended) range, the administration possible range (medium difficulty), and the administration impossible range (high difficulty) can be freely changed by the physician.

[0138] Alternatively, gadolinium-enhanced T1 images can show areas within 1 mm of large intracerebral blood vessels as areas where administration is prohibited. Furthermore, since there is a high possibility of blood vessel damage when the needle is very close to a large intracerebral blood vessel, it is also possible to classify the safety of the route based on the distance between the needle and the large intracerebral blood vessel. For example, it can be classified as follows: · Safe (recommended) range: The distance between the needle and a large blood vessel in the brain is 5 mm or more. - Administration range (medium difficulty): The distance between the needle and a large blood vessel in the brain is 5 mm or more but less than 1 mm. -Area where administration is impossible (high difficulty): The distance between the needle and a large blood vessel in the brain is less than 1 mm (including cases where the needle penetrates the blood vessel). The numerical values ​​used to classify the distance between the needle and the large blood vessels in the brain into the safe (recommended) range, the range where administration is possible (medium difficulty), and the range where administration is not possible (high difficulty) can be freely changed by the doctor.

[0139] In addition, among the straight-line routes connecting the candidate cell administration location and the recommended insertion area, routes can be preferentially shown that have a distance between the brain surface and the skull that is within a safe (recommended) range, a distance between the cerebral sulcus and the needle that is within a safe (recommended) range, and a distance between the needle and a large blood vessel in the brain that is within a safe (recommended) range, and that do not pass through an area / area where administration is not possible.

[0140] Alternatively, an exemplary program can acquire MRI images of the brain of a patient with cerebral infarction, and import gadolinium-enhanced T1, T2, FLAIR, and DTI images from the acquired MRI images into a computer to determine the route of cell administration.

[0141] This program shows skin areas where the distance between the brain surface and the skull just below the skin is less than 5 mm and where the apex of the cerebral gyrus is just below the skin as recommended areas for insertion, and skin areas directly below the eloquent area as non-insertable areas. Skin areas with large veins just below the skin on gadolinium-enhanced T1 images are shown as non-insertable areas. Previous skin incision sites are shown as skin depressions on MRI images. Next, areas above previous incisions are shown as recommended incision areas, areas less than 3 cm from previous incisions as incisable areas, areas more than 3 cm away from previous incisions as non-insertable areas, and areas with artificial objects such as artificial bone, artificial dura mater, or titanium plates as non-insertable areas. FLAIR / In T2 images, the sulcal region is shown as an administration-prohibited region, and in gadolinium-enhanced T1 images, the region within 1 mm of large intracerebral blood vessels and sulcal blood vessels is shown as an administration-prohibited region.Of the straight-line routes connecting the candidate cell administration position and the recommended insertion and incision regions, routes in which the distance between the brain surface and the skull is within a safe (recommended) range, the distance between the sulcus and the needle is within a safe (recommended) range, and the distance between the needle and large intracerebral blood vessels is within a safe (recommended) range, and which do not pass through the administration-prohibited site / region, can be preferentially shown.

[0142] All references cited herein, including scientific literature, patents, patent applications, and the like, are incorporated by reference in their entirety to the same extent as if each were specifically set forth.

[0143] The present disclosure has been described above by showing preferred embodiments for ease of understanding. The present disclosure will be described below based on examples. However, the above description and the following examples are provided for illustrative purposes only and are not intended to limit the present disclosure. Therefore, the scope of the present disclosure is not limited to the embodiments or examples specifically described herein, but is limited only by the scope of the claims. [Example]

[0144] Examples are described below. Human subjects used in the following examples were treated with informed consent, where necessary, in accordance with the standards established by regulatory authorities and the Declaration of Helsinki, respecting ICH standards, in accordance with the ethical standards established by Hokkaido University, and in accordance with GCP. The standards advocated by the Declaration of Helsinki and ICH, as well as the various standards established by the Hokkaido University Ethics Committee, were observed. The reagents used were specifically those listed in the examples, but equivalent products from other manufacturers (e.g., Sigma-Aldrich) can also be used.

[0145] Example 1: Determining the administration site In this example, to determine the cell injection site, motor fibers are visualized in advance using brain MRI. The damaged areas of the visualized motor fibers (if the brain is severely damaged and the motor fibers are not visualized, healthy motor fibers on the contralateral side are used as a reference) are identified, and an injection site is selected that is as close as possible to the damaged area (within a 1.5 cm radius) and that is not thought to play an important role in neural function.

[0146] The procedure is as follows:

[0147] The injection site will be determined using at least DWI, T2, FLAIR, and DTI images.

[0148] First, the area damaged by the cerebral infarction is identified from the DWI image. (This area will not be injected because there is no blood flow and cells will die.) Using T2 and FLAIR images, we evaluate areas that are DWI negative (avoiding cell death) but have severe edema (which is reversible but not necessarily desirable for administration), and we visualize motor fibers using DTI images to evaluate where the motor fibers are torn.

[0149] The cell injection site should be selected to be close to the torn or weakened area on tractography (usually a white area on DWI) and also to be a safe location (a location that will cause minimal damage even if bleeding or an allergic reaction occurs; generally, this is outside the area known as the eloquent area in AVM). When selecting the site, care should be taken to avoid areas with high signal intensity on T2 / FLAIR images and inject the cells as close to these areas as possible.

[0150] If tractography cannot be visualized due to excessive damage, the course of nerve fibers is estimated using the contralateral tractography as a reference, and the cell administration site is determined by creating an estimated tractography.

[0151] To prevent cells from leaving the injection site, positions close to the brain surface (within 2 cm of the brain surface) are excluded from candidate injection sites.

[0152] The injection site is finally determined using MRI-based navigation software. The MRI used can be taken at another hospital. (Example 2: Administration location determination example 1) The location of cell administration was determined in a 74-year-old woman with lacunar infarction.

[0153] The DWI image revealed a white area in the right corona radiata, which was determined to be the site of infarction (Figure 1A). The DTI image showed that the infarcted area was a tractography pathway, i.e., motor nerve fibers (blue) were passing through the cerebral infarction (and the signal was weaker than on the other side). Therefore, it was determined that the motor fibers had been severed within this area, resulting in paralysis (Figure 1B). The white matter of the right superior caudate nucleus was selected, as this area is a silent area that rarely produces symptoms even if cerebral hemorrhage or cell allergy occurs (Figure 1C). 20 million cells were injected into the selected location. (result) 360 days after administration, there was a decrease in the National Institute of Health Stroke Scale (NIHSS), a stroke severity assessment scale, and improvements in the Functional Independence Measure (FIM) and Barthel Index (BI), but there was no change in the Fugl-Meyer Assessment (FMA) (Table 2).

[0154] [Table 2]

[0155] (Example 3: Administration location determination example 2) The location of cell administration was determined in a 67-year-old man with neonatal cerebral embolism and right middle cerebral vein occlusion.

[0156] The DWI image showed a white area from the corona radiata to the posterior limb of the internal capsule, and this area was determined to be the infarct site (Figure 2A). The DTI image showed that motor nerve fibers (blue) were passing through the cerebral infarction (and the signal was weaker than on the contralateral side), and it was determined that the motor fibers were severed within this area. Taking into account the infarct site and tractography (Figure 2B), the injection site was determined to be outside the infarct site confirmed by DWI (Figure 2C). 20 million cells were injected into the selected location.

[0157] (result) After 360 days of treatment, a decrease in NIHSS and improvements in FIM and BI were observed, but FMA remained unchanged. Improvements in motor function were observed over time (Table 3).

[0158] [Table 3]

[0159] Example 4: Administration site determination example 3 The location of cell administration was determined in a 58-year-old man with atherothrombotic infarction and right cervical carotid artery occlusion.

[0160] DWI revealed widespread cerebral infarction in the left hemisphere (Fig. 3A), but motor fibers were not visualized by tractography within the infarcted area (due to widespread damage) (Fig. 3B). Therefore, taking into account (1) normal brain tissue and (2) the contralateral and anatomically estimated motor fiber distribution, 20 million cells were administered to the subcortical white matter of the left postcentral gyrus (Fig. 3C).

[0161] (result) 360 days after administration, a decrease in NIHSS and an improvement in FIM were observed, but BI and FMA remained unchanged (Table 4).

[0162] [Table 4]

[0163] Example 5: Administration Site Determination Example 4 The location of cell administration was determined in a 64-year-old man with atherothrombotic infarction and right middle cerebral artery stenosis. DWI images revealed scattered high-intensity white areas in the left frontal lobe, and this area was determined to be the infarct site (Figure 4A). DTI images confirmed a weak tractography signal within the infarct site, and the signal was weaker than on the opposite side, indicating that motor fibers were disrupted within this area (Figure 4B). The injection site was determined to be as close as possible to this area, anterior and lateral to the infarct site confirmed by DWI (Figure 4C). 50 million cells were injected into the selected location.

[0164] (result) After 180 days of treatment, there was a decrease in NIHSS and improvements in FIM and BI, but no change in FMA (Table 5).

[0165] [Table 5]

[0166] (Example 6: Administration site determination example 5) A widespread cerebral infarction occurred in the right hemisphere (Figure 5A). It was found that motor nerve fibers (blue) were passing through the cerebral infarction (and the signal was weaker than on the other side), and it was thought that the nerve fibers were damaged and causing paralysis at the site where the tractography passed through in the DWI (Figure 5B). Therefore, cells were administered to the right caudate nucleus, which was considered to be safe and close to the site (Figure 5C).

[0167] (result) One year after surgery, improvements were observed in all scores: NIHSS, BI, FMA, and FIM (Table 6).

[0168] [Table 6]

[0169] (Example 7: Administration Site Determination Example 6) Because tractography in the left internal capsule passed through the cerebral infarction (positive on DWI) (Figures 6A and 6B), we concluded that the paralysis was caused by this area, and administered cells to the head of the left caudate nucleus, which was immediately adjacent to the cerebral infarction (DWI) (Figure 6C). (result) Six months after surgery, improvements were observed in all scores: NIHSS, BI, FMA, and FIM (Table 7).

[0170] [Table 7]

[0171] (Example 8: Administration site determination example 7) DWI revealed an acute cerebral infarction in the corona radiata of the deep white matter of the right frontal lobe (Figure 7A). Tractography was not visualized, but this was thought to be due to the infarction passing through the interior of the infarction (Figure 7B). Therefore, cells were administered from the contralateral side to the lateral white matter of the right caudate nucleus, which was considered safe and close to the expected tractography (Figure 7C). (result) One month after administration, improvements were observed in NIHSS, FIM, BI, and FMA compared with those 7 days before administration. There was no change in mRS (Table 8).

[0172] [Table 8]

[0173] Example 9: Determination of the passage area of ​​the administration needle In this example, a brain MRI was used to identify large veins on the brain surface in advance, and the needle was designed to avoid penetrating these areas during passage. Furthermore, a path was selected that would prevent the needle from entering the brain's sulci once inserted (entering the sulci could potentially damage the small veins and arteries running along the brain's surface). This technique can be described as a surgical procedure, or it can be written as a program.

[0174] The procedure is as follows:

[0175] MRI FLAIR, T2, and gadolinium-enhanced T1 images will be used to determine the route of cell administration.

[0176] If the skin has already been incised, that incision is basically used. If the intended burr hole is significantly off from the previous incision line, the skin is incised longer and Galea is peeled off.

[0177] The skin incision site is confirmed as a skin depression by importing MRI images into Medtronic's navigation calculation system, FlameLink.

[0178] To prevent postoperative infection, if possible, exclude areas where artificial objects such as artificial bone, artificial dura mater, or titanium plates are present from the administration route.

[0179] The burr hole is selected so that the insertion point does not overlap with the functional site.

[0180] If the brain is atrophied and significantly sunken (about 5 mm), incising the dura mater may be too far to reach the brain, which could result in an accident. Therefore, the administration route should be chosen to be the area where the brain surface is directly below the bone (the apex of the gyrus).

[0181] If the burr hole is to be positioned near the midline, there is a possibility that a large vein (which may form a venous lake) may be present that supplies the superior sagittal sinus (SSS). Therefore, use FlameLink to confirm beforehand that there are no large veins around the dural incision site.

[0182] Because there is a risk of damaging the relatively large blood vessels running on the brain surface if the needle enters the cerebral sulci, an administration route is selected that enters the brain parenchyma immediately below the burr hole and does not enter the cerebral sulci until it reaches the target administration location.To confirm the administration route, FLAIR / T2 images are used to confirm that the needle does not enter the cerebral sulci as it advances through the brain, and gadolinium images are used to confirm that it does not come into contact with large blood vessels within the brain or those around the sulci.

[0183] Example 10: Example of determining the passage area of ​​the administration needle The cell administration route was determined using MRI FLAIR, T2, and gadolinium-enhanced T1 images. Because the skin had been previously incised, the route was determined to be a burr hole using the incision. By importing MRI images into Medtronic's FlameLink navigation calculation system, the skin incision site was confirmed as a skin depression, and the administration route was selected to be the area where the brain surface was directly under the bone (the apex of the gyrus) and where the insertion point did not overlap with functional areas. After determining the administration route, FLAIR / T2 images were used to confirm that the needle advancing into the brain did not enter the cerebral sulci, and gadolinium images were used to confirm that it did not come into contact with large intracerebral blood vessels or blood vessels around the sulci. (result) No complications such as intracerebral hemorrhage were observed in any of the patients treated.

[0184] Example 11: Method for preventing cerebrospinal fluid leakage In this example, when the arachnoid membrane on the surface of the brain is incised, cerebrospinal fluid leaks out. Because the brain appears to float in the cerebrospinal fluid, brain shift (sinking) occurs over time. To prevent this, before incising the arachnoid membrane, an electrosurgical device such as bipolar coagulating forceps can be used to coagulate and adhere the arachnoid membrane and pia mater on the surface of the brain at the planned puncture site. This prevents the brain from shifting during needle insertion. This is particularly important when multiple punctures are required.

[0185] The procedure is as follows:

[0186] The arachnoid membrane was coagulated until it became cloudy, and then adhered to the pia mater.

[0187] Even when the arachnoid mater was incised while the pia mater was still attached, no cerebrospinal fluid leakage occurred, and cells could be administered to the originally planned site. No brain shift (sinking) occurred.

[0188] Example 12: Example 1 of a program for determining the cell administration position In this example, the cell administration position is determined using a program.

[0189] MRI images of the brain of a patient with cerebral infarction are taken, and DWI, T2, FLAIR, and DTI images of the taken MRI images are imported into the program.

[0190] The program performs the following steps to determine the site of cell administration: The safe area for cell administration is defined as a region where cells are pre-incorporated and where there is little risk of damage even if bleeding or an allergic reaction occurs (a region other than the eloquent area of ​​cerebral arteriovenous malformation (AVM)). The white areas in the DWI image are designated as areas where cell administration is not possible. The area within 2 cm from the brain surface is designated as a cell administration-unavailable area. Areas where edema is evident in T2 and FLAIR images (areas that meet both of the following criteria: A) areas of high signal intensity in FLAIR images plotted against signal intensity, and B) areas of high signal intensity in T2-weighted images plotted against signal intensity) are designated as areas where cell administration is not possible. In the DTI image, the precentral gyrus, posterior limb of the internal capsule, and pons are selected as the region of interest (ROI) to visualize the motor fibers. The area where the motor fiber data is lower than other areas (areas where the FA value (fractional anisotropy value) is at least 50% lower) is identified as the location of the lesion. The area with a radius of 1.5 cm centered on the identified lesion location, excluding the motor fiber site, which is also a safe area for cell administration and excludes the area where cell administration is not possible, is shown as a candidate cell administration location.

[0191] Example 13: Example 2 of a program for determining the cell administration position In this example, a program is used to determine the cell administration position when the brain is severely damaged.

[0192] MRI images of the brain of a patient with cerebral infarction are taken, and DWI, T2, FLAIR, and DTI are measured on the MRI images. The images obtained by the measurements are imported into the program.

[0193] The program performs the following steps to determine the site of cell administration: The safe area for cell administration is defined as a region where cells are pre-incorporated and where there is little risk of damage even if bleeding or an allergic reaction occurs (a region other than the eloquent area in AVM). The white areas in the DWI image are designated as areas where cell administration is not possible. The area within 2 cm from the brain surface is designated as a cell administration-unavailable area. Areas where edema is evident in T2 and FLAIR images (areas that meet both of the following criteria: A) areas of high signal intensity in FLAIR images plotted against signal intensity, and B) areas of high signal intensity in T2-weighted images plotted against signal intensity) are designated as areas where cell administration is not possible. If the brain is severely damaged and motor fibers cannot be visualized by selecting the precentral gyrus, posterior limb of the internal capsule, and pons as ROIs, or by visualizing only the precentral gyrus, posterior limb of the internal capsule, and pons, the course of nerve fibers is estimated by referring to the contralateral healthy cerebral nerve. The area where the tractography points overlap with the damaged area shown as high signal intensity on DWI images in the acute phase, or the damaged area shown as low signal intensity on T2 / FLAIR images in the chronic phase, is estimated to be the site of motor fiber rupture. The area with a radius of 1.5 cm centered on the identified lesion location, excluding the motor fiber site, which is also a safe area for cell administration and excludes the area where cell administration is not possible, is shown as a candidate cell administration location.

[0194] Example 14: Example 3 of a program for determining cell administration position In this example, the cell administration position is determined using a program.

[0195] MRI images of the brain of a patient with cerebral infarction are taken, and DWI, T2, FLAIR, and DTI are measured on the MRI images. The images obtained by the measurements are imported into the program.

[0196] The program performs the following steps to determine the site of cell administration: The safe area for cell administration is defined as a region where cells are pre-incorporated and where there is little risk of damage even if bleeding or an allergic reaction occurs (a region other than the eloquent area in AVM). If the patient is in the acute stage of trauma or cerebral hemorrhage, areas with high signal intensity (at least 50 Hounsfield units) on CT scans are designated as areas where cell administration is not possible. The area within 2 cm from the brain surface is designated as a cell administration-unavailable area. Areas with significant edema in T2 and FLAIR images are shown as areas where cell administration is not possible. In the DTI image, the precentral gyrus, posterior limb of the internal capsule, and pons are selected as the region of interest (ROI) to visualize the motor fibers, and the area where the motor fiber trajectory data is lower than other areas (areas where the FA value is at least 50% lower) is identified as the location of the lesion. The area with a radius of 1.5 cm centered on the identified lesion location, excluding the motor fiber site, which is also a safe area for cell administration and excludes the area where cell administration is not possible, is shown as a candidate cell administration location.

[0197] Example 15: Example 4 of a program for determining the cell administration position In this example, a program is used to determine the cell administration position when the brain is severely damaged.

[0198] MRI images of the brain of a patient with cerebral infarction are taken, and DWI, T2, FLAIR, and DTI are measured on the MRI images. The images obtained by the measurements are imported into the program.

[0199] The program performs the following steps to determine the site of cell administration: The safe area for cell administration is defined as a region where cells are pre-incorporated and where there is little risk of damage even if bleeding or an allergic reaction occurs (a region other than the eloquent area in AVM). If the patient is in the acute stage of trauma or cerebral hemorrhage, areas with high signal intensity on CT scans are shown as areas where cells cannot be administered. The area within 2 cm from the brain surface is designated as a cell administration-unavailable area. Areas with significant edema in T2 and FLAIR images are shown as areas where cell administration is not possible. If the brain is severely damaged and motor fibers cannot be visualized even when the precentral gyrus, posterior limb of the internal capsule, and pons are selected as ROIs, the course of nerve fibers can be estimated using the contralateral healthy motor nerve as a reference. The area with a radius of 1.5 cm centered on the identified lesion location, excluding the motor fiber site, which is also a safe area for cell administration and excludes the area where cell administration is not possible, is shown as a candidate cell administration location.

[0200] Example 16: Example 5 of a program for determining cell administration position In this example, the cell administration position is determined using a program.

[0201] MRI images of the brain of a patient with cerebral infarction are taken, and DWI, T2, FLAIR, and DTI are measured on the MRI images. The images obtained by the measurements are imported into the program.

[0202] The program performs the following steps to determine the site of cell administration: The safe area for cell administration is defined as a region where cells are pre-incorporated and where there is little risk of damage even if bleeding or an allergic reaction occurs (a region other than the eloquent area in AVM). If the patient is in the chronic stage of cerebral infarction or the chronic stage of trauma / cerebral hemorrhage, areas that meet both of the following criteria will be designated as areas where cell administration is not possible: A) areas with high signal intensity in FLAIR images plotted against signal intensity, and B) areas with high signal intensity in T2-weighted images plotted against signal intensity. The area within 2 cm from the brain surface is designated as a cell administration-unavailable area. Areas with significant edema in T2 and FLAIR images are shown as areas where cell administration is not possible. In the DTI image, the precentral gyrus, posterior limb of the internal capsule, and pons are selected as the region of interest (ROI) to visualize the motor fibers, and the area where the motor fiber trajectory data is lower than other areas (areas where the FA value is at least 50% lower) is identified as the location of the lesion. The area with a radius of 1.5 cm centered on the identified lesion location, excluding the motor fiber site, which is also a safe area for cell administration and excludes the area where cell administration is not possible, is shown as a candidate cell administration location.

[0203] Example 17: Example 6 of a program for determining cell administration location In this example, a program is used to determine the cell administration position when the brain is severely damaged.

[0204] MRI images of the brain of a patient with cerebral infarction are taken, and DWI, T2, FLAIR, and DTI are measured on the MRI images. The images obtained by the measurements are imported into the program.

[0205] The program performs the following steps to determine the site of cell administration: The safe area for cell administration is defined as a region where cells are pre-incorporated and where there is little risk of damage even if bleeding or an allergic reaction occurs (a region other than the eloquent area in AVM). If the patient is in the chronic stage of cerebral infarction or trauma / cerebral hemorrhage, areas with high signal intensity on T2 / FLAIR are shown as areas where cell administration is not possible. The area within 2 cm from the brain surface is designated as a cell administration-unavailable area. Areas with significant edema in T2 and FLAIR images are shown as areas where cell administration is not possible. If the brain is severely damaged and motor fibers cannot be visualized even when the precentral gyrus, posterior limb of the internal capsule, and pons are selected as ROIs, the course of nerve fibers can be estimated using healthy motor fibers on the contralateral side as a reference. The area with a radius of 1.5 cm centered on the identified lesion location, excluding the motor fiber site, which is also a safe area for cell administration and excludes the area where cell administration is not possible, is shown as a candidate cell administration location.

[0206] Example 18: Example 1 of a program for determining a cell administration route In this example, after one of the candidate cell administration locations is selected, the cell administration route is determined using a program.

[0207] MRI images of the brain of a patient with cerebral infarction are taken, and gadolinium-enhanced T1, T2, FLAIR, and DTI images of the taken MRI images are imported into the program.

[0208] The program performs the following steps to determine the route of administration of the cells: The brain regions are classified according to the distance between the brain surface and the skull just below the skin as follows:

[0209] Safe (recommended) range: The distance between the brain surface and the skull is less than 5 mm.

[0210] Administration range: The distance between the brain surface and the skull is 5 mm or more and less than 10 mm.

[0211] Area where administration is not possible: The distance between the brain surface and the skull is 10 mm or more. The area of ​​skin directly beneath the eloquent area is designated as a no-penetration area. On gadolinium-enhanced T1 images, areas of the skin with large veins directly underneath are shown as areas where needles cannot be inserted. Areas where artificial objects such as artificial bone, artificial dura mater, or titanium plates are present are indicated as areas where administration is not permitted. In FLAIR / T2 images, sulcal regions (areas that satisfy both (A) low signal areas in FLAIR images plotted against signal intensity, and (B) high signal areas in T2-weighted images plotted against signal intensity) are shown as non-administrable areas. According to the distance between the needle and the cerebral sulcus, the brain regions are classified as follows:

[0212] Safe (recommended) range: The distance between the cerebral sulcus and the needle is 5 mm or more.

[0213] Administration range: The distance between the cerebral sulcus and the needle is 1 mm or more and less than 5 mm.

[0214] Area where administration is not possible: The distance between the cerebral sulcus and the needle is less than 1 mm (including cases where the needle penetrates the cerebral sulcus). On gadolinium-enhanced T1 images, the brain regions are classified as follows according to the distance between the needle and the large intracerebral blood vessels:

[0215] Safe (recommended) range: The distance between the needle and a large blood vessel in the brain is 5 mm or more.

[0216] Administration range: The distance between the needle and a large blood vessel in the brain is 1 mm or more but less than 5 mm.

[0217] Unadministerable range: The distance between the needle and a large blood vessel in the brain is less than 1 mm (including cases where the needle penetrates a blood vessel). Among the straight-line routes connecting the candidate cell administration location and the recommended insertion area, routes that have a safe (recommended) range for the distance between the brain surface and the skull, a safe (recommended) range for the distance between the cerebral sulcus and the needle, and a safe (recommended) range for the distance between the needle and a large blood vessel in the brain, and that do not pass through areas / areas where administration is not possible, are given priority.

[0218] Example 19: Example 2 of a program for determining a cell administration route In this example, after one of the candidate cell administration locations is selected, the cell administration route is determined using a program.

[0219] MRI images of the brain of a patient with cerebral infarction are taken, and gadolinium-enhanced T1, T2, FLAIR, and DTI images of the taken MRI images are imported into the program.

[0220] The program performs the following steps to determine the route of administration of the cells: The recommended area for insertion is the skin area where the distance between the brain surface and the skull directly below the skin is less than 5 mm and the apex of the gyrus is directly below the skin. The area of ​​skin directly beneath the eloquent area is designated as a no-penetration area. On gadolinium-enhanced T1 images, areas of the skin with large veins directly underneath are shown as areas where needles cannot be inserted. Previous skin incision sites are shown as skin depressions on MRI images, and the area above the previous incision is then shown as the recommended incision area, the area less than 3 cm from the previous incision as the incisable area, and the area more than 3 cm away from the previous incision as the non-incisable area. Areas where artificial objects such as artificial bone, artificial dura mater, or titanium plates are present are indicated as areas where administration is not permitted. - On FLAIR / T2 images, the sulcal region is shown as an area where administration is not permitted. On gadolinium-enhanced T1 images, areas within 1 mm of large intracerebral blood vessels and sulcal blood vessels are designated as non-administration areas. Among the straight-line routes connecting the candidate cell administration location and the recommended insertion and incision areas, routes that are within the safe (recommended) range of the distance between the brain surface and the skull, the safe (recommended) range of the distance between the cerebral sulcus and the needle, and the safe (recommended) range of the distance between the needle and large blood vessels in the brain, and that do not pass through areas / areas where administration is not possible, are shown preferentially.

[0221] Example 20: Example 1 of a system for preventing cerebrospinal fluid leakage In this embodiment, a system for preventing cerebrospinal fluid leakage is disclosed, using the degree of opacity of the arachnoid membrane as an index.

[0222] This system can be used to determine the degree of opacity of the arachnoid membrane during ablation. This system consists of a camera part that obtains an image of the state of the arachnoid membrane, and a judgment part that judges the degree of opacity of the arachnoid membrane image obtained from the camera part. The image of the arachnoid membrane during ablation obtained from the camera part is sent to the judgment part. Upon receiving the image of the arachnoid membrane during ablation, the judgment part compares it with the image of the arachnoid membrane before ablation. If blood vessels visible in the image of the arachnoid membrane before ablation are no longer visible in the image of the arachnoid membrane during ablation, the judgment part displays a warning to stop the ablation.

[0223] Example 21: Example 2 of a system for preventing cerebrospinal fluid leakage In this embodiment, a system for preventing cerebrospinal fluid leakage is disclosed, using the cauterization time and bipolar output as indicators.

[0224] The system predicts the time required for ablation by inputting the bipolar power and the area of ​​the area to be ablated. The system starts ablation and displays a warning to stop ablation after the predicted ablation time has elapsed. Example 22: Prediction of the probability of adverse effects of cell therapy based on the location of cell administration (1) Target patients The target patients are those with cerebral infarction. (2) MRI imaging Brain MRI images were taken for each patient at the subacute and chronic stages. The images were taken using an MRI system (3T Achieva TX (Philips Medical Systems)) with the default settings (b = 0, 1000 s mm-2, The imaging was performed using a 3D imager with a TR / TE of 5032 / 85 msec, NEX of 1, voxel size of 3 x 3 x 3 mm3, no. of slices of 43, and 32 diffusion gradient directions. (3) MRI image analysis Based on the MRI images taken, the distance from the brain surface, the distance from the lesion location in the brain, the distance from the edema area, and whether the area is outside the eloquent area of ​​the cerebral arteriovenous malformation (AVM) are evaluated, and the location for cell administration is determined. (4) Preparation and administration of bone marrow stem cells After enrollment, the patient's bone marrow will be collected promptly, and cell culture and bone marrow stem cell preparation will be carried out in the Cell Processing Laboratory of the Hokkaido University Hospital Clinical Research and Development Center. The prepared bone marrow stem cells (20 million or 50 million cells per patient) will be administered directly into the patient's brain 3 to 5 weeks after bone marrow collection. (5) Adverse Impact Assessment After administration, patients will be evaluated for any adverse effects attributable to cell therapy (such as adverse effects on motor function, sensory function, language function, or vision, or blood loss). (6) Results It has been found that the probability of adverse effects from cell therapy is correlated with the distance from the brain surface, the distance from the lesion location in the brain, the distance from the edema area, and whether the area is outside the eloquent area of ​​a cerebral arteriovenous malformation (AVM). By displaying these results, those skilled in the art can be helped to make the optimal decision regarding the administration location to be adopted. Example 23: Prediction of the probability of adverse effects of cell therapy based on the cell administration route (1) Target patients The target patients are those with cerebral infarction. (2) MRI imaging Brain MRI images were taken for each patient at the subacute and chronic stages. The images were taken using an MRI system (3T Achieva TX (Philips Medical Systems)) with the default settings (b = 0, 1000 s mm-2, The imaging was performed using a 3D imager with a TR / TE of 5032 / 85 msec, NEX of 1, voxel size of 3 x 3 x 3 mm3, no. of slices of 43, and 32 diffusion gradient directions. (3) MRI image analysis Based on the MRI images taken, the following are evaluated to determine the cell administration route: the distance between the skull and the brain surface just below the skin where the injection needle passes; whether the area just below the injection point of the injection needle is an eloquent area; whether there is a large vein just below the injection point of the injection needle; whether the injection needle passes through an artificial object such as an artificial bone, artificial dura mater, or titanium plate; the distance between the cerebral sulcus and the injection needle; and the distance between the injection needle and a large blood vessel in the brain. (4) Preparation and administration of bone marrow stem cells After enrollment, the patient's bone marrow will be collected promptly, and cell culture and bone marrow stem cell preparation will be carried out in the Cell Processing Laboratory of the Hokkaido University Hospital Clinical Research and Development Center. The prepared bone marrow stem cells (20 million or 50 million cells per patient) will be administered directly into the patient's brain 3 to 5 weeks after bone marrow collection. (5) Adverse Impact Assessment After administration, patients will be evaluated for any adverse effects attributable to cell therapy (such as adverse effects on motor function, sensory function, language function, or vision, or blood loss). (6) Results It has been found that the probability of adverse effects from cell therapy is correlated with the distance between the brain surface just below the skin through which the administration needle passes and the skull, whether the area just below the injection point of the administration needle is an eloquent area, whether there is a large vein just below the injection point of the administration needle, whether the administration needle passes through an artificial object such as an artificial bone, artificial dura mater, or titanium plate, the distance between the cerebral sulcus and the administration needle, and the distance between the administration needle and a large blood vessel in the brain. By displaying these results, those skilled in the art can help make the optimal decision regarding the administration route to be adopted. Example 24: Prediction of the probability of adverse effects of cell therapy based on the cell administration location and the cell administration route for administration to the cell administration location (1) Target patients: Patients with cerebral infarction. (2) MRI imaging Brain MRI images were taken for each patient at the subacute and chronic stages. The images were taken using an MRI system (3T Achieva TX (Philips Medical Systems)) with the default settings (b = 0, 1000 s mm-2, The imaging was performed using a 3D imager with a TR / TE of 5032 / 85 msec, NEX of 1, voxel size of 3 x 3 x 3 mm3, no. of slices of 43, and 32 diffusion gradient directions. (3) MRI image analysis Based on the MRI images taken, the distance from the brain surface, the distance from the lesion in the brain, the distance from the edema area, and whether the area is outside the eloquent area of ​​cerebral arteriovenous malformation (AVM) are evaluated to determine the location for cell administration.The cell administration route is then determined by evaluating the distance between the brain surface just below the skin where the injection needle passes and the skull, whether the area just below the injection point of the injection needle is in the eloquent area, whether there is a large vein just below the injection point of the injection needle, whether the injection needle passes through artificial objects such as artificial bone, artificial dura mater, or titanium plate, the distance between the cerebral sulcus and the injection needle, and the distance between the injection needle and large blood vessels in the brain. (4) Preparation and administration of bone marrow stem cells After enrollment, the patient's bone marrow will be collected promptly, and cell culture and bone marrow stem cell preparation will be carried out in the Cell Processing Laboratory of the Hokkaido University Hospital Clinical Research and Development Center. The prepared bone marrow stem cells (20 million or 50 million cells per patient) will be administered directly into the patient's brain 3 to 5 weeks after bone marrow collection. (5) Adverse Impact Assessment After administration, patients will be evaluated for any adverse effects attributable to cell therapy (such as adverse effects on motor function, sensory function, language function, or vision, or blood loss). (6) Results It has been found that the probability of adverse effects of cell therapy is correlated with the distance from the brain surface, the distance from the lesion location in the brain, the distance from the edema area, whether the area is other than the area called the eloquent area in cerebral arteriovenous malformation (AVM), the distance between the brain surface directly below the skin where the administration needle passes and the skull, whether the area directly below the injection point of the administration needle is an eloquent area, whether there is a large vein directly below the injection point of the administration needle, whether the administration needle passes through an artificial object such as an artificial bone, artificial dura mater, or titanium plate, the distance between the cerebral sulcus and the administration needle, and the distance between the administration needle and a large blood vessel in the brain. Displaying these results can help those skilled in the art make optimal decisions about the injection location and route to be adopted.

[0225] (Note) Although the present disclosure has been illustrated using preferred embodiments thereof, it is understood that the scope of the present disclosure should be interpreted solely by the claims. It is understood that the patents, patent applications, and other documents cited herein are incorporated by reference in their entirety as if the contents themselves were specifically set forth herein. This application claims priority to Japanese Patent Application No. 2019-239560, filed on December 27, 2019, with the Japan Patent Office, the contents of which are incorporated by reference in their entirety. [Industrial Applicability]

[0226] The present disclosure provides various approaches to successful cell therapy of the brain and finds applicability in the medical technology and medical device industries.

Claims

[Claim 1] The invention as shown in the drawings.

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