Method and system for planning SEEG deep electrode placement path based on medical imaging

Abstract

The present invention discloses a method and system for planning a SEEG deep electrode placement path based on medical images, wherein the method comprises: receiving medical image data of the brain of an epileptic patient; performing data fusion on the medical image data to obtain a target brain anatomical image, wherein the target brain anatomical image is annotated with a plurality of cortical target position ranges and a plurality of cortical entry point positions; matching and searching a target experience module in an experience database based on the anatomical-electrical-clinical evidence of the epileptic patient, wherein the target experience module includes a plurality of fixed path combinations, and each path has a fixed cortical entry point and target range; the experience database is established based on prior experience; and the target SEEG electrode path is selected based on the individual characteristic dynamics of the target brain anatomical image and the target experience module calculation. The optimal path of the SEEG electrode for epilepsy is determined for an individual.

Description

Technical Field

[0001] The present invention relates to the technical field of stereotactic electroencephalogram (EEG) data processing, and in particular to a method and system for planning a SEEG deep electrode placement path based on medical imaging. Background Art

[0002] Epilepsy is a central nervous system disease caused by sudden abnormal discharges of brain neurons. It is one of the most common neurological diseases worldwide.

[0003] At present, there are three main treatments for epilepsy: drug therapy, surgical treatment, and neuromodulation therapy. Drug therapy is currently the most important treatment method. About 70% of epilepsy can be controlled by drugs, but there are still about 30% of patients who cannot be treated with drugs. These patients have drug-resistant epilepsy, and surgical resection of the epileptogenic lesion is the best choice for treatment. Stereotactic electroencephalography (SEEG) is a method of placing deep electrodes into specific locations deep in the brain (that is, target points) through minimally invasive surgery, and locating epileptogenic areas through electrical signals. For the target location area of ​​​​electrode placement, it is usually mainly dependent on the doctor's clinical experience to design the electrode placement path.

[0004] In the prior art, there are also methods of planning electrode placement paths with the help of computers. For example, a Chinese patent with publication number CN109771033A discloses a stereotactic EEG electrode surgery planning method and system, which segments multimodal brain imaging data into specific brain structures, such as gray matter, white matter, etc., interactively delineates areas of interest such as suspected lesions, and automatically generates suitable direct-insert electrodes to place targets based on the delineated areas. This method of planning paths based on targets relies on manual delineation of suspected lesions. In fact, this method has assumed the location of the target before planning.

[0005] The theory of localization of the epileptogenic zone emphasizes the identification and location of the epileptogenic zone. The theory of localization of the epileptogenic zone emphasizes comprehensive and multi-dimensional information analysis in order to understand and locate the epileptogenic zone more comprehensively and dynamically. The epileptogenic zone refers to the starting area that triggers epileptic seizures. Factors that need to be considered include the type and range of electrophysiological activities and normal physiological functions. In the prior art, the positioning method that relies on the target focuses on the accuracy of anatomy and geometry. Specifically, the prior art solutions generally assume that the specific location of the target is known, and then the electrode path is planned based on the specific location, which may ignore the electrophysiological characteristics and dynamic changes of the epileptogenic zone.

[0006] Therefore, when the target location is uncertain, how to plan the SEEG deep electrode placement path to ensure the optimal path distribution of each SEEG deep electrode is a technical problem that needs to be solved urgently. Summary of the invention

[0007] Based on the above situation, the main purpose of the present invention is to provide a method and system for planning the SEEG deep electrode placement path based on medical imaging, so as to plan the SEEG deep electrode placement path to ensure the optimal path distribution of each SEEG deep electrode when the target position is uncertain.

[0008] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0009] In a first aspect, an embodiment of the present invention discloses a method for planning a SEEG deep electrode placement path based on medical imaging, comprising:

[0010] Step S100, receiving medical image data of the brain of an epileptic patient, wherein the medical image data is acquired by an image acquisition device from the brain of the epileptic patient;

[0011] Step S200, performing data fusion on the medical image data to obtain a target brain anatomical image, wherein the target brain anatomical image is annotated with a plurality of cortical target point position ranges and a plurality of cortical entry point positions, the cortical entry points are located in the convex cortical area of ​​the brain, and the target point position range is the non-convex area of ​​the brain on the same side of the cortical entry points;

[0012] Step S300, matching and searching for a target experience module in an experience database based on the anatomical, electrical and clinical evidence of an epilepsy patient, wherein the target experience module includes a plurality of fixed path combinations, each path having a fixed cortical entry point range and a cortical target point position range; the experience database is established based on prior experience;

[0013] Step S400, based on the individual characteristics of the target brain anatomical image, the restriction conditions and the target experience module, the target SEEG electrode path is dynamically calculated and screened, and the target SEEG electrode path represents the insertion path from the target cortical entry point to the target target point, and the target SEEG electrode path is the path of the target point position range of multiple SEEG electrodes.

[0014] Optionally, in step S400:

[0015] The restriction conditions include one or more of avoiding critical areas, the lower limit of the distance between the SEEG electrode and the blood vessel, and the evaluation of the cranial angle; and, including:

[0016] The target SEEG electrode path is obtained by screening through the restriction conditions.

[0017] Optionally, the step S420 includes: weighting and scoring each factor in the restriction condition to obtain an evaluation score of each electrode path; and determining the electrode path with the highest evaluation score as the target SEEG electrode path.

[0018] Optionally, the cranial insertion angle is evaluated as follows: the smaller the absolute value of the difference between the angle of the SEEG electrode and the skull and 90°, the better.

[0019] Optionally, between step S200 and step S300, the following steps are further included:

[0020] Step S210, dividing the target brain anatomical image into brain regions according to a preset rule;

[0021] In the step S300, the target brain anatomical image after the region division is used as the object to match and search for the target experience module in the experience database.

[0022] Optionally, between step S200 and step S400, the following steps are further included:

[0023] Step S220, obtaining the key area information of the patient's brain, and marking the key area in the target brain anatomical image according to the key area information.

[0024] Optionally, in step S100, the image acquisition device includes magnetic resonance imaging and / or CT.

[0025] Optionally, in step S300, the anatomical-electrical-clinical evidence includes:

[0026] Based on the patient's individualized epilepsy imaging results, scalp EEG characteristic data between attacks and during attacks, and the patient's characteristic seizure symptom data captured by video EEG monitoring.

[0027] In a second aspect, an embodiment of the present invention discloses a device for planning a SEEG deep electrode placement path based on medical imaging, comprising:

[0028] An image data acquisition module, used for receiving medical image data of the brain of an epileptic patient, wherein the medical image data is acquired by an image acquisition device from the brain of the epileptic patient;

[0029] A data fusion module, used for fusing the medical image data to obtain a target brain anatomical image, wherein the target brain anatomical image is annotated with a plurality of cortical target point position ranges and a plurality of cortical entry point positions, wherein the cortical entry point is located in a convex cortical area of ​​the brain, and the target point position range is a non-convex area of ​​the brain on the same side of the cortical entry point;

[0030] A target module matching module is used to match and search for a target experience module in an experience database based on the anatomical, electrical and clinical evidence of epilepsy patients, wherein the target experience module includes a plurality of fixed path combinations, each path having a fixed cortical entry point range and a cortical target point position range; the experience database is established based on prior experience;

[0031] The target path adjustment module is used to dynamically calculate and screen the target SEEG electrode path based on the individual characteristics of the target brain anatomical image, the restriction conditions and the target experience module. The target SEEG electrode path is the path of multiple SEEG electrodes placed in the target position range.

[0032] In a third aspect, an embodiment of the present invention discloses a system for planning a SEEG deep electrode placement path based on medical imaging, comprising:

[0033] An image acquisition device, used to acquire target sampled image data from the patient's brain;

[0034] The controller adopts the method disclosed in the first aspect to perform epilepsy SEEG electrode path planning; or includes the device disclosed in the second aspect.

[0035] In a fourth aspect, an embodiment of the present invention discloses a computer-readable storage medium having a computer program stored thereon, wherein the computer program stored in the storage medium is used to be executed by a processor to implement the method disclosed in the first aspect above.

[0036]

Beneficial Effects

[0037] According to a method and system for planning a SEEG deep electrode placement path based on medical imaging disclosed in an embodiment of the present invention, after receiving medical imaging data of the brain of an epileptic patient, the medical imaging data is fused to obtain a target brain anatomical image, and the target brain anatomical image is annotated with a number of target point position ranges and a number of cortical entry point position ranges. According to the target brain anatomical image, a target experience module can be matched and searched in an experience database, that is, a matching target experience module can be obtained using prior knowledge, so that the module can better match the current target brain characteristics. On this basis, the target experience module is dynamically adjusted using individual characteristics and restrictions, so as to obtain a target SEEG electrode path that is more in line with the target brain characteristics, thereby realizing the rapid acquisition of a matching experience module based on prior knowledge, and the target experience module associates the cortical entry point and the cortical target That is, rather than considering the position of the target point alone, the target experience module is determined by the path correspondence between the cortical entry point and the target point, so that the selected target experience module can organically combine the cortical entry point and the cortical target point, and dynamically adjust the target SEEG electrode path according to the target brain characteristics, thereby realizing the optimization of the SEEG electrode path, that is, it can ensure that the optimal electrode path of each SEEG deep electrode is found for different individuals; and, since the target brain anatomical image is annotated with a number of cortical target point position ranges without assuming the actual target point, that is, the target point is unknown before the SEEG electrode is implanted, but the actual target point (that is, the real epileptogenic brain area) is confirmed by the electrode coverage pattern that conforms to its epilepsy network. Compared with the prior art where the target point itself may be wrong (that is, the assumption is wrong), the present application increases the probability of finding the real epileptogenic brain area.

[0038] Other beneficial effects of the present invention will be explained in the specific implementation manner through the introduction of specific technical features and technical solutions. Through the introduction of these technical features and technical solutions, those skilled in the art should be able to understand the beneficial technical effects brought about by the technical features and technical solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The embodiments of the present invention will be described below with reference to the accompanying drawings.

[0040] Figure 1 A flowchart of a method for planning a SEEG deep electrode placement path based on medical imaging disclosed in this embodiment;

[0041] Figure 2 This is a schematic diagram of the structure of a device for planning a SEEG deep electrode placement path based on medical imaging, which is also disclosed in this embodiment;

[0042] Figure 3 This is a schematic block diagram of a system for planning a SEEG deep electrode placement path based on medical imaging disclosed in this embodiment. DETAILED DESCRIPTION

[0043] The present invention is described below based on embodiments, but the present invention is not limited to these embodiments. In the following detailed description of the present invention, some specific details are described in detail. In order to avoid confusing the essence of the present invention, known methods, processes, procedures, and components are not described in detail.

[0044] In addition, persons of ordinary skill in the art will appreciate that the drawings provided herein are for illustration purposes and are not necessarily drawn to scale.

[0045] Unless the context clearly requires otherwise, throughout the specification and claims, the words "include", "comprising" and similar words should be interpreted in an inclusive sense rather than an exclusive or exhaustive sense; that is, in the sense of "including but not limited to".

[0046] In the description of the present invention, it should be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0047] In order to determine the optimal path of SEEG electrodes for an individual, this embodiment discloses a method for planning the SEEG deep electrode placement path based on medical imaging. Please refer to Figure 1 , Figure 1 The flowchart of a method for planning a SEEG deep electrode placement path based on medical imaging disclosed in this embodiment includes: step S100, step S200, step S300 and step S400, wherein:

[0048] Step S100, receiving medical imaging data of the brain of an epileptic patient. In this embodiment, the medical imaging data is acquired by an image acquisition device from the brain of an epileptic patient. Specifically, the image acquisition device includes magnetic resonance and / or CT. In the specific implementation process, magnetic resonance images can be acquired by magnetic resonance, and CT images can be acquired by CT equipment. Of course, DSA images can also be acquired. In this embodiment, the medical imaging data is one or more combinations of the aforementioned images. In this embodiment, by receiving medical imaging data of the brain of an epileptic patient, it is convenient to plan the SEEG deep electrode placement path based on the medical imaging data as an object.

[0049] Step S200, data fusion is performed on the medical image data to obtain a target brain anatomical image. In the specific implementation process, an individualized brain anatomical image with coordinate values ​​can be calculated and output according to the medical image data. For example, a neural network model can be used to perform data fusion on the medical image data, and a brain anatomical image with a three-dimensional coordinate system is obtained by fusion. On this basis, the individualized brain anatomical image is annotated with several cortical target position ranges and several cortical entry point positions, wherein the cortical entry point is located in the convex cortical area of ​​the brain, and each area can be connected or disconnected; the target position range is the non-convex area of ​​the brain on the same side of the cortical entry point, and it contains the actual target of the epileptogenic brain area (that is, the target position range includes the real epileptogenic brain area and may also include the non-epileptic brain area). Specifically, the brain is divided into left and right hemispheres. In this embodiment, the target position range and the corresponding cortical entry point are in the same hemisphere. Generally speaking, the target position is located in the midline of the brain and the medial cortex. In the present application, the target in a narrow sense refers to the real epileptogenic brain area. Before the SEEG electrode is implanted, the target in a narrow sense is unknown. Therefore, compared with the solution in the prior art that directly assumes the target and then plans the implantation path based on the assumed target, in this embodiment, no specific target is assumed in advance, but the target position range is divided. On this basis, multiple SEEG deep electrodes are used to implant these ranges, and the epileptogenic network is used to accurately locate the target, thereby making the clinical data more accurate and reliable.

[0050] Step S300, match and search the target experience module in the experience database based on the anatomical-electrical-clinical evidence of the epilepsy patient. In a specific embodiment, in step S300, the anatomical-electrical-clinical evidence includes the individualized epilepsy imaging results based on the patient, the scalp EEG characteristics during the interictal and ictal periods, and the patient's characteristic seizure symptoms captured by video EEG monitoring. The user forms clinical evidence of the location of the epileptogenic zone by comprehensively summarizing these data, and then selects the model corresponding to the clinical evidence in the system. In this embodiment, by selecting a common epilepsy network model for the design of intracranial EEG, the errors or mistakes caused by human input can be reduced, the probability of error is reduced, and the accuracy of data acquisition is ensured; in addition, the user's input efficiency is also improved.

[0051] In this embodiment, the target experience module includes several fixed path combinations, each path has a fixed cortical entry point and a cortical target position range. The experience database presets at least one corresponding cortical entry point placement path for each target, that is, the placement channel of the SEEG deep electrode from the cortical entry point to the target point. On this placement path, the SEEG deep electrode can collect EEG signals in the entry point brain area, target area and path. Of course, these preset paths should try to avoid passing through key brain structures to reduce the probability of damaging key brain structures.

[0052] In this embodiment, the so-called experience database is established based on prior experience. Specifically, the implantation path combinations of multiple patients in the past are entered into the experience database. Specifically, for example, brain anatomical images of 200 epilepsy patients are obtained, and the implantation paths and implantation effects of these patients are scored, and the most commonly used path combinations are entered into the database. In other words, the path combinations stored in the experience database are also screened to select relatively better path combinations. In this way, the implantation path can be planned efficiently and safely, and since the path combinations in the experience database are screened, the number of alternative test path combinations can also be reduced, thereby further reducing the amount of calculation.

[0053] Step S400, dynamically calculate and select the target SEEG electrode path based on the individual characteristics, constraints and target experience module of the target brain anatomical image. In this embodiment, the so-called target SEEG electrode path represents the insertion path from the target cortical entry point to each suspected target point in the target point range, and the target cortical entry point is one of several cortical entry points, so that the SEEG electrode is inserted from the target cortical entry point to each suspected target point in the target point range according to the target SEEG electrode path. In the specific implementation process, since the target experience module has been matched and found in the experience database, it is only necessary to calculate and filter the target SEEG electrode path from the target experience module, thereby reducing the amount of calculation and efficiently planning the insertion path. In addition, in the calculation and screening process, the dynamic calculation is based on the individual characteristics of the epilepsy patient, so the screened target SEEG electrode path can meet the individual characteristics of the epilepsy patient.

[0054] It should be emphasized that the target refers to the real epileptogenic brain area, which is the area where the onset of epilepsy is expected to be captured through electrode monitoring. Before the SEEG electrode is implanted, the target in a narrow sense is unknown. In other words, if the target of the epileptogenic brain area is known, the implantation of SEEG will be meaningless. In this embodiment, in the actual clinical operation process, multiple SEEG electrodes are implanted in the brain to form a confirmed epileptogenic network. Some of these electrodes are designed to be located in the suspected epileptogenic area. In addition, the human cerebral cortex is distributed on both sides, and the epileptogenic area can be located in any part. Therefore, in this application, the entry point of the SEEG electrode refers to the specific position where the electrode enters the brain, which is located in the area of ​​the cerebral cortex, and the target of the SEEG electrode refers to the non-cerebral convex area on the same side of the cortical entry point (usually in the midline or medial position of the brain). In the prior art, electrode planning based on the target is based on the perspective of a single electrode, emphasizing the anatomical and geometric accuracy of the single electrode positioning method, that is, the target in a narrow sense. The planning method in this application is based on the corresponding positions of the target and entry points, emphasizing how to safely and reasonably place multiple electrodes in various brain regions after a comprehensive analysis of the epileptogenic network to ensure that each SEEG deep electrode reaches the target position along the optimal path.

[0055] In order to avoid damaging key brain structures, in an optional embodiment, in step S400, the restriction conditions include one or more of avoiding key areas, the lower limit of the distance between the SEEG electrode and the blood vessel, and the evaluation of the cranial entry angle; step S400 includes: step S420, obtaining the target SEEG electrode path through the restriction conditions.

[0056] In this embodiment, the so-called critical areas include one or more of the cerebral sulci, the midsagittal plane, and the brainstem, wherein the cerebral sulci can be, for example, the lateral sulcus, the cingulate sulcus, the parieto-occipital sulcus, the central sulcus, etc. The above-mentioned brain structures are set as critical areas, and the insertion path should avoid passing through these critical areas to prevent the SEEG electrode from damaging the critical brain structure and ensure the safety of the operation.

[0057] In this embodiment, the blood vessel may be, for example, the basilar artery, the posterior parietal artery, the choroidal vein, the great cerebral vein, etc. In the process of screening and planning the target SEEG electrode path, the SEEG electrode should be kept away from the blood vessel. In the specific implementation process, the lower limit of the distance between the SEEG electrode and the blood vessel can be determined based on experience. In this embodiment, by setting the lower limit of the distance between the SEEG electrode and the blood vessel, the SEEG electrode can be prevented from puncturing the blood vessel to cause surgical accidents.

[0058] In this embodiment, the cranial angle refers to the angle between the normal direction of the intersection and the extension line of the test path at the intersection when the insertion path is extended toward the skull. In a preferred embodiment, the cranial angle is evaluated as the angle between the SEEG electrode and the skull being perpendicular is better than the non-perpendicular angle. Specifically, the cranial angle is evaluated as the absolute value of the difference between the SEEG electrode and the skull and 90° being as small as possible, thereby avoiding slipping on the hard skull surface during skull drilling and electrode implantation, which is beneficial to improving the accuracy of subsequent electrode implantation.

[0059] In order to comprehensively determine the optimal SEEG electrode path, in an optional embodiment, step S420 includes: weighted scoring of each factor in the constraint condition to obtain an evaluation score for each electrode path; and determining the electrode path with the highest evaluation score as the target SEEG electrode path. Specifically, in the scoring process, the performance of the electrode path itself can be evaluated by various factors in the constraint condition, such as whether to avoid the critical area. If the critical area is not avoided, the score is unqualified, and conversely, the farther from the critical area, the higher the score; another example is whether the distance from the blood vessel is sufficient. When the distance between the SEEG electrode and the blood vessel exceeds the lower limit, it is qualified, and the farther the distance, the higher the score; another example is whether the cranial angle is close to 90°. The closer the cranial angle is to 90°, the higher the score. The qualified electrode path can be screened out through the evaluation score, and then one of these qualified electrode paths is selected as the target SEEG electrode path. When the selected paths all meet the above-mentioned constraints, these factors of the constraints can be scored separately, and then each factor can be weighted to obtain an evaluation score. The higher the evaluation score, the better the "path effect". In this embodiment, the electrode path with the highest evaluation score is used as the target SEEG electrode path.

[0060] To facilitate matching and searching the target experience module in the experience database, in an optional embodiment, between step S200 and step S300, the following is further included:

[0061] In step S210, the target brain anatomical image is divided into brain regions according to preset rules; in step S300, the target brain anatomical image after region division is used as the object to match and search for the target experience module in the experience database. Specifically, the brain region division can be performed by a neural network. In the specific implementation process, the patient's medical image can include medical images of multiple modalities, and the patient's brain structure partition, such as brain atlas partition, vascular structure, etc., can be obtained by processing it. The brain atlas and structures such as blood vessels can be unified into the same space. In this embodiment, by dividing the target brain anatomical image into brain regions, and then using the brain region as an object to search for the target experience module, a modular search and matching target experience module can be achieved, thereby reducing the amount of calculation on the one hand, and improving the matching accuracy of each brain region on the other hand.

[0062] In an optional embodiment, between step S200 and step S400, the method further includes: step S220, obtaining key area information of the patient's brain, and marking key areas in the target brain anatomical image according to the key area information. Specifically, the key area information can be input by the user, or can be generated by the system using a neural network or the like based on the target brain anatomical image recommendation. In this embodiment, the execution order between step S210 and step S220 is not limited. In some embodiments, step S210 and step S220 can also be executed together.

[0063] This embodiment also discloses a device for planning the SEEG deep electrode placement path based on medical imaging, please refer to Figure 2 , Figure 2 This is a schematic diagram of a device structure for planning a SEEG deep electrode placement path based on medical imaging, which is also disclosed in this embodiment. The device includes: an image data acquisition module 100, a data fusion module 200, a target module matching module 300 and a target path adjustment module 400, wherein:

[0064] The image data acquisition module 100 is used to receive medical image data of the brain of an epileptic patient, where the medical image data is acquired by an image acquisition device from the brain of the epileptic patient;

[0065] The data fusion module 200 is used to fuse the medical image data to obtain a target brain anatomical image, wherein the target brain anatomical image is annotated with a plurality of cortical target point position ranges and a plurality of cortical entry point positions, the cortical entry points are located in the convex cortical area of ​​the brain, and the target point position range is the non-convex area of ​​the brain on the same side of the cortical entry points;

[0066] The target module matching module 300 is used to match and search for a target experience module in an experience database based on the anatomical-electrical-clinical evidence of epilepsy patients. The target experience module includes a number of fixed path combinations, each path has a fixed cortical entry point range and a cortical target point position range; the experience database is established based on prior experience;

[0067] The target path adjustment module 400 is used to dynamically calculate and screen the target SEEG electrode path based on the individual characteristics of the target brain anatomical image, the restriction conditions and the target experience module. The target SEEG electrode path is the path of multiple SEEG electrodes placed in the target position range.

[0068] This embodiment also discloses a system for planning a SEEG deep electrode placement path based on medical imaging. Figure 3 , Figure 3 This is a schematic block diagram of a system for planning a SEEG deep electrode placement path based on medical imaging disclosed in this embodiment. The system includes: an image acquisition device 1 and a controller 2, wherein:

[0069] The image acquisition device 1 is used to acquire target sampled image data from the patient's brain;

[0070] The controller 2 adopts the method disclosed in the above embodiment to perform epilepsy SEEG electrode path planning; or includes the device disclosed in the above embodiment.

[0071] According to a method and system for planning a SEEG deep electrode placement path based on medical imaging disclosed in an embodiment of the present invention, after receiving medical imaging data of the brain of an epileptic patient, data fusion is performed on the medical imaging data to obtain a target brain anatomical image, and the target brain anatomical image is annotated with a number of target point position ranges and a number of cortical entry point position ranges. According to the target brain anatomical image, a target experience module can be matched and searched in an experience database, that is, a matching target experience module can be obtained by using prior knowledge, so that the module can better match the current target brain characteristics. On this basis, the target experience module is dynamically adjusted by using individual characteristics and restriction conditions, so as to obtain a target SEEG electrode path that better matches the target brain characteristics, thereby realizing the rapid acquisition of a matching experience module based on prior knowledge, and the target experience module is associated with the cortical entry point and The target point, that is, the target position is not considered alone, but the target experience module is determined by the path correspondence between the cortical entry point and the target point, so that the selected target experience module can organically combine the cortical entry point and the target point, and the target SEEG electrode path is obtained by dynamic adjustment according to the target brain characteristics, thereby realizing the optimization of the SEEG electrode path, that is, it can ensure that the optimal electrode path of each SEEG deep electrode is found for different individuals; and, since the target brain anatomical image is annotated with a number of cortical target position ranges, and the actual target point is not assumed, that is, the target point is unknown before the SEEG electrode is implanted, but the actual target point (that is, the real epileptogenic brain area) is confirmed by the electrode coverage pattern that conforms to its epileptic network. Compared with the prior art where the target point itself may be wrong (that is, the assumption is wrong), the present application ensures the accuracy of the clinical data.

[0072] In addition, the present invention also provides a computer-readable storage medium, such as a chip, a CD, etc., on which an execution program is stored. When the execution program is executed, the method disclosed in the above embodiment is implemented.

[0073] It should be noted that the computer-readable storage medium described in the embodiments of the present disclosure is not limited to the above-mentioned embodiments, and may also be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the embodiments of the present disclosure, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device.

[0074] It will be appreciated by those skilled in the art that, under the premise of no conflict, the above-mentioned preferred solutions can be freely combined and superimposed. Among them, the flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment, or a part of a code, and the module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings, for example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. The numbering of each step in this article is only for the convenience of description and reference, and is not used to limit the order of execution. The specific execution order is determined by the technology itself, and those skilled in the art can determine various allowable and reasonable orders based on the technology itself.

[0075] It should be noted that the use of step numbers (letters or numbers) to refer to certain specific method steps in the present invention is only for the purpose of convenience and brevity of description, and is by no means intended to limit the order of these method steps by letters or numbers. Those skilled in the art will understand that the order of the relevant method steps should be determined by the technology itself and should not be inappropriately limited by the existence of step numbers. Those skilled in the art can determine various permissible and reasonable step orders based on the technology itself.

[0076] Those skilled in the art will appreciate that, without conflict, the above-mentioned preferred solutions can be freely combined and superimposed.

[0077] It should be understood that the above-mentioned embodiments are merely illustrative and not restrictive. Without departing from the basic principles of the present invention, various obvious or equivalent modifications or substitutions that can be made by those skilled in the art to the above-mentioned details will all be included in the scope of the claims of the present invention.

Claims

1. A method for planning a SEEG deep electrode placement path based on medical imaging, characterized in that: include: Step S100, receiving medical image data of the brain of an epileptic patient, wherein the medical image data is acquired by an image acquisition device from the brain of the epileptic patient; Step S200, performing data fusion on the medical image data to obtain a target brain anatomical image, wherein the target brain anatomical image is annotated with a plurality of cortical target point position ranges and a plurality of cortical entry point positions, the cortical entry points are located in the convex cortical area of ​​the brain, and the target point position range is the non-convex area of ​​the brain on the same side of the cortical entry points; Step S300, matching and searching for a target experience module in an experience database based on the anatomical-electrical-clinical evidence of epilepsy patients, wherein the target experience module includes a plurality of fixed path combinations, each path having a fixed cortical entry point range and a fixed cortical target point position range; the experience database is established based on prior experience, and the anatomical-electrical-clinical evidence includes: brain anatomical images based on multiple patients, scalp EEG characteristic data during interictal and ictal periods, and characteristic seizure symptom data of patients captured by video EEG monitoring; Step S400, based on the individual characteristics of the target brain anatomical image, the restriction conditions and the target experience module dynamically calculate and screen the target SEEG electrode path, the target SEEG electrode path is the path of the target position range of multiple SEEG electrodes, the individual characteristics include several cortical target position ranges and several cortical entry point positions marked in the target brain anatomical image of the epileptic patient, the restriction conditions include one or more of avoiding the critical area, the lower limit of the distance between the SEEG electrode and the blood vessel, and the cranial entry angle evaluation.

2. The method for planning a SEEG deep electrode placement path based on medical imaging according to claim 1, characterized in that: The step S400 includes: Step S420, obtaining the target SEEG electrode path by screening through the restriction conditions.

3. The method for planning a SEEG deep electrode placement path based on medical imaging as claimed in claim 2, characterized in that: The step S420 includes: weighting and scoring each factor in the restriction condition to obtain an evaluation score of each electrode path; and determining the electrode path with the highest evaluation score as the target SEEG electrode path.

4. The method for planning a SEEG deep electrode placement path based on medical imaging as claimed in claim 3, characterized in that: The cranial angle evaluation is that the smaller the absolute value of the difference between the angle between the SEEG electrode and the skull and 90°, the better.

5. The method for planning a SEEG deep electrode placement path based on medical imaging according to any one of claims 1 to 4, characterized in that: Between step S200 and step S300, the method further includes: Step S210, dividing the target brain anatomical image into brain regions according to a preset rule; In the step S300, the target brain anatomical image after the region division is used as the object to match and search for the target experience module in the experience database.

6. The method for planning a SEEG deep electrode placement path based on medical imaging as claimed in claim 2, characterized in that: Between step S200 and step S400, the method further includes: Step S220, obtaining key area information of the patient's brain, and marking the key area in the target brain anatomical image according to the key area information.

7. The method for planning a SEEG deep electrode placement path based on medical imaging according to any one of claims 1 to 4, characterized in that: In the step S100, the image acquisition device includes magnetic resonance imaging and / or CT.

8. A device for planning the SEEG deep electrode placement path based on medical imaging, characterized in that: include: An image data acquisition module (100) is used to receive medical image data of the brain of an epileptic patient, wherein the medical image data is acquired by an image acquisition device from the brain of the epileptic patient; A data fusion module (200) is used to perform data fusion on the medical image data to obtain a target brain anatomical image, wherein the target brain anatomical image is annotated with a plurality of cortical target point position ranges and a plurality of cortical entry point positions, the cortical entry points are located in the convex cortical area of ​​the brain, and the target point position range is a non-convex area of ​​the brain on the same side of the cortical entry points; The target module matching module (300) is used to match and search for a target experience module in an experience database based on the anatomical-electrical-clinical evidence of an epileptic patient, wherein the target experience module includes a plurality of fixed path combinations, each path having a fixed cortical entry point range and a fixed cortical target point position range; the experience database is established based on prior experience, and the anatomical-electrical-clinical evidence includes: brain anatomical images of multiple patients, scalp EEG characteristic data during interictal and ictal periods, and characteristic seizure symptom data of the patient captured by video EEG monitoring; The target path adjustment module (400) is used to dynamically calculate and select a target SEEG electrode path based on the individual characteristics of the target brain anatomical image, the restriction conditions and the target experience module, wherein the target SEEG electrode path is a path within a range of target position of multiple SEEG electrodes, wherein the individual characteristics include a plurality of cortical target position ranges and a plurality of cortical entry point positions marked in the target brain anatomical image of the epileptic patient, and the restriction conditions include one or more of avoiding a critical area, a lower limit of the distance between the SEEG electrode and the blood vessel, and an evaluation of the cranial angle.

9. A system for planning SEEG deep electrode placement path based on medical imaging, characterized in that: include: An image acquisition device, used to acquire target sampled image data from the patient's brain; A controller, which performs SEEG electrode path planning for epilepsy using the method described in any one of claims 1 to 7; or, includes the device described in claim 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer program stored in the storage medium is used to be executed by a processor to implement the method according to any one of claims 1 to 7.

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