Diagnostic support device, program, and diagnostic support method

Abstract

To reduce false negatives and false positives in nuclear medicine image diagnosis.SOLUTION: A diagnosis support device includes a matching unit and an estimation unit. The matching unit matches first portion information, which is information on an accumulation portion of a diagnostic agent obtained from a nuclear medicine image of a specimen and second portion information, which is information on a portion of origin of exosome including the diagnostic agent taken from the specimen. As a result of the matching, the estimation unit estimates that a tumor exists in the portion of the first portion information that matches the second portion information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The embodiments disclosed in the present specification and drawings relate to a diagnosis support device, a program, and a diagnosis support method. [Background technology]

[0002] In nuclear medicine imaging, tumor location is estimated based on the accumulation of diagnostic agents, but it is known that judgment varies greatly depending on the proficiency of the radiologist, and false negatives and false positives can occur. For example, in cases of suspected lung malignant tumors, it has been reported that 18.4% of results are false negative and 4.35% are false positive. In addition, in cases of suspected residual or recurrent oropharyngeal squamous cell carcinoma after chemoradiotherapy, it has been reported that 59.2% of results are false positive. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2012-149994 Summary of the Invention [Problem to be solved by the invention]

[0004] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to reduce false negatives and false positives in nuclear medicine imaging diagnosis. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described below can also be positioned as other problems. [Means for solving the problem]

[0005] The diagnostic support device according to the embodiment includes a collation unit and an estimation unit. The collation unit compares first site information, which is information on the site where a diagnostic agent has accumulated obtained from nuclear medicine imaging of a specimen, with second site information, which is information on the site from which exosomes containing the diagnostic agent collected from the specimen originate. Based on the comparison, the estimation unit estimates that a tumor is present in a site in the first site information that matches the second site information. [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 is a block diagram showing an example of a diagnosis support apparatus according to the first embodiment. [Figure 2] FIG. 2 is a chart showing an example of a method executed by the diagnostic assistance method according to the second embodiment and the diagnostic assistance program according to the third embodiment. [Figure 3] FIG. 3 is a flowchart showing an example of a diagnosis support method according to the fourth embodiment. [Figure 4] FIG. 4 is a flowchart showing an example of a diagnosis support method according to the fourth embodiment. [Figure 5] FIG. 5 is a schematic diagram showing an example of metabolism of a diagnostic agent in the diagnostic support method according to the fourth embodiment. [Figure 6] FIG. 6 is a schematic diagram showing an example of metabolism of a diagnostic agent in the diagnostic support method according to the fourth embodiment. [Figure 7] FIG. 7 is a Venn diagram showing an example of estimation conditions in the diagnosis support method according to the fourth embodiment. [Figure 8] FIG. 8 is a flowchart showing an example of an estimation procedure in the diagnostic support method according to the second embodiment and the method executed by the diagnostic support program according to the third embodiment. [Figure 9] FIG. 9 is a flowchart showing an example of a diagnosis support method according to the embodiment. [Figure 10] Fig. 10 is a photograph showing an example of imaging according to the embodiment. Fig. 8A is a plain CT scan of the chest. Fig. 8B is a PET / CT scan of the chest. Fig. 8C is a plain CT scan of the abdomen. [Figure 11]FIG. 11 is a photograph showing an example of display of an estimation result according to the embodiment. [Figure 12] FIG. 12 is a block diagram illustrating an example of a diagnosis support device according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0007] Hereinafter, embodiments of a diagnostic support device, a program, and a diagnostic support method will be described in detail with reference to the drawings.

[0008] (First embodiment) An example of the diagnostic support device according to the first embodiment is a device for use in a diagnostic support method that estimates the location of a tumor in a subject by combining information on the accumulation site of a diagnostic agent obtained from nuclear medicine imaging of the same subject with information on the origin site obtained from exosome analysis of the same subject.

[0009] FIG. 1 is a diagram showing an example of the configuration of a diagnosis support device according to the first embodiment. For example, as shown in FIG. 1, the diagnosis support device 1 according to this embodiment includes at least a collation unit 2 and an estimation unit 3. The collation unit 2 collates information on the accumulation site of a diagnostic agent obtained from nuclear medicine imaging of the subject (hereinafter also referred to as "first site information") with information on the site of origin of exosomes containing a diagnostic agent collected from the subject (hereinafter also referred to as "second site information"). Based on the result of the collation, the estimation unit 3 estimates that a tumor is present in a site of the first site information that matches the second site information.

[0010] For example, the estimation unit determines, as a result of the matching, determining that a tumor is present (positive) in a site that is included in the first site information and that is included in the second site information; determining that a site that is included in the first site information but not included in the second site information contains something other than a tumor (false positive); It may be determined that a tumor exists in a site that is not included in the first site information but is included in the second site information (false negative).

[0011] (Second embodiment) As shown in FIG. 2a, the diagnostic support method according to the second embodiment may be a diagnostic support method that estimates the location of a tumor in a subject (step S) using information on the site where a diagnostic agent has accumulated, obtained from nuclear medicine imaging of the subject, and information on the site of origin of exosomes containing the diagnostic agent contained in the subject.

[0012] 2b is a flowchart showing an example of the configuration of a diagnostic support method according to the second embodiment. For example, as shown in FIG. 2b, the diagnostic support method according to this embodiment may include the following steps: First site information, which is information on the accumulation site of the diagnostic agent obtained from nuclear medicine imaging of the subject, is compared with second site information, which is information on the origin of the exosome containing the diagnostic agent collected from the subject (step S1); As a result of the comparison, it is estimated that a tumor is present in a site of the first site information that matches the second site information (step S2).

[0013] For example, step S1 may be executed in the collation unit 2 of the diagnosis support device 1 according to the first embodiment, and step S2 may be executed in the estimation unit 3.

[0014] As a third embodiment, for example, a program may be provided that causes the diagnostic support device shown in Figure 1 to execute the diagnostic support method shown in Figures 2a and 2b. An example of such a diagnostic support program is as follows: The diagnostic support method may include comparing first site information, which is information on the accumulation site of a diagnostic agent obtained from nuclear medicine imaging of a subject, with second site information, which is information on the site of origin of exosomes containing a diagnostic agent collected from the subject (S1), and estimating the presence of a tumor at a site in the first site information that matches the second site information as a result of the comparison (S2). For example, such a program may be a program that can be implemented by a processing system such as a computer to implement the diagnostic support method of the embodiment, and may be a diagnostic support program that executes steps S1 and S2.

[0015] For example, step S1 obtaining nuclear medicine images from a subject administered a diagnostic agent; acquiring first site information, which is information on a site where the diagnostic agent has accumulated, from the obtained captured image; Obtaining molecular information of exosomes collected from the subject and containing the diagnostic agent; Obtaining second site information, which is information on the site of origin of the exosome, from the molecular information of the exosome; and Matching the first region information with the second region information; may also include:

[0016] In other words, a further configuration example of the diagnosis support method according to the second embodiment is as follows: obtaining nuclear medicine images from a subject administered a diagnostic agent; acquiring first site information, which is information on a site where the diagnostic agent has accumulated, from the obtained captured image; Obtaining molecular information of exosomes collected from the subject and containing the diagnostic agent; Obtaining second site information, which is information on the site of origin of the exosome, from the molecular information of the exosome; Matching the first region information with the second region information; and As a result of the comparison, it is estimated that a tumor is present in a region of the first region information that matches the second region information. Includes.

[0017] (Fourth embodiment) The diagnosis support method according to the fourth embodiment may be performed using the diagnosis support device 1. The diagnosis support method according to the fourth embodiment may include the following steps as shown in FIG. 4: Administering a diagnostic agent to a subject (step S1); nuclear medicine imaging of the subject (step S2); Obtaining first site information, which is information on the site where the diagnostic agent has accumulated, from the captured image (step S3). Collecting exosomes containing a diagnostic agent from the subject (step S4); Obtaining molecular information of exosomes (step S5), Obtaining second site information, which is information on the site of origin of the exosome, from the exosome molecular information (step S6); Matching the first site information with the second site information (step S7); and As a result of the comparison, it is estimated that a tumor is present in a site of the first site information that matches the second site information (step S8).

[0018] An example of detailed procedures of the diagnosis support method according to the fourth embodiment will be described below with reference to FIGS.

[0019] As shown in FIGS. 3 and 4, first, a diagnostic agent 5 is administered to a subject 4 (step S1).

[0020] The subject 4 is preferably a human. However, it may be an animal other than a human. The non-human animal may be, for example, a mammal, a bird, an amphibian, a reptile, or a fish. The mammal may be, for example, a primate such as a monkey; a rodent such as a mouse, a rat, or a guinea pig; a companion animal such as a dog, a cat, or a rabbit; a livestock animal such as a horse, a cow, or a pig; or an animal kept on display.

[0021] The diagnostic agent 5 is, for example, a substance that accumulates in tumor cells and can be detected by a nuclear medicine imaging device. For example, the diagnostic agent 5 is a compound containing a radioisotope. Such a compound can be, for example, 18 F]2-Fluorodeoxy-D-glucose ([ 18 F]FDG), [ 18 F]6-Fluoro-m-tyrosine, L-[3- 18 F]-a-Methyltyrosine, S-[Methyl- 11 C]-methionine, trans-1-Amino-3-[ 18 F]fluorocyclobutanecarboxylic acid, 3'-Deoxy-[3'- 18 F]thymidine, 11C-Methyl]thymidine, 2-[ 11 C]Tymidine, 11 C]Methionine, 18 F]Fluorothymidine, 4'-[Methyl- 11 C]-thiotymidine, [ 11 C]Acetate, 11 C]Choline, 18 F]Fluorocholine, 18 F]Fluoromisonidazole, 18 F]Fluoroazomycin arabinofuranoside, and / or [ 62 Cu]Diacetyl-bis(N4-methylthiosemicarbazone), etc.

[0022] The method of administering the diagnostic agent 5 to the subject 4 is not particularly limited, and may be any known method capable of delivering the diagnostic agent to the target site of the diagnostic support method according to the embodiment. For example, the diagnostic agent may be administered intravenously, intraarterially, intradermally, subcutaneously, intramuscularly, or orally. For example, for whole-body imaging, the diagnostic agent may be administered by intravenous injection.

[0023] The diagnostic agent 5 administered in step S1 can diffuse into the subject 4 and be taken up by various cells. For example, as shown in part (a) of FIG. 5, the diagnostic agent 5 accumulates in cells 50 (tumor cells) where the diagnostic agent 5 ("X" in the figure) does not undergo metabolism. In some cases, the diagnostic agent 5 accumulates in a state where it has undergone several stages of metabolism ("X'" or "X''" in the figure).

[0024] Next, nuclear medicine imaging of the subject 4 is performed (FIG. 4, step S2).

[0025] Nuclear medicine imaging is performed using, for example, a nuclear medicine imaging device 6, as shown in FIG. 3. When the radioisotope contained in the diagnostic agent 5 emits a positron, the positron emitted from the radioisotope annihilates a nearby electron, resulting in the emission of two annihilation radiation rays (gamma rays) in directions 180 degrees opposite to each other. For example, a nuclear medicine imaging device 6 can be used that detects signals and creates an image by coincidence counting the gamma rays emitted in two directions. That is, in such an apparatus, two gamma rays are simultaneously detected by a plurality of gamma ray detectors arranged in a ring around the sample, thereby obtaining data, such as a sinogram, indicating that a radioisotope exists on the line connecting the gamma ray detectors where the gamma rays were detected. The data is then reconstructed into an image to obtain a tomographic image of the distribution of the radioisotope. For example, such a device may be a positron emission tomography (PET) device, a PET-CT device that combines a PET device with an X-ray computed tomography (CT) device, or a TOF-PET (time-of-flight PET) device.

[0026] When a radioisotope emits gamma rays, for example, a nuclear medicine imaging device 6 can be used that detects such gamma rays using a gamma ray detector equipped with a collimator, e.g., a parallel-type collimator, on the sample side. As a result of the detection, data such as the position of the gamma ray detector where the gamma ray arrived and output a power pulse, and the number of times the power pulse was detected, can be obtained, and a planar image can be created from this data. The gamma ray detector detects gamma rays from various directions of the sample to collect planar images, and a computer can reconstruct the images to obtain a tomographic image of the distribution of the radioisotope. For example, such a device can be a single photon emission computed tomography (SPECT) device, or a SPECT device that combines a SPECT device and a CT device.

[0027] By the above-described imaging, it is possible to obtain information (first site information) 7 about the site where the diagnostic agent 5 has accumulated in the subject 4. Since the diagnostic agent 5 accumulates in tumor cells, the first site information 7 is information about the site where it is determined that a tumor is present in nuclear medicine imaging.

[0028] As used herein, a "site" refers to an organ or tissue of a subject 4. Organs include, but are not limited to, the brain, lung, breast, esophagus, stomach, rectum, colon, liver, pancreas, bladder, prostate, cervix, or ovary. Tissues are further classifications of the above organs, and in the case of the lung, they may be non-small cell, small cell, glandular, squamous, or large cell.

[0029] The first region information 7 may be acquired by a technician or a radiologist visually checking the imaging data, or may be acquired automatically by image analysis software or the like. Alternatively, the acquisition may be performed by accessing a database that is internal or external to the nuclear medicine imaging device 6 and comparing the imaging data with information stored in the database.

[0030] Meanwhile, after step S1, exosomes containing diagnostic agent 5 are collected from the subject 4 (Figure 4, step S4).

[0031] As explained above with respect to part (a) of Figure 5, administration of diagnostic agent 5 causes the diagnostic agent 5 to accumulate in cells 50 in which the diagnostic agent 5 is not metabolized. However, as shown in part (b) of Figure 5, when exosomes 9 are produced from cells 50, the accumulated diagnostic agent 5 can be incorporated into exosomes 9. As a result, exosomes 9 containing diagnostic agent 5 are released into the blood.

[0032] Diagnostic drug 5 is 18 F]2-Fluorodeoxy-D-glucose ([ 18 An example in which [F]FDG is administered to subject 4 will be described with reference to FIG. 18 The [F]FDG is taken up by cells 50 in the subject 4. 18 F]FDG is metabolized by hexokinase and18 [F]FDG-6-P is generated. [F]FDG-6-P accumulates in the cells. 18 [F]FDG-6-P is incorporated into exosomes9 and released into the blood.

[0033] Exosomes9 are tiny vesicles approximately 100 nm in diameter found in living organisms. They are secreted by cells and possess a lipid bilayer membrane structure containing nucleic acids and proteins. They travel between distant organs, transporting substances and transmitting information. The lipid bilayer membrane contains proteins or glycoproteins, and it has also been reported that nucleic acids such as DNA are attached to the periphery. The types and combinations of these molecules are specific to the type of cell in which they are produced, and their analysis can provide information about the cell origin50 from which exosomes9 were produced. Hereinafter, these molecules specific to the type of exosome are also referred to as "exosome molecules10."

[0034] Exosomes can be collected, for example, by drawing blood from a subject 4 and isolating exosomes 9 containing a diagnostic agent 5 from the obtained blood 8 as shown in Figure 3.

[0035] In order to isolate exosomes 9 containing the diagnostic agent 5, blood sampling is preferably performed before the half-life of the radioisotope contained in the diagnostic agent 5 has elapsed. For example, 18 [F]FDG[ 18 The half-life of [F] is approximately 2 hours, so it is suitable as a diagnostic drug. 18 When [F]FDG is used, blood sampling is preferably performed within 2 hours after administration.

[0036] The diagnostic support device 1 may display the time of blood collection or the time until blood collection. When blood 8 is collected from multiple subjects 4, the diagnostic support device 1 may display the time of blood collection or the time until blood collection for each of the multiple subjects 4. This display may be on a display unit that the diagnostic support device 1 may further include, or may be on a display unit that the nuclear medicine imaging device 1 or molecular information collating device 14 that is connected to the diagnostic support device 1 may include. In addition to or separately from the display, the time may be indicated by a signal such as sound or light.

[0037] Exosomes 9 can be isolated by known methods, for example, using a commercially available exosome isolation kit. At this time, an operation to separate exosomes 9 containing diagnostic agent 5 from exosomes 9 not containing diagnostic agent 5 may be performed.

[0038] Next, molecular information 11 of the exosomes 9 is obtained (Figure 4, step S5).

[0039] The molecular information 11 includes information such as the type and / or amount of exosome molecules 10 contained in the collected exosomes 9. As shown in Figure 3, the molecular information 11 can be obtained, for example, by extracting the exosome molecules 10 from isolated exosomes 9 and identifying and / or quantifying them.

[0040] The exosome molecule 10 includes, for example, nucleic acids, enzymes, membrane proteins, scaffolding proteins, single molecules, and / or chaperone proteins, etc. The exosome molecule 10 may include, for example, an exosome molecule 10 that can be linked to information on the cell 50 (origin) in which it was produced, and an exosome molecule 10 that can be linked to the fact that it is an exosome itself.

[0041] For example, examples of exosome molecules 10 that can be linked to information on the cell 50 (origin) in which they were produced include, but are not limited to, exosome microRNA (miRNA), messenger RNA (mRNA), and / or DNA.

[0042] Furthermore, examples of exosome molecules 10 that can be linked to being exosomes themselves include, but are not limited to, enzymes such as GAPDH, PK, ATPase, PGK, and enolase; cytoskeletal proteins such as actin, myosin, vimentin, tubulin, cofilin, profilin, and fibronectin; signal molecules such as EGF-R, HIF-1a, CDC42, PI-3K, ARF1, and Rab5b; chaperone proteins such as HSP70, HSP90, HSP60, and HSC70; tetraspanins such as CD9, CD63, and CD81; integrins such as α6β4, α6β1, and αvβ5; MHC class I molecules, class II molecules; multivesicular molecules such as TSG101, clathrin, ubiquitin, and Alix; and lipid rafts such as flotillin-1.

[0043] The exosome molecules 10 can be extracted by dissolving the exosomes in a buffer similar to water and then using a known method appropriate for the type of exosome, such as a commercially available nucleic acid extraction kit or protein extraction kit.

[0044] Next, the extracted exosome molecules 10 are identified and / or quantified. Protein identification and quantification can be performed, for example, by a protein sequencer method, a sequence tag method, or a peptide mass fingerprinting method. Nucleic acids can be identified and quantified, for example, by a nucleic acid amplification method such as PCR, LAMP, or TRC, or a sequencer method.

[0045] Next, exosome-origin site information (second site information) 12 is obtained (step S6) from the obtained exosome molecular information 11. The second site information 12 can be obtained, for example, by comparing the exosome molecular information 11 with a group of information linking a large number of exosome molecules 10 obtained from previous findings with their origin sites.

[0046] For example, if the information included in the exosome molecule information 11 is exosome molecules a, b, c, and d, a, b, c, and d are each compared, and information on the site of origin of the matching exosome molecule 10 is obtained. Multiple site of origin information may be obtained for one type of exosome molecule 10. Examples of linkages between exosome molecules 10 and their site of origin include, but are not limited to, miR-30c and lung cancer, miR-181c and breast cancer or brain tumor, miR-34a and ovarian cancer, or MMP-1 mRNA and ovarian cancer.

[0047] Alternatively, a combination of multiple exosome molecules 10 may be linked to specific site-of-origin information, and when that combination is included in the exosome molecule information 11 (e.g., a and b), that specific site-of-origin may be acquired. Furthermore, the amount of exosome molecules 10 may be linked to specific site-of-origin information, and the site-of-origin that matches the amount of exosome molecules (e.g., the amount of a, the amount of b, etc.) may be acquired. Such matching and acquisition of second site information 12 may be performed using a molecular information matching device 14 as shown in Figure 3. The molecular information matching device 14 is, for example, a computer, and has a matching unit 15 that matches a group of information linking a large number of exosome molecules 10 to their sites of origin stored in a database (DB) 13 with exosome molecule information 11.

[0048] The database 13 may be located within the molecular information matching device 14 or may be located outside the device. The external database 13 may be stored in, for example, a web service (e.g., cloud 16, etc.), and the information group may be accessed by connecting the molecular information matching device 14 to the cloud 16. The database 13 may be, for example, a domestic or international medical database, a chemical database, a review, an explanation, or a textbook. Note that the various data handled in this specification are typically digital data.

[0049] For example, when exosome molecular information 11 of a specific subject 4 is input to the molecular information matching device 14, the matching unit 15 accesses the database 13, reads the information group contained therein, and matches the exosome molecular information 11 of the subject 4 with that information group. As a result of the matching, the site-derived information that matches the exosome molecular information 11 of the subject 4 is output as second site information 12. Alternatively, the database 13 may be equipped with the function of the matching unit 15, in which case the exosome molecular information 11 is sent to the database 13, where matching is performed, and the second site information 12 is sent to the molecular information matching device 14.

[0050] When there are multiple subjects 4, for example, matching may be performed for each subject 4 and the matching results may be returned for each subject 4.

[0051] Furthermore, it may be possible to simultaneously determine whether the collected sample contains exosomes based on the exosome molecular information 11. For example, the exosome molecular information 11 is compared with a database 13 storing information on exosome molecules 10 that can be linked to the exosomes described above. If a mismatch is found, it is preferable to discontinue the process and re-collect the exosomes. This comparison allows for more accurate results.

[0052] As described above, diagnostic agent accumulation site information (first site information) 7 is obtained by steps S2 to S3 of performing nuclear medicine imaging, and exosome origin site information (second site information) 12 is obtained by steps S4 to S6 of performing exosome analysis. Steps S2 to S3 and steps S4 to S6 may be performed in either order, or they may be performed simultaneously. The procedure up to this point can be determined so as to obtain accurate information, taking into account, for example, the half-life of the radioisotope of the diagnostic agent 5.

[0053] Next, the first region information 7 and the second region information 12 are collated (step S7). The collation is performed, for example, by the collation unit 2 of the diagnosis support device 1. The diagnosis support device 1 receives the first region information 7 from the nuclear medicine imaging device 6 and the second region information 12 from the molecular information collation device 14, and these are sent to the collation unit 2. Next, the collation unit 2 collates the first region information 7 and the second region information 12. The collation may be performed, for example, by investigating whether each region included in the first region information 7 is included in the second region information 12.

[0054] Of the sites included in the first site information 7, those for which the collation results match are determined to have a tumor (positive) (step S7-1). If there is a mismatch, it is determined that there is a site in the first site information 7 where no tumor is present (there is a possibility that a disease other than a tumor is present) (false positive), or that there is a site not included in the first site information 7 but where a tumor is present (false negative) (Fig. 4, step S7-2).

[0055] Here, "positive", "false positive", and "false negative" are judgments based on the first region information 7 obtained by nuclear medicine imaging.

[0056] False positives are thought to occur in cases of active inflammation, such as acute inflammation, chronic inflammation, abscess, tuberculosis, sarcoidosis, or chronic thyroiditis, or in cases of salivary gland tumors, benign bone tumors, intestinal hyperperistalsis, enteritis, an artificial anus site, colon polyps, menstrual endometrium, ovaries during ovulation, lactating mammary glands, uterine fibroids, endometriosis, benign ovarian tumors (chocolate cysts and teratomas), or brown fat (in cold periods), which show high physiological accumulation of the diagnostic agent 5 regardless of whether the patient is in a diseased state or not.

[0057] False negative results are thought to occur, for example, when the tumor diameter is 9 mm or less, when G-6-P phosphatase activity is high as in primary liver cancer, when the tumor has a low cell density as in gastric signet ring cell carcinoma and ovarian mucinous cystic adenocarcinoma, when the tumor is in contact with the urinary tract as in renal cancer, bladder cancer, prostate cancer, etc., or when the tumor is well-differentiated as in well-differentiated lung adenocarcinoma and ovarian borderline malignant tumor.

[0058] By performing this flow of step S7, it is possible to estimate the presence of a tumor in the subject 4. Estimating the presence of a tumor can mean summarizing the determinations for each site above to estimate the site where the tumor is present in the subject 4. For example, it is estimated that a tumor is present in a site that was determined to be positive.

[0059] The judgment and estimation can be performed, for example, by the estimation unit 3 of the diagnosis support device 1. The estimation unit 3 performs the above judgment and estimation based on the collation result sent from the collation unit 2, and outputs the estimation result.

[0060] In a further embodiment, the estimation unit 3 may make a determination according to the Venn diagram shown in Fig. 7. For example, if diagnostic agent accumulation site information (first site information) 7 obtained from nuclear medicine imaging is "A" and exosome origin site information (second site information) 12 obtained from exosome analysis is "B", a determination can be made according to the conditions in Table 1 below.

[0061] [Table 1]

[0062] In the judgment according to the conditions in Table 1, first, all the part information included in both the first part information 7 and the second part information 12 (A∪B) is acquired, and the parts included therein are applied to the above four conditions one by one to make the following judgment: For the areas included in A and B of condition 1, it is determined that a tumor is present (true positive), For areas that are included in A but not B of condition 2, it is determined that there is a possibility that no tumor is present or that a disease other than a tumor is present (false positive), For a region that is included in A but also included in B of condition 3, it is determined that a tumor is present (false negative) even though it could not be detected by nuclear medicine imaging.

[0063] In addition, for areas that are not included in either A or B of condition 4, it can be determined that no tumor is present (true negative).

[0064] From the above determination results, the presence of a tumor in the subject 4 can be estimated (step S8).

[0065] Such determination and estimation can be performed by the estimation unit 3, for example, according to a flow as shown in Fig. 8. First, all part information (analysis population) included in both the first part information 7 and the second part information 12 (A∪B) is acquired (step S10). Then, the parts included therein are applied one by one to the following flow.

[0066] First, it is determined whether the site is included in the first site information 7 (step S11). If it is included (Yes), it is then determined whether it is included in the second site information 12 (step S12). If it is included (Yes), it is determined to be a true positive (step S13). If it is not included (No), it is determined to be a false positive (step S14).

[0067] If the result of step S11 is that the sample is not included (No), it is then determined whether it is included in the second site information 12 (step S15). If it is included (Yes), it is determined to be a false negative (step S16). Here, if there is a sample that is not included in the analysis population acquired in S10 but is determined to be not included (No) in step S15, it is determined to be a true negative (step S17).

[0068] This process is repeated for all regions included in the analysis population. As a result, each region is judged as one of the three processes S13, S14, and S16, and one of four processes including S17 if necessary. Based on the information on the judgments for each region, the region where the tumor is present in the subject 4 is estimated (process S8). According to this estimation method, the first region information 7 can be classified into four types of judgment results based on four conditions.

[0069] The following is a summary of the diagnostic drug 5 administered to subject 4 (female) who was suspected of having right lobe lung cancer: 18 An example of administration of [F]FDG will be described with reference to FIG. 9.

[0070] First, subject 4 was 18After administration of [F]FDG (step S20), whole-body FDG-PET / CT imaging (S21) and blood sampling (S23) were performed 60 minutes later.

[0071] FDG-PET / CT imaging images are shown in Figure 10. Figure 10A is a simple CT image of the chest, showing the right lung lobe, right hilar lymph nodes, and left breast (arrow position). 18 Figure 10B shows a PET / CT image of the same chest, showing high accumulation of [F]FDG in the right lung lobe, right hilar lymph nodes, and left breast (circled). 18 Figure 10C shows a simple CT image of the abdomen, showing high accumulation of [F]FDG in the ovaries. 18 High accumulation of [F]FDG was confirmed. Therefore, the right lung lobe, left breast, and ovary were obtained as first region information 7 (step S22).

[0072] Next, exosomes were isolated from the collected blood (S24). Proteins and nucleic acids were extracted from the exosomes and identified (S25). As a result, exosomes were enriched in miR-30c and miR-181c, which are exosome molecules 10. In other words, exosome molecular information 11, "miR-30c-rich" and "miR-181c-rich," was obtained. When this information was compared with the information group in database 13, it was found that miR-30c is a specific molecule for lung cancer, and miR-181c is a specific molecule for breast cancer and brain metastasis. However, miR-34a and MMP-1 mRNA, which are specific molecules for ovarian cancer, were not included. Therefore, lung, breast, and brain were obtained as second site information 12 (step 26).

[0073] Next, the first region information 7 was compared with the second region information 12. In the comparison, the region information (lungs, breast, ovaries, brain) included in both the first region information 7 and the second region information 12 was first obtained (step S27), and then each region was subjected to the conditions shown in Table 1. For each region, the following judgment was made (step S28): lungs and breast were true positives because they were included in the first region information 7 and the second region information 12; ovaries were false positives because they were included in the first region information 7 but not in the second region information 12; and brain was false negatives because it was not included in the first region information 7 but was included in the second region information 12.

[0074] From the above, it was estimated that the subject had tumors in the lungs and breast (step S29). Here, since it was known from FDG-PET / CT imaging that the lungs were the right lobe and the breast was the left breast, it may be estimated that tumors exist in the right lobe and left breast, rather than simply in the lungs and breast.

[0075] For example, the estimation results obtained by the estimation unit 3 of the diagnosis support device 1 may be displayed for each diagnostic agent accumulation site together with the captured image as shown in Fig. 11. Furthermore, false negative brain metastases may be displayed as "other suspicions."

[0076] Furthermore, for brain metastases determined as false negatives, brain FDG-PET / CT imaging was performed (step S30). As a result, multiple brain metastases were confirmed. From this, it was estimated that subject 4 had brain metastases (step S31). For sites determined as false negatives in this way, it is possible to reconfirm the authenticity of the determination by conducting another test.

[0077] According to the diagnosis support apparatus and diagnosis support method of the above-described embodiment, it is possible to reduce false positives and false negatives when nuclear medicine imaging diagnosis is used alone, and to make a more accurate diagnosis.

[0078] Furthermore, it is possible to reduce the variation in the quality of medical care that was previously caused by differences in the level of expertise of nuclear medicine imaging readers, thereby standardizing the quality.

[0079] Furthermore, the diagnosis support device and the diagnosis support method according to the embodiment are minimally invasive, requiring only imaging and blood sampling, thereby reducing the burden on the subject 4 and medical staff.

[0080] According to a further embodiment, the diagnosis support device 1 may have further units in addition to the matching unit 2 and the estimation unit 3. An example of such units is shown in Fig. 12. The diagnosis support device 100 includes, for example, a receiving unit 110, a processing unit 120 including the matching unit 2 and the estimation unit 3, a storage unit 130, a display unit 140, and an input unit 150. These units are electrically connected via a bus 160.

[0081] The receiving unit 110 receives the first region information 7 from the nuclear medicine imaging device 6, and also receives the second region information 12 from the molecular information collating device 14. The received information is sent to the storage unit .

[0082] The memory unit 130 includes, for example, a non-volatile memory and a volatile memory, and stores the first body part information 7 and the second body part information 12 sent from the receiving unit 110, the matching result 131 sent from the matching unit 2, the estimation result 132 sent from the estimation unit 3, and a program P that performs matching and estimation and controls each of the other units.

[0083] Processing unit 120 includes a matching unit 2 and an estimation unit 3. Matching unit 2 matches first body part information 7 with second body part information 12 in accordance with program P, and sends matching result 131 to storage unit 130. Estimation unit 3 retrieves matching result 131 stored in storage unit 130, and performs estimation based on matching result 131 in accordance with program P. Estimation unit 3 also sends estimation result 132 to storage unit 130.

[0084] The display unit 140 includes, for example, a display or a printer, and displays or outputs the estimation result 132 .

[0085] The input unit 150 includes, for example, a mouse, keyboard, touch panel, buttons, or scanner, and is used to input parameters required for starting and ending matching and estimation, or for each process.

[0086] The diagnosis support device 100 may be integrated with the nuclear medicine imaging device 6 and / or the molecular information collating device 14, for example.

[0087] As described above, the diagnostic assistance program according to the third embodiment may, as a further embodiment, be a program that executes a part of the steps or procedures of the method described herein, the entire method, or any combination thereof. For example, according to a further embodiment, a program for estimating the location of a tumor in a subject is provided. The program compares information on the accumulation site of a diagnostic agent obtained from nuclear medicine imaging of the subject as first site information with information on the site of origin of exosomes containing the diagnostic agent collected from the subject as second site information (second site information), and, as a result of the comparison, estimates that a tumor is present in a site in the first site information that matches the second site information.

[0088] For example, the program may further include a program for performing the condition classification in Table 1 and / or the matching and estimation according to the flow described with reference to FIG.

[0089] According to at least one of the embodiments described above, it is possible to reduce false negatives and false positives in nuclear medicine imaging diagnosis, and also to standardize the quality of medical care.

[0090] Although several embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as defined in the claims. The inventions described in the original claims of this application are set forth below. [1] A diagnostic support device comprising: a comparison unit that compares first site information, which is information on the accumulation site of a diagnostic agent obtained from nuclear medicine imaging of a subject, with second site information, which is information on the site of origin of exosomes containing the diagnostic agent collected from the subject; and an estimation unit that, as a result of the comparison, estimates that a tumor is present in a site in the first site information that matches the second site information. [2] The diagnostic support device according to [1], wherein the information on the site of origin of the exosome is information collected from the subject before the half-life of the diagnostic agent has elapsed. [3] The diagnostic support device according to [1] or [2], wherein, as a result of the comparison, the estimation unit determines that a site that is included in the first site information and the second site information is positive, indicating the presence of a tumor; determines that a site that is included in the first site information and not the second site information is false positive, indicating the presence of something other than a tumor; and determines that a site that is not included in the first site information and included in the second site information is false negative, indicating the presence of a tumor. [4] A diagnostic support program that compares first site information, which is information on the accumulation site of a diagnostic agent obtained from nuclear medicine imaging of a subject, with second site information, which is information on the site of origin of exosomes containing the diagnostic agent collected from the subject, and estimates, as a result of the comparison, that a tumor is present in a site of the first site information that matches the second site information. [5] The program described in [4], wherein the collection is performed before the half-life of the diagnostic agent has elapsed. [6] The program described in [4] or [5], which, as a result of the comparison, determines that a site included in the first site information and the second site information is positive, indicating the presence of a tumor, determines that a site included in the first site information but not the second site information is false positive, indicating the presence of something other than a tumor, and determines that a site not included in the first site information but included in the second site information is false negative, indicating the presence of a tumor. [7] A diagnostic support method for estimating the location of a tumor in a subject, using information on the location where a diagnostic agent has accumulated, obtained from nuclear medicine imaging of the subject, and information on the location of origin of exosomes containing the diagnostic agent contained in the subject. [8] A diagnostic support method comprising: administering a diagnostic agent to a subject; performing nuclear medicine imaging of the subject; obtaining first site information, which is information about a site where the diagnostic agent has accumulated, from the obtained image; collecting exosomes containing the diagnostic agent from the subject; obtaining molecular information about the exosomes; obtaining second site information, which is information about a site from which the exosomes originate, from the molecular information about the exosomes; comparing the first site information with the second site information; and, based on the result of the comparison, inferring that a tumor is present at a site in the first site information that matches the second site information. [9] The diagnostic support method described in [8], wherein the collection is performed before the half-life of the diagnostic agent has elapsed.

[10] The diagnostic agent is 18 The diagnostic support method according to [8] or [9], wherein the FDG is [F]FDG.

[11] The diagnostic support method according to any one of [8] to

[10] , wherein the second site information is obtained by comparing the molecular information of the exosome with a group of information linking molecular information of a plurality of exosomes and sites of origin of the exosomes stored in a database. [Explanation of symbols]

[0091] 1...diagnostic support device, 2...matching unit, 3...matching unit, 4...subject, 5...diagnostic agent, 6...nuclear medicine imaging device, 7...first information site, 8...blood, 9...exosome, 10...exosome molecule, 11...exosome molecular information, 12...second site information, 13...database, 14...molecular information matching device, 15...matching unit, 16...cloud, 50...cell, 100...diagnostic support device, 110...receiving unit, 120...processing unit, 130...memory unit, 131...matching result, 132...estimation result, 140...display unit, 150...input unit, 160...bus, P...program.

Claims

1. A collation unit that collates first site information, which is information on the accumulation site of the diagnostic agent obtained from nuclear medicine imaging of the subject, with second site information, which is information on the origin of the exosome containing the diagnostic agent collected from the subject; a display unit that displays, as a result of the comparison, a region of the first region information that matches the second region information.

2. The display unit 2. The diagnostic support device according to claim 1, wherein a region of the first region information that matches the second region information is displayed on the image obtained from the nuclear medicine imaging, and a message indicating that the matching region is estimated to be the region where a tumor is present is displayed.

3. The diagnostic support device according to claim 1 or 2, wherein the information on the site of origin of the exosome is information collected from the subject before the half-life of the diagnostic agent has elapsed.

4. As a result of the collation, determining that a tumor is present in a site that is included in the first site information and the second site information; determining a site that is included in the first site information but not included in the second site information as a false positive, indicating that something other than a tumor is present; determining a site that is not included in the first site information but is included in the second site information as a false negative, indicating the presence of a tumor; The diagnosis support device according to claim 1 , further comprising an estimation unit.

5. A diagnostic support program that compares first site information, which is information on the accumulation site of a diagnostic agent obtained from nuclear medicine imaging of a subject, with second site information, which is information on the origin of exosomes containing the diagnostic agent collected from the subject.

6. 6. The diagnostic support program according to claim 5, wherein the computer-implemented program estimates and displays that a tumor is present in a region of the first region information that matches the second region information as a result of the comparison.

7. The program described in claim 5 or 6, wherein the collection of exosomes containing the diagnostic agent is performed before the half-life of the diagnostic agent has elapsed.

8. As a result of the comparison, determining that a tumor is present in a site that is included in the first site information and the second site information; determining a site that is included in the first site information but not included in the second site information as a false positive, indicating that something other than a tumor is present; The program according to any one of claims 5 to 7, wherein a site that is not included in the first site information but is included in the second site information is determined to be a false negative, indicating the presence of a tumor.

9. A control method for a diagnosis support device equipped with a matching unit, comprising: the collation unit of the diagnosis support device acquiring first site information, which is information on an accumulation site of a diagnostic agent obtained from nuclear medicine imaging of a subject; The collation unit of the diagnostic support device acquires second site information, which is information on the site of origin of the exosome containing the diagnostic agent collected from the subject; a step in which the collation unit of the diagnosis support device compares the first region information with the second region information; A method for controlling a diagnosis support device comprising:

10. The diagnosis support device further includes an estimation unit and a display unit, a step in which the estimation unit of the diagnosis support device estimates a site where a tumor is present in the subject based on a result of the matching by the matching unit; a step in which the display unit of the diagnosis support device displays an estimation result by the estimation unit; The method for controlling a diagnosis support device according to claim 9, further comprising:

11. A control method for a diagnosis support device equipped with a matching unit, comprising: a step of acquiring, by the collation unit of the diagnosis support device, first region information, which is information on a region where the diagnostic agent has accumulated, from an image obtained by administering a diagnostic agent to the subject and then performing nuclear medicine imaging of the subject; a step of collecting exosomes containing the diagnostic agent from the subject, and then acquiring second site information, which is information on the site of origin of the exosomes, from molecular information of the exosomes by the collating unit of the diagnostic support device; and comparing the first region information with the second region information.

12. The diagnosis support device further includes an estimation unit and a display unit, a step of estimating, by the estimation unit of the diagnosis support device, that a tumor is present in a region of the first region information that matches the second region information as a result of the comparison; The method for controlling a diagnosis support device according to claim 11 , further comprising: causing the display unit of the diagnosis support device to display a result of estimation by the estimation unit.

13. The method for controlling a diagnosis support device according to claim 11 or 12, wherein the collection is performed before a half-life of the diagnostic agent has elapsed.

14. The diagnostic agent comprises: １８ The method for controlling the diagnosis support device according to any one of claims 11 to 13, wherein the target substance is FDG.

15. The method for controlling a diagnostic support device according to any one of claims 11 to 14, wherein the second site information is obtained by comparing the molecular information of the exosome with a group of information linking molecular information of a plurality of exosomes and sites of origin of the exosomes stored in a database.

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