CN119868813B

CN119868813B - Individual target localization methods, systems, and procedures for transcranial magnetic stimulation

Info

Publication number: CN119868813B
Application number: CN202510125684.6A
Authority: CN
Inventors: 陈缘缘; 柳天阳; 王曦明; 马亮; 李相龙
Original assignee: Shanghai Kongshan Ci Technology Co ltd
Current assignee: Shanghai Kongshan Ci Technology Co ltd
Priority date: 2025-01-27
Filing date: 2025-01-27
Publication date: 2025-12-19
Anticipated expiration: 2045-01-27
Also published as: CN119868813A

Abstract

The application relates to the technical field of transcranial magnetic stimulation target positioning, and provides a transcranial magnetic stimulation individual target positioning method, a transcranial magnetic stimulation individual target positioning system and a transcranial magnetic stimulation individual program product, wherein magnetic resonance brain imaging data of a tested individual are obtained; the method comprises the steps of preprocessing magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data, carrying out superficial brain region division according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional subareas, determining individual target stimulation targets of transcranial magnetic stimulation according to the functional subareas, reducing fluctuation of functional connection strength among different voxels, effectively counteracting instability of resting state functional connection in a tested individual, and keeping functional characteristics of the whole functional subarea relatively consistent even if connection strength of some voxels changes with time, thereby improving robustness of target positioning.

Description

Method, system and program product for locating individual target spots through transcranial magnetic stimulation

Technical Field

The application relates to the technical field of transcranial magnetic stimulation target positioning, in particular to a method, a system and a program product for positioning an individual target of transcranial magnetic stimulation.

Background

The resting state functional connection of the superficial brain region and the deep nucleolus can be used as a marker for searching an individuation optimal stimulation target point of transcranial magnetic stimulation (TRANSCRANIAL MAGNETI C Stimulation, TMS), and when the individuation optimal stimulation target point is found by the existing transcranial magnetic stimulation individuation optimal stimulation target point positioning algorithm, the position with the strongest resting state functional connection with the target deep nucleolus is searched for in the superficial brain region by voxels by determining the superficial brain region which can be directly stimulated by transcranial magnetic stimulation, and the position with the most negative resting state functional connection with the target deep nucleolus is used as the individuation optimal stimulation target point, for example, the voxel position with the most negative resting state functional connection with the below-knee anterior cingulate cortex is searched for in the left dorsal lateral prefrontal cortex, and the individuation optimal stimulation target point is used for treating depression.

However, voxels are the smallest unit of magnetic resonance imaging in space, not the smallest unit of division of the functional area of the cerebral cortex, so that finding the optimal stimulation target point from voxel to voxel ignores the functional information of the brain, in addition, the resting state functional connection is unstable in an individual, the connection strength of the same voxel and the deep nucleus can be different at different times, and therefore, the method of finding the individualized optimal target point from voxel to voxel is easily affected by the instability, so that the calculated optimal stimulation target point is not robust enough.

Disclosure of Invention

In order to solve or at least partially solve the technical problems, the application provides an individual target spot positioning method, an individual target spot positioning system and an individual target spot positioning program product for transcranial magnetic stimulation, which can divide a superficial brain area into a plurality of functional subareas, and then search individual optimal target spots from functional subareas by taking the functional subareas as small search units.

In a first aspect, the present application provides a method for locating an individual target site by transcranial magnetic stimulation, comprising:

Acquiring magnetic resonance brain imaging data of a tested individual, wherein the magnetic resonance brain imaging data comprises a functional magnetic resonance image and a structural magnetic resonance image;

preprocessing the magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data;

And performing superficial brain region division according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional subareas.

And determining individual target stimulation targets of transcranial magnetic stimulation according to the functional subregions. .

In a second aspect, the present application provides a transcranial magnetic stimulation individual target positioning system comprising:

The acquisition module is used for acquiring magnetic resonance data of the tested individual, wherein the magnetic resonance data comprises a functional magnetic resonance image and a structural magnetic resonance image;

the preprocessing module is used for preprocessing the magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data;

And the division module is used for carrying out superficial brain region division according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional subareas.

And the positioning module is used for determining an individual target stimulation target point of transcranial magnetic stimulation according to the functional subareas.

In a third aspect, embodiments of the present application also provide an individual target positioning system for transcranial magnetic stimulation, comprising a processor and a memory, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising the steps of the individual target positioning method for transcranial magnetic stimulation as described in the first aspect.

In a fourth aspect, embodiments of the present application also provide a computer program product, which when executed by a computer enables the computer to perform the aforementioned method of positioning an individual target site by transcranial magnetic stimulation.

According to the embodiment of the application, the individual target point positioning method of transcranial magnetic stimulation is realized by acquiring magnetic resonance brain imaging data of a tested individual, wherein the magnetic resonance brain imaging data comprises a functional magnetic resonance image and a structural magnetic resonance image, preprocessing the magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data, preprocessing the magnetic resonance brain imaging data to remove noise introduced in a signal acquisition process, reserving the real functional activity of the brain of the tested individual so as to provide a reliable basis for subsequent functional connection calculation, then carrying out superficial brain region division according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional subregions, determining individual target stimulation targets of transcranial magnetic stimulation according to the plurality of functional subregions, searching for an individual optimal target point by taking the functional subregions as a minimum search unit, comprehensively considering the spatial and temporal dual characteristics of the superficial brain cortex of the brain, arranging the nerve elements in space to have continuity, enabling the nerve elements with high functional similarity to be generally closer to the superficial brain in space, carrying out functional connection between the functional subregions according to the preprocessed magnetic resonance brain imaging data, carrying out functional sub-region division to be different in the function sub-regions, carrying out functional connection voxel-region division according to different functional fluctuation characteristics, and carrying out functional sub-region division on the functional sub-region-division to be better than voxel-domain function connection, and the functional sub-division is better than functional connection feature is carried out functional sub-voxel division, the instability of resting state functional connection in a tested individual is effectively counteracted, and even if the connection strength of certain voxels changes with time, the functional characteristics of the whole functional subarea still keep relatively consistent, so that the robustness of target positioning is improved.

Drawings

In order to more clearly illustrate the embodiments of the present application, a brief description of the related drawings will be provided below. It is to be understood that the drawings described below are only for illustrating some embodiments of the present application, and that one of ordinary skill in the art can obtain many other technical features and connection relationships not mentioned herein from the drawings.

FIG. 1 is a schematic flow diagram of an individual target location system for transcranial magnetic stimulation according to an embodiment of the present application;

FIG. 2 is a schematic illustration of a system for acquiring magnetic resonance brain imaging data of a subject using transcranial magnetic stimulation in accordance with an embodiment of the present application;

FIG. 3 is a schematic diagram of a preprocessed resting-state functional MRI data according to an embodiment of the present application;

FIG. 4 is a schematic diagram of functional subregion division of a superficial brain region according to an embodiment of the present application;

FIG. 5 is a schematic diagram of another method for locating individual targets by transcranial magnetic stimulation according to an embodiment of the present application;

FIG. 6 is a schematic diagram of an embodiment of a transcranial magnetic stimulation individual target positioning system according to the present application;

Fig. 7 is a schematic structural diagram of an individual target positioning system for transcranial magnetic stimulation according to an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

The terms "first," "second," "third," and "fourth" and the like in the description and in the claims and drawings are used for distinguishing between different objects and not necessarily for describing a particular sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Explicitly and implicitly by those skilled in the art

Studies show that the resting state functional connection of the superficial brain region and the deep nucleolus can be used as a marker for searching an individual optimal stimulation target point of transcranial magnetic stimulation.

In several studies across species (mice, marmosets, macaques) comprehensive and high resolution brain transcriptomes and spatial cytograms revealed a high correspondence between transcriptome identity and spatial specificity for each cell type, i.e. continuity of spatial arrangement of neurons in the brain, closer spatial location of neurons of high functional similarity. According to the scheme, based on a space-time dual-feature segmentation individuation target algorithm, the space-time dual features of neurons, namely functional connection strength and spatial position information, are estimated by adopting magnetic resonance brain imaging data, so that functional subregions of cerebral cortex are divided, and further, the optimal treatment target of a tested person is calculated by utilizing the functional subregions which accord with the high correspondence principle of functional similarity and position specificity of the neurons.

The method and the device have the advantages that the superficial brain region is divided into a plurality of functional subareas, then the functional subareas are used as minimum search units, the individualized optimal target points are searched for one functional subarea by one, the spatial arrangement of neurons in the brain is continuous by comprehensively considering the space-time dual characteristics of the superficial cerebral layer of the brain, the neurons with high functional similarity are usually more close in space, the time characteristics of the functional subareas of the superficial brain region are the functional connection strength among voxels, the functional similarity among different voxels is reflected, the spatial characteristics are the spatial distance among different voxels and are aimed at restricting the division of the functional subareas, the minimum unit for target point search can better reflect the functional characteristics of the brain by dividing the superficial brain region into the functional subareas, the voxels in each functional subarea correspond to similar cognitive functions, the division can reduce the fluctuation of the functional connection strength among different voxels, effectively offset the instability of the functional connection of the rest state in a tested subject, and even if the connection strength of certain voxels changes with time, the functional characteristics of the whole functional subareas are relatively consistent, so that the robustness of the positioning of the target points is improved.

The following describes the technical solution in the embodiment of the present application in detail with reference to the drawings in the embodiment of the present application.

Example 1

As shown in fig. 1, fig. 1 is a schematic flow chart of a transcranial magnetic stimulation individual target positioning method according to an embodiment of the present application, and one embodiment of the present application provides a transcranial magnetic stimulation individual target positioning method, which includes:

101. magnetic resonance brain imaging data of the tested individual is acquired, wherein the magnetic resonance brain imaging data comprises a functional magnetic resonance image and a structural magnetic resonance image.

Wherein magnetic resonance brain imaging data of the subject may be acquired using a magnetic resonance imager, the magnetic resonance brain imaging data including functional magnetic resonance images (functional magnetic resonance imaging, fMRI) and structural magnetic resonance images (structural magnetic resonance imaging, sMRI).

102. And preprocessing the functional magnetic resonance image and the structural magnetic resonance image to obtain preprocessed magnetic resonance brain imaging data.

Preprocessing the magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data, wherein the preprocessing comprises the following steps:

preprocessing the magnetic resonance brain imaging data to perform at least one preprocessing operation of head motion correction, spatial alignment, slice time correction, spatial smoothing, signal filtering and denoising.

Specifically, the head motion correction refers to correcting image distortion caused by head motion of a tested person by using a motion correction algorithm, the slice time correction refers to synchronizing different slices at each time point to eliminate signal time delay generated by different acquisition times of the slices, the spatial smoothing refers to reducing noise by using Gaussian smoothing kernel to improve the detectability of the signals and improve the result of statistical analysis, the signal filtering refers to retaining frequency band signals related to neural activity by a band-pass filter, the denoising processing refers to whole brain physiological noise, and particularly removing noise caused by physiological factors such as heartbeat and respiration, and the noise can influence neural activity signals of a specific area, and the noise is a schematic diagram of the preprocessed resting state functional magnetic resonance imaging data (resting-state cerebral functional magnetic resonance imaging, rs-fMRI) as shown in fig. 3.

Spatial alignment refers to the steps of dividing, establishing a coordinate change deformation field between a standard space and a structural magnetic resonance image space, and establishing a coordinate change matrix of the structural magnetic resonance image space and a functional magnetic resonance image space. A population standard map, such as a superficial brain region area range and a deep nucleus region area range defined in a Broadmann-partition (Broadmann area, BA) map, may be converted from the population standard space to the functional magnetic resonance image space using a coordinate-changing deformation field between the standard space and the structural magnetic resonance image space, and a coordinate-changing matrix of the structural magnetic resonance image space and the functional magnetic resonance image space, for example, the superficial brain region may be a superficial left dorsal lateral prefrontal cortex (dorsal lateral prefrontal cortex, DLPFC), the deep nucleus may be a below-knee anterior cingulate cortex (subgenual anterior cingulate cortex, sgACC), the DLPFC is BA46, sgACC is BA25.

The functional magnetic resonance image is preprocessed to remove noise introduced in the signal acquisition process, and the real functional activities of the brain of the tested individual are reserved, so that a reliable basis is provided for subsequent functional connection calculation.

103. And performing superficial brain region division according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional subareas.

According to the application, the superficial brain region is divided into a plurality of functional subareas, so that the position with the strongest resting state functional connection with the deep nucleolus can be searched for in the superficial brain region one by one from the functional subareas and used as an individualized optimal stimulation target point.

According to prior information and brain map, selecting a superficial brain region which can be directly affected by transcranial magnetic stimulation and is associated with a target deep nucleus, calculating a functional connection matrix of the superficial brain region, further determining core voxels of a plurality of initial functional subregions according to the functional connection matrix, and carrying out region growth by using each core voxel to obtain a plurality of functional subregions.

In one embodiment, the computational functional connections (functional connectivity, FC) are a common method of accurately locating DLPFC of patients with TMS-treated refractory major depressive disorder (major depressive disorder, MDD), with the depressed core abnormal brain region below the anterior cingulate cortex (subgenual anterior cingulate cortex, sgACC) located deep in the brain as an anchor point, by setting sgACC as the region of interest (region of interest, ROI), the full brain level functional connections are calculated, and the best therapeutic target is found in the superficial left dorsal lateral prefrontal cortex (dorsal lateral prefrontal cortex, DLPFC). Specifically, as shown in fig. 2, a schematic diagram of acquiring magnetic resonance brain imaging data of a tested individual by using transcranial magnetic stimulation (TRANSCRANIAL MAGNETIC Stimulation, TMS) technology is shown, the TMS technology uses alternating current in a stimulation coil to generate an alternating magnetic field outside the brain so as to excite induced current in the brain to change the electrical activity of neurons, thereby triggering a series of nerve electrophysiological effects and affecting cognition and behaviors of the individual to a certain extent, in fig. 2, a superficial brain region is DLPFC, a deep nucleus is sgACC, and the scheme is used as an individual optimal stimulation target by searching a position with the strongest resting state function connection with the deep nucleus sgACC in the superficial brain region.

Alternatively, in one embodiment, using transcranial magnetic stimulation techniques for obsessive-compulsive therapy, the superficial brain region may be the orbital frontal cortex (Orbitofrontal cortex, OFC), the deep nucleus is the amygdala, and the location within the superficial brain region with the strongest resting state functional connection to the target deep nucleus is found as the individualized optimal stimulation target.

Alternatively, in one embodiment, transcranial magnetic stimulation techniques are employed to promote associative memory, the superficial cortex may be the posterior parietal cortex (posterior parietal cortex, PPC), the deep nuclei are hippocampus, and the location with the strongest resting state functional connection to the target deep nuclei is found voxel by voxel within the superficial brain region as the individualized optimal stimulation target.

That is, the present approach may be employed in the context of depression treatment, obsessive-compulsive disorder treatment, and promotion of associative memory.

The method comprises the steps of dividing a superficial brain region into a plurality of functional subareas, then taking the functional subareas as a minimum search unit, searching for an individual optimal target point from the functional subareas to the functional subareas, comprehensively considering the space-time dual characteristics of the superficial cerebral layer of the brain, wherein the spatial arrangement of neurons in the brain is continuous, the neurons with high functional similarity are generally closer in space, the temporal characteristics of the functional subarea division basis of the superficial brain region are the functional connection strength among voxels, the functional similarity among different voxels is reflected, the spatial characteristics are the spatial distance among the different voxels, and the division of the functional subareas is aimed at being restrained.

104. And determining individual target stimulation targets of transcranial magnetic stimulation according to the functional subregions.

The method comprises the steps of determining individual target stimulation targets of transcranial magnetic stimulation according to the functional subareas, specifically determining functional connection strength of the functional subareas of the superficial brain region and the deep nucleolus, determining target functional subareas according to the functional connection strength of the functional subareas and the deep nucleolus, for example, determining the functional subarea with the maximum functional connection strength as the target functional subarea, further determining individual target stimulation targets of transcranial magnetic stimulation according to the target functional subareas, for example, determining the gravity center of the target functional subarea as the individual target stimulation targets of transcranial magnetic stimulation, and determining the target functional subarea according to the functional connection strength, wherein the larger the functional connection strength is, the more likely to bring more energy stimulation to the deep nucleolus to stimulate the functional subarea.

Or determining individual target stimulation targets of transcranial magnetic stimulation according to the functional subareas, specifically determining the volumes of the functional subareas, then determining the target functional subareas according to the volumes of the functional subareas, for example, taking the volumetric functional subareas as the target functional subareas, further determining individual target stimulation targets of transcranial magnetic stimulation according to the target functional subareas, for example, determining the gravity center of the target functional subareas as the individual target stimulation targets of transcranial magnetic stimulation, and by determining the target functional subareas according to the volumes of the functional subareas, the larger the volumes are, the more effectively representing that energy applied by transcranial magnetic stimulation falls into the area.

According to the method, individual target stimulation targets of transcranial magnetic stimulation are determined according to a plurality of functional subareas, the superficial brain area is divided into the functional subareas, the minimum unit of target point search can better reflect the functional characteristics of the brain, voxels in each functional subarea correspond to similar cognitive functions, the division can reduce fluctuation of functional connection strength among different voxels, instability of resting state functional connection in a tested individual can be effectively counteracted, even if the connection strength of certain voxels changes with time, the functional characteristics of the whole functional subareas still keep relatively consistent, and therefore the robustness of target point positioning is improved.

Optionally, the performing superficial brain region division according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional sub-regions includes:

Extracting time sequence signals of each voxel in the superficial brain region from the preprocessed magnetic resonance brain imaging data, and calculating signal correlation among the voxels to obtain a functional connection matrix of the superficial brain region;

Determining the average functional connection strength of each voxel and all other voxels in the superficial brain region according to the functional connection matrix, and sequencing according to the order of the average functional connection strength from big to small;

Selecting a plurality of voxels as core voxels of the functional subareas according to the sequence from big to small of the average functional connection strength to obtain a plurality of core voxels;

And carrying out region growth by taking each core voxel as a center, and carrying out region division on the superficial brain region division to obtain a plurality of functional subregions.

As shown in fig. 4, a schematic diagram of functional subregion division of a superficial brain region is shown, where the superficial brain region may be DLPFC, for example, a functional connection matrix of the superficial brain region may be calculated first, a time-series signal of each voxel in the superficial brain region is extracted from the preprocessed magnetic resonance brain imaging data, and a signal correlation between the voxels is calculated, so as to obtain the functional connection matrix of the superficial brain region.

Then, determining the average functional connection strength of each voxel and all other voxels in the superficial brain region according to the functional connection matrix, and sorting the voxels according to the order from the big to the small of the average functional connection strength, wherein the core voxels of the functional subregion usually show higher functional connection characteristics with the other voxels in the functional subregion, so that the average functional connection strength of each voxel and all other voxels in the superficial brain region can be calculated, the results are sorted in a descending order, and then, a plurality of voxels with the highest average connection strength are selected as the core voxels of the initial functional subregion, namely, a plurality of voxels are selected as the core voxels of the functional subregion according to the order from the big to the small of the average functional connection strength, so as to obtain a plurality of core voxels.

And finally, carrying out region growth by taking each core voxel as a center, carrying out region division on the superficial brain region division to obtain a plurality of functional subregions, wherein a region growth algorithm can be adopted for region growth, the region growth algorithm is an image segmentation method based on pixel similarity, and the core voxels are growth centers for region growth.

The plurality of voxels are selected as core voxels of the functional sub-region according to the sequence from large to small of the average functional connection strength, so that the plurality of core voxels are obtained, and then the core voxels are used as a growth center for region growth, so that the functional sub-region with larger average functional connection strength can be obtained, the functional sub-region can meet the continuity of neuron space arrangement, and the individuation treatment target point is more suitable.

Optionally, the region growing is performed with each core voxel as a center, so as to perform region division on the superficial brain region division, so as to obtain a plurality of functional sub-regions, including:

Calculating a functional connection value between the growth center and a new voxel which is adjacent to the periphery and is not included in other functional subregions by taking the core voxel as a growth center, and when the functional connection value between the growth center and the new voxel is larger than a first preset value, entering the new voxel into the functional subregion to which the growth center belongs; and continuing to expand by taking the newly incorporated voxels as new growth centers until new voxels meeting the conditions cannot be found, and determining that the division of the functional subareas is completed.

Wherein the function connection value is used for representing the function connection strength, specifically, the larger the function connection value is, the larger the function connection strength is; the first preset value may be, for example, 0.5, when the functional connection value between the growth center and the new voxel is greater than 0.5, the new voxel is incorporated into the functional subregion to which the growth center belongs, the newly incorporated voxel is used as the new growth center, the expansion is continued, the incorporation condition is that the functional connection strength between the new voxel and the incorporated voxel is greater than the first preset value, when the new voxel meeting the condition cannot be found, the division of the functional subregion is determined to be completed, and the steps are repeated, all the functional subregions are determined one by one until all the functional subregions of the core voxel are identified and determined.

Optionally, the method further comprises regarding the functional subarea with the completed area growth, when the functional connection strength between the voxels in the functional subarea is smaller than a third preset value or the volume of the functional subarea is smaller than a fourth preset value, taking all voxels which are not incorporated into the functional subarea as new core voxels, and carrying out area growth by using the new core voxels so as to carry out functional subarea division.

When the functional connection strength between the voxels in the functional subregion is smaller than a third preset value or the volume of the functional subregion is smaller than a fourth preset value, the situation that the core voxels of the functional subregion are missed is indicated, specifically, when the functional connection strength between the voxels in one functional subregion is too low or the area volume of the functional subregion is too small, the situation that the core voxels of the functional subregion are missed may occur, at this time, all the voxels which are not incorporated into the functional subregion need to be taken as new core voxels, and the functional subregion is searched again according to the area growth process of the area growth algorithm to find all the functional subregions.

Optionally, the method further comprises the steps of judging whether region fusion is needed for the functional subareas with the completed region growth, and when the two functional subareas meet the fusion condition, carrying out region fusion on the two functional subareas meeting the fusion condition to obtain a plurality of fused functional subareas, wherein the fusion condition is that the functional connection strength between voxels of the functional subareas is larger than a second preset value or the volume of the functional subareas is larger than a fifth preset value.

The method comprises the steps of carrying out fusion and adjustment on functional subareas which finish area growth, wherein the division of the functional subareas highly depends on the core voxels of the determined initial functional subareas, and when the connection strength between all voxels in one functional subarea is too high or the volume of the subarea area is too large, namely, the functional connection strength between the voxels of the functional subareas is larger than a second preset value or the volume of the functional subarea is larger than a fifth preset value, a plurality of voxels which originally belong to the same functional subarea are possibly proposed as the core voxels of the independent functional subarea, and at the moment, all the functional subareas which finish growth are required to be judged, and whether the functional subareas need to be fused or not is judged. When the two functional subregions meet a fusion condition (for example, the functional connection strength between voxels in the two functional subregions is greater than 0.5), the two functional subregions are fused to ensure that the division of the functional subregions is more accurate.

Optionally, the determining an individual target stimulation target of transcranial magnetic stimulation according to the plurality of functional subregions includes:

determining the functional connection strength of a plurality of functional subregions of the superficial brain region and the deep nucleolus;

determining a volume of the plurality of functional subregions;

Determining a target functional sub-region according to the functional connection strength of the functional sub-regions and the deep nucleolus and the volumes of the functional sub-regions;

and determining an individualized target stimulation target point of transcranial magnetic stimulation according to the target functional subregion.

The method comprises the steps of determining a target functional subarea according to the functional connection strength of a plurality of functional subareas and deep nucleolus and the volumes of the functional subareas, determining an individualized target stimulation target point of transcranial magnetic stimulation according to the target functional subarea, wherein the larger the functional connection strength is, the more likely the functional subarea is stimulated to bring greater energy stimulation to the deep nucleolus, the larger the volume is, the more effectively the energy applied by transcranial magnetic stimulation is represented to fall into the area, the functional connection strength and the volumes of the functional subareas can be integrated, the more accurate target functional subarea is obtained, and the individualized target stimulation target point is further positioned.

Optionally, the determining the target functional subarea according to the functional connection strength of the functional subareas and the deep nucleolus and the volumes of the functional subareas includes:

Determining target score values corresponding to the functional subareas according to the first weight corresponding to the functional connection strength, the second weight corresponding to the volume of the functional subareas, the functional connection strength of the functional subareas and the deep nucleolus and the volume of the functional subareas;

and determining the functional subarea with the maximum target score value as the target functional subarea.

The first weight corresponding to the functional connection strength and the second weight corresponding to the volume of the functional subarea can be preset, so that the functional connection strength and the volume of the functional subarea can be integrated, a more accurate target functional subarea can be obtained, and an individual target stimulation target point can be positioned.

Optionally, the determining an individual target stimulation target point of transcranial magnetic stimulation according to the target functional subregion includes:

Determining the gravity center of a target functional subarea, taking the gravity center position of the target functional subarea as an individual target stimulation target point of transcranial magnetic stimulation, wherein the gravity center position generally represents the center of functional activity in the functional subarea, and stimulating the gravity center can more effectively influence the peripheral neuron population and maximize the energy transfer of transcranial magnetic stimulation.

Example two

As shown in fig. 5, an embodiment of the present application proposes another method for locating an individual target spot by transcranial magnetic stimulation, and fig. 5 is a schematic flow chart of another method for locating an individual target spot by transcranial magnetic stimulation, which includes:

201. Magnetic resonance brain imaging data of the tested individual is acquired, wherein the magnetic resonance brain imaging data comprises a functional magnetic resonance image and a structural magnetic resonance image.

202. Preprocessing the magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data.

203. Extracting time sequence signals of each voxel in the superficial brain region from the preprocessed magnetic resonance brain imaging data, and calculating signal correlation among the voxels to obtain a functional connection matrix of the superficial brain region.

204. And determining the average functional connection strength of each voxel and all other voxels in the superficial brain region according to the functional connection matrix, and sequencing the voxels according to the order of the average functional connection strength from high to low.

205. And selecting a plurality of voxels as core voxels of the functional subareas according to the order of the average functional connection strength from large to small to obtain a plurality of core voxels.

206. And calculating the functional connection value between the growth center and a new voxel which is adjacent to the surrounding and is not included in other functional subareas by taking the core voxel as the growth center.

207. And judging whether the functional connection value between the growth center and the new voxel is a first preset value or not.

208. If yes, the new voxels are included in the functional subareas which the growth centers belong to, the newly included voxels are used as the new growth centers, expansion is continued until the new voxels which meet the conditions cannot be found, the functional subareas are determined to be divided, so that a plurality of functional subareas are obtained, and if not, the functional subareas are determined to be divided, so that a plurality of functional subareas are obtained.

209. Functional connection strength of a plurality of functional subregions of the superficial brain region and the deep nucleolus is determined.

210. A volume of the plurality of functional subregions is determined.

211. And determining target score values corresponding to the functional subareas according to the first weight corresponding to the functional connection strength, the second weight corresponding to the volume of the functional subareas, the functional connection strength of the functional subareas and the deep nucleolus and the volumes of the functional subareas.

212. And determining the functional subarea with the maximum target score value as the target functional subarea.

213. And determining the gravity center of the target functional subarea, and taking the gravity center position of the target functional subarea as an individual target stimulation target point of transcranial magnetic stimulation.

The embodiment comprises the steps of extracting time sequence signals of each voxel in a superficial brain region from preprocessed magnetic resonance brain imaging data, calculating signal correlation among the voxels to obtain a functional connection matrix of the superficial brain region, determining average functional connection strength of each voxel and all other voxels in the superficial brain region according to the functional connection matrix, sequencing according to the average functional connection strength from large to small, selecting a plurality of voxels as core voxels of a functional subregion according to the order of the average functional connection strength from large to small to obtain a plurality of core voxels, taking the core voxels as growth centers, calculating functional connection values between the growth centers and adjacent new voxels which are not included in other functional subregions, taking the new voxels as the new growth centers when the functional connection values between the growth centers and the new voxels are larger than a first preset value, continuing to expand until the new voxels meeting the conditions are not found, determining that functional division is completed, determining a plurality of functional subregions of the superficial brain region, determining the core voxels as core voxels of the functional subregions according to the order of the average functional connection strength, determining the corresponding functional connection values of the core voxels and the functional subregions of the functional subregions, determining the corresponding functional connection values of the core voxels and the functional subregions according to the corresponding functional connection values of the functional connection values and the functional connection values of the core body and the functional subregions of the functional connection values and the functional connection values of the functional subregions, the method comprises the steps of selecting a plurality of voxels as core voxels of a functional subarea according to the sequence from large to small of average functional connection strength, obtaining a plurality of core voxels, further carrying out regional growth by taking the core voxels as growth centers, obtaining a functional subarea with larger average functional connection strength, enabling the functional subarea to meet the continuity of neuron space arrangement, enabling an individuation treatment target to be more suitable, determining a target functional subarea according to the functional connection strength of the functional subareas and deep nucleolus and the volumes of the functional subareas, determining an individuation target stimulation target spot of the transcranial magnetic stimulation according to the target functional subarea, enabling the larger functional connection strength to represent that the functional subarea is more likely to bring larger energy stimulation to the deep nucleolus, enabling the larger volume to represent the energy applied by transcranial magnetic stimulation to fall into the area more effectively, combining the functional connection strength and the volumes of the functional subarea, further positioning the individuation target stimulation target spot, enabling the barycenter position of the target functional subarea to serve as the functional connection strength of the functional subarea to be the functional connection strength of the transcranial magnetic stimulation target spot, and the individuation target area can represent the maximum stimulation target spot of the transcranial magnetic stimulation, and the functional subarea can normally represent the stimulation target spot of the functional stimulation target area around the functional magnetic stimulation.

Example III

As shown in fig. 6, fig. 6 provides an individual target localization system 300 for transcranial magnetic stimulation according to an embodiment of the present application, comprising:

an acquisition module 301, configured to acquire magnetic resonance data of a subject, where the magnetic resonance data includes a functional magnetic resonance image;

A preprocessing module 302, configured to preprocess the magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data;

the division module 303 is configured to perform superficial brain region division according to the preprocessed magnetic resonance brain imaging data, so as to obtain a plurality of functional sub-regions;

The positioning module 304 is configured to determine an individual target stimulation target point of transcranial magnetic stimulation according to the plurality of functional subregions.

Optionally, in the aspect of preprocessing the magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data, the preprocessing module 302 is specifically configured to:

Preprocessing the magnetic resonance brain imaging data to perform at least one preprocessing operation of head motion correction, slicing time correction, space smoothing, signal filtering and denoising.

Optionally, in the aspect of performing superficial brain region division according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional sub-regions, the division module 303 is specifically configured to:

Optionally, in the aspect of performing region growing with each core voxel as a center to perform region division on the superficial brain region to obtain a plurality of functional sub-regions, the division module 303 is specifically configured to:

Optionally, the dividing module 303 is further configured to, for the functional subregion with the region growing completed, when the functional connection strength between the voxels in the functional subregion is smaller than the third preset value or the volume of the functional subregion is smaller than the fourth preset value, take all voxels not included in the functional subregion as new core voxels, and perform region growing with the new core voxels to perform functional subregion division.

Optionally, the dividing module 303 is further configured to determine whether region fusion is required for the functional subregions that have completed region growth, and when two functional subregions satisfy a fusion condition, perform region fusion on the two functional subregions that satisfy the fusion condition, to obtain a plurality of fused functional subregions, where the fusion condition is that the functional connection strength between voxels of the functional subregions is greater than a second preset value or the volume of the functional subregion is greater than a fifth preset value.

Optionally, in the determining an individual target stimulation target point of transcranial magnetic stimulation according to the plurality of functional subregions, the positioning module 304 is specifically configured to:

determining a volume of the plurality of functional subregions;

Optionally, in the aspect of determining the target functional subarea according to the functional connection strength of the functional subareas and the deep nucleolus and the volumes of the functional subareas, the positioning module 304 is specifically configured to:

Optionally, the determining an individual target stimulation target aspect of transcranial magnetic stimulation according to the target functional subregion, and the positioning module 304 is specifically configured to:

and determining the gravity center of the target functional subarea, and taking the gravity center position of the target functional subarea as an individual target stimulation target point of transcranial magnetic stimulation.

According to the method for positioning the target spot of the individual through the transcranial magnetic stimulation, magnetic resonance brain imaging data of a tested individual are obtained, and the magnetic resonance brain imaging data comprise functional magnetic resonance images and structural magnetic resonance images; the method comprises preprocessing magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data, preprocessing the magnetic resonance brain imaging data to remove noise introduced in a signal acquisition process, reserving real functional activities of brains of a tested subject, providing a reliable basis for subsequent functional connection calculation, dividing a superficial brain region according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional subareas, determining individual target stimulation targets of transcranial magnetic stimulation according to the plurality of functional subareas, dividing the superficial brain region into a plurality of functional subareas, then taking the functional subareas as a minimum search unit, searching for individual optimal targets by taking the functional subareas, comprehensively considering spatial and temporal dual characteristics of the superficial cerebral cortex, wherein the spatial arrangement of neurons in the brain has continuity, the neurons with high functional similarity are generally more close in space, the temporal characteristics according to the division of the functional subareas are functional connection strength between voxels, reflect the functional similarity between different voxels, the spatial characteristics are different spatial distances between the different voxels, the functional subareas can be compared with each functional subarea with the constraint condition, the functional subarea can be better compared with the functional connection strength between the functional subareas, the functional subareas can be better compared with the functional connection performance of the functional subareas, and the functional subarea can be better compared with the functional connection conditions of the functional subareas is better compared with the functional subareas, even if the connection strength of some voxels changes with time, the functional characteristics of the whole functional subarea still remain relatively consistent, thereby improving the robustness of target positioning.

Example IV

Referring to fig. 7, the embodiment of fig. 7 provides a transcranial magnetic stimulation individual target positioning system, which includes a processor 410 and a memory 420, and one or more programs, where the one or more programs are stored in the memory, and the memory 420 may be a high-speed RAM memory or a nonvolatile memory (non-volatile memory), for example, a disk memory. The memory 4000 is used for storing a set of program codes, and the processor 410 is used for calling the program codes stored in the memory 420 to execute the following operations:

Acquiring magnetic resonance brain imaging data of a tested individual, wherein the magnetic resonance brain imaging data comprises a functional magnetic resonance image;

Performing superficial brain region division according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional subregions;

and determining individual target stimulation targets of transcranial magnetic stimulation according to the functional subregions.

In one possible example, in said preprocessing of said magnetic resonance brain imaging data, in obtaining the preprocessed magnetic resonance brain imaging data, the processor 410 is specifically configured to:

In one possible example, the processor 410 is specifically configured to, in terms of performing superficial brain region division according to the preprocessed magnetic resonance brain imaging data, obtain a plurality of functional sub-regions:

In one possible example, in the aspect of performing region growing with each core voxel as a center to perform region division on the superficial brain region division to obtain a plurality of functional subregions, the processor 410 is specifically configured to calculate, with the core voxel as a center, a functional connection value between the center and a new voxel adjacent to the surrounding and not included in other functional subregions, and when the functional connection value between the center and the new voxel is greater than a first preset value, to include the new voxel in the functional subregion to which the center belongs, and to continue expanding with the newly included voxel as a new center until a new voxel satisfying the condition cannot be found, to determine that the functional subregion division is completed.

In a possible example, the processor 410 is further configured to, for a functional sub-region that has completed the region growing, when the functional connection strength between the voxels in the functional sub-region is smaller than the third preset value or the volume of the functional sub-region is smaller than the fourth preset value, take all voxels that are not included in the functional sub-region as new core voxels, and perform the region growing with the new core voxels to perform the functional sub-region division.

In one possible example, the processor 410 is further configured to determine whether region fusion is required for the functional subregions that have completed region growth, and when two functional subregions satisfy a fusion condition, perform region fusion on the two functional subregions that satisfy the fusion condition, to obtain a plurality of fused functional subregions, where the fusion condition is that the functional connection strength between voxels of the functional subregions is greater than a second preset value or the volume of the functional subregion is greater than a fifth preset value.

In one possible example, the processor 410 is specifically configured to, in determining the individual target stimulation targets for transcranial magnetic stimulation from the plurality of functional subregions:

determining a volume of the plurality of functional subregions;

In one possible example, the processor 410 is specifically configured to, in determining the target functional sub-area according to the functional connection strength of the plurality of functional sub-areas and the deep nucleolus and the volumes of the plurality of functional sub-areas:

In one possible example, the processor 410 is specifically configured to determine a center of gravity of the target functional sub-region, and take the location of the center of gravity of the target functional sub-region as the target stimulation target of the individual transcranial magnetic stimulation in terms of the determination of the target stimulation target of the individual transcranial magnetic stimulation based on the target functional sub-region.

The method for positioning individual targets by transcranial magnetic stimulation comprises the steps of obtaining magnetic resonance brain imaging data of a tested individual, preprocessing the magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data, preprocessing the magnetic resonance brain imaging data to remove noise introduced in a signal acquisition process, reserving real functional activities of the brain of the tested individual, providing a reliable basis for subsequent functional connection calculation, dividing superficial brain regions according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional subregions, determining individual target stimulation targets by transcranial magnetic stimulation according to the plurality of functional subregions, searching for individual optimal targets one by taking the functional subregions as a minimum search unit, comprehensively considering the spatial arrangement of neurons in the brain by taking the spatial double features of the superficial brain layer into consideration, enabling neurons with high functional similarity to be generally closer to each other in the space, searching for the functional target points in different functional subregions according to the different spatial characteristics of the functional subregions, and reducing the functional characteristics of the functional connection points between the functional subregions by the different functional connection points in the different functional regions, and reducing the functional characteristics of the functional connection points between the functional regions by the different functional connection points between the functional regions of the functional regions, even if the connection strength of some voxels changes with time, the functional characteristics of the whole functional subarea still remain relatively consistent, thereby improving the robustness of target positioning.

Embodiments of the present application also provide a computer program product, wherein the computer program product comprises a non-transitory computer readable program product storing a computer program operable to cause a computer to perform some or all of the steps described in any of the transcranial magnetic stimulation individual target positioning methods as described in the embodiments of the present application. The computer program product may be a software installation package.

Although the application is described herein in connection with various embodiments, other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed application, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

It will be apparent to those skilled in the art that embodiments of the present application may be provided as a method, apparatus (device), or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. A computer program may be stored/distributed on a suitable medium supplied together with or as part of other hardware, but may also take other forms, such as via the Internet or other wired or wireless telecommunication systems.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable human-vehicle track analysis device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable human-vehicle track analysis device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable human-vehicle trajectory analysis device to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable human vehicle track analysis device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer implemented process such that the instructions which execute on the computer or other programmable device provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

Although the application has been described in connection with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made without departing from the spirit and scope of the application. Accordingly, the specification and drawings are merely exemplary illustrations of the present application as defined in the appended claims and are considered to cover any and all modifications, variations, combinations, or equivalents that fall within the scope of the application. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims

1. A method for locating an individual target site by transcranial magnetic stimulation, comprising:

determining individual target stimulation targets of transcranial magnetic stimulation according to the functional subregions;

the performing superficial brain region division according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional subareas, including:

Performing region growth by taking each core voxel as a center, and performing region division on the superficial brain region division to obtain a plurality of functional subregions;

the determining individual target stimulation targets of transcranial magnetic stimulation according to the plurality of functional subregions comprises:

determining a volume of the plurality of functional subregions;

2. The method for locating an individual target spot by transcranial magnetic stimulation according to claim 1, wherein the preprocessing the magnetic resonance brain imaging data to obtain preprocessed magnetic resonance brain imaging data comprises:

3. The method of claim 1, wherein the performing region growing with each core voxel as a center to perform region division on the superficial brain region to obtain a plurality of functional sub-regions comprises:

4. A method of locating an individual target site for transcranial magnetic stimulation according to claim 3, further comprising:

And when the functional connection strength among all voxels in the functional subarea is smaller than a third preset value or the volume of the functional subarea is smaller than a fourth preset value, taking all voxels which are not included in the functional subarea as new core voxels, and carrying out area growth by using the new core voxels so as to divide the functional subareas.

5. A method of locating an individual target site for transcranial magnetic stimulation according to claim 3, further comprising:

Judging whether region fusion is needed for the functional subareas with the completed region growth, and when the two functional subareas meet the fusion condition, carrying out region fusion on the two functional subareas meeting the fusion condition to obtain a plurality of fused functional subareas, wherein the fusion condition is that the functional connection strength between voxels of the functional subareas is larger than a second preset value or the volume of the functional subareas is larger than a fifth preset value.

6. The method of claim 1, wherein determining the target functional subregion based on the functional junction strength of the plurality of functional subregions and the deep nuclei and the volumes of the plurality of functional subregions comprises:

7. The method of claim 6, wherein determining the target stimulation target of the transcranial magnetic stimulation based on the target functional sub-region comprises:

8. A transcranial magnetic stimulation individual target positioning system, comprising:

The acquisition module is used for acquiring magnetic resonance brain imaging data of the tested individual, wherein the magnetic resonance brain imaging data comprises a functional magnetic resonance image and a structural magnetic resonance image;

The division module is used for carrying out superficial brain region division according to the preprocessed magnetic resonance brain imaging data to obtain a plurality of functional subareas;

The positioning module is used for determining an individual target stimulation target point of transcranial magnetic stimulation according to the functional subareas;

The dividing module is further configured to:

the positioning module is also used for:

determining a volume of the plurality of functional subregions;

9. An individual target localization system for transcranial magnetic stimulation comprising a processor and a memory, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising steps for the individual target localization method for transcranial magnetic stimulation according to any one of claims 1 to 7.

10. A computer program product, characterized in that a computer program of the computer program product, when being executed by a processor, is capable of carrying out the steps of the individual target localization method of transcranial magnetic stimulation according to any one of claims 1 to 7.