CN116570267A - rTMS target positioning system - Google Patents
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Abstract
The invention relates to an rTMS target positioning system, which belongs to the field of target positioning and comprises the following components: the healthy person fine double-hand pinching task module acquires a first fMRI image when the healthy person performs a fine double-hand pinching task; the patient's healthy side hand fine pinching task module acquires a second fMRI image when the patient's healthy side hand fine pinching task; the center processing module is used for determining that a fine double-hand pinching autonomous movement region of a healthy person is used as a Mask on the first fMRI image; determining a patient healthy side activation point on the second fMRI image, the patient healthy side activation point serving as an rTMS stimulation target of the patient healthy side; and determining the rTMS stimulation target point of the affected side by taking the rTMS stimulation target point of the healthy side of the patient as a seed point. According to the invention, the accurate hand pinching autonomous movement area of the healthy person is determined, the accurate hand pinching autonomous movement area of the healthy person is taken as a reference, the position of the rTMS stimulation target point on the patient side is determined according to the position of the rTMS stimulation target point on the patient side, and the rTMS stimulation target point of the patient is positioned more accurately.
Description
Technical Field
The invention belongs to the technical field of target positioning, and particularly relates to an rTMS target positioning system.
Background
Repeated transcranial magnetic stimulation (rTMS) is a common rehabilitation means for patients with ischemic stroke in unilateral basal ganglia, and the key point of treatment is to find an rTMS target, and at present, the positioning of the rTMS target is generally based on scalp anatomical landmark positioning, individuation is not considered, and the obtained target position is not accurate enough. Or the cortical movement hot spot measured based on transcranial magnetic stimulation is adopted as a target point, and the functional specificity is not improved aiming at the fine hand function. fMRI (magnetic resonance imaging) can provide target coordinates with functional specificity, and personalized accurate positioning of rTMS targets is achieved.
Disclosure of Invention
The invention aims to solve the technical problem of providing an rTMS target positioning system which improves the positioning accuracy.
In order to solve the problems, the invention adopts the following technical scheme: an rTMS target localization system comprising:
the healthy person fine double-hand pinching task module is used for acquiring a first fMRI image when the healthy person performs a fine double-hand pinching task;
the patient's healthy side hand fine pinching task module is used for acquiring a second fMRI image when the patient's healthy side hand fine pinching task is performed;
the central processing module is used for determining a fine opposite pinching autonomous motion area of both hands of a healthy person on the first fMRI image as a Mask; determining a patient healthy side activation point on the second fMRI image, the patient healthy side activation point serving as an rTMS stimulation target of the patient healthy side; taking an rTMS stimulation target point on a healthy side of a patient as a seed point, extracting a time sequence signal of the seed point, and calculating the Pelson correlation of each voxel in a Mask for pinching an autonomous movement region to the hands of a healthy person on the opposite side, so as to obtain a Pelson correlation value of each voxel, and taking the voxel with the largest Pelson correlation value as the rTMS stimulation target point on the patient side.
Further, the first fMRI image acquired by the healthy person double-hand fine pinching task module comprises first task state functional images in each time period, and the central processing module normalizes the first task state functional images to an MNI space and then determines a double-hand fine pinching autonomous movement region of the healthy person;
the second fMRI image acquired by the patient healthy side hand fine pinching task module comprises a T1 structural image, a second task state functional image and a second rest state functional image which are sequentially acquired in each time period, and the central processing module registers the T1 structural image, the second task state functional image and the second rest state functional image in the same time period and then determines rTMS stimulation targets of the healthy side and the affected side.
Further, the process of registering the T1 structural image, the second task state functional image and the second rest state functional image in the same time period by the central processing module is as follows: and fixing the T1 structural image, and respectively converting and registering the second task state functional image and the second rest state functional image to the T1 structural image.
Further, the process of transforming and registering the second task state functional image and the second rest state functional image to the T1 structural image comprises the following steps:
s1, correcting interlayer acquisition time difference of a second task state functional image and a second rest state functional image;
s2, rearranging rigid bodies among layers to correct head movements;
s3, aligning the second task state functional image and the second rest state functional image to the T1 structural image;
s4, dividing the T1 structural image, and converting the Mask from the MNI standard space back to the patient individual space by an inverse matrix generated in the dividing process so as to limit the position of a task activation peak point;
s5, performing space smoothing on the second task state functional image and the second rest state functional image by using a full width half maximum 6 mm Gaussian smoothing kernel.
Further, the process of the central processing module for normalizing the first task state functional image to the MNI space is as follows:
s1, correcting interlayer acquisition time difference of a first task state functional image;
s2, rearranging rigid bodies among layers to correct head movements;
s3, standardizing the first task state functional image to an MNI space;
s4, performing space smoothing on the first task state functional image by using a full width half maximum 6 mm Gaussian smoothing kernel.
Further, the central processing module is provided with SPM12 software, and after the second fMRI image registration, the SPM12 software is adopted to conduct individual patient level activation analysis.
Further, the healthy person double-hand fine pinching task module is used for acquiring first fMRI images when n healthy persons carry out a hand fine pinching task, wherein n is more than or equal to 90; after registering the first fMRI images, the central processing module constructs a hand fine pinching task group activation statistical graph of n healthy people, and performs FDR correction on the hand fine pinching task group activation statistical graph, wherein the corrected P value is smaller than 0.05.
Further, the central processing module is provided with SPM12 software, and after the first fMRI image is normalized to the MNI space, SPM12 software is adopted to perform individual horizontal activation analysis of healthy people and construct a group activation statistical graph.
Further, the healthy person's both hands are meticulous to pinching task module and patient's healthy side hand are meticulous to pinching task module all including pinching force dynamometer and fMRI scanning equipment, pinching force dynamometer is used for carrying out the meticulous task of pinching of hand, fMRI scanning equipment is used for obtaining fMRI image.
The beneficial effects of the invention are as follows: according to the method, the fine pinching autonomous movement area of the hands of the healthy person is firstly determined, the fine pinching autonomous movement area of the hands of the healthy person is used as a reference, the activation peak point of the healthy side of the patient is limited in the region and is used as the rTMS stimulation target point position of the healthy side of the patient, then the healthy side stimulation target point is determined by calculating functional connection in the corresponding region of the affected side according to the healthy side stimulation target point coordinates, and the rTMS stimulation target point of the patient is positioned more individually, accurately and functionally and specially.
Drawings
FIG. 1 is a schematic diagram of the construction of an rTMS target localization system of the invention;
FIG. 2 is a schematic representation of a second task fMRI image prior to registration;
FIG. 3 is a second resting state fMRI diagram prior to registration;
FIG. 4 is a schematic illustration of a T1 structural image prior to registration;
FIG. 5 is a schematic representation of a registered second task fMRI image;
FIG. 6 is a second resting state fMRI diagram after registration;
FIG. 7 is a schematic illustration of a registered T1 structural image;
FIG. 8 is a schematic diagram of an fMRI scanner of the present invention;
FIG. 9 is a schematic cross-sectional view of A-A of FIG. 8;
reference numerals: 1-a task module for a healthy person to pinch the hands finely; 2, a task module for the fine pinching of the patient's healthy side hands; 3-a central processing module; 4-a pinching force measuring device; 5-fMRI scanner; 51—an equipment body; 52—an examination bed; 53-a rotating shaft; 54-a rotational drive mechanism; 55-a cross beam; 56-a slider; 57-suspension wire; 58-a linear drive mechanism; 59—hand position detection element.
Detailed Description
The invention will be further described with reference to the drawings and examples.
Example 1 the rTMS target localization system of this example, as shown in fig. 1, comprises:
the healthy person fine double-hand pinching task module 1 is used for acquiring a first fMRI image when the healthy person performs a fine double-hand pinching task;
the patient's healthy side hand fine pinching task module 2 is used for acquiring a second fMRI image when the patient's healthy side hand fine pinching task is performed;
a central processing module 3, configured to determine, on the first fMRI image, a fine double-hand pinching autonomous motion region of a healthy person as a Mask; determining a patient healthy side activation point on the second fMRI image, the patient healthy side activation point serving as an rTMS stimulation target of the patient healthy side; taking an rTMS stimulation target point on a healthy side of a patient as a seed point, extracting a time sequence signal of the seed point, and calculating the Pelson correlation of each voxel in a Mask for pinching an autonomous movement region to the hands of a healthy person on the opposite side, so as to obtain a Pelson correlation value of each voxel, and taking the voxel with the largest Pelson correlation value as the rTMS stimulation target point on the patient side.
The healthy person's both hands fine pinching task module 1 and the patient's healthy side hands fine pinching task module 2 comprise two parts, namely a pinching force measuring device 4 and an fMRI scanning device 5, the pinching force measuring device 4 is used for executing the hand fine pinching task, and the fMRI scanning device 5 is used for acquiring fMRI images. The same pinch force measuring device 4 and fMRI scanning device 5 can be used by the healthy person's both hands fine pinch task module 1 and the patient's healthy side hand fine pinch task module 2.
The specific mode of the fine hand pinching task is as follows: the pinching force measuring device 4 is clamped by the index finger and the thumb of the subject, different pinching forces are applied to the pinching force measuring device 4, when pinching force is applied to the pinching force measuring device 4 by the subject, the movement of the index finger and the thumb is controlled by the corresponding functional areas of the cerebral cortex, and at the moment, the position of the functional areas can be found on the fMRI image by carrying out fMRI scanning on the brain of the subject to obtain the fMRI image.
Before formally performing a hand fine pinching task, a motor cognition experiment is required to be performed for testing the force required for different fine degrees in the hand fine pinching task. The method comprises the following steps:
a healthy person is taken as an experimental object, a thumb and an index finger are used for clamping a real-time feedback pinching force measuring device 4 and resisting resistance (low, medium, high and high levels) with different intensities, and the pinching force of each person is recorded and used for quantifying the low, medium, high and high forces. The task stimulation program can be written through E-prime software, the experimental time of each person is 20 minutes, the whole task program comprises 40 blocks, each block lasts for 30 seconds, blocks with five forces randomly appear, a subject applies a kneading force to the kneading force measuring device 4 according to a prompt (the prompt content is the kneading force grade applied), the kneading force intensity of the kneading force measuring device 4 is displayed by utilizing a display screen, and when the kneading force reaches the target force, the kneading force is stopped. In the experimental process, only the pinching force of each grade is measured and used for quantifying the pinching force of each grade, and fMRI scanning is not performed.
When a healthy person carries out a fine pinching task with both hands, the pinching task is carried out with the left hand and the right hand respectively, rather than simultaneously.
Through the above experiment, the pinching force of five grades is standardized, and in the subsequent task process, the healthy subjects and the patients apply standardized pinching force to the pinching force measuring device 4.
The specific process of the healthy person's fine double-hand pinching task module 1 obtaining the first fMRI image when the healthy person carries out the fine double-hand pinching task is as follows: the healthy subject applies the pinching force to the pinching force dynamometer 4 according to the prompt (the prompting content is the pinching force grade), the pinching force can be gradually increased, the pinching force dynamometer 4 detects the pinching force, the prompt is performed again when the pinching force reaches the standard value, the pinching force is kept unchanged by the subject, and the pinching force is continuously applied to the pinching force dynamometer 4. At this time, fMRI scanning is performed on the subject by the fMRI scanning apparatus 5, and fMRI images of the brain of the subject are acquired.
The process of acquiring the second fMRI image of the patient's healthy side hand fine pinching task module 2 during the patient's healthy side hand fine pinching task is substantially the same as the process of acquiring the first fMRI image, but the acquired second fMRI image mainly consists in studying the fMRI image of the patient's healthy side brain, and the first fMRI image consists of the fMRI images of the left and right brain.
In the invention, the brain is divided into left and right sides, and the brain on one side of the ischemic cerebral apoplexy patient is in a healthy state, and the healthy side refers to the healthy side of the brain of the patient, and the diseased side refers to the diseased side of the patient. Both sides of the brain of healthy subjects are healthy.
In the conventional fMRI scanning apparatus 5, functional images and structural images cannot be obtained simultaneously in the fMRI scanning process, and there is a time difference of several minutes. The structural image can clearly display the cerebral cortex structure, the functional image is an image for researching cerebral functions, and the untreated original image cannot display effective information. In the invention, a first fMRI image acquired by a healthy person double-hand fine pinching task module 1 comprises a first task state functional image in each time period, and a central processing module 3 normalizes the first task state functional image to an MNI space and then determines a double-hand fine pinching autonomous motion area of the healthy person; the second fMRI image acquired by the patient's healthy side hand fine pinching task module 2 comprises a T1 structural image, a second task state functional image and a second rest state functional image which are sequentially acquired in each time period, and the central processing module 3 registers the T1 structural image, the second task state functional image and the second rest state functional image in the same time period and then determines rTMS stimulation targets of the healthy side and the affected side.
The task state refers to a brain state when the subject applies a pinching force to the pinching force measuring device 4, the rest state refers to a brain state when the subject does not perform any task, i.e. does not apply pinching force to the pinching force measuring device 4, the brain is different in performance under the two states, and an activated area of the brain under the task state, i.e. an area where the brain control hands are finely in pinching motion, is used for determining an rTMS stimulation target point of a healthy person, wherein the both hands are finely in pinching autonomous motion area and a healthy side of the patient, and the rest state is used for determining an rTMS stimulation target point of the patient side.
Generally, the structural image can clearly display the brain structure, while the functional image cannot be directly observed from the original image, and the brain functional activity can be observed only through professional image processing. As shown in fig. 2, 3 and 4, fig. 2, 3 and 4 are respectively a second task state fMRI image, a second rest state fMRI image and a T1 structural image, and as can be seen from fig. 2, 3 and 4, the second task state fMRI image and the second rest state fMRI image cannot provide effective information, and the T1 structural image is clearly discernable. Thus, in determining the location of the target site stimulated by the patient rTMS, binding the functional image to the structural image is required to clearly determine the location of the target site.
During magnetic resonance scanning, each imaging sequence, namely, different brain images, need to be obtained in sequence, and as the structural image, the resting state functional image and the task state functional image in the same time period are slightly different in acquisition time points and are different in a plurality of minutes, the head is difficult to ensure to be completely immobilized in an image acquisition gap, and the position and the posture of the head are changed, so that the position of a certain part of the brain on different images is different, namely, the images are misplaced, and errors can occur in subsequent processing. Therefore, the second fMRI image is registered, the image error caused by the position and posture change of the head of the subject in the image acquisition process is eliminated, and then the next processing is carried out, so that the accuracy of target positioning can be improved.
The registration is a common process of the prior fMRI image processing, but the prior fMRI image generally has only one functional image in a state, so the prior registration mode is that the functional image is kept still, and the structural image is transformed, so that the registration of the functional image and the structural image is realized. However, if the existing registration mode is adopted, the structural image needs to be transformed twice, and the task state functional image and the rest state functional image are independent from each other, so that the three images cannot be combined uniformly, that is, the registration requirement cannot be met, and the target positioning is inaccurate. Therefore, in the present invention, the process of registering the T1 structural image, the second task state functional image and the second rest state functional image in the same time period by the central processing module 3 is as follows: and the T1 structural image is fixed, and the second task state functional image and the second rest state functional image are respectively transformed and registered to the T1 structural image. After registration, the three images are combined into a whole, so that the accuracy of target positioning is ensured.
The process of the central processing module 3 for standardizing the first task state functional image to the MNI space is as follows:
s1, correcting interlayer acquisition time difference of a first task state functional image;
s2, rearranging rigid bodies among layers to correct head movements;
s3, standardizing the first task state functional image to an MNI space;
s4, performing space smoothing on the first task state functional image by using a full width half maximum 6 mm Gaussian smoothing kernel.
After the first task state functional image is standardized to the MNI space, the fine opposite pinching autonomous movement region of the two hands of the healthy person can be found out on the first task state functional image.
In order to increase the number of samples of healthy people, the healthy people double-hand fine pinching task module 1 is used for acquiring first fMRI images when n healthy people carry out hand fine pinching tasks, wherein n is more than or equal to 90, for example, 100 healthy people can sequentially carry out hand fine pinching tasks, and acquiring first fMRI images of 100 healthy people. After registering the first fMRI images, the central processing module 3 constructs a hand fine pinching task group activation statistical graph of n healthy people, and performs FDR correction on the hand fine pinching task group activation statistical graph, wherein the corrected P value is smaller than 0.05.
The central processing module 3 is provided with SPM12 (Statistical Parametric Mapping, version 12) software, and after the first fMRI image is normalized to the MNI space, the SPM12 software is adopted to perform individual horizontal activation analysis of healthy people and further construct a group activation statistical chart.
The SPM12 software is the existing software, and the process of carrying out individual level activation analysis of healthy people and further constructing a group activation statistical chart by adopting the SPM12 software comprises the following steps:
individual level activation analysis is performed in the specific 1st-level function module in SPM12, with task activation calculated for each individual, finding the activation region for each individual. The method mainly comprises the following three steps: (1) generating a design matrix comprising: set Units for design, interscan interval, microtime resolution, microtime set, multiple regressors, high-pass filter, generate SPM. (2) And estimating (Estimate) by adopting the SPM.mat file generated in the last step. (3) And (3) carrying out statistical test (Result-coherent), importing the SPM.mat file generated in the last step, selecting t-coherent, clicking done, and generating spmT_000x.nii file, wherein the spmT_000x.nii file shows the task activation area of the individual.
The group level activation map is built in a specific 2st-level function module in the SPM12, activated for the group level calculation task, a group of tested common activation areas are found, and according to the research purpose, a subdivision function of "single sample t-test" is selected in the Design function module, i.e. the activation value is compared with zero. Also, the method comprises three steps, (1) generating a design matrix, including: design (i.e., single sample t-test), scans (input individual level activation analysis generated con_xxx.nii file) are set. (2), estimation (Estimate). And estimating by adopting the SPM.mat file generated in the last step. (3), statistical test (Result). The SPM.mat file generated in the last step is imported, t-relatives are selected, and after done is clicked, the spmT_000x.nii file is generated, and the spmT_000x.nii file shows a group horizontal task activation area. The group level activation graph is imported into a DPABI V7.0 (http:// rfmri. Org/DPABI) software package, and strict multiple comparison correction (false discovery rate, FDR correction, p < 0.05) is performed, and the corrected result is saved as a binary image to be used as a Mask. For individual patient level activation analysis, the location of the activation peak point is limited (i.e., only the coordinates of the activation point located within the Mask, which is the stimulation target of the healthy side hemisphere, are selected).
Because the patient is analyzed in the individual space, the individuation and the accurate positioning are emphasized, different patients have different individuation detail characteristics, and the analysis of the patient needs to be more accurate, the registration of the structural image and the functional image is needed. However, the analysis purpose of healthy people is to find out common characteristics of people, and fine characteristics brought by structural images are unfavorable for finding out commonalities of people, so that the structural images are not needed when the first fMRI images of healthy people are registered, and only functional images are analyzed.
Therefore, the process of transforming and registering the second task state functional image and the second rest state functional image to the T1 structural image is as follows:
s1, correcting interlayer acquisition time difference of a second task state functional image and a second rest state functional image;
s2, rearranging rigid bodies among layers to correct head movements;
s3, aligning the second task state functional image and the second rest state functional image to the T1 structural image;
s4, dividing the T1 structural image, and converting the Mask from the MNI standard space back to the patient individual space by an inverse matrix generated in the dividing process so as to limit the position of a task activation peak point;
the MNI template is a processing template commonly used for medical images, the T1 structural image is segmented by adopting an MNI standard template, and the segmented images are in an MNI standard space. The Mask in this step is obtained during the set of horizontal activation map construction described above. The main purpose of obtaining a group level activation map on multiple fMRI images of healthy people is to obtain a Mask, and then the Mask is used for limiting the position of the activation peak point of the fine pinch task of the healthy side hands of the patient so as to accurately find the stimulation target point of the healthy side hemispheres of the patient.
S5, performing space smoothing on the second task state functional image and the second rest state functional image by using a full width half maximum 6 mm Gaussian smoothing kernel.
As shown in fig. 2, 3 and 4 before registration of the second fMRI image, as shown in fig. 5, 6 and 7 after registration, fig. 5, 6 and 7 are the registered second task fMRI image, the registered second rest fMRI image and the T1 structural image in sequence.
After registration of the second fMRI image, individual patient level activation analysis was performed using SPM12 software.
The individual level activation analysis of the patient is performed in the specific 1st-level function module in SPM12, with task activation calculated for the individual, finding the activation region for each individual. The method mainly comprises the following three steps: (1) generating a design matrix comprising: set Units for design, interscan interval, microtime resolution, microtime set, multiple regressors, high-pass filter. (2), estimation (Estimate). And estimating by adopting the SPM.mat file generated in the last step. (3) statistical test (Result-coherent). And importing the SPM.mat file generated in the previous step, selecting t-relatives, clicking done, and generating the spmT_000x.nii file. The document shows the individual task activation areas (activation peak points within the Mask, i.e. stimulation targets of the healthy side hemisphere).
After the rTMS stimulation target point of the healthy side of the patient is determined, the rTMS stimulation target point of the healthy side of the patient is taken as a seed point, a time sequence signal of the seed point is extracted, the pearson correlation is calculated for each voxel in the Mask of the autonomous movement region by fine pair pinching of the opposite healthy human hands, the pearson correlation value of each voxel is obtained, and the voxel with the largest pearson correlation value is taken as the rTMS stimulation target point of the affected side.
Since the brain is divided into left and right sides, the opposite side of the left side is the right side, and the opposite side of the right side is the left side. Assuming the healthy side of the patient is the left side and the affected side is the right side, where the rTMS stimulation target of the healthy side of the patient is on the left side, the rTMS stimulation target on the right side of the patient needs to be determined, "computing the" opposite side "in pearson's correlation" to each voxel in the Mask of the autonomous locomotion region with both hands of the opposite side "refers to the opposite side on the left side, i.e., the right side, but simulating the right side of the patient on the right side of the healthy person. Taking an rTMS stimulation target point on the left side of a patient as a seed point, taking a hand fine pinching autonomous movement region on the right side of a healthy person as a Mask of the hand fine pinching autonomous movement region on the right side of the patient, calculating a pearson correlation for each voxel in the Mask, obtaining a pearson correlation value of each voxel, and taking a voxel with the largest pearson correlation value as an rTMS stimulation target point on the affected side of the patient to realize the positioning of the rTMS stimulation target point on the affected side of the patient.
The fMRI scanning apparatus 5 is an existing apparatus comprising a couch and a scanning imaging apparatus, in operation, a subject lies on the couch and then enters the scanning imaging apparatus with the couch. Since the invention needs to carry out the fine hand-to-hand pinching task during fMRI scanning, the subject has to hold the pinching force measurer 4, and since fMRI scanning time is long, the pinching force measurer 4 may slip off the hand. In addition, when the first fMRI image of a healthy person is acquired, the left hand and the right hand apply pinching force to the pinching force measuring device 4 respectively, in order to ensure that one hand does not exert force when the other hand exerts force, preferably only the pinching force measuring device 4 is arranged in the exerting force, and the pinching force measuring device 4 is not arranged in the exerting force, therefore, the pinching force measuring device 4 needs to be transferred from the left hand to the right hand in the experimental process, or the pinching force measuring device 4 is transferred from the right hand to the left hand, the action amplitude may be excessively large in the transfer process, and the brain position deviation is large, so that the image dislocation is more.
In order to solve the above problems, as shown in fig. 8 and 9, the fMRI scanning apparatus 5 of the present invention includes an apparatus body 51 and an examination couch 52, wherein a vertical rotation shaft 53 is provided at one side of the middle part of the examination couch 52, and a rotation driving mechanism 54 is connected to the lower end of the rotation shaft 53, and the rotation driving mechanism 54 may be a stepping motor, and can drive the rotation shaft 53 to rotate by a set angle. The upper end of the rotating shaft 53 is provided with a horizontal cross beam 55, the cross beam 55 is provided with a sliding block 56 which is in sliding fit with the cross beam 55, the pinching force dynamometer 4 is suspended on the sliding block 56 through a flexible suspension wire 57, and the sliding block 56 is connected with a linear driving mechanism 58 which drives the sliding block 56 to slide. The lower surface of the slider 56 is provided with a hand position detecting element 59.
When the fMRI scanning equipment 5 is used, a subject lies on the examination bed 52, then the rotating driving mechanism 54 is utilized to drive the rotating shaft 53 to rotate, the rotating shaft 53 drives the cross beam 55 to rotate to the upper side of a human body, the cross beam 55 is perpendicular to the length direction of the examination bed 52, the position of the subject on the examination bed 52 is adjusted, and the hand of the subject is ensured to be positioned below the cross beam 55. Then the examination bed 52 drives the subject to enter the equipment body 51, when the hand fine pinching task starts, the linear driving mechanism 58 drives the sliding block 56 to move along the cross beam 55, the sliding block 56 drives the pinching force measuring device 4 to synchronously move, the hand position detecting element 59 detects the hand position, when the sliding block 56 moves to the position right above the hand, the linear driving mechanism 58 stops running, the sliding block 56 keeps still, at the moment, the pinching force measuring device 4 moves to the position close to the hand, the subject can feel the pinching force measuring device 4 and pinch the pinching force measuring device 4 by adopting the thumb and the index finger, and the hand fine pinching is performed according to the prompt. After the fine pinching task of one hand is completed, the linear driving mechanism 58 continues to drive the slider 56 to move, the hand position detecting element 59 detects the position of the other hand, when the slider 56 moves to the position right above the other hand, the linear driving mechanism 58 stops operating, the slider 56 remains stationary, and the other hand can easily find the position of the pinching force dynamometer 4 and pinch the pinching force dynamometer 4. After the scanning is completed, the inspection bed 52 moves out of the equipment body 51, the rotation driving mechanism 54 drives the rotating shaft 53 to rotate, and the cross beam 55 returns to the initial position.
The invention adopts the flexible suspension wire 57 to suspend the pinching force dynamometer 4, the suspension wire 57 has proper length, and the pinching force dynamometer 4 can be contacted with a human body in the process of moving the sliding block 56 from left hand to right hand, for example, the human body can sense the position of the pinching force dynamometer 4, so that the pinching force dynamometer 4 can be pinched quickly. During the scanning, if the pinching force sensor 4 accidentally falls off the hand, the subject can quickly re-pinch the pinching force sensor 4. In the process of transferring the pinching force dynamometer 4 from one hand to the other hand, the subject does not need a large-amplitude action, so that the position change amplitude of the brain is reduced, and the subsequent image processing difficulty is reduced.
The suspension wire 57 may be a twine, a rubber rope, or the like. The hand position detecting element 59 may be a camera, etc., and in addition, the hand position detecting element 59 may be a signal receiving element, where a signal emitting element, such as a light source, is disposed on the hand of the subject, and the signal receiving element uses a light receiver, and when the signal receiving element receives the signal emitted by the signal emitting element, the linear driving mechanism 58 stops operating.
The linear drive mechanism 58 may employ a motor driven lead screw nut pair mechanism.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
- An rtms target location system comprising:the healthy person fine double-hand pinching task module (1) is used for acquiring a first fMRI image when the healthy person performs a fine double-hand pinching task;the patient's healthy side hand fine pinching task module (2) is used for acquiring a second fMRI image when the patient's healthy side hand fine pinching task is performed;a central processing module (3) for determining a fine double-hand pinching autonomous motion region of a healthy person on the first fMRI image as a Mask; determining a patient healthy side activation point on the second fMRI image, the patient healthy side activation point serving as an rTMS stimulation target of the patient healthy side; taking an rTMS stimulation target point on a healthy side of a patient as a seed point, extracting a time sequence signal of the seed point, and calculating the Pelson correlation of each voxel in a Mask for pinching an autonomous movement region to the hands of a healthy person on the opposite side, so as to obtain a Pelson correlation value of each voxel, and taking the voxel with the largest Pelson correlation value as the rTMS stimulation target point on the patient side.
- 2. The rTMS target localization system of claim 1, wherein the first fMRI image acquired by the healthy person's hands fine pinch task module (1) comprises a first task state functional image in each time period, and the central processing module (3) normalizes the first task state functional image to MNI space and then determines the healthy person's hands fine pinch autonomous movement region;the second fMRI images acquired by the patient healthy side hand fine pinching task module (2) comprise a T1 structural image, a second task state functional image and a second rest state functional image which are sequentially acquired in each time period, and the central processing module (3) registers the T1 structural image, the second task state functional image and the second rest state functional image in the same time period and then determines rTMS stimulation targets of the healthy side and the affected side.
- 3. The rTMS target localization system of claim 2, wherein the process of registering the T1 structural image, the second mission state functional image, and the second rest state functional image for the same time period by the central processing module (3) is: and fixing the T1 structural image, and respectively converting and registering the second task state functional image and the second rest state functional image to the T1 structural image.
- 4. The rTMS target localization system of claim 3, wherein the second task state functional image and the second rest state functional image are registered to the T1 structural image by a transformation comprising:s1, correcting interlayer acquisition time difference of a second task state functional image and a second rest state functional image;s2, rearranging rigid bodies among layers to correct head movements;s3, aligning the second task state functional image and the second rest state functional image to the T1 structural image;s4, dividing the T1 structural image, and converting the Mask from the MNI standard space back to the patient individual space by an inverse matrix generated in the dividing process so as to limit the position of a task activation peak point;s5, performing space smoothing on the second task state functional image and the second rest state functional image by using a full width half maximum 6 mm Gaussian smoothing kernel.
- 5. rTMS target localization system according to claim 2, characterized in that the process of normalizing the first task state function image to MNI space by the central processing module (3) is:s1, correcting interlayer acquisition time difference of a first task state functional image;s2, rearranging rigid bodies among layers to correct head movements;s3, standardizing the first task state functional image to an MNI space;s4, performing space smoothing on the first task state functional image by using a full width half maximum 6 mm Gaussian smoothing kernel.
- 6. rTMS target localization system as claimed in claim 2, 3 or 4, characterized in that the central processing module (3) is provided with SPM12 software and that after registration of the second fMRI images the individual patient level activation analysis is performed using the SPM12 software.
- 7. The rTMS target localization system of claim 2 or 5, wherein the healthy person's both-hand fine pinch task module (1) is configured to obtain a first fMRI image when n healthy persons perform a hand fine pinch task, where n is greater than or equal to 90; after the central processing module (3) normalizes the first fMRI image to an MNI space, a hand fine pinching task group activation statistical graph of n healthy people is constructed, FDR correction is carried out on the hand fine pinching task group activation statistical graph, and the corrected P value is smaller than 0.05.
- 8. rTMS target localization system according to claim 7, characterized in that the central processing module (3) is equipped with SPM12 software, and that after normalization of the first fMRI image to MNI space, SPM12 software is used for individual level activation analysis of healthy persons and for further construction of group activation statistics.
- 9. The rTMS target localization system of claim 1, wherein the healthy person's both hand fine pinch task module (1) and the patient's healthy side hand fine pinch task module (2) each comprise a pinch force gauge (4) and an fMRI scanning device (5), the pinch force gauge (4) being for performing a hand fine pinch task, the fMRI scanning device (5) being for acquiring fMRI images.
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