Diabetes cognitive impairment effect analysis system and method based on brain function image

Abstract

The application discloses a diabetes cognitive impairment effect analysis system and method based on brain function images, and belongs to the medical system field.The application performs cognitive abnormality change analysis based on acquired brain function image change conditions and corresponding period cognitive impairment score conditions, performs diabetes abnormal development analysis based on disease data of diabetes patients, performs cognitive impairment development prediction based on diabetes abnormal development analysis results and cognitive abnormality change analysis results, performs cognitive impairment early warning in a treatment process based on cognitive impairment development prediction results, compares brain function image change trends before and after treatment, combines cognitive impairment score changes, evaluates the effect of a treatment scheme on cognitive function protection, further evaluates the effect of the treatment scheme on diabetes disease control, comprehensively analyzes brain function images, cognitive scores and diabetes disease data, evaluates the overall matching degree of the treatment scheme, and effectively improves the accuracy of matching analysis.

Description

Technical Field

[0001] The present application belongs to the field of medical systems, and more specifically, relates to a system and method for analyzing the effects of diabetic cognitive impairment based on brain functional imaging. Background Art

[0002] With the increasing prevalence of diabetes, research on diabetic complications has become a key focus in the medical field. Diabetes not only triggers a range of systemic complications but is also closely associated with cognitive impairment. Studies have shown that patients with diabetes are at significantly increased risk of cognitive impairment and dementia. Cognitive impairment caused by diabetes (diabetic cognitive impairment, DCD) has become a significant issue affecting patients' quality of life and long-term health.

[0003] Existing technologies primarily rely on biochemical markers such as blood glucose and glycated hemoglobin (HbA1c) for the diagnosis and assessment of diabetic cognitive function, while the assessment of cognitive function in diabetic patients is still in its infancy. Traditional methods for assessing cognitive impairment rely on observation of clinical symptoms and simple psychological assessments, lacking dynamic monitoring and accurate assessment of cognitive function. Furthermore, current treatment plans prioritize diabetes control but lack effective intervention and monitoring methods for concurrent cognitive impairment, limiting the personalized and precise nature of treatment outcomes.

[0004] To address the above issues, a system and method for analyzing the effects of diabetic cognitive impairment based on brain functional imaging was proposed. This system achieves early identification, dynamic monitoring, and prediction of cognitive impairment in diabetic patients by comprehensively analyzing changes in brain functional imaging, cognitive impairment scores, and diabetes condition data, providing a scientific basis for the optimization and personalization of treatment plans. Summary of the Invention

[0005] In order to address the deficiencies in the prior art mentioned in the background technology, the present application proposes a system and method for analyzing the effects of cognitive impairment on diabetes based on brain function imaging. The present application analyzes cognitive abnormality changes based on the changes in brain function imaging and the cognitive impairment scores of the corresponding period, analyzes the abnormal development of diabetes based on the condition data of diabetic patients, predicts the development of cognitive impairment based on the results of the analysis of abnormal development of diabetes and the analysis of abnormal cognitive changes, and provides early warning of cognitive impairment during treatment based on the results of the prediction of cognitive impairment development. The changing trends of brain function imaging before and after treatment are compared, and combined with the changes in cognitive impairment scores, the effect of the treatment plan on protecting cognitive function is evaluated, and then the effect of the treatment plan on controlling the diabetic condition is evaluated. The brain function imaging, cognitive scores and diabetic condition data are comprehensively analyzed to evaluate the overall matching degree of the treatment plan, thereby effectively improving the accuracy of the matching analysis.

[0006] To achieve the above objectives, the present application provides the following technical solutions: In the first aspect, the present application provides a method for analyzing the effects of diabetic cognitive impairment based on brain function imaging, which comprises the following specific steps:

[0007] Step 1: Obtain the changes in brain function imaging during treatment, the cognitive impairment scores of the corresponding cycles, and the condition data of the diabetic patients;

[0008] Step 2: Analyze cognitive abnormalities based on the changes in brain function imaging and the cognitive impairment scores of the corresponding period;

[0009] Step 3: Analyze the abnormal development of diabetes based on the condition data of the diabetic patients;

[0010] Step 4: predicting the development of cognitive impairment based on the analysis results of abnormal development of diabetes and abnormal changes in cognition;

[0011] Step 5: Provide early warning of cognitive damage during treatment based on the predicted results of cognitive damage development.

[0012] Preferably, based on the above scheme, the specific contents of obtaining the changes in brain function imaging during treatment, the cognitive impairment score of the corresponding period, and the condition data of the diabetic patient are:

[0013] Step 101: During the treatment process, a corresponding brain function imaging terminal is used to collect brain tissue imaging data of a corresponding period. During the treatment process, it is necessary to regularly collect brain images to analyze the impact of diabetes on various functional areas of the patient's brain.

[0014] Step 102: Obtain cognitive function score data for each brain functional area at a corresponding time period during the treatment process. The cognitive function score data for each brain functional area is obtained to differentiate damage to each brain functional area.

[0015] Step 103: The blood glucose concentration change curve of the diabetic patient is obtained. The blood glucose concentration here can be collected at a corresponding blood glucose concentration collection time, and the collected data and the curve are stored in a corresponding storage component.

[0016] Preferably, based on the above scheme, the analysis of cognitive abnormality changes based on the changes in brain function images and the cognitive impairment scores of the corresponding period includes the following specific steps:

[0017] Step 201: Obtain changes in brain function images of each functional area during treatment, and perform abnormal analysis of changes in the corresponding functional area based on the changes in brain function images of each functional area. The abnormal analysis formula for the corresponding functional area is: , where mz is the abnormal change analysis result of the zth functional area, n is the number of functional areas, and xm is the set distance standard value. is the distance from the i-th functional area to the corresponding functional area, is the damage value of the i-th functional area, where the distance from the i-th functional area to the corresponding functional area is the average distance between the two functional areas, and the distance between the corresponding functional area is 0. Since the abnormal changes of the functional areas need to be analyzed, the influence of the adjacent functional areas on the corresponding functional areas should also be analyzed. The closer to the corresponding functional area, the greater the influence on the corresponding functional area. The damage value of the functional area is analyzed by the change of the image;

[0018] Step 202: Obtain the change in cognitive function score of the corresponding functional area, and perform cognitive function abnormality analysis based on the change in cognitive function score within the cycle. The cognitive function abnormality analysis formula for the i-th functional area is: , where exp() is the power of the natural constant e, kiz is the cognitive function score of the i-th functional area at the start of the cycle, kip is the cognitive function score of the i-th functional area at the end of the cycle, and kiq is the average cognitive function score of the i-th functional area of ​​the current person. This formula is used to analyze the changes in the cognitive function scores of the patient's functional areas during the treatment process. In order to avoid negative results that affect subsequent calculations, the power of the natural constant e is used to make the calculation result positive;

[0019] Step 203: Perform cognitive abnormality change analysis based on the obtained abnormal change results of the corresponding functional areas and the abnormal analysis results of the cognitive function of the functional areas. The cognitive abnormality change analysis formula is: ,in, is the influence coefficient of the i-th cognitive function area, is the abnormal change analysis result of the i-th functional area. In this formula, the influence of abnormal changes in unit functional areas on abnormal cognitive functions is analyzed through the corresponding abnormal change results of functional areas and the abnormal analysis results of cognitive functions in functional areas. The influence coefficient of the i-th cognitive function area here has different weights because different cognitive functions have different degrees of influence on the human body.

[0020] Preferably, based on the above scheme, the analysis of abnormal development of diabetes includes the following specific steps:

[0021] Step 301: Obtain a blood glucose concentration change curve of a diabetic patient during a monitoring period;

[0022] Step 302: Based on the blood glucose concentration change curve of the diabetic patient during the monitoring period, the abnormal development of diabetes in the diabetic patient is analyzed. The abnormal development analysis formula of diabetes is: , where Qm is the median of the safe range of blood glucose concentration, is the blood glucose concentration collected for the kth time in the cycle, dt is the time integral, T is the number of blood glucose concentration collections in the cycle, b is the average abnormality proportion weight, c is the change abnormality proportion weight, Qz is the average blood glucose concentration in the second half of the monitoring cycle, Qc is the average blood glucose concentration in the first half of the monitoring cycle, and the average blood glucose concentration in the second half of the monitoring cycle minus the average blood glucose concentration in the first half of the monitoring cycle is the change in blood glucose concentration. This change represents the change in the degree of blood glucose abnormality from the beginning to the end of the previous operating cycle, and can reflect the changing trend of blood glucose. Specifically, the previous formula only represents the average abnormality degree in one cycle, and cannot reflect the changing trend within the cycle. On the basis of comprehensively considering the average degree and change of diabetes abnormality, a more comprehensive assessment of the abnormal state of diabetes can be made.

[0023] Preferably, based on the above scheme, the prediction of cognitive impairment progression based on the analysis results of abnormal diabetes progression and abnormal cognitive changes includes the following specific contents:

[0024] The abnormal development analysis results of diabetes and the abnormal cognitive change analysis results obtained by evaluation are obtained, and the prediction result of cognitive damage development is obtained by weighted summing the abnormal development analysis results of diabetes and the abnormal cognitive change analysis results.

[0025] Preferably, based on the above scheme, the cognitive damage warning during the treatment process based on the cognitive damage development prediction result includes the following specific steps: obtaining the cognitive damage development prediction result, comparing the obtained cognitive damage development prediction result with the set cognitive damage development prediction threshold; if the cognitive damage development prediction result is greater than or equal to the set cognitive damage development prediction threshold, it means that the treatment process will cause cognitive damage to the patient, the treatment process does not match the patient, a mismatch warning is issued, and the treatment method needs to be changed; if the cognitive damage development prediction result is less than the set cognitive damage development prediction threshold, it means that the treatment process matches the patient.

[0026] In the second aspect, the present application provides a system for analyzing the effects of cognitive impairment on diabetes based on brain function imaging, which is implemented based on the above-mentioned method for analyzing the effects of cognitive impairment on diabetes based on brain function imaging, and specifically includes a data acquisition module, a cognitive abnormality change analysis module, a diabetes abnormal development analysis module, a cognitive impairment development prediction module and a cognitive impairment early warning module; wherein, the data acquisition module acquires the changes in brain function imaging during treatment, the cognitive impairment scores of the corresponding period and the condition data of the diabetic patient; the cognitive abnormality change analysis module performs cognitive abnormality change analysis based on the acquired brain function imaging changes and the cognitive impairment scores of the corresponding period; the diabetes abnormal development analysis module performs diabetes abnormal development analysis based on the condition data of the diabetic patient; the cognitive impairment development prediction module performs cognitive impairment development prediction based on the results of the diabetes abnormal development analysis and the results of the cognitive abnormal change analysis; the cognitive impairment early warning module performs cognitive impairment early warning during treatment based on the results of the cognitive impairment development prediction.

[0027] In a third aspect, the present application provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0028] The processor executes the above-mentioned method for analyzing the effects of diabetic cognitive impairment based on brain function imaging by calling the computer program stored in the memory.

[0029] In a fourth aspect, the present application provides a computer-readable storage medium storing instructions, which, when executed on a computer, enables the computer to execute the above-mentioned method for analyzing the effects of diabetic cognitive impairment based on brain functional imaging.

[0030] At the same time, compared with the existing technology, the technical effects and advantages of this application are:

[0031] The advantages of the present application are as follows: the present application analyzes changes in cognitive abnormalities based on changes in brain function images and cognitive impairment scores of corresponding periods, analyzes abnormal development of diabetes based on the condition data of diabetic patients, predicts the development of cognitive impairment based on the results of the analysis of abnormal development of diabetes and the analysis of abnormal changes in cognitive abilities, and provides early warning of cognitive impairment during treatment based on the results of the prediction of cognitive impairment development. The application compares the changing trends of brain function images before and after treatment, and evaluates the effect of the treatment plan on protecting cognitive function in combination with the changes in cognitive impairment scores, and then evaluates the effect of the treatment plan on controlling the diabetic condition. The application comprehensively analyzes brain function images, cognitive scores and diabetic condition data, evaluates the overall matching degree of the treatment plan, and effectively improves the accuracy of the matching analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0033] Figure 1 This is a schematic diagram of the overall process of the analysis method of diabetic cognitive impairment based on brain functional imaging;

[0034] Figure 2 This is a schematic diagram of the specific process of step 2 of the method for analyzing the effects of diabetic cognitive impairment based on brain functional imaging;

[0035] Figure 3 This is a schematic diagram of the specific process of step 3 of the method for analyzing the effects of diabetic cognitive impairment based on brain functional imaging;

[0036] Figure 4 This is a schematic diagram of the module composition of the diabetic cognitive impairment analysis system based on brain functional imaging;

[0037] Figure 5 This is a schematic diagram of the electronic equipment used in this application. DETAILED DESCRIPTION

[0038] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are only some embodiments of the present application, rather than all embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is in no way intended to limit the present application, its application, or use.

[0039] In addition, the accompanying drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor and / or microcontroller approaches.

[0040] It should be understood that although the terms "first," "second," and the like may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used solely to distinguish one element from another. For example, a first element may be referred to as a second element, and a similar second element may be referred to as a first element, without departing from the scope of the exemplary embodiments. The term "and / or" as used herein includes any and all combinations of one or more of the listed associated items.

[0041] To solve the technical problems raised in the background technology: In the existing technology, the diagnosis and evaluation of diabetes mainly rely on biochemical indicators such as blood sugar and glycosylated hemoglobin (HbA1c), while the evaluation of cognitive function in diabetic patients is still in its early stages. Traditional cognitive impairment assessment methods rely on the observation of clinical symptoms and simple psychological assessments, and lack dynamic monitoring and accurate evaluation of cognitive function. In addition, current treatment plans focus on the control of diabetic conditions, but lack effective intervention and monitoring methods for concurrent cognitive impairment, resulting in limited personalization and accuracy of treatment effects. This application provides a preferred embodiment: Figure 1-Figure 3 As shown, the method for analyzing the effects of diabetic cognitive impairment based on brain functional imaging includes the following specific steps:

[0042] Step 1: Obtain the changes in brain function imaging during treatment, the cognitive impairment scores of the corresponding cycles, and the condition data of the diabetic patients;

[0043] In this embodiment, the specific contents of obtaining the changes in brain function imaging during treatment, the cognitive impairment score of the corresponding period, and the condition data of the diabetic patient are as follows:

[0044] Step 101: During the treatment process, brain tissue image data of corresponding periods are collected through a corresponding brain function image collection terminal. During the treatment process, it is necessary to regularly collect brain images to analyze the impact of diabetes on various functional areas of the patient's brain. Exemplarily, the corresponding brain function image collection terminal includes MRI and CT brain image collection terminals, from which image changes of various functional areas of the brain are obtained;

[0045] Step 102: Acquire cognitive function score data for each brain functional area at a corresponding time period during the treatment process. Exemplarily, the cognitive function score may be the MMSE (Mini-Mental State Examination) scoring standard. The MMSE is a widely used standardized test tool for assessing an individual's cognitive function status. It primarily covers several key areas of cognitive function, including orientation, memory, attention, calculation ability, language function, and visual-spatial ability. The MMSE has a full score of 30 points. A lower score indicates more severe cognitive dysfunction. Acquiring cognitive function score data for each brain functional area here is for distinguishing damage to each brain functional area.

[0046] Step 103: The blood glucose concentration change curve of the diabetic patient is obtained. The blood glucose concentration here can be collected at a corresponding blood glucose concentration collection time. For example, the collection is performed at a specified time every day within a month to make the data comparable and avoid errors. The collected data and the curve are stored in a corresponding storage component.

[0047] Step 2: Analyze cognitive abnormalities based on the changes in brain function imaging and the cognitive impairment scores of the corresponding period;

[0048] In this embodiment, analyzing cognitive abnormality changes based on changes in brain function imaging and cognitive impairment scores during corresponding periods includes the following specific steps:

[0049] Step 201: Obtain changes in brain function images of each functional area during treatment, and perform abnormal analysis of changes in the corresponding functional area based on the changes in brain function images of each functional area. The abnormal analysis formula for the corresponding functional area is: , where mz is the abnormal change analysis result of the zth functional area, n is the number of functional areas, and xm is the set distance standard value. is the distance from the i-th functional area to the corresponding functional area, is the damage value of the i-th functional area, wherein the distance from the i-th functional area to the corresponding functional area is the average distance between the points of the two functional areas, and the distance between the corresponding functional area and the corresponding functional area is 0. Since it is necessary to analyze the abnormal changes of the functional areas, it is also necessary to analyze the influence of the adjacent functional areas on the corresponding functional areas. The closer to the corresponding functional area, the greater the influence on the corresponding functional area. The damage value of the functional area is analyzed by the change of the image. For example, the damage value calculation formula of the i-th functional area is: , where mi is the number of pixels in the i-th functional area, is the pixel value of the jth pixel in the i-th functional area, is the pixel value of the jth pixel in the i-th functional area at the previous monitoring moment, is the pixel value of the jth pixel point in the i-th functional area when it is not diseased. In this way, the damage of the functional area is analyzed by the change of pixels in this formula;

[0050] Step 202: Obtain the change in cognitive function score of the corresponding functional area, and perform cognitive function abnormality analysis based on the change in cognitive function score within the cycle. The cognitive function abnormality analysis formula for the i-th functional area is: , where exp() is the power of the natural constant e, kiz is the cognitive function score of the i-th functional area at the start of the cycle, kip is the cognitive function score of the i-th functional area at the end of the cycle, and kiq is the average cognitive function score of the i-th functional area of ​​the current person. This formula is used to analyze the changes in the cognitive function scores of the patient's functional areas during the treatment process. In order to avoid negative results that affect subsequent calculations, the power of the natural constant e is used to make the calculation result positive;

[0051] Step 203: Perform cognitive abnormality change analysis based on the obtained abnormal change results of the corresponding functional areas and the abnormal analysis results of the cognitive function of the functional areas. The cognitive abnormality change analysis formula is: ,in, is the influence coefficient of the i-th cognitive function area, is the abnormal change analysis result of the i-th functional area. In this formula, the influence of abnormal changes in the unit functional area on cognitive function abnormality is analyzed by the corresponding abnormal change results of the functional area and the abnormal analysis results of the cognitive function of the functional area. The influence coefficient of the i-th cognitive function area here has different weights because different cognitive functions have different effects on the human body, such as attention and calculation ability. It is obtained by experts in this field scoring according to the needs of human cognitive function.

[0052] Step 3: Analyze the abnormal development of diabetes based on the condition data of the diabetic patients;

[0053] In this embodiment, the analysis of abnormal development of diabetes includes the following specific steps:

[0054] Step 301: Obtain a blood glucose concentration change curve of a diabetic patient during a monitoring period;

[0055] Step 302: Based on the blood glucose concentration change curve of the diabetic patient during the monitoring period, the abnormal development of diabetes in the diabetic patient is analyzed. The abnormal development analysis formula of diabetes is: , where Qm is the median of the safe range of blood glucose concentration, is the blood glucose concentration collected for the kth time in the cycle, dt is the time integral, T is the number of blood glucose concentration collections in the cycle, b is the average abnormality proportion weight, c is the change abnormality proportion weight, Qz is the average blood glucose concentration in the second half of the monitoring cycle, Qc is the average blood glucose concentration in the first half of the monitoring cycle, and the average blood glucose concentration in the second half of the monitoring cycle minus the average blood glucose concentration in the first half of the monitoring cycle is the blood glucose concentration change. This change represents the change in the degree of blood glucose abnormality from the beginning to the end of the previous operating cycle, and can reflect the trend of blood glucose changes. Specifically, the previous formula only represents the average abnormality in one cycle and cannot reflect the change trend within the cycle. On the basis of comprehensively considering the average degree and change of diabetes abnormality, a more comprehensive assessment of the abnormal state of diabetes can be achieved;

[0056] Step 4: predicting the development of cognitive impairment based on the analysis results of abnormal development of diabetes and abnormal changes in cognition;

[0057] In this embodiment, the prediction of cognitive impairment progression based on the analysis results of abnormal diabetes progression and abnormal cognitive changes includes the following specific contents:

[0058] Obtaining the assessed results of the abnormal development of diabetes and the abnormal cognitive change analysis, and obtaining a prediction result of cognitive impairment development by weighted summing the results of the abnormal development of diabetes and the abnormal cognitive change analysis;

[0059] Step 5: Early warning of cognitive impairment during treatment based on the predicted results of cognitive impairment development;

[0060] In this embodiment, the cognitive damage development prediction result based on the cognitive damage development prediction result during the treatment process includes the following specific steps: obtaining the cognitive damage development prediction result, comparing the obtained cognitive damage development prediction result with the set cognitive damage development prediction threshold, if the cognitive damage development prediction result is greater than or equal to the set cognitive damage development prediction threshold, it means that the treatment process will cause cognitive damage to the patient, the treatment process does not match the patient, and a mismatch warning is issued, and the treatment method needs to be changed. If the cognitive damage development prediction result is less than the set cognitive damage development prediction threshold, it means that the treatment process matches the patient.

[0061] Furthermore, the setting parameters in this embodiment (such as thresholds and weights for setting each parameter) are obtained by experiments using historical data. Specific experimental methods include, for example, obtaining changes in brain function imaging during historical treatment, cognitive impairment scores for corresponding periods, and condition data of diabetic patients, obtaining a judgment result on whether the cognitive impairment of historical patients after treatment is within a safe range, substituting the historical data into the steps of this embodiment to obtain a calculation result on whether the treatment process matches the patient, importing the calculation results and judgment results into the fitting software, and outputting the values ​​of the setting parameters (such as thresholds and weights for setting each parameter) that meet the maximum accuracy of the judgment result.

[0062] Furthermore, the benefits of this embodiment are explained here. This embodiment performs cognitive abnormality change analysis based on the changes in brain function images and cognitive damage scores of corresponding periods, performs diabetes abnormality development analysis based on the condition data of diabetic patients, predicts cognitive damage development based on the results of diabetes abnormal development analysis and cognitive abnormality change analysis, and performs cognitive damage early warning during treatment based on the results of cognitive damage development prediction. The changing trends of brain function images before and after treatment are compared, and combined with the changes in cognitive damage scores, the effect of the treatment plan on protecting cognitive function is evaluated, and then the effect of the treatment plan on controlling the diabetic condition is evaluated. The brain function images, cognitive scores and diabetic condition data are comprehensively analyzed to evaluate the overall matching degree of the treatment plan, thereby effectively improving the accuracy of the matching analysis.

[0063] Secondly, if Figure 4 As shown, this embodiment also provides a diabetes cognitive impairment effect analysis system based on brain function imaging, which specifically includes a data acquisition module, a cognitive abnormality change analysis module, a diabetes abnormal development analysis module, a cognitive impairment development prediction module and a cognitive impairment early warning module; wherein, the data acquisition module acquires the changes in brain function imaging during treatment, the cognitive impairment score of the corresponding period and the condition data of the diabetic patient; the cognitive abnormality change analysis module performs cognitive abnormality change analysis based on the acquired brain function imaging changes and the cognitive impairment score of the corresponding period; the diabetes abnormal development analysis module performs diabetes abnormal development analysis based on the condition data of the diabetic patient; the cognitive impairment development prediction module performs cognitive impairment development prediction based on the diabetes abnormal development analysis results and the cognitive abnormality change analysis results; the cognitive impairment early warning module performs cognitive impairment early warning during treatment based on the cognitive impairment development prediction results, wherein the connection relationship between the data acquisition module, the cognitive abnormality change analysis module, the diabetes abnormal development analysis module, the cognitive impairment development prediction module and the cognitive impairment early warning module is as shown in FIG. Figure 4 shown.

[0064] Then, if Figure 5As shown, this embodiment further provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0065] The processor executes the above-mentioned method for analyzing the effects of diabetes cognitive impairment based on brain function imaging by calling the computer program stored in the memory.

[0066] The electronic device may vary significantly due to different configurations or performance, and may include one or more processors and one or more memories, wherein the memories store at least one computer program, which is loaded and executed by the processor to implement the method for analyzing the effects of diabetic cognitive impairment based on brain functional imaging provided in the above method embodiment. The electronic device may also include other components for implementing the functions of the device. For example, the electronic device may also have components such as a wired or wireless network interface and an input / output interface for data input and output. This embodiment will not be described in detail here.

[0067] Finally, this embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0068] When the computer program is executed on a computer device, the computer device is caused to execute the above-mentioned method for analyzing the effects of diabetes cognitive impairment based on brain function imaging.

[0069] For example, the computer readable storage medium can be a read-only memory, a random access memory, a read-only CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0070] Those skilled in the art will appreciate that embodiments of the present invention may provide methods, systems, or computer program products. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0071] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0072] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0073] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0074] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0075] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0076] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0077] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not preclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0078] The above are merely embodiments of the present invention and are not intended to limit the present invention. It will be apparent to those skilled in the art that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A system for analyzing the effects of diabetic cognitive impairment based on brain function imaging, characterized in that: It specifically includes a data acquisition module, a cognitive abnormality change analysis module, a diabetes abnormal development analysis module, a cognitive damage development prediction module and a cognitive damage early warning module; wherein, the data acquisition module acquires changes in brain function images during treatment, cognitive damage scores of corresponding periods and the condition data of diabetic patients; the cognitive abnormality change analysis module performs cognitive abnormality change analysis based on the acquired brain function image changes and cognitive damage scores of corresponding periods; the diabetes abnormal development analysis module performs diabetes abnormal development analysis based on the condition data of diabetic patients; the cognitive damage development prediction module performs cognitive damage development prediction based on the results of diabetes abnormal development analysis and cognitive abnormality change analysis; the cognitive damage early warning module performs cognitive damage early warning during treatment based on the results of cognitive damage development prediction; The analysis of cognitive abnormality changes based on the changes in brain function imaging and the cognitive impairment scores of the corresponding period includes the following specific steps: Step 201: Obtain changes in brain function images of each functional area during treatment, and perform abnormal analysis of changes in the corresponding functional area based on the changes in brain function images of each functional area. The abnormal analysis formula for the corresponding functional area is: , where mz is the abnormal change analysis result of the zth functional area, n is the number of functional areas, and xm is the set distance standard value. is the distance from the i-th functional area to the corresponding functional area, is the damage value of the i-th functional area, where the distance from the i-th functional area to the corresponding functional area is the average distance between the two functional areas; Step 202: Obtain the change in cognitive function score of the corresponding functional area, and perform cognitive function abnormality analysis based on the change in cognitive function score within the cycle. The cognitive function abnormality analysis formula for the i-th functional area is: , where exp() is the power of the natural constant e, kiz is the cognitive function score of the i-th functional area at the start of the cycle, kip is the cognitive function score of the i-th functional area at the end of the cycle, and kiq is the average cognitive function score of the i-th functional area of ​​the current person; Step 203: Perform cognitive abnormality change analysis based on the obtained abnormal change results of the corresponding functional areas and the abnormal analysis results of the cognitive function of the functional areas. The cognitive abnormality change analysis formula is: ,in, is the influence coefficient of the i-th cognitive function area, is the abnormal analysis result of the change of the i-th functional area; The abnormal development analysis of diabetes mellitus comprises the following specific steps: Step 301: Obtain a blood glucose concentration change curve of a diabetic patient during a monitoring period; Step 302: Based on the blood glucose concentration change curve of the diabetic patient during the monitoring period, the abnormal development of diabetes in the diabetic patient is analyzed. The abnormal development analysis formula of diabetes is: , where Qm is the median of the safe range of blood glucose concentration, is the blood glucose concentration collected for the kth time in the cycle, dt is the time integral, T is the number of blood glucose concentration collections in the cycle, b is the average abnormality proportion weight, c is the change abnormality proportion weight, Qz is the average blood glucose concentration in the second half of the monitoring cycle, and Qc is the average blood glucose concentration in the first half of the monitoring cycle; The prediction of cognitive impairment development based on the analysis results of abnormal diabetes development and abnormal cognitive changes includes the following specific contents: Obtaining the assessed results of the abnormal development of diabetes and the abnormal cognitive change analysis, and obtaining a prediction result of cognitive impairment development by weighted summing the results of the abnormal development of diabetes and the abnormal cognitive change analysis; The cognitive damage development prediction result based on the cognitive damage development prediction result during the treatment process includes the following specific steps: obtaining the cognitive damage development prediction result, comparing the obtained cognitive damage development prediction result with the set cognitive damage development prediction threshold, if the cognitive damage development prediction result is greater than or equal to the set cognitive damage development prediction threshold, it means that the treatment process will cause cognitive damage to the patient, the treatment process does not match the patient, and a mismatch warning is issued, and the treatment method needs to be changed. If the cognitive damage development prediction result is less than the set cognitive damage development prediction threshold, it means that the treatment process matches the patient.

2. The system for analyzing diabetic cognitive impairment based on brain function imaging according to claim 1, wherein: The specific contents of obtaining the changes in brain function imaging during treatment, the cognitive impairment scores of the corresponding periods, and the condition data of the diabetic patients are as follows: Step 101: During the treatment process, the corresponding brain function image acquisition terminal is used to collect brain tissue image data of the corresponding period; Step 102: Obtain cognitive function score data corresponding to each brain functional area in a corresponding time period during the treatment process; Step 103: The blood glucose concentration variation curve of the diabetic patient is obtained, and the collected data and the curve are stored in a corresponding storage component.

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