A method and system for assessing the effectiveness of postherpetic neuralgia treatment with ultrashort focused ultrasound

Abstract

The application provides a method and system for evaluating the effect of treating post-herpes zoster neuralgia by using ultrashort focused ultrasound, and the method comprises the following steps: constructing a dynamic pain atlas by using baseline data, obtaining a tenderness range thermogram, an itch-pain coupling index, a nerve conduction velocity recovery rate and a C-fiber response characteristic; obtaining a microvessel density and other index change rates based on characteristic evaluation; tracking the indexes to obtain a nerve growth factor and other ratio change curves; analyzing the curves to obtain a pain matrix reconstruction index; comprehensively determining the treatment effect to obtain an individualized treatment effect classification. The application integrates key indexes to construct a whole-chain evaluation dimension, replaces subjective evaluation with objective detection technology, and breaks through the limitations of traditional detection; pain matrix reconstruction is tracked by dynamic sampling and analysis, whole-process dynamic monitoring is realized, and finally, individualized treatment effect classification is formed through a multi-dimensional evaluation matrix and a scoring system, so that the problems of standard ambiguity and individualization deficiency in traditional methods are solved.

Description

Technical Field

[0001] This invention relates to the field of efficacy evaluation technology for treating postherpetic neuralgia, and in particular to a method and system for evaluating the efficacy of ultrashort focused ultrasound treatment for postherpetic neuralgia. Background Technology

[0002] Postherpetic neuralgia (PHN) is a chronic neuropathic pain caused by the varicella-zoster virus. The assessment of its treatment efficacy has long relied on subjective observation by clinicians and patient self-reporting. Traditional assessment methods mainly include the Visual Analogue Scale (VAS), the McGill Pain Questionnaire, and neurophysiological testing. These methods qualitatively assess pain by visually observing patient signs (such as skin erythema and the extent of tenderness) or inquiring about the nature of the pain (such as stinging or burning), lacking objective quantitative tracking of the nerve repair process. Although some studies have attempted to combine neurophysiological indicators (such as nerve conduction velocity) or single imaging techniques (such as contrast-enhanced ultrasound) to assist in assessment, the overall assessment remains at a local, static level, failing to dynamically reflect the complex interactions of peripheral nerve repair, inflammatory response regulation, and central pain matrix remodeling during treatment.

[0003] The shortcomings of existing technologies are mainly reflected in the following aspects: First, the assessment dimensions are singular, focusing only on pain intensity or nerve conduction function, ignoring key indicators such as itching-pain coupling, microvascular angiogenesis, and central nervous system plasticity; Second, data collection methods are limited, such as human eye assessment being easily influenced by physician experience, and neurophysiological testing only reflecting the function of large fiber nerves, unable to quantify the repair status of small fiber nerves such as C fibers; Third, there is a lack of dynamic tracking capabilities, as traditional methods mostly use single-point comparisons before and after treatment, failing to capture the biological characteristics of key time points such as changes in the NGF / BDNF ratio and fluctuations in IL-6 / TNF-α inflammatory factors during nerve repair; Fourth, the criteria for judging efficacy are vague, failing to establish a multi-level quantitative indicator system from the periphery to the central nervous system, and from molecular signals to network reconstruction, resulting in a lack of scientific basis for individualized treatment effect grading. Summary of the Invention

[0004] This invention aims to at least address the problem of limited evaluation dimensions in existing technologies, and innovatively proposes a method and system for evaluating the efficacy of ultrashort focused ultrasound therapy for postherpetic neuralgia.

[0005] To achieve the above-mentioned objectives of this invention, this invention provides a method for evaluating the efficacy of ultrashort focused ultrasound therapy for postherpetic neuralgia, the method comprising: S1. Utilize the patient's baseline data to establish a dynamic pain atlas and obtain a heat map of tenderness range and an itching-pain coupling index; S2. Based on the thermal map of the tenderness range and the pruritus-pain coupling index, high-frequency ultrasound combined with laser evoked potential detection is performed to obtain the nerve conduction velocity recovery rate and C-fiber response characteristics. S3. Based on the nerve conduction velocity recovery rate and C-fiber response characteristics, perform multimodal tissue repair imaging assessment to obtain the change rate of microvascular density, epidermal nerve fiber density, and spinal cord T2-weighted imaging values. S4. The change rate of microvascular density, epidermal nerve fiber density and spinal cord T2-weighted imaging value is dynamically tracked by serum markers to obtain the change curves of nerve growth factor / brain-derived neurotrophic factor ratio and interleukin-6 / tumor necrosis factor-α ratio. S5. Perform functional magnetic resonance imaging dynamic causal model analysis on the change curves of the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio to obtain the pain matrix reconstruction index. S6. Based on the output of each step from S1 to S5, a comprehensive efficacy assessment is performed to obtain an individualized treatment effect grading.

[0006] In another aspect, the present invention also provides an efficacy evaluation system for ultrashort focused ultrasound treatment of herpes zoster neuralgia, the system comprising the aforementioned efficacy evaluation method for ultrashort focused ultrasound treatment of herpes zoster neuralgia; the system further comprising: The data acquisition module is used to collect the patient's baseline data; A pain atlas construction module is used to construct a dynamic pain atlas based on the baseline data; A high-frequency ultrasound and laser evoked potential detection module is used for high-frequency ultrasound combined with laser evoked potential detection; The multimodal tissue repair image assessment module is used to perform multimodal tissue repair image assessment. The serological biomarker dynamic tracking module is used to dynamically track the changes in microvascular density, epidermal nerve fiber density, and spinal cord T2-weighted imaging values ​​using serological biomarkers. The functional magnetic resonance imaging (fMRI) analysis module is used to perform dynamic causal model analysis on the change curves of the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio using fMRI. The efficacy assessment module is used to comprehensively assess the efficacy based on the output data of the aforementioned modules, and obtain an individualized treatment effect grading.

[0007] The beneficial effects of this invention are: 1. This invention integrates key indicators such as tenderness range heatmap, pruritus-pain coupling index, C-fiber response characteristics, microvascular density, epidermal nerve fiber density, spinal cord T2 value change rate, and pain matrix reconstruction index, and constructs a full-chain assessment dimension from peripheral nerve repair (nerve conduction velocity recovery rate, C-fiber γ-band synchronization intensity) to central pain network remodeling (PMRI). 2. This invention also employs objective detection technologies such as high-frequency ultrasound, laser evoked potentials, OCT, and fMRI to replace subjective assessments based on human visual observation. At the same time, it precisely quantifies the function of small fibers such as C fibers through laser evoked potentials, breaking through the limitation that traditional neurophysiological testing can only reflect the function of large fibers. 3. This invention captures the changes in the NGF / BDNF ratio and IL-6 / TNF-α ratio at key time points before treatment, 1 week, 2 weeks, and 4 weeks by a dynamic sampling plan of serological markers, and dynamically tracks the pain matrix reconstruction process by combining fMRI DCM analysis. This achieves full-process dynamic monitoring from molecular signals to network function, and finally forms an individualized treatment effect grading through a multi-dimensional efficacy evaluation matrix and comprehensive scoring system, which solves the defects of traditional methods such as vague standards and insufficient individualization.

[0008] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0009] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart of a method for evaluating the effect of ultrashort focused ultrasound treatment for postherpetic neuralgia according to the present invention. Detailed Implementation

[0010] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0011] Example 1 like Figure 1 As shown, a method for evaluating the efficacy of ultrashort focused ultrasound treatment for postherpetic neuralgia is provided, the method comprising: S1. Utilize the patient's baseline data to establish a dynamic pain atlas and obtain a heat map of tenderness range and an itching-pain coupling index; S2. Based on the thermal map of the tenderness range and the pruritus-pain coupling index, high-frequency ultrasound combined with laser evoked potential detection is performed to obtain the nerve conduction velocity recovery rate and C-fiber response characteristics. S3. Based on the nerve conduction velocity recovery rate and C-fiber response characteristics, perform multimodal tissue repair imaging assessment to obtain the change rate of microvascular density, epidermal nerve fiber density, and spinal cord T2-weighted imaging values. S4. The change rate of microvascular density, epidermal nerve fiber density and spinal cord T2-weighted imaging value is dynamically tracked by serum markers to obtain the change curves of nerve growth factor / brain-derived neurotrophic factor ratio and interleukin-6 / tumor necrosis factor-α ratio. S5. Perform functional magnetic resonance imaging dynamic causal model analysis on the change curves of the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio to obtain the pain matrix reconstruction index. S6. Based on the output of each step from S1 to S5, a comprehensive efficacy assessment is performed to obtain an individualized treatment effect grading.

[0012] The principle of the method for evaluating the effect of ultrashort focused ultrasound treatment for postherpetic neuralgia in this embodiment is as follows: First, baseline patient data was collected, including but not limited to age, gender, medical history, and pain intensity. This data was then used to construct a dynamic pain atlas, a pain distribution map that changes over time, visually displaying the area and intensity of pain. Building upon this, a tenderness heatmap was obtained, using different colors to mark areas of varying tenderness intensity, helping to quickly locate pain hotspots. Simultaneously, an itching-pain coupling index was calculated, reflecting the correlation between itching and pain.

[0013] Next, based on the thermogram of tenderness range and the pruritus-pain coupling index, high-frequency ultrasound combined with laser evoked potential detection technology was used. High-frequency ultrasound can non-invasively observe nerve structure and blood flow, while laser evoked potentials can accurately assess the state of nerve function. By combining these two technologies, the recovery rate of nerve conduction velocity and C-fiber response characteristics were obtained, and these indicators directly reflect the progress of nerve repair and functional recovery.

[0014] Then, a multimodal imaging assessment of tissue repair was performed, utilizing advanced medical imaging techniques such as contrast-enhanced ultrasound, optical coherence tomography (OCT), and magnetic resonance imaging (MRI) to conduct in-depth analysis of the areas indicated by nerve conduction velocity recovery rate and C-fiber response characteristics. This process helped obtain changes in microvascular density, epidermal nerve fiber density, and spinal cord T2-weighted imaging values, parameters that reveal the progress and effectiveness of tissue repair from different perspectives.

[0015] After obtaining the aforementioned imaging parameters, dynamic tracking of serological biomarkers was performed. Serum samples were collected from patients periodically to detect changes in the concentrations of key molecules such as nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α), and their ratio changes were calculated. These serological biomarkers not only reflect molecular-level changes during nerve repair but are also closely related to pain perception and inflammation regulation.

[0016] Subsequently, the changes in the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio were analyzed using a functional magnetic resonance imaging dynamic causal model (DCM). DCM is a powerful tool capable of revealing the functional connectivity and dynamic interactions between different brain regions. Through this process, a pain matrix remodeling index was obtained, which reflects the remodeling of the central pain network during neural repair.

[0017] Finally, based on the output data from each step S1 to S5, a multi-dimensional efficacy evaluation matrix was constructed. This matrix integrates several key indicators, including a heatmap of tenderness range, nerve conduction velocity recovery rate, microvascular density change rate, nerve growth factor / brain-derived neurotrophic factor ratio, and pain matrix reconstruction index. By standardizing and weighting these indicators, a comprehensive efficacy score was calculated, and individualized treatment effects were categorized into four levels: excellent, good, moderate, and poor. This grading system provides an objective and quantitative basis for clinical decision-making.

[0018] As an optional embodiment of the present invention, optionally, obtaining the thermal map of the tenderness range and the pruritus-pain coupling index in step S1 includes: S101. Collect the patient's baseline data, which includes three-dimensional coordinates of the pain site, dynamic pain intensity score, qualitative description of the nature of pain, marking of itching sites, and neurophysiological test data. In step S101, it should be noted that the neurophysiological testing data includes, but is not limited to, somatosensory evoked potentials, motor evoked potentials, and electromyography data. These data provide a neurophysiological basis for constructing a dynamic pain atlas. Through comprehensive analysis of this data, the details of the pain atlas can be further refined, improving the accuracy of pain localization and the recognition rate of pain characteristics. Simultaneously, the introduction of pruritus site marking allows this invention to simultaneously focus on two closely related sensory abnormalities: pain and pruritus, providing a more comprehensive perspective for evaluating the treatment effect of postherpetic neuralgia.

[0019] S102. Based on the three-dimensional coordinates of the pain site and the dynamic score of pain intensity in the baseline data, the pain area is marked on the virtual human body model through gesture interaction, and the marking data of the itchy area is recorded simultaneously. In step S102, it should be noted that, through gesture interaction technology, doctors or operators can visually mark the patient's pain areas on a virtual three-dimensional human body model. This interaction method not only improves the accuracy of pain area marking but also allows the distribution and trends of pain to be presented in an easily understandable way. Simultaneously, the synchronously recorded data on the marking of itching areas provides valuable information for subsequent analysis of the interaction between pain and itching.

[0020] S103. The Gaussian kernel density estimation algorithm is used to spatially locate and intensity-weight the marked pain areas to generate an initial pain density distribution. In step S103, it should be noted that the Gaussian kernel density estimation algorithm is a non-parametric statistical method that generates a continuous pain density distribution map by smoothing the marked pain areas. This distribution map not only shows the main areas of pain but also reflects the differences in pain intensity between different areas through intensity weighting.

[0021] S104. Based on the initial pain density distribution and dynamic pain intensity score, a heat map of tenderness range is generated by color gradient mapping, where the red area corresponds to high-intensity pain and the blue area corresponds to low-intensity pain. In step S104, it should be noted that color gradient mapping enables the tenderness heatmap to visually display the spatial distribution of pain intensity. Doctors can quickly identify pain hotspots and pain-relief areas, which is crucial for evaluating treatment effectiveness and developing subsequent treatment plans. Furthermore, by combining the data from the itching site markings with the pain heatmap, the spatial relationship between itching and pain can be further analyzed.

[0022] S105. Calculate the itch-pain coupling index based on the synchronously recorded dynamic scores of pain intensity and itch intensity.

[0023] In step S105, it is important to explain in detail that the pruritus-pain coupling index is a quantitative indicator used to assess the correlation between the two sensory abnormalities of pruritus and pain. Specifically, this index calculates the correlation between them by comparing the dynamic changes in the intensity of pruritus and pain over the same time period. A high coupling index indicates a strong interaction between pruritus and pain, which can significantly impact a patient's daily life. By calculating this index, the present invention provides physicians with crucial information about the complexity of a patient's symptoms, helping to develop more personalized treatment plans.

[0024] As an optional embodiment of the present invention, optionally, the expression of the Gaussian kernel density estimation algorithm in step S103 is: in, Represents position in two-dimensional space Pain density value at the location, This represents the total number of pain-labeled samples. This represents the Gaussian kernel bandwidth parameter. Indicates the first Pain intensity weights for each sample Indicates the first The spatial x-coordinate of each pain marker sample Indicates the first The spatial ordinate of a pain-labeled sample; The expression for calculating the pruritus-pain coupling index in step S105 is as follows: in, Indicates the pruritus-pain coupling index. Indicates the observation duration. express Constant pain rating express Itching score based on the duration of itching.

[0025] As an optional embodiment of the present invention, optionally, obtaining the nerve conduction velocity recovery rate and C-fiber response characteristics in step S2 includes: S201. Based on the aforementioned thermal map of the tenderness range, locate high-intensity pain areas and prioritize screening them using the pruritus-pain coupling index. Regions ≥k innervated by nerves were identified as high-priority detection regions after localization, where k represents... The threshold; In step S201, it should be explained in detail that k equals 0.5; through this step, the present invention can ensure that high-frequency ultrasound and laser evoked potential detection are focused on those areas most likely to benefit from neural repair assessment, thereby improving detection efficiency and accuracy.

[0026] S202. Based on the high-priority detection area, high-frequency ultrasound is used to strongly stimulate the distal and proximal ends of the nerve to record compound muscle action potentials, and the nerve conduction velocity (NCV (m / s)) before treatment is calculated based on the compound muscle action potentials. In step S202, it is important to explain in detail that high-frequency ultrasound stimulation is a non-invasive technique that temporarily interferes with or activates nerve conduction by delivering high-intensity ultrasound energy to nerve tissue, thereby helping to assess the functional state of the nerves. In this step, ultrasound stimulation is applied to the distal and proximal ends of the nerves within a high-priority detection area. By recording the resulting compound muscle action potentials, the patient's nerve conduction velocity (NCV (m / s)) before treatment can be calculated.

[0027] NCV (m / s) = latency difference (ms) / distance between two stimulus points (mm); S203. Based on the high-priority detection region, peripheral nerves are stimulated by laser evoked potentials, and C-fiber response characteristics are recorded. The C-fiber response characteristics include latency, amplitude, and γ-band synchronization intensity. In step S203, it is important to explain in detail that laser-evoked potentials (LAPs) are a technique that uses short-pulse lasers to stimulate peripheral nerves and record the resulting potential changes. It features high temporal and spatial resolution, enabling precise assessment of the functional state of fine nerve fibers such as C-fibers. In this step, laser stimulation is applied to peripheral nerves within a high-priority detection area. By recording response characteristics such as the latency, amplitude, and gamma-band synchronization intensity of C-fibers, the functional recovery of C-fibers during nerve repair can be further understood. These characteristic parameters not only reflect the conduction velocity and excitability of C-fibers but are also closely related to neural plasticity and pain modulation mechanisms. Through in-depth analysis of these parameters, this invention provides physicians with more detailed information about nerve repair effects and pain relief mechanisms, helping to develop more precise treatment strategies.

[0028] S204. Repeat steps S202 to S203 to calculate the nerve conduction velocity recovery rate (NRI) based on the pre-treatment nerve conduction velocity before and after treatment.

[0029] In step S204, it is necessary to explain in detail that the formula for calculating the Nerve Conduction Velocity Recovery Rate (NRI) is: NRI = [(Post-treatment NCV - Pre-treatment NCV) / Pre-treatment NCV] × 100%. This indicator directly reflects the degree of improvement in nerve conduction function after treatment and is one of the key parameters for evaluating the effectiveness of nerve repair. By comparing the NCV values ​​before and after treatment, doctors can quantitatively assess the effectiveness of the treatment. Simultaneously, by combining the changes in C-fiber response characteristics, a more comprehensive understanding of the process and mechanism of nerve repair can be obtained, providing patients with more personalized treatment plans.

[0030] C-fiber response rate = (total number of stimulations / number of effective responses) × 100%; As an optional embodiment of the present invention, optionally, obtaining the rate of change of microvascular density, epidermal nerve fiber density, and spinal cord T2-weighted imaging values ​​in step S3 includes: S301. Based on the nerve conduction velocity recovery rate, locate and repair the nerve area. When the nerve conduction velocity recovery rate is ≥ c%, start high-frequency ultrasound contrast imaging to record microvessel density and calculate the change rate (MVD change rate (%)). In step S301, it should be explained in detail that in this embodiment, c equals 80. When the nerve conduction velocity recovery rate reaches or exceeds 80%, it indicates that the nerve repair process may have entered a relatively significant stage, and it is appropriate to initiate high-frequency ultrasound contrast imaging at this time. High-frequency ultrasound contrast imaging technology, by injecting microbubble contrast agents into the body and utilizing the scattering and reflection characteristics of ultrasound waves, can observe the perfusion of microvessels in real time and dynamically, thereby accurately measuring microvessel density. By comparing the microvessel density values ​​before and after treatment, the rate of change in microvessel density can be calculated. This parameter reflects the degree and efficiency of angiogenesis during nerve repair. Angiogenesis is an important foundation for nerve repair. It not only provides necessary nutrients and oxygen to nerve tissue but also promotes the regeneration of nerve fibers and the recovery of function.

[0031] MVD change rate (%) = (Post-treatment MVD − Pre-treatment MVD) / Pre-treatment MVD × 100%; S302. In the region where the C-fiber response characteristics show a γ-band synchronization intensity ≥ j%, the epidermal layer is scanned using an OCT scanner to calculate the epidermal nerve fiber density and statistically analyze the rate of change (IENFD change rate (%)). In step S302, it needs to be explained in detail that in this embodiment, j equals 80; the γ-band synchronization intensity is an important indicator reflecting the synchronous firing ability of nerve fibers. When this indicator reaches or exceeds 80%, it means that the nerve fibers in the relevant area may have recovered good synchronization, which provides valuable clues for further evaluation of the density of epidermal nerve fibers. Optical coherence tomography (OCT) is a high-resolution, non-invasive imaging technique that can observe the microstructure of the skin epidermis in real time and dynamically, including the distribution and density of epidermal nerve fibers. By comparing OCT images before and after treatment, the rate of change in epidermal nerve fiber density can be accurately calculated. This parameter not only reflects the regeneration of nerve fibers but is also closely related to the degree of pain relief and nerve function recovery in patients. The increase in epidermal nerve fiber density is one of the important markers of nerve repair, which helps improve patients' sensory functions such as touch and temperature sensation, and improve their quality of life.

[0032] IENFD change rate (%) = (IENFD after treatment − IENFD before treatment) / IENFD before treatment × 100%; S303. For spinal cord segments with a nerve conduction velocity recovery rate ≥ s% and a C-fiber response rate ≥ z%, T2 values ​​of the spinal cord are obtained by T2-weighted imaging and the rate of change is calculated.

[0033] In step S303, it needs to be explained in detail that in this embodiment, s equals 80 and z equals 86.7. Spinal cord T2-weighted imaging is a commonly used magnetic resonance imaging technique. By performing T2-weighted scanning on spinal cord tissue, it can reflect the transverse relaxation time of water molecules in the spinal cord, thereby indirectly reflecting the microstructure and pathological changes of the spinal cord. When the nerve conduction velocity recovery rate and C-fiber response rate simultaneously reach or exceed the preset threshold, it indicates that significant nerve repair may have occurred in the relevant spinal cord segment. At this time, it is meaningful to obtain the spinal cord T2 value through T2-weighted imaging and calculate its rate of change. The change in spinal cord T2 value reflects the change in water content of spinal cord tissue before and after treatment. This parameter is closely related to the resolution of inflammation, reduction of edema, and regeneration of nerve fibers in the spinal cord tissue during nerve repair. By comparing the spinal cord T2 values ​​before and after treatment, the rate of change of spinal cord T2 value can be calculated, providing doctors with an objective quantitative indicator of the spinal cord repair effect, which helps to formulate more precise treatment strategies. The implementation of this step further enriches the evaluation system of the present invention, making the evaluation of the treatment effect of herpes zoster neuralgia more comprehensive and in-depth.

[0034] T2 change rate (%) = (T2 value after treatment - T2 value before treatment) / T2 value before treatment × 100%; As an optional embodiment of the present invention, optionally, obtaining the change curves of the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio in step S4 includes: S401. Based on the microvascular density change rate ≥15% and the spinal cord T2 value change rate ≥-20%, a dynamic sampling plan is formulated, setting the pre-treatment, 1 week, 2 weeks and 4 weeks after treatment as key time nodes. In step S401, it is important to explain in detail that changes in microvascular density and spinal cord T2 values ​​are crucial biomarkers in the nerve repair process. Increased microvascular density reflects the activity of angiogenesis during nerve repair, while changes in spinal cord T2 values ​​are closely related to the resolution of inflammation, reduction of edema, and regeneration of nerve fibers in the spinal cord tissue. Therefore, selecting areas with a microvascular density change rate ≥15% and a spinal cord T2 value change rate ≥-20% as key areas for dynamic sampling allows for more accurate capture of crucial information during nerve repair. By setting pre-treatment, 1 week, 2 weeks, and 4 weeks post-treatment as key time points, this invention can systematically monitor the dynamic changes of these biomarkers during treatment, providing doctors with more detailed information about nerve repair efficacy and pain relief mechanisms. This information helps doctors develop more precise treatment strategies and adjust treatment plans, thereby accelerating the patient's recovery process.

[0035] S402. Collect patient serum samples based on a dynamic sampling plan, detect the concentrations of nerve growth factor and brain-derived neurotrophic factor by ELISA, and calculate the ratio of nerve growth factor to brain-derived neurotrophic factor. In step S402, it is important to explain in detail that nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF) are two important neurotrophic factors that play crucial roles in the development, maintenance, and repair of the nervous system. NGF primarily promotes neuronal growth, differentiation, and survival, while BDNF significantly influences synaptic plasticity and neurotransmission efficiency. By detecting the concentrations of these two factors in the patient's serum using ELISA and calculating their ratio, this invention can assess the dynamic changes of neurotrophic factors during nerve repair, providing physicians with objective indicators of the state of nerve function recovery. This step not only helps physicians understand the effectiveness of nerve repair but also provides a scientific basis for developing and adjusting treatment plans.

[0036] NGF / BDNF ratio = BDNF concentration (pg / ml) / NGF concentration (pg / ml); S403. Detect the concentrations of interleukin-6 and tumor necrosis factor-α by flow cytometry and calculate the ratio of interleukin-6 to tumor necrosis factor-α.

[0037] In step S403, it is important to explain in detail that interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) are two important inflammatory cytokines that play crucial roles in neuroinflammation and pain regulation. IL-6 is primarily involved in immune responses and inflammatory reactions, while TNF-α has broad biological activity, capable of inducing inflammatory responses, apoptosis, and tissue damage. By detecting the concentrations of these two cytokines in the patient's serum using flow cytometry and calculating their ratio, this invention can assess the dynamic changes in the inflammatory response during nerve repair. This step further enriches the assessment system of this invention, making the evaluation of the therapeutic effect of herpes zoster neuralgia more comprehensive and in-depth. The IL-6 / TNF-α ratio = TNF-α concentration (pg / ml) / IL-6 concentration (pg / ml). Through changes in this ratio, physicians can more accurately understand the decline of the inflammatory response during nerve repair.

[0038] As an optional embodiment of the present invention, optionally, in step S5, the change curves of the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio are analyzed by functional magnetic resonance imaging dynamic causal model to obtain the pain matrix reconstruction index, including: S501. Based on the change curves of the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio, construct a time series data model; In step S501, it is important to explain in detail that the time-series data model can capture the dynamic changes in the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio during treatment, providing foundational data for subsequent causal model analysis. These data reflect changes in key biomarkers during nerve repair and inflammatory responses, which are of great significance for understanding pain relief mechanisms and neurological function recovery.

[0039] In this embodiment, the specific steps for constructing a time-series data model are as follows: First, data on the ratios of nerve growth factor (NGF) to brain-derived neurotrophic factor (BDNF) and interleukin-6 (IL-6) to tumor necrosis factor-α (TNF-α) are collected at different time points (such as before treatment, 1 week after treatment, 2 weeks after treatment, and 4 weeks after treatment) to ensure the accuracy and completeness of the data. Then, using statistical software or specialized data analysis tools, these data are arranged and organized according to time series to form a time-series dataset. Next, based on the characteristics of the data and the analysis requirements, a suitable time-series data model is selected for fitting, such as the autoregressive moving average (ARMA) model or the autoregressive integral moving average (ARIMA) model. During the model fitting process, the model parameters need to be continuously adjusted to optimally describe the dynamic changes in the data. Finally, the fitted time-series data model is validated and evaluated to ensure that the model can accurately reflect the dynamic changes in the NGF / BDNF ratio and the I-6 / TNF-α ratio during the treatment process.

[0040] S502. Functional magnetic resonance imaging (fMRI) is used to scan the patient's brain to obtain blood oxygenation level-dependent signals in pain-related brain regions. In step S502, it is important to explain in detail that functional magnetic resonance imaging (fMRI) is a non-invasive neuroimaging technique that utilizes changes in blood oxygen level-dependent (BOLD) signals to reflect dynamic changes in brain neural activity. In this step, scanning the patient's brain using fMRI allows for the precise capture of BOLD signals in pain-related brain regions. These signals reflect the neural activity patterns of the brain when processing pain information. Pain-related brain regions include several areas associated with pain perception, emotion processing, and cognitive regulation, such as the thalamus, anterior cingulate cortex, and insula. By acquiring BOLD signals from these brain regions, this invention can further understand the reconstruction of the pain matrix during neural repair, providing physicians with more detailed information about pain relief mechanisms. This information helps physicians develop more effective pain management strategies and improve patients' quality of life.

[0041] S503. The time series data model is fused with the blood oxygen level-dependent signal, and the dynamic causal model is applied to analyze the changes in the effective connectivity strength between pain-related brain regions. In step S503, it is important to explain in detail that fusing the time-series data model with blood oxygen level-dependent signals is one of the key steps of this invention. By combining time-series data reflecting the dynamic changes of nerve growth factor, brain-derived neurotrophic factor, interleukin-6, and tumor necrosis factor-α with blood oxygen level-dependent signals reflecting brain neural activity patterns, this invention enables a deeper understanding of the relationship between changes in these biomarkers and brain pain processing mechanisms. Dynamic causal models are an advanced neuroimaging analysis method that uses time-series data to infer changes in the effective connectivity strength between different brain regions, thereby revealing causal relationships in neural activity. In this step, applying dynamic causal models to analyze changes in the effective connectivity strength between pain-related brain regions can further reveal the reconstruction mechanism of the pain matrix during neural repair, providing physicians with deeper information about pain relief and neurological function recovery. This information not only helps physicians develop more precise treatment strategies but also provides new perspectives and ideas for research in the field of neuroscience.

[0042] In this embodiment, the dynamic causal model is the existing Dynamic Causal Modeling (DCM). DCM is a Bayesian framework-based model that uses prior knowledge and observational data to infer the strength and direction of connections between brain regions. In this application, DCM reveals how the effective connection strength between pain-related brain regions changes over time by analyzing the correlation between time-series data models (including changes in the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio) and blood oxygen level-dependent signals. This process involves constructing the DCM, setting model parameters, fitting the model using observational data, and updating the understanding of the model parameters through Bayesian inference. Ultimately, the output of the DCM provides dynamic change maps of the effective connection strength between pain-related brain regions. These maps reflect the reconstruction of the pain matrix during neural repair, providing physicians with quantitative indicators of pain relief and neurological function recovery. S504. Calculate the pain matrix reconstruction index based on changes in effective connection strength.

[0043] In step S504, it is important to explain in detail that the Pain Matrix Reconstruction Index is a quantitative indicator that comprehensively assesses the effectiveness of neural repair and pain relief mechanisms. It is calculated based on changes in the effective connectivity strength between pain-related brain regions, derived from dynamic causal model analysis. Changes in this index reflect the dynamic reconstruction of pain processing mechanisms during neural repair, providing physicians with objective evidence regarding the state of neural function recovery and the degree of pain relief. By comparing the Pain Matrix Reconstruction Index before and after treatment, physicians can more accurately assess treatment effectiveness, formulate more precise treatment strategies, and thus accelerate the patient's recovery process.

[0044] As an optional embodiment of the present invention, optionally, the mathematical expression for calculating the pain matrix reconstruction index in step S504 is: in, Indicates the pain matrix reconstruction index. This indicates the number of regions of interest in the pain matrix. Indicates the first day after treatment brain regions to the first Effective connectivity strength of individual brain regions Indicates the first day before treatment brain regions to the first Effective connectivity strength of individual brain regions.

[0045] As an optional embodiment of the present invention, optionally, obtaining the individualized treatment effect grading in step S6 includes: S601. Based on the output data from steps S1 to S5, construct a multi-dimensional efficacy evaluation matrix. The output data includes a heat map of the tenderness range, the recovery rate of nerve conduction velocity, the rate of change of microvascular density, the ratio of nerve growth factor to brain-derived neurotrophic factor, and the pain matrix reconstruction index. In step S601, it is necessary to explain in detail that the multidimensional efficacy assessment matrix is ​​a comprehensive assessment tool that integrates multiple key indicators to comprehensively evaluate the treatment effect of herpes zoster neuralgia. These indicators include a tenderness area heatmap, nerve conduction velocity recovery rate, microvascular density change rate, nerve growth factor / brain-derived neurotrophic factor ratio, and pain matrix reconstruction index, which reflect the process and effect of nerve repair from different perspectives. The tenderness area heatmap visually displays the distribution and changes of the patient's pain area, providing doctors with an intuitive basis for pain assessment. The nerve conduction velocity recovery rate directly reflects the degree of nerve function recovery and is one of the important indicators for assessing treatment effectiveness. The microvascular density change rate reflects the activity of angiogenesis during nerve repair and is closely related to the recovery of nerve function. The nerve growth factor / brain-derived neurotrophic factor ratio assesses the dynamic changes of neurotrophic factors, providing doctors with an objective indicator of the state of nerve function recovery. The Pain Matrix Reconstruction Index is a quantitative indicator that comprehensively assesses the effectiveness of nerve repair and pain relief mechanisms. It is calculated based on the changes in the effective connectivity strength between pain-related brain regions obtained from dynamic causal model analysis, providing doctors with objective evidence regarding the state of nerve function recovery and the degree of pain relief.

[0046] In constructing the multi-dimensional efficacy evaluation matrix, this invention integrates and analyzes the output data from steps S1 to S5. First, this output data is collected and organized to ensure its accuracy and completeness. Then, statistical software or specialized data analysis tools are used to comprehensively analyze this data and construct the multi-dimensional efficacy evaluation matrix. This matrix can intuitively display the treatment effects on patients at different treatment stages. By comparing changes in different indicators, doctors can more accurately understand the patient's nerve repair process and pain relief, thereby developing more precise treatment strategies. This step improves the accuracy of evaluating the treatment effect of herpes zoster neuralgia.

[0047] S602. Based on the efficacy assessment matrix, perform data standardization processing, map continuous indicators to the [0,1] interval using linear normalization, and perform binarization transformation on target-achieving indicators to generate a standardized dataset. In step S602, it is important to explain in detail that, due to potential differences in the data range and units of different indicators, direct comparison and analysis may lead to inaccurate results. Therefore, this invention employs data standardization to eliminate these differences, enabling fair comparisons between different indicators. For continuous indicators, such as nerve conduction velocity recovery rate and microvascular density change rate, this invention uses linear normalization to map them to the [0,1] interval. Linear normalization is a commonly used data standardization method that linearly transforms the original data to a specified range, giving the data a uniform scale and distribution. For compliance indicators, such as whether the tenderness range heatmap has shrunk to a certain range or whether the nerve growth factor / brain-derived neurotrophic factor ratio has reached a certain threshold, this invention performs binarization, converting them into 0 or 1. Binarization simplifies the data analysis process, making compliance immediately apparent. Through data standardization, this invention generates a standardized dataset.

[0048] S603. Calculate the comprehensive efficacy score based on the preset weight allocation rules of the standardized dataset; In step S603, it is important to explain in detail that the comprehensive efficacy score is calculated based on a standardized dataset and preset weighting rules, enabling a comprehensive assessment of the patient's treatment effectiveness at different stages. In this invention, the preset weighting rules are determined based on the importance of each indicator in the nerve repair and pain relief process. These weights reflect the contribution of different indicators to the evaluation of treatment effectiveness, ensuring the accuracy and reliability of the comprehensive efficacy score. When calculating the comprehensive efficacy score, this invention multiplies each indicator value in the standardized dataset by its corresponding weight, and then sums the weighted indicator values ​​to obtain the comprehensive efficacy score. This score directly reflects the patient's treatment effect. By comparing the comprehensive efficacy scores at different treatment stages, doctors can more accurately understand the patient's nerve repair progress and treatment effect, thereby developing more precise treatment strategies. The implementation of this step improves the efficiency and accuracy of evaluating the treatment effect of herpes zoster neuralgia.

[0049] The expression for calculating the overall therapeutic effect score is: in, Indicates the first Number of indicators within each dimension This represents the value after normalization or binarization; S604. Based on the comprehensive efficacy score, the individualized treatment effect is divided into four levels: excellent, good, moderate, and poor. Among them, a comprehensive efficacy score ≥ 0.9 is judged as excellent, 0.7 ≤ comprehensive efficacy score < 0.9 is judged as good, 0.5 ≤ comprehensive efficacy score < 0.7 is judged as moderate, and a comprehensive efficacy score < 0.5 is judged as poor.

[0050] In step S604, it is important to explain in detail that the grading of individualized treatment effectiveness provides doctors with a direct assessment of the patient's treatment outcome, helping them to formulate and adjust treatment strategies. By comparing the comprehensive efficacy score with a pre-defined grading standard, doctors can quickly understand the patient's treatment effectiveness level and take appropriate treatment measures. For example, for patients with a treatment effectiveness rating of "excellent," doctors can maintain the current treatment plan and continue to observe the patient's recovery; for patients with a treatment effectiveness rating of "good" or "moderate," doctors can adjust the treatment plan according to the specific situation, strengthening certain aspects of treatment to improve the effectiveness; for patients with a treatment effectiveness rating of "poor," doctors need to analyze the reasons in depth, which may require trying new treatment methods or adjusting the treatment strategy to improve the patient's symptoms and quality of life. The implementation of this grading standard not only improves the efficiency of evaluating the treatment effectiveness of herpes zoster neuralgia but also provides doctors with more precise treatment guidance, helping to accelerate the patient's recovery process.

[0051] Example 2 A system for evaluating the efficacy of ultrashort focused ultrasound (UFI) therapy for herpes zoster neuralgia, the system comprising the aforementioned method for evaluating the efficacy of UFI in treating herpes zoster neuralgia; the system further comprising: The data acquisition module is used to collect the patient's baseline data; A pain atlas construction module is used to construct a dynamic pain atlas based on the baseline data; A high-frequency ultrasound and laser evoked potential detection module is used for high-frequency ultrasound combined with laser evoked potential detection; The multimodal tissue repair image assessment module is used to perform multimodal tissue repair image assessment. The serological biomarker dynamic tracking module is used to dynamically track the rate of change of microvascular density, epidermal nerve fiber density, and spinal cord T2-weighted imaging values. The functional magnetic resonance imaging (fMRI) analysis module is used to perform dynamic causal model analysis on the changes in the ratios of nerve growth factor (NGF) to brain-derived neurotrophic factor (BDNF) and interleukin-6 (IL-6) to tumor necrosis factor-α (TNF-α). The efficacy assessment module is used to comprehensively assess the efficacy based on the output data of the aforementioned modules and obtain an individualized treatment effect grading.

[0052] In this embodiment, an efficacy evaluation system for ultrashort focused ultrasound treatment of herpes zoster neuralgia is used to implement the efficacy evaluation method for ultrashort focused ultrasound treatment of herpes zoster neuralgia in Embodiment 1. The data acquisition module is responsible for collecting various baseline data from patients, which form the basis for subsequent analysis and evaluation. Baseline data may include basic information such as the patient's age, gender, medical history, and pain level, as well as relevant physiological indicators and imaging data before and after treatment.

[0053] The pain mapping module then constructs a dynamic pain map based on this baseline data. This map visually displays the region, intensity, and trend of pain in patients, providing doctors with intuitive pain assessment data and helping them to understand patients' pain status more accurately.

[0054] The high-frequency ultrasound and laser evoked potential detection module combines high-frequency ultrasound technology with laser evoked potential detection technology to conduct a detailed assessment of the patient's neurological and muscular function. This step can reveal key information such as nerve conduction velocity and muscle activity status, providing doctors with direct evidence regarding the recovery of neurological function.

[0055] The multimodal tissue repair imaging assessment module utilizes various imaging techniques, such as ultrasound, CT, and MRI, to perform multimodal imaging assessments of the patient's damaged neural tissue. By comparing imaging changes before and after treatment, doctors can evaluate the degree and effectiveness of neural tissue repair.

[0056] The serological biomarker dynamic tracking module focuses on the dynamic changes of serological biomarkers such as microvascular density, epidermal nerve fiber density, and the rate of change of T2-weighted imaging values ​​in the spinal cord. These biomarkers reflect key processes such as angiogenesis and nerve fiber regeneration during nerve repair, and their changes can provide doctors with objective indicators of the state of nerve function recovery.

[0057] The functional magnetic resonance imaging (fMRI) analysis module focuses on performing dynamic causal model analysis on the changes in the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio using fMRI. This step can reveal the relationship between changes in these biomarkers and the brain's pain processing mechanisms, providing physicians with deeper information about pain relief and neurological function recovery.

[0058] The efficacy assessment module performs a comprehensive efficacy assessment based on the output data from the aforementioned modules. Using pre-defined algorithms and rules, combined with a multi-dimensional efficacy evaluation matrix and a comprehensive efficacy score, it categorizes individualized treatment effects into four levels: excellent, good, moderate, and poor. This assessment provides doctors with an intuitive understanding of the patient's treatment effectiveness, helping them to formulate and adjust treatment strategies and accelerate the patient's recovery process.

[0059] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for evaluating the efficacy of ultrashort focused ultrasound therapy for postherpetic neuralgia, characterized in that, The method includes: S1. Utilize the patient's baseline data to establish a dynamic pain atlas and obtain a heat map of tenderness range and an itching-pain coupling index; S2. Based on the thermal map of the tenderness range and the pruritus-pain coupling index, high-frequency ultrasound combined with laser evoked potential detection is performed to obtain the nerve conduction velocity recovery rate and C-fiber response characteristics. S3. Based on the nerve conduction velocity recovery rate and C-fiber response characteristics, perform multimodal tissue repair imaging assessment to obtain the change rate of microvascular density, epidermal nerve fiber density, and spinal cord T2-weighted imaging values. S4. The change rate of microvascular density, epidermal nerve fiber density and spinal cord T2-weighted imaging value is dynamically tracked by serum markers to obtain the change curves of nerve growth factor / brain-derived neurotrophic factor ratio and interleukin-6 / tumor necrosis factor-α ratio. S5. Perform functional magnetic resonance imaging dynamic causal model analysis on the change curves of the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio to obtain the pain matrix reconstruction index. S6. Based on the output of each step from S1 to S5, a comprehensive efficacy assessment is performed to obtain an individualized treatment effect grading.

2. The method for evaluating the effect of ultrashort focused ultrasound treatment for postherpetic neuralgia as described in claim 1, characterized in that, In step S1, the heatmap of tenderness range and the pruritus-pain coupling index are obtained, including: S101. Collect the patient's baseline data, which includes three-dimensional coordinates of the pain location, dynamic pain intensity score, qualitative description of the nature of pain, marking of itching locations, and neurophysiological test data. S102. Based on the three-dimensional coordinates of the pain site and the dynamic score of pain intensity in the baseline data, the pain area is marked on the virtual human body model through gesture interaction, and the marking data of the itchy area is recorded simultaneously. S103. The Gaussian kernel density estimation algorithm is used to spatially locate and intensity-weight the marked pain areas to generate an initial pain density distribution. S104. Based on the initial pain density distribution and dynamic pain intensity score, a heat map of tenderness range is generated by color gradient mapping, where the red area corresponds to high-intensity pain and the blue area corresponds to low-intensity pain. S105. Calculate the itch-pain coupling index based on the synchronously recorded dynamic scores of pain intensity and itch intensity.

3. The method for evaluating the effect of ultrashort focused ultrasound treatment for postherpetic neuralgia as described in claim 2, characterized in that, The expression for the Gaussian kernel density estimation algorithm in step S103 is as follows: in, Represents position in two-dimensional space Pain density value at the location, This represents the total number of pain-labeled samples. This represents the Gaussian kernel bandwidth parameter. Indicates the first Pain intensity weights for each sample, Indicates the first The spatial x-coordinate of each pain marker sample Indicates the first The spatial ordinate of a pain-labeled sample; The expression for calculating the pruritus-pain coupling index in step S105 is as follows: in, Indicates the pruritus-pain coupling index. Indicates the observation duration. express Constant pain rating express Itching score based on the duration of itching.

4. The method for evaluating the effect of ultrashort focused ultrasound treatment for postherpetic neuralgia as described in claim 1 or 3, characterized in that, The nerve conduction velocity recovery rate and C-fiber response characteristics obtained in step S2 include: S201. Based on the aforementioned thermal map of the tenderness range, locate high-intensity pain areas and prioritize screening them using the pruritus-pain coupling index. Regions ≥k innervated by nerves were identified as high-priority detection regions after localization, where k represents... The threshold; S202. Based on the high-priority detection area, high-frequency ultrasound is used to strongly stimulate the distal and proximal ends of the nerve to record the compound muscle action potential, and the nerve conduction velocity before treatment is calculated based on the compound muscle action potential. S203. Based on the high-priority detection region, peripheral nerves are stimulated by laser evoked potentials, and C-fiber response characteristics are recorded. The C-fiber response characteristics include latency, amplitude, and γ-band synchronization intensity. S204. Repeat steps S202 to S203 to calculate the nerve conduction velocity recovery rate based on the pre-treatment nerve conduction velocity before and after treatment.

5. The method for evaluating the effect of ultrashort focused ultrasound treatment for postherpetic neuralgia as described in claim 1, characterized in that, In step S3, the changes in microvascular density, epidermal nerve fiber density, and spinal cord T2-weighted imaging values ​​are obtained, including: S301. Based on the nerve conduction velocity recovery rate, locate and repair the nerve area. When the nerve conduction velocity recovery rate is ≥ c%, start high-frequency ultrasound contrast imaging to record microvascular density and calculate the rate of change. S302. In the region where the C-fiber response characteristics show a γ-band synchronization intensity ≥ j%, the epidermal layer is scanned using an OCT scanner to calculate the epidermal nerve fiber density and statistically analyze the rate of change. S303. For spinal cord segments with a nerve conduction velocity recovery rate ≥ s% and a C-fiber response rate ≥ z%, T2 values ​​of the spinal cord are obtained by T2-weighted imaging and the rate of change is calculated.

6. The method for evaluating the effect of ultrashort focused ultrasound treatment for postherpetic neuralgia as described in claim 1, characterized in that, In step S4, the curves showing the changes in the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio include: S401. Based on the microvascular density change rate ≥15% and the spinal cord T2 value change rate ≥-20%, a dynamic sampling plan is formulated, setting the pre-treatment, 1 week, 2 weeks and 4 weeks after treatment as key time nodes. S402. Collect patient serum samples based on a dynamic sampling plan, detect the concentrations of nerve growth factor and brain-derived neurotrophic factor by ELISA, and calculate the ratio of nerve growth factor to brain-derived neurotrophic factor. S403. Detect the concentrations of interleukin-6 and tumor necrosis factor-α by flow cytometry and calculate the ratio of interleukin-6 to tumor necrosis factor-α.

7. The method for evaluating the effect of ultrashort focused ultrasound treatment for postherpetic neuralgia as described in claim 1, characterized in that, In step S5, the changes in the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio are analyzed using a functional magnetic resonance imaging dynamic causal model to obtain the pain matrix reconstruction index, including: S501. Based on the change curves of the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio, construct a time series data model; S502. Functional magnetic resonance imaging (fMRI) is used to scan the patient's brain to obtain blood oxygenation level-dependent signals in pain-related brain regions. S503. The time series data model is fused with the blood oxygen level-dependent signal, and the dynamic causal model is applied to analyze the changes in the effective connectivity strength between pain-related brain regions. S504. Calculate the pain matrix reconstruction index based on changes in effective connection strength.

8. The method for evaluating the effect of ultrashort focused ultrasound treatment for postherpetic neuralgia as described in claim 7, characterized in that, The mathematical expression for calculating the pain matrix reconstruction index in step S504 is as follows: in, Indicates the pain matrix reconstruction index. This indicates the number of regions of interest in the pain matrix. Indicates the first day after treatment brain regions to the first Effective connectivity strength of individual brain regions Indicates the first day before treatment brain regions to the first Effective connectivity strength of individual brain regions.

9. The method for evaluating the effect of ultrashort focused ultrasound treatment for postherpetic neuralgia as described in claim 1, characterized in that, Obtaining individualized treatment efficacy grading in step S6 includes: S601. Based on the output data from steps S1 to S5, construct a multi-dimensional efficacy evaluation matrix. The output data includes a heat map of the tenderness range, the recovery rate of nerve conduction velocity, the rate of change of microvascular density, the ratio of nerve growth factor to brain-derived neurotrophic factor, and the pain matrix reconstruction index. S602. Based on the efficacy assessment matrix, perform data standardization processing, map continuous indicators to the [0,1] interval using linear normalization, and perform binarization transformation on target-achieving indicators to generate a standardized dataset. S603. Calculate the comprehensive efficacy score based on the preset weight allocation rules of the standardized dataset; S604. Based on the comprehensive efficacy score, the individualized treatment effect is divided into four levels: excellent, good, moderate, and poor. Among them, a comprehensive efficacy score ≥ 0.9 is judged as excellent, 0.7 ≤ comprehensive efficacy score < 0.9 is judged as good, 0.5 ≤ comprehensive efficacy score < 0.7 is judged as moderate, and a comprehensive efficacy score < 0.5 is judged as poor.

10. A system for evaluating the efficacy of ultrashort focused ultrasound therapy for postherpetic neuralgia, characterized in that, The system includes a method for evaluating the efficacy of ultrashort focused ultrasound treatment for herpes zoster neuralgia as described in any one of claims 1 to 9; the system further includes: The data acquisition module is used to collect the patient's baseline data; A pain atlas construction module is used to construct a dynamic pain atlas based on the baseline data; A high-frequency ultrasound and laser evoked potential detection module is used for high-frequency ultrasound combined with laser evoked potential detection; The multimodal tissue repair image assessment module is used to perform multimodal tissue repair image assessment. The serological biomarker dynamic tracking module is used to dynamically track the changes in microvascular density, epidermal nerve fiber density, and spinal cord T2-weighted imaging values ​​using serological biomarkers. The functional magnetic resonance imaging (fMRI) analysis module is used to perform dynamic causal model analysis on the change curves of the nerve growth factor / brain-derived neurotrophic factor ratio and the interleukin-6 / tumor necrosis factor-α ratio using fMRI. The efficacy assessment module is used to comprehensively assess the efficacy based on the output data of the aforementioned modules, and obtain an individualized treatment effect grading.

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