Method for measuring pain intensity

Abstract

The present disclosure relates to a method for measuring pain intensity, and more particularly provides a method for measuring pain intensity by providing a pain template.

Description

Technical Field

[0001] The present disclosure relates to a method for objectively measuring pain intensity, and more particularly, provides a method capable of objectively measuring pain intensity by providing a pain template. Background Art

[0002] Pathological pain is different from natural physiological pain. It has no survival benefit and is mainly caused by abnormal nervous systems. Neuropathic pain is a typical pathological pain. Individuals suffering from neuropathic pain usually perceive harmless external sensory stimuli as harmful and feel pain. In the past few decades, active research has been conducted on neuropathic pain. However, currently, no standard method for objectively evaluating pain intensity has been established. Since the chronic pain symptoms and pain intensity after nerve injury vary from person to person, it is difficult to develop a standard evaluation method for objectively evaluating them. The degree of pain amplification depends on the individual, and no objective diagnostic method has been established. Therefore, currently, there is no choice but to rely on the patient's own subjective statements to measure the patient's pain level. Summary of the Invention

[0003] Technical Problem

[0004] Traditional techniques aimed at diagnosing neuropathic pain mainly rely on the patient's self-report and several physical diagnostic methods. Traditional tools for screening neuropathic pain include: Michigan Neuropathy Screening Instrument, Neuropathic Pain Scale, Leeds Assessment of Neuropathic Symptoms and Signs, Neuropathic Pain Questionnaire, Neuropathic Pain Symptom Inventory, "Douleur Neuropathique en 4 questions", Pain Detect, Pain Quality Assessment Scale, Short-Form McGill Pain Questionnaire. Although there are some differences, all of the above techniques rely on the patient's self-report of the pain felt in response to sensory stimuli.

[0005] The standardized method mainly used in clinical practice for quantitatively measuring neuropathic pain was introduced in 2006 by the German Research Network on Neuropathic Pain (Deutscher Forschungsverbund Neuropathischer Schmerz [DFNS]). Sensory stimuli are applied to the skin to record the intensity of the pain felt by the individual. Different types of external stimuli are applied to the individual by changing the intensity, and then it is recorded whether the individual suffers from pain. Among them, von Frey filaments, graded needle prick stimuli, and pressure stimuli are used as mechanical stimuli. von Frey uses filaments of different thicknesses to apply stimuli, where different bending forces are generated according to the thickness of the filaments, and the intensity of the stimuli is graded. This is a suitable method for precisely controlling the amount of stimuli applied.

[0006] Due to the self-report nature of patients, it is difficult for traditional methods to distinguish false reports from patients. Moreover, it is impossible to record the severity of pain caused by stimuli in patients with language communication difficulties, children, or those with weaker cognitive functions. Even when using methods that only record behavioral changes, such as paw withdrawal under a certain degree of external stimulus without language communication, it cannot be applied to unconscious patients or patients with impaired motor functions.

[0007] Technical Solution

[0008] Therefore, the present inventors intend to provide a pain template using the expression pattern of an indicator substance, and a method capable of objectively measuring pain intensity by using the pain template.

[0009] One aspect of the present disclosure provides a method for objectively measuring the degree of pain through an image of the brain without relying on language communication or behavioral responses.

[0010] Another aspect of the present disclosure relates to generating a pain template using the expression pattern of an indicator substance according to the intensity of pain, and a method for measuring the pain intensity of a target individual using the pain template. Specifically, the present disclosure provides a method for measuring the pain intensity in a test individual by analyzing the correlation between the pain indicator substance and the pain intensity in the brain of a reference individual to generate a pain template, and applying the expression pattern of the indicator substance measured in the test individual to the pain template.

[0011] More specifically, the present disclosure relates to a method for measuring pain intensity, which includes the following steps:

[0012] Generating a pain template that indicates the correlation between the availability of the indicator substance measured at each pain intensity in at least two or more brain regions of a reference individual and each stage of each brain region and pain intensity; and

[0013] Applying the availability of the indicator substance measured in at least two brain regions of the test individual to the pain template, and selecting, through similarity analysis, the stage of pain intensity that has the highest similarity to the availability of the indicator substance at each stage of pain intensity to determine the pain intensity of the test individual.

[0014] The at least two or more brain regions are regions in which the availability of the indicator substance is altered due to pain, and may be two or more selected from the group consisting of: (1) the rostral caudate-putamen of the striatum, left side, (2) the caudal caudate-putamen of the striatum, left side, (3) the insular cortex, left side, (4) the secondary somatosensory cortex, left side, (5) the hippocampus, right side; rostral, (6) the hippocampus, right side; caudal, (7) the primary somatosensory cortex, left side; trunk region, (8) the primary somatosensory cortex, right side; trunk region, (9) the primary somatosensory cortex, right side; hindlimb region, (10) the secondary somatosensory cortex, right side, (11) the hypothalamus, right side; posterior nucleus, and (12) the anterior midcingulate cortex.

[0015] The pain template is generated by performing the following steps: normalizing by dividing the availability of the indicator substance in at least two or more brain regions by the average value of the availability of the indicator substance in each brain region; and subdividing the normalized values into stages with a pain intensity of at least 200 through regression analysis, and the average value of each brain region is the average value of the availability of the indicator substance in each brain region obtained from a painless control group.

[0016] The similarity analysis can be performed by one or more analysis methods selected from the group consisting of: Pearson correlation coefficient analysis, Spearman correlation coefficient analysis, Euclidean distance analysis, Mahalanobis distance analysis, support vector analysis, cosine distance analysis, Manhattan distance analysis, Jaccard coefficient analysis, and extended Jaccard coefficient analysis, but not limited thereto.

[0017] The Pearson correlation coefficient analysis is performed by the following mathematical formula 2, and the similarity can be evaluated as the degree when the r value calculated by mathematical formula 2 is close to 1.

[0018] [Mathematical formula 2]

[0019]

[0020] X: The normalized availability of the indicator substance measured in the brain region of the test individual

[0021] Y: The availability of the indicator substance in any one pain stage of the pain template

[0022] The sample mean of X

[0023] The sample mean of Y

[0024] n: The number of brain regions.

[0025] The present disclosure will be described in more detail below.

[0026] The present disclosure provides a method for measuring the pain intensity of a test individual by analyzing the correlation between an indicator substance of pain and the pain intensity in the brain of a reference individual to generate a pain template, and applying the availability pattern or expression pattern of the indicator substance measured in the test individual to the pain template. Thus, in the present disclosure, the availability or expression pattern of a pain indicator substance in the brain of a reference substrate is analyzed to generate a pain template, and the availability or expression pattern of the indicator substance in the test individual is measured and applied to the pain template.

[0027] As used herein, the term "availability" of an indicator substance refers to the amount of the indicator substance in a state capable of binding to a binding substance, and may encompass the expression level or functional activity of the indicator substance in vivo. For example, the availability of an indicator substance can be measured by the expression level of the indicator substance. Alternatively, the availability of an indicator substance can be measured by the activity of the indicator substance.

[0028] An indicator substance for pain intensity is a substance present in a specific brain region involved in the processing of pain information, and may be a substance whose availability or expression level of the indicator substance shows a specific pattern depending on the pain intensity felt by the target individual. Examples of the indicator substance may be metabotropic glutamate receptor 5 (mGluR5). One embodiment of the present disclosure is a method capable of objectively measuring pain intensity by using the availability or expression pattern of metabotropic glutamate receptors present in the brain. The availability or expression level of metabotropic glutamate receptors present in a specific brain region involved in the processing of pain information shows a specific pattern depending on the pain intensity felt by an individual. For example, in the present disclosure, the indicator substance may be a substance that shows changes such as an increase or decrease in the brain of an individual. In the present disclosure, the indicator substance may be, for example, metabotropic glutamate receptor 5 (mGluR5), but is not limited thereto.

[0029] Metabotropic glutamate receptor 5 (mGluR5) is a G protein-related receptor and is highly expressed in the hippocampus and cerebral cortex. It is known to control neural plasticity by being mainly distributed on the postsynaptic membrane of nerve cells, and mGluR5 is directly related to nervous system diseases such as fragile X syndrome and neuropathic pain. Diseases related to mGluR5 include pain and drug dependence, neurodegenerative diseases such as amyotrophic lateral sclerosis and multiple sclerosis, Alzheimer's disease, dementia, Parkinson's disease, Hunting pain chorea, mental illnesses such as schizophrenia and anxiety disorders, depression, and the like.

[0030] Methods for measuring the availability of an indicator substance based on the intensity of pain include positron emission tomography (PET), single photon emission computed tomography (SPECT), etc. Positron emission tomography (PET) in the present disclosure is a method for determining the amount of the substance present in a specific region of the body by attaching and injecting a radioactive isotope tracer into a substance that selectively binds to a specific substance present in the body, and then reconstructing the measured radioactive signal into an image by a detector.

[0031] In one embodiment of the present disclosure, when mGluR5 is used as an indicator substance according to the intensity of pain, methods for measuring its availability or expression pattern can use PET, SPECT, etc. For example, the availability or expression pattern of mGluR5 can be measured by binding a labeling substance to ABP688 and tracing the bound labeling substance. In the present disclosure, the means for measuring the amount of the indicator substance by specifically binding a tracer substance to the indicator substance can be, for example, a radioactive isotope tracer. For example, the radioactive isotope tracer can be [11C]ABP688, which is a chemical substance that specifically binds to mGluR5 and can measure the availability of mGluR5 by labeling the radioactive isotope [11C], but is not limited thereto.

[0032] ABP688 is a chemical substance that selectively binds to metabotropic glutamate receptor 5 (mGluR5), and [11C]ABP688 is a substance obtained by labeling ABP688 with the radioactive isotope [11C]. [11C]ABP688 can be used as a radioactive isotope tracer to measure the level of mGluR5 by performing a positron emission tomography (PET) scan. Specifically, a radioactive isotope tracer that specifically binds to metabotropic glutamate receptor 5 is injected into a subject, and then the metabotropic glutamate receptor 5 in the brain is measured using the PET method and the expression pattern of an individual subject is analyzed, whereby the presence or absence of pain and the pain level can be objectively and accurately measured.

[0033] In the present disclosure, a brain region in which the availability of the indicator substance is changed due to pain refers to a brain region in which the availability of the indicator substance increases or decreases when pain is applied to an individual. For example, in the present disclosure, a brain region in which the availability of the indicator substance is changed due to pain can be a brain region in which the availability of the indicator substance is changed due to neuropathic pain induced in the right hind leg.

[0034] For example, in the present disclosure, in the case of inducing neuropathic pain in the right hind leg, a brain region in which the availability of the indicator is changed due to pain can be one or two or more selected from the group consisting of:

[0035] (1) The rostral caudate putamen of the striatum, left side (abbreviation: Cpu_rostral_left),

[0036] (2) The caudal caudate putamen of the striatum, left side (abbreviation: Cpu_caudal_left),

[0037] (3) The insular cortex, left side (abbreviation: Ins_left),

[0038] (4) The secondary somatosensory cortex, left side (abbreviation: S2_left),

[0039] (5) The hippocampus, right side; rostral (abbreviation: Hippo_rostral_right),

[0040] (6) The hippocampus, right side; caudal (abbreviation: Hippo_caudal_right),

[0041] (7) The primary somatosensory cortex, left side; trunk area (abbreviation: S1_trunk_left),

[0042] (8) The primary somatosensory cortex, right side; trunk area (abbreviation: S1_trunk_right),

[0043] (9) The primary somatosensory cortex, right side; hindlimb area (abbreviation: S1_hindlimb_right),

[0044] (10) The secondary somatosensory cortex, right side (abbreviation: S2_right)

[0045] (11) The hypothalamus, right side; posterior nucleus (abbreviation: hypothalamus_right), and

[0046] (12) The anterior midcingulate cortex (abbreviation: aMCC), but not limited to this. Alternatively, the brain regions in which the availability of the indicator substance is altered due to pain can be 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 11 or more, or 12 or more selected from the above (1) to (12). As an option, the brain regions in which the availability of the indicator substance is altered due to pain may be the striatum; caudate putamen, primary somatosensory cortex, secondary somatosensory cortex, and cingulate cortex, but not limited to this.

[0047] The method for measuring pain intensity in a test individual according to the present disclosure includes the following steps: generating a pain template by analyzing the correlation between the indicator substance of pain and the pain intensity in the brain of a reference individual.

[0048] More specifically, the present disclosure relates to a method for determining pain intensity, which includes the following steps:

[0049] Generate a pain template that indicates the correlation between the availability of an indicator substance measured at each pain intensity in at least two or more brain regions of a reference individual and each brain region and each stage of pain intensity; and

[0050] Apply the availability of the indicator substance measured in at least two brain regions of a test individual to the pain template, and select the stage of pain intensity with the highest similarity by analyzing the availability and similarity of the indicator substance at each stage of pain intensity through similarity analysis to determine the pain intensity of the test individual.

[0051] In the present disclosure, in order to objectively measure the level of hyperalgesia caused by pathological pain, first, behavioral responses are used to discover the patterns shown in brain images. The behavioral technique uses the paw withdrawal threshold used by von Frey, which is a measurement technique widely used in patients and animal models. After analyzing the brain image patterns of the paw withdrawal threshold, the corresponding brain image patterns can be established as a standard for comparison. After that, when new brain images are acquired, the brain images are compared with the brain image patterns established as the comparison standard, so that the pain level of an individual can be measured even without a diagnosis such as a paw withdrawal threshold.

[0052] In the present disclosure, an individual can be one or more selected from the group consisting of: rodents, mice, rats, hamsters, guinea pigs, reptiles, amphibians, mammals, canines, felines, rabbitnecks, pigs, cows, sheep, monkeys, primates, non-human mammals, non-human primates, and humans.

[0053] In the present disclosure, a reference individual refers to an individual whose pain intensity is already known, and refers to an individual whose pain intensity has been determined by biological or statistical methods and can be used as a reference. For example, it can be an individual whose paw withdrawal threshold has been measured by von Frey's method, but is not limited thereto. For example, in the present disclosure, a reference individual can cause neuropathic pain in the right hind leg. Alternatively, it can be an individual who has undergone surgery to unilaterally damage a nerve and induce neuropathic pain through surgery, and 15 days later, the paw withdrawal threshold is measured by von Frey's method. The neuropathic pain caused by surgery can reduce the tactile threshold and make it more sensitive to stimuli, but although the treatment is carried out in the same surgical and experimental environment, the degree of threshold reduction varies from person to person. In this way, reference individuals with various pain intensities can be obtained. Alternatively, it can be an individual whose pain intensity has been determined through verbal communication, physical diagnosis, behavioral measurement, etc., but is not limited thereto.

[0054] In the present disclosure, a pain template refers to a template for measuring the availability of an indicator substance in at least two or more regions of the brain of a reference individual that are related to pain, where the reference individual is an individual whose pain intensity has been objectively determined, and the availability of the indicator substance by brain region for each pain stage is shown by using the above.

[0055] More specifically, in the present disclosure, a pain template refers to showing the availability of an indicator substance measured according to the pain intensity in at least two or more brain regions of a reference individual according to the pain intensity and each brain region. For example, in the present disclosure, a pain template can use [11C]ABP688 to measure the availability of mGluR5 in a specific region of the brain of a reference individual, and show the availability of the indicator substance in each specific brain region at the corresponding pain stage by using the above method, but is not limited thereto.

[0056] In the present disclosure, a pain template can divide the pain level into at least more than 10 stages, more than 20 stages, more than 30 stages, more than 40 stages, more than 50 stages, more than 60 stages, more than 70 stages, more than 80 stages, more than 90 stages, more than 100 stages, more than 110 stages, more than 120 stages, more than 130 stages, more than 140 stages, more than 150 stages, more than 160 stages, more than 170 stages, more than 180 stages, more than 190 stages or more than 200 stages. More preferably, it can divide the pain level into at least more than 100 stages. More preferably, the pain level can be divided into at least more than 200 stages.

[0057] In the present disclosure, a pain template can subdivide pain stages by regression analysis. For example, it can be subdivided into 200 pain stages by performing a regression analysis on the availability of an indicator substance measured according to the pain intensity in at least two brain regions of 10 reference individuals. Least squares method can be used to perform the regression analysis, but is not limited thereto.

[0058] The method for measuring the pain intensity of a test individual according to the present disclosure may include: using a pain template obtained from a reference individual to determine the pain intensity of a test individual with an unknown pain intensity. Specifically, the pain intensity of the test individual is determined by the following method: applying the availability of the indicator substance measured in at least two brain regions of the test individual to the pain template, analyzing the availability of the indicator substance and the correlation coefficient for each stage of the pain intensity, selecting the stage of the pain intensity with the highest correlation, and determining the stage of the pain intensity of the test individual. In the present disclosure, the pain intensity of the test individual can be measured by comparing the availability of the indicator substance for each brain region of the test individual with the pain template.

[0059] Specifically, the availability of the indicator substance measured in at least two brain regions of the test individual is compared with each pain intensity in the pain template, and the pain intensity determined to have the highest correlation can be determined as the pain intensity of the test individual. The indicator material is preferably the same as the indicator material of the reference individual used in the step of generating the pain template.

[0060] Specifically, the steps of determining the pain intensity of the test individual using the pain template include: (i) measuring the availability of the indicator substance measured in at least two brain regions of the test individual; (ii) applying the measured availability of the indicator to the pain template to analyze the availability and similarity of the indicator substance at each pain intensity stage; and (iii) selecting the stage of the pain intensity with the highest similarity from the similarity analysis results to determine the pain intensity stage of the test individual.

[0061] For example, through similarity analysis, the matching degree is calculated, thereby calculating the availability of the indicator substance in each brain region measured in the test individual, and the availability of the indicator substance in each brain region at each pain level from 1 to 200 of the pain template. As a result, when it is found that the pain level of 100 stages and the availability of the indicator substance in each brain region are the most matched, this may mean that the pain intensity of the test individual is determined as the 100th stage among the 1 to 200 stages.

[0062] In the similarity analysis, the similarity can be calculated by an algorithm for calculating the degree of similarity. For example, it can be performed by one or more selected from the group consisting of: a method of calculating the degree of correlation using Pearson correlation coefficient analysis, a method of calculating the degree of correlation using Spearman correlation coefficient analysis, a method of calculating similarity using each Euclidean distance on a multi-dimensional coordinate plane, a method of calculating the degree of similarity using Mahalanobis distance, a method of calculating the degree of similarity using support vector, a method of calculating the degree of similarity using cosine distance, a method of calculating the degree of similarity using Manhattan distance, a method of calculating the degree of similarity using Jaccard coefficient, and a method of calculating the degree of similarity using extended Jaccard coefficient, but not limited thereto.

[0063] For example, the Pearson correlation coefficient analysis method can be used to calculate the matching degree between the availability of the indicator substance in each brain region measured in the test individual and the availability of the indicator substance at each pain stage of the pain template. More specifically, the pain stage of the pain template with the value of the correlation coefficient calculated by the following mathematical formula 2 being closest to 1 can be determined as the pain intensity of the test individual.

[0064] The Pearson correlation analysis method is an analysis method used to find the correlation between two variables. The Pearson correlation coefficient of two variables X and Y is a value obtained by dividing the degree to which X and Y change together by the degrees to which X and Y change respectively. The Pearson correlation coefficient can be calculated by the following mathematical formula 1.

[0065] [Mathematical formula 1]

[0066]

[0067] Wherein, represents the sample mean of variable X, represents the sample mean of variable Y, s x represents the standard deviation of variable X, and s y represents the standard deviation of variable Y. Mathematical formula 1 can be summarized as the following mathematical formula 2.

[0068] [Mathematical formula 2]

[0069]

[0070] In Mathematical formulas 1 and 2, the variable X is a standardized value obtained by dividing the availability of the indicator substance measured in n regions of interest (ROIs) of the brain of the test individual by the average value of each region.

[0071] In Mathematical formulas 1 and 2, the variable Y is the availability of the indicator substance at any pain stage of the pain template.

[0072] More specifically, the variable X is a standardized value obtained by measuring the availability of the indicator substance in n brain regions of the test individual and then dividing it by the average availability of the indicator substance in each brain region obtained from multiple control individuals. That is to say, the variable X is the standardized availability of the indicator substance measured in n brain regions of the test individual, is the average of the standardized values of the availability of the indicator substance measured in n brain regions of the test individual. In other words, the variable X is the data of the test subject, which is shown as a red square in the upper part of, for example, Figure 5a which shows an example of the variable X.

[0073] More specifically, the variable Y is the availability of an indicator substance measured in n brain regions during a pain phase of a pain template. That is, the variable Y is the availability of the indicator substance in each of the n brain regions during any pain phase of the pain template. For example, if the pain template is subdivided into pain intensities of 1 to 200 phases, it means the availability of the indicator substance in each brain region under any one phase of the pain intensity. More specifically, when the paw withdrawal threshold is in the range of 0 to 4 g, that is, the pain intensity is subdivided into 200 phases to generate a pain template, such that each phase has a range of 0.02 g, the variable Y represents the value of the indicator substance in the n brain regions within a range of 0.02 g in any phase of the pain template. In other words, the variable Y is a value extracted from any phase included in the pain template generated from a reference individual. For example, Figure 5a The lower part of

[0074] Reference Figure 5a , it can be seen that for each of the 200 phases, the following task is repeatedly calculated: calculating whether the data of a test individual (variable X) has a certain degree of correlation coefficient with the value of a phase of the pain template (variable Y), and displaying the result.

[0075] Another embodiment of the present disclosure relates to a pain template that represents the correlation between the availability of an indicator substance measured in at least two brain regions of a reference individual and the pain intensity induced in the reference individual.

[0076] The pain intensity can be divided into at least more than 10 phases, more than 50 phases, more than 100 phases, or more than 200 phases.

[0077] Another embodiment of the present disclosure relates to a method for generating a pain template, the method comprising the steps of: inducing artificial pain in a reference individual; measuring the availability level of an indicator in at least two brain regions of the reference individual in which pain has been induced; and generating a pain template indicating the correlation between the pain intensity artificially induced in the reference individual and the availability level of the indicator substance in each brain region.

[0078] The method for generating a pain template may further comprise the steps of: normalizing by dividing the measured availability level of the indicator substance in each of at least two or more brain regions by the average of the availability levels of the indicator substance in each brain region obtained in a control group in which no pain has been induced; and using the normalized values to subdivide the pain intensity.

[0079] Another embodiment of the present disclosure relates to a method for generating a pain template, the method comprising the steps of: inducing artificial pain in a reference individual and selecting brain regions and indicator substances that are meaningful for pain; measuring the availability levels of the indicator in at least two selected brain regions of the reference individual with induced pain; in a control group without induced pain, measuring the availability of the indicator substance in brain regions corresponding to the brain regions in which the availability of the indicator substance was measured in each reference individual with induced pain; dividing the availability level of the indicator substance in each brain region of the reference individual by the availability level of the indicator substance in the corresponding brain region of the control group to standardize it; then using the values of the standardized availability levels to divide the pain intensity into two or more stages and obtaining a pain template, wherein the availability levels of the indicator substance are plotted to correspond to each stage of the divided pain intensity.

[0080] The availability level of the indicator substance in each brain region of the control group can be the average of the availability levels of the indicator substance in each brain region measured in at least two or more control groups.

[0081] Another embodiment of the present disclosure relates to a method for measuring the pain intensity of a test individual, which comprises comparing the availability of the indicator substance measured in at least two brain regions of the test individual with each pain stage of the pain template.

[0082] Another embodiment of the present disclosure relates to a method for measuring the pain intensity of a test individual, the method comprising the steps of: inducing artificial pain in a reference individual, and selecting brain regions and an indicator substance that are meaningful for pain; measuring the availability level of the indicator in at least two selected brain regions of the reference individual with induced pain; in a control group without induced pain, measuring the availability of the indicator substance in the brain regions corresponding to each of the brain regions where the availability level of the indicator substance was measured in the reference individual with induced pain; dividing the availability level of the indicator substance in each brain region of the reference individual by the availability level of the indicator substance in the corresponding brain region of the control group to standardize it; then using the values of the standardized availability levels to divide the pain intensity into two or more stages and obtaining a pain template, wherein the availability levels of the indicator substance are plotted to correspond to each stage of the divided pain intensity; in the brain regions of the test individual corresponding to the brain regions where the availability level of the indicator substance was measured in the reference individual using the selected brain regions and indicator substance, measuring and standardizing the availability level of the indicator substance in the brain regions of the test individual; comparing the measured availability level of the indicator substance of the test individual with the availability levels of the indicator substance at each stage of the pain intensity in the pain template through similarity analysis; determining the stage of the pain intensity in the pain template where the availability level of the indicator substance has the highest similarity in the comparison step as the pain intensity stage of the test individual.

[0083] The availability level of the indicator substance in each brain region of the control group can be the average of the availability levels of the indicator substance in each brain region measured in at least two or more control groups.

[0084] The comparison step can be performed through similarity analysis.

[0085] The method for measuring the pain intensity of a test individual can further comprise the step of: determining the stage of the pain intensity in the pain template with the highest similarity in the comparison step as the stage of the pain intensity of the test individual.

[0086] Beneficial effects

[0087] When generating a pain template as a comparison standard according to the embodiments of the present disclosure, it is sufficient to measure only the expression pattern of the indicator substance in the test individual to diagnose pain in a test individual with unknown pain intensity, and there is no need to communicate verbally, perform a physical diagnosis, or measure behavior with the test individual to determine the pain level. There is no need to deliberately induce pain by applying external stimuli to the test individual. Description of the drawings

[0088] Figure 1aShows the distribution of paw withdrawal thresholds measured using von Frey on day 15 after SNL surgery in 103 mice.

[0089] Figure 1b Shows the distribution of paw withdrawal thresholds in 10 selected mice in which neuropathic pain was successfully induced.

[0090] Figures 2a to 2d Shows regions negatively correlated with paw withdrawal threshold in regions showing pain-related significance in the brain area.

[0091] Figures 3a to 3f Shows regions positively correlated with paw withdrawal threshold in regions showing pain-related significance in the brain area.

[0092] Figure 4a Shows the mGluR5 values of each brain region of SNL individuals.

[0093] Figure 4b Shows the mGluR5 values of each brain region of individuals in the sham surgery group.

[0094] Figure 4c Shows that normalization is performed by dividing the mGluR5 value of each brain region of SNL individuals by the average value of each region.

[0095] Figure 4d Shows that normalization is performed by dividing the mGluR5 value of each brain region of individuals in the sham surgery group by the average value of each region.

[0096] Figure 4e Shows a pain template that shows the mGluR5 pattern in the brain of pain groups according to pain levels.

[0097] Figure 5a Shows the task of comparing the mGluR5 information in the brain of SNL 1 with the pain template.

[0098] Figure 5b Shows the process of calculating the correlation coefficient of the pattern of each experimental animal in the pain group for the pain template.

[0099] Figure 6a Shows the r values of the pattern of mGluR5 values of SNL individuals and the pattern of the pain template.

[0100] Figure 6b Shows the p value of the pattern of mGluR5 values of SNL individuals and the pattern of the pain template.

[0101] Figure 6c Shows the inverse estimation of the original paw withdrawal threshold of experimental animals by highly correlated coefficients.

[0102] Figure 6d Shows the r values of the pattern of mGluR5 values and the pattern of pain templates for Sham individuals.

[0103] Figure 6e Shows the p values of the pattern of mGluR5 values and the pattern of pain templates for Sham individuals.

[0104] Figure 6f Is a graph showing the sensitivity and specificity according to the r value. Detailed Description

[0105] Hereinafter, the present disclosure will be described in more detail by way of examples. However, this description is for illustrative purposes only, and the scope of the present disclosure is not limited thereto.

[0106] Example 1: Preparation of Reference Individuals by Constructing a Pain Model

[0107] To measure the pain level of patients or experimental animals (hereinafter referred to as "individuals") suffering from neuropathic pain, the paw withdrawal threshold to von Frey stimulation was measured. Individuals in which pain was induced in spinal nerve ligation (hereinafter referred to as "SNL") had different pain degrees according to the individual.

[0108] Eight-week-old male Sprague-Dawley rats (Samtako, Seoul) were anesthetized with isoflurane, and the right L5 spinal nerve was ligated (SNL), and the control group was sham-operated.

[0109] In the SNL surgery group, the right L5 spinal nerve was isolated and tightly ligated with 5-0 silk to induce neuropathic pain. In the sham surgery group as the control group, the L5 spinal nerve was isolated but not ligated.

[0110] The paw withdrawal threshold of the right hind leg was measured using von Frey before the upcoming surgery and on days 1, 5, 9, and 15 after the surgery. Animals with abnormal motor neuropathy after the surgery were excluded from the analysis.

[0111] Figure 1a Shows the distribution of the paw withdrawal threshold measured using von Frey on the 15th day after SNL surgery in 103 mice. When the paw withdrawal threshold of the mouse ( Figure 1a on the y-axis) is small, it is sensitive even to small stimuli. It can be concluded that when the paw withdrawal threshold is reduced to less than half compared to before the surgery, neuropathic pain can be successfully induced. Ten mice in which neuropathic pain was successfully induced were selected, and the selected mice are shown in red in Figure 1a . The paw withdrawal thresholds of the selected mice are shown in Figure 1b , and PET scans were performed on these mice. Figure 1bShows the distribution of the paw withdrawal thresholds of 10 selected mice in which neuropathic pain was successfully induced.

[0112] Example 2: Determination of the indicator substance

[0113] Measure the metabotropic glutamate receptor 5 (hereinafter referred to as "mGluR5") in the brain of the pain model of the reference individual. To measure this substance, [11C]ABP688 was used, which is a tracer with the radioactive isotope [11C] attached to ABP688, and ABP688 is a chemical substance that specifically binds to mGluR5. The signal of the PET image can be converted into non-displaceable binding potential information using a simplified reference tissue model, and this information indicates the availability of mGluR5 in each coordinate space. Specifically, the pain model was anesthetized with isoflurane, and [11C]ABP688 (5.05 - 16.15 MBq / 100 g) was injected into the tail vein. Brain images were acquired for 60 minutes in list mode using a microPET / CT scanner (eXplore VISTA, GE Healthcare). The mGluR5 binding potential (non-displaceable binding potential, BPND) of [11C]ABP688 was calculated using a simplified reference tissue model with the cerebellum as the reference region. All [11C]ABP688 BPND images were averaged to create a brain mGluR5 standard image, and then all BPND images were spatially normalized to the brain mGluR5 standard image. The 3D voxels were resampled to 0.2 * 0.2 * 0.2 mm and smoothed using a 0.8 mm full width at half maximum Gaussian filter. The images were processed using SPM8, the MarsBaR toolbox, and the imgsrtm program of the Turku PET Center.

[0114] Example 3: Generation of a pain template

[0115] 3-1: Search for brain regions involved in pain

[0116] Based on the experimental data of the pain levels measured in Examples 1 and 2, a regression analysis was performed on the mGluR5 availability information in the brain obtained by [11C]ABP688-PET.

[0117] Specifically, in order to search for the correlation between the mGluR5 level in the brain and the paw withdrawal threshold, a 3D voxel (volume element) regression analysis was performed using the data from the animals in the SNL group. Through the regression analysis, clusters of more than 20 voxels that were statistically significantly correlated (p-value < 0.005) with the paw withdrawal threshold were screened out. According to the anatomical location of the clusters, each spherical region with a radius of 0.5 mm was set as the region of interest (ROI), and the BPND was extracted from each ROI using the MarsBaR toolbox.

[0118] As a result, significant correlations were found in several brain regions involved in pain. To visualize the brain regions showing significance, these regions were superimposed on MRI images and are shown in Figures 2a to 2d and Figures 3a to 3f .

[0119] Figures 2a to 2d is the region showing a negative correlation with the paw withdrawal threshold, Figures 3a to 3f is the region showing a positive interaction with the paw withdrawal threshold. In the graphs below each brain region image, the mGluR5 values in the ROI (region of interest) are shown on the x-axis, while the paw withdrawal threshold (representing the pain level of the experimental animals) is shown on the y-axis.

[0120] 3-2: Determine the pain template

[0121] Regions of the same size are defined for each coordinate, and the mGluR5 values are extracted and shown in Figure 4. In Figure 4, SNL 1 to SNL 10 are the identification numbers of each experimental animal. SNL 1 has a high paw withdrawal threshold, while SNL 10 has a low paw withdrawal threshold. That is, it can be seen that SNL 1 has a relatively weak insensitive pain level among the 10 pain groups, while SNL 10 is the most sensitive with the most severe pain level.

[0122] The y-axis represents each experimental animal individual from SNL 1 to SNL 10, and the x-axis represents the brain regions that are statistically significantly correlated with the paw withdrawal threshold in the above analysis. The mGluR5 values in each region have different distributions in each brain region ( Figure 4a ). Therefore, normalization is performed by dividing the mGluR5 value of each region of an individual by the average value of each region, as Figure 4c shown. The average value of each region is calculated based on the data obtained from the pain-free control group (sham operation group). The normalized mGluR5 levels in each brain region are regressed against the paw withdrawal threshold.

[0123] More specifically, if the n paw withdrawal thresholds obtained from n reference individuals are regarded as the independent variable x, and the n mGluR5 values extracted and normalized from any ROI are set as the dependent variable y, the mGluR5 value of the region of interest can be represented by the following mathematical formula 3.

[0124] [Mathematical formula 3]

[0125] y = β 0 + β 1 x + ε

[0126] In mathematical formula 3, β 0 is the y-axis intercept, β 1is the regression coefficient (the slope of the linear equation), and ε is the error. The relevant expression of y = β 0 + β 1 x is obtained through regression analysis, and the mGluR5 value in the region of interest is predicted accordingly.

[0127] First, regression analysis using the least squares method is performed as follows, and the regression coefficient β 1 .

[0128] [Mathematical formula 4]

[0129]

[0130] where represents the mean value of the independent variable x (the paw withdrawal threshold), and y represents the mean value of the dependent variable y (the mGluR5 value extracted from and normalized in a region of interest).

[0131] Based on the above results, the y-intercept β 0 can be estimated.

[0132] [Mathematical formula 5]

[0133]

[0134] Using the obtained relational expression y = β 0 + β 1 x, the mGluR5 value of the region of interest is estimated and displayed in a column.

[0135] In each region of interest, the regression analysis described above is performed separately, and then the estimated values obtained in each region are displayed in each column ( Figure 4e ).

[0136] As Figure 4e shown, through the above regression analysis, the pain stages within the paw withdrawal threshold range of 0 to 4 g are divided into 200 stages, and the mGluR5 availability in each ROI obtained through regression analysis is displayed in 200 rows in each column. In this way, the rows of the regression mGluR5 template represent the ideal mGluR5 patterns of virtual SNL individuals with corresponding paw withdrawal thresholds. This makes it possible to estimate the mGluR5 pattern in the brain of a virtual individual with the corresponding paw withdrawal threshold (pain level) ( Figure 4e ). That is, Figure 4e the figure shown is calculated based on Figure 4c , shows the mGluR5 pattern in the brain of the pain group according to the pain level, and is used as a reference for comparison to determine whether there is future neuropathic pain and the degree of pain.

[0137] Call this comparison criterion the future "pain template". The data of the pain-free control group are shown in Figure Figure 4b and 4d . In the control group, no pattern can be seen from the pain group.

[0138] Example 4: Objectively measuring pain using the pain template

[0139] 4-1: Validation of the pain template

[0140] When using the pain template and giving the mGluR5 information in the brain, by comparing which part of the pain template this information matches, the presence or absence of pain and the pain level can be determined. For example, in Figure 5a is shown the task of comparing the mGluR5 information in the brain of experimental animal No. 1 (SNL1) within the pain group with the pain template.

[0141] Since the pain template is estimated based on the actual information of experimental animals 1 to 10, the pattern of SNL 1 will match the pattern in the top row of the pain template. Each row of the SNL 1 pattern was compared to see if it also showed a certain degree of correlation with the pain template. The paw withdrawal threshold of SNL 1 was 3.86 g. Figure 5a Shows the process of calculating the Pearson correlation coefficient and displaying it in red as the correlation coefficient increases. The row represented by the red square is the mGluR5 pattern of SNL 1, and this row is compared one by one with each row of the pain template shown at the bottom. The correlation coefficient of each row is shown in color in the lower left corner.

[0142] Repeat this for each experimental animal (SNL 1 to SNL 10), and it can be graphically represented whether each experimental animal matches each row of the pain template to some extent. In Figure 5b is shown the process of calculating the correlation coefficient that each experimental animal pattern has for the pain template.

[0143] 4-2: Objective measurement of pain using the pain template

[0144] Through the same process as in Example 4-1, the degree to which the pattern of the standardized mGluR5 value of each individual is similar to the pattern of the reference individual (pain template) can be calculated. Several methods can be used for the calculation, but here, the similarity is calculated by the Pearson correlation coefficient analysis method.

[0145] The Pearson correlation analysis method is an analysis method for finding the correlation between two variables. The Pearson correlation coefficient of two variables X and Y is a value obtained by dividing the degree to which X and Y change together by the degree to which X and Y change separately. The calculation method of the sample correlation coefficient is as follows.

[0146] [Mathematical formula 1]

[0147]

[0148] Wherein, represents the sample mean of variable X, represents the sample mean of variable Y, s x represents the standard deviation of variable X, and s y represents the standard deviation of variable Y. The above mathematical formula can be summarized as follows.

[0149] [Mathematical formula 2]

[0150]

[0151] In Mathematical formulas 1 and 2, variable X is a standardized value obtained by dividing the availability of the indicator substance measured in n regions of interest (ROIs) of the brain of a test individual by the average value of each region. More specifically, variable X is a standardized value obtained by the following method: measuring the availability of the indicator substance in n brain regions of a test individual, and then dividing it by the average value of the availability of the indicator substance in each region obtained from multiple control individuals. That is to say, variable X is the standardized availability of the indicator substance measured in n brain regions of a test individual, is the average value of the standardized availability of the indicator substance measured in n brain regions of a test individual. In other words, variable X is the data of the test subject, which is shown as a red square in the upper part of, for example, Figure 5a showing an example of variable X.

[0152] In Mathematical formulas 1 and 2, variable Y is the availability of the indicator substance at any pain stage of the pain template. More specifically, variable Y is the availability of the indicator substance measured in n brain regions at one pain stage of the pain template. That is, variable Y is the availability of the indicator substance in each of n brain regions at any one pain stage of the pain template. For example, if the pain template is subdivided into pain intensities from 1 to 200 stages, it represents the availability of the indicator substance in each brain region at the pain intensity of any one stage. More specifically, when the paw withdrawal threshold is in the range of 0 to 4, that is, the pain intensity is subdivided into 200 stages to generate a pain template, so that each stage has a range of 0.02 g, variable Y represents the value of the indicator substance in n brain regions within a range of 0.02 g for any pain template. In other words, variable Y is a value extracted from any one stage included in the pain template generated from reference individuals. For example, Figure 5a the lower part of shows a plurality of black squares, showing examples of variable Y.

[0153] Here, it is assumed that the data of any individual actually observed (test individual) is assigned to variable X, and the data of one of the 200 rows in the pain template is assigned to variable Y. By comparing the correlation coefficients of these two variables, the mGluR5 availability pattern in the brain extracted from n ROIs of a given individual can be compared with the pattern in a row of the corresponding pain template. The value of the Pearson correlation coefficient r is between -1 and 1. As the correlation coefficient r approaches 1, the two variables can have a stronger positive correlation (i.e., the higher the similarity). By repeating this analysis for the 200 rows of the pain template, it can be calculated whether the mGluR5 expression pattern possessed by any individual is most similar to any row of the pain template. Reference Figure 5a It can be seen that for each of the 200 phases, the task of repeatedly calculating how the data of a test individual (variable X) is correlated with the values of the pain template phase (variable Y) in a certain degree is performed, and the results are shown. Here, since the 0 to 4 g range of the paw withdrawal threshold is divided by the 200 - row pain template and created and used, the range of one row of the pain template is 0.02 g. The r - values that an individual has for each of the 200 rows of the pain template are represented by a column, and the higher 25% r - value range in a column is used to estimate the paw withdrawal threshold within a 1 g range.

[0154] When the patterns of 10 individuals in the SNL group are compared with the 200 rows of each pain template through correlation coefficient analysis, it is confirmed that all individuals are exactly matched with the patterns of certain rows existing in the pain template, which is well confirmed by the r - values and p - values of the correlation coefficient ( Figure 6a and 6b ). Additionally, through a high correlation coefficient, the original paw withdrawal threshold of the experimental animals can be successfully back - inferred ( Figure 6c ).

[0155] 4-3: Comparison with the control group

[0156] To confirm whether this method can successfully distinguish only the pain group, this time, the mGluR5 patterns in the brains of the pain - free sham - operated group were compared with the patterns of the pain template.

[0157] As a result, different from the pain group, the patterns of the control group do not exactly match the pain template. The r - values of the correlation coefficient are generally low. The p - values of the correlation coefficient also cannot guarantee statistical significance ( Figure 6d , 6e and 6f). The presence or absence of pain can be predicted by classifying the matching degree criteria through the correlation coefficient ( Figure 6f ).

Claims

1. A method for determining pain intensity, which comprises the following steps: generating a pain template by using the availability of an indicator substance measured in two or more brain regions of a reference individual having pain in stages of 50 or more pain intensities, which indicates the correlation between the availability of the indicator substance in two or more brain regions and the stages of 50 or more pain intensities; and applying the availability of the indicator substance measured in the two or more brain regions of a test individual to the pain template to perform a similarity analysis of the availability of the test individual and the availability of the stages of two or more pain intensities in the pain template; determining the stage of pain intensity of the test individual by selecting a stage of pain intensity from the pain template, wherein the stage of pain intensity from the pain template corresponds to the availability having the highest similarity to the availability of the test individual, wherein the indicator substance is metabotropic glutamate receptor 5 (mGluR5), wherein the two or more brain regions are: (1) the rostral caudate nucleus of the striatum, left side, (2) the caudal caudate nucleus of the striatum, left side, (3) the insular cortex, left side, (4) the secondary somatosensory cortex, left side, (5) the hippocampus, right side; rostral, (6) the hippocampus, right side; caudal, (7) the primary somatosensory cortex, left side; trunk area, (8) the primary somatosensory cortex, right side; trunk area, (9) the primary somatosensory cortex, right side; hindlimb area, (10) the secondary somatosensory cortex, right side, (11) the hypothalamus, right side; posterior nucleus, and (12) the anterior midcingulate cortex.

2. The method according to claim 1, wherein, the two or more brain regions are regions where the availability of the indicator substance is changed due to pain.

3. The method according to claim 1, wherein, the pain template is generated by the following steps: performing a standardization step by dividing the availability of the indicator substance in two or more brain regions by the average value of the availability of the indicator substance in each brain region; and subdividing the steps of the pain intensity by regression analysis of the standardized values, and wherein the average value of the availability of the indicator substance in each brain region is the average value of the availability of the indicator substance in each brain region obtained from a painless control group.

4. The method according to claim 1, wherein, the similarity analysis is performed by one or more analysis methods selected from the group consisting of: Pearson correlation coefficient analysis, Spearman correlation coefficient analysis, Euclidean distance analysis, Mahalanobis distance analysis, support vector analysis, cosine distance analysis, Manhattan distance analysis, Jaccard coefficient analysis, and extended Jaccard coefficient analysis.

5. The method according to claim 4, wherein, the Pearson correlation coefficient analysis is performed by the following mathematical formula 2, and the similarity evaluation is the degree when the r value calculated by the mathematical formula 2 is close to 1, [Mathematical formula 2] X: The standardized availability of the indicator substance measured in the brain region of the test individual Y: Availability of the indicator substance in any pain phase of the pain template Sample mean of X Sample mean value of Y n: Number of brain regions.

6. The method according to claim 1, wherein, the availability of the indicator substance is measured by using a radioisotope tracer specific to the indicator substance.

7. The method according to claim 6, wherein, the radioisotope tracer is [11C]ABP688.

8. The method according to claim 1, wherein, the availability of the indicator substance measured according to pain intensity is obtained by using reference individuals of 10 or more individuals.

9. The method according to claim 1, wherein, the reference individuals have induced neuropathic pain in the right hind leg.

10. A method for generating a pain template, which comprises the following steps: inducing artificial pain in a reference individual and selecting two or more brain regions and an indicator that are meaningful for pain; measuring the availability level of the indicator substance in two or more selected brain regions of the reference individual with induced pain; in a control group without induced pain, measuring the availability level of the indicator substance in the brain regions corresponding to each of the two or more brain regions where the availability level of the indicator substance was measured in the reference individual with induced pain; normalizing the availability level of the indicator substance in the two or more brain regions of the reference individual by dividing by the availability level of the indicator substance in the two or more brain regions of the corresponding control group; and using the values of the normalized availability levels to divide the pain intensity into 50 or more phases and obtaining a pain template, wherein for each phase of the divided pain intensity, the availability level of the indicator substance is plotted, wherein the indicator substance is metabotropic glutamate receptor 5 (mGluR5), wherein the two or more brain regions are: (1) Rostral caudate putamen of the striatum, left, (2) Caudal caudate putamen of the striatum, left, (3) Insular cortex, left, (4) Secondary somatosensory cortex, left, (5) Hippocampus, right; rostral, (6) Hippocampus, right; caudal, (7) Primary somatosensory cortex, left; trunk region, (8) Primary somatosensory cortex, right; trunk region, (9) Primary somatosensory cortex, right; hindlimb region, (10) Secondary somatosensory cortex, right, (11) Hypothalamus, right; posterior nucleus, and (12) Anterior midcingulate cortex.

11. The method according to claim 10, wherein, the availability level of the indicator substance in each brain region of the control group is the average of the availability levels of the indicator substance in each brain region measured in two or more control groups.

12. A method for measuring the pain intensity of a test individual, which comprises the following steps: inducing artificial pain in a reference individual and selecting two or more brain regions and an indicator substance that are meaningful for pain; measuring the availability level of the indicator substance in two or more selected brain regions of the reference individual with induced pain; In a control group without induced pain, the availability level of the indicator substance in brain regions corresponding to each of two or more brain regions in a reference individual with induced pain is measured; The availability level of the indicator substance in two or more brain regions of the reference individual is normalized by dividing by the availability level of the indicator substance in two or more brain regions of the corresponding control group; The pain intensity is divided into 50 or more stages using the values of the normalized availability levels, and a pain template is obtained, wherein for each stage of the divided pain intensity, the availability level of the indicator substance is plotted; By using the selected brain regions and the indicator substance, the availability level of the indicator substance in the brain regions of a test individual is measured and normalized, the brain regions corresponding to the brain regions in which the availability level of the indicator substance was measured in the reference individual; By similarity analysis, the measured availability level of the indicator substance in the test individual is compared with the availability level of the indicator substance at each stage of pain intensity in the pain template; and The pain intensity stage in which the availability level of the indicator substance has the highest similarity in the pain template in the comparison step is determined as the pain intensity stage of the test individual, wherein the indicator substance is metabotropic glutamate receptor 5 (mGluR5), wherein the two or more brain regions are: (1) the rostral caudate nucleus of the striatum, left side, (2) the caudal caudate nucleus of the striatum, left side, (3) the insular cortex, left side, (4) the secondary somatosensory cortex, left side, (5) the hippocampus, right side; rostral, (6) the hippocampus, right side; caudal, (7) the primary somatosensory cortex, left side; trunk area, (8) the primary somatosensory cortex, right side; trunk area, (9) the primary somatosensory cortex, right side; hindlimb area, (10) the secondary somatosensory cortex, right side, (11) the hypothalamus, right side; posterior nucleus, and (12) the anterior midcingulate cortex.

13. The method according to claim 12, wherein, the availability level of the indicator substance in each brain region of the control group is the average of the availability levels of the indicator substance in each brain region measured in two or more control groups.

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