Microcirculation and bioelectricity joint detection-based pterygium grading method

Abstract

The invention relates to the technical field of ophthalmic lesion analysis and evaluation, in particular to a microcirculation and bioelectricity joint detection-based pterygium grading method, which comprises the following steps of S1, microcirculation parameter acquisition; s2, a bioelectricity parameter acquisition step; s3, an activity comprehensive index calculation step; and S4, a grading step. The invention discloses a pterygium grading method based on microcirculation and bioelectricity combined detection, and aims to establish a grading method capable of objectively and quantitatively evaluating the biological activity of pterygium so as to overcome the limitation of subjective evaluation only by morphological observation in the prior art. Therefore, a reliable biological basis is provided for clinical diagnosis, operation opportunity selection and prognosis judgment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ophthalmic lesion analysis and evaluation, and particularly relates to a pterygium grading method based on microcirculation and bioelectricity combined detection. BACKGROUND

[0002] Pterygium is a common ocular surface proliferative disease characterized by the invasive growth of conjunctival tissue and underlying fibrovascular tissue onto the corneal surface. This disease not only affects the appearance of patients, but also can cause corneal astigmatism and even block the pupil area during the progression, thereby causing serious damage to vision. The management of pterygium in clinic, especially the selection of surgical timing and the assessment of postoperative recurrence risk, is an important issue faced by ophthalmologists.

[0003] Currently, the evaluation of pterygium biological activity, i.e., determining whether it is in the stationary phase or the progressive phase, largely depends on the subjective observation and morphological assessment of clinicians. Doctors usually observe under a slit lamp microscope and make judgments based on morphological characteristics of pterygium, such as the range of corneal invasion, the thickness of the tissue (or "hypertrophy degree"), and the degree of surface vascular congestion. For example, a pterygium with bright red color, thick body and obvious neovascularization in the head is usually subjectively considered to be "active" or "progressive"; on the contrary, a pterygium with light color, flat tissue and not obvious blood vessels may be judged to be "stationary". Although this evaluation method is widely used in clinical practice, it has inherent and difficult-to-overcome defects.

[0004] Firstly, this evaluation method has significant subjectivity. Different doctors may have different understanding and judgment standards for descriptive words such as "hypertrophy" and "congestion", resulting in lack of consistency and repeatability of the evaluation results between different observers or even the same observer at different time points. Secondly, the traditional morphological evaluation is essentially a static observation, which can only reflect the appearance state of pterygium at a certain time point, but cannot reveal the underlying and dynamic biological processes. The blood perfusion level and cell metabolic activity of the tissue are key factors determining its growth potential, but these information cannot be directly obtained by naked eye observation. Therefore, relying solely on static morphology to predict the future growth rate of pterygium or the possibility of postoperative recurrence has limited accuracy. It is often seen in clinic that pterygium which looks "stationary" by appearance progresses rapidly in a short period of time, or pterygium which is "active" in morphology does not recur after surgery, which fully illustrates the insufficient prediction ability of the existing evaluation method.

[0005] In order to improve the objectivity of the evaluation, there are attempts to use imaging techniques such as anterior segment optical coherence tomography (AS-OCT) to quantify the thickness of pterygium, but this is still limited to the morphological category and fails to touch the biological activity core of the lesion tissue. Therefore, there is an urgent need in the art for a new method that can overcome the limitations of traditional morphological observation, objectively and quantitatively evaluate the internal activity of pterygium from the perspective of biological function, and integrate key biological information reflecting the proliferation and metabolic state of the tissue, thereby providing a more reliable tool for clinicians to accurately judge the progression risk of pterygium and scientifically develop individualized treatment plans including surgical timing, surgical selection and postoperative adjuvant therapy. SUMMARY

[0006] In order to solve the problems existing in the prior art as much as possible, the present application provides a pterygium grading method based on microcirculation and bioelectricity combined detection, aiming to establish a grading method that can objectively and quantitatively evaluate the biological activity of pterygium, to overcome the limitations of subjective evaluation by morphological observation in the prior art, and to provide reliable biological basis for clinical diagnosis, surgical timing selection and prognosis.

[0007] The present application discloses a pterygium grading method based on microcirculation and bioelectricity combined detection, comprising the following steps:

[0008] S1, microcirculation parameter acquisition step: acquiring the microcirculation parameters of the pterygium area to be measured and the normal bulbar conjunctiva control area of the same eye, the microcirculation parameters at least including vascular density (VD) and blood flow index (FI);

[0009] S2, bioelectricity parameter acquisition step: measuring the bioelectricity parameters of the pterygium area and the normal bulbar conjunctiva control area, the bioelectricity parameters being the resting transmembrane potential difference (RPD) relative to the same reference electrode;

[0010] S3, activity comprehensive index calculation step: based on the microcirculation parameters acquired in the step S1 and the bioelectricity parameters acquired in the step S2, the activity comprehensive index (PAI) of pterygium is calculated through a preset weighting model, wherein the calculation of the activity comprehensive index (PAI) includes the process of comparing and integrating the vascular density (VD), the blood flow index (FI) and the resting transmembrane potential difference (RPD) of the pterygium area and the normal bulbar conjunctiva control area;

[0011] S4, grading step: according to the numerical value of the activity comprehensive index (PAI) calculated in the step S3, the pterygium is divided into at least two biological activity grades.

[0012] Specifically, the technical scheme of the present application first acquires microcirculation parameters through the S1 microcirculation parameter acquisition step, uses non-invasive imaging techniques such as anterior segment optical coherence tomography blood flow imaging (OCTA), and respectively detects the pterygium lesion area of the patient's eye and the normal conjunctiva control area in the same affected eye that is not affected, to obtain quantitative data reflecting the blood perfusion state of the tissue, i.e., vascular density (VD) and blood flow index (FI). The key to this step is to collect normal tissue in the same affected eye as a control, establishing a personalized, endogenous reference for subsequent comparative analysis, thereby effectively eliminating the interference caused by individual physiological differences. Next, in the S2 biological electric parameter acquisition step, a micro contact electrode probe is used to measure the aforementioned pterygium area and normal conjunctiva control area after topical anesthesia of the ocular surface, and record the resting transmembrane potential difference (RPD) of the two areas relative to the same external reference electrode (such as placed on the earlobe or forehead). The resting transmembrane potential difference is the difference between the intramembrane and extramembrane potentials in the resting state of the cell, and its change can indirectly reflect the metabolic activity and ion exchange activity of the tissue cells. Therefore, the change in the potential difference between the pterygium area and the normal area reveals the pathological changes in the electrophysiological level.

[0013] The above two steps complete the objective data acquisition of the pterygium tissue state from two different dimensions of hemodynamics and electrophysiology. Subsequently, the method enters the core S3 activity comprehensive index calculation step. In this step, instead of simply listing the measured parameters, a pre-set weighted model is used to deeply integrate the microcirculation parameters obtained in S1 and the biological electric parameters obtained in S2. The integration process includes a key comparison step, i.e., comparing (e.g., calculating the ratio) the vascular density (VD pterygium ) and blood flow index (FI pterygium ) of the pterygium area with the corresponding values (VD normal , FI normal ) of the normal control area, and comparing the resting transmembrane potential difference (RPD pterygium ) of the pterygium area with the potential (RPD normal) are compared (e.g. the absolute value of the difference is calculated). These normalized relative change values are then put into a weighted linear model to calculate a single, quantitative activity composite index (PAI). This index reflects the degree of vascular proliferation, the level of blood perfusion and the metabolic activity of the pterygium relative to normal tissue. Finally, in the S4 classification step, the specific value of the activity composite index (PAI) calculated in S3 is compared to a threshold value that has been established in advance through large sample clinical studies, thereby objectively classifying the pterygium into at least two biological activity levels, such as "quiescent" or "progressive", etc. Throughout the process, S1 and S2 are the data basis, S3 is the core of data fusion and quantification, and S4 is the conversion of the quantification results into a classification conclusion with clear clinical guidance significance. Each step is linked together, and together they form a complete objective evaluation system.

[0014] Further, in step S1, the pterygium area and the normal conjunctival control area are scanned by using an optical coherence tomography angiography (OCTA) technique or a laser speckle flow imaging (LSCI) technique to obtain the microcirculation parameters. That is, the microcirculation parameter obtaining step (S1) is implemented by using the optical coherence tomography angiography (OCTA) technique or the laser speckle flow imaging (LSCI) technique. It needs to be particularly pointed out that the OCTA and the LSCI are not new technologies created by the present application, but two non-invasive examination methods that have been mature and widely used in the current ophthalmic clinical diagnosis field, and the present application is an innovative application on this basis. Specifically, the optical coherence tomography angiography (OCTA) is a high-resolution fundus and anterior segment blood vessel imaging technology. Its basic principle is similar to "optical ultrasound", which uses low-coherence near-infrared light harmless to the human body to perform high-speed, layer-by-layer scanning on the eye tissue. By comparing the tomographic images of the same position obtained continuously in a very short time, the system can identify the signal changes caused by the flow of red blood cells in the blood. The reflection signals of static tissues such as the retinal nerve layer remain stable, while the red blood cells flowing in the blood vessels will cause fluctuations in the signals. Through special algorithms such as frequency amplitude decorrelation algorithm, the OCTA can clearly construct the three-dimensional microvascular network morphology of the retina, choroid and other parts of the present application concerned, such as the conjunctiva and the superficial layer of the sclera, without the need for injection of contrast medium. In the present application, the OCTA device is used to scan the pterygium and the normal conjunctival area adjacent thereto, so that the total length of blood vessels per unit area or the blood vessel coverage area can be directly and accurately calculated, thereby obtaining the quantitative vascular density (VD) parameter. On the other hand, the laser speckle flow imaging (LSCI) is another mature technology that has been used in clinical practice to evaluate the blood perfusion of tissue surface. Its technical principle is based on the speckle phenomenon in physical optics. When a coherent laser beam is irradiated onto the diffusely reflecting surface of biological tissues such as pterygium, an interference pattern called "laser speckle" composed of a large number of light and dark random speckles is formed. If there is no blood cell flow in the tissue, this speckle pattern is static; when there is blood flow in the tissue, the moving red blood cells act like tiny moving scatterers, causing the speckle pattern to fluctuate rapidly and randomly in time and become blurred. The LSCI system captures the dynamic changes of this speckle pattern through a high-speed camera and analyzes its blurring degree using algorithms. The faster the blood flow, the higher the blurring degree of the speckle. By quantifying this blurring degree, a two-dimensional pseudo-color map reflecting the blood perfusion of the tissue surface can be generated, and the blood flow index (FI) representing the average blood flow velocity can be calculated therefrom. The use of the two standardized imaging techniques in the field of ophthalmology, OCTA and LSCI, to obtain the microcirculation parameters has the technical effect that: first, it ensures the objectivity and quantifiability of the data source.They will change the traditional evaluation method of pterygium activity, which depends on the subjective observation of the clinician through slit lamp, to a physical principle-based, accurate to a specific value (quantitative) measurement, providing solid and reliable input data for the subsequent calculation of the activity comprehensive index. Second, it improves the repeatability and consistency of the test results. Because these devices have standardized operating procedures and automated analysis software, they can minimize the subjective judgment differences between different operators and at different time points by the same operator, significantly improving the stability of the grading method. Therefore, the innovative application of these two clinical routine examination methods to the quantitative evaluation of pterygium activity is an important technical basis for the realization of precise and objective grading.

[0015] Specifically, in step S2, the measurement is achieved by a contact measurement electrode probe and a reference electrode placed away from the skin surface of the eye, and the potential difference between the measurement electrode probe and the reference electrode is recorded by a bioelectric amplifier.

[0016] That is, in this technical solution, the bioelectric parameter acquisition step (S2) is achieved by a specific measurement system, which includes a contact measurement electrode probe, a reference electrode placed away from the skin surface of the eye, and a bioelectric amplifier. The contact probe can be designed in a miniaturized structure to achieve precise positioning measurement of specific small areas such as the head and body of pterygium. The reference electrode is usually placed on the ipsilateral earlobe or forehead to provide a stable and uniform zero potential reference for potential measurement. The bioelectric amplifier has high input impedance and low noise characteristics, which can accurately capture and amplify the extremely weak potential difference signal between the measurement probe and the reference electrode without signal distortion due to instrument load effect or environmental noise interference. The technical effect of this technical solution is that it builds a high-fidelity bioelectric signal acquisition link, ensuring that the measured resting transmembrane potential difference (RPD) can truly reflect the local electrophysiological state of the pterygium tissue, providing accurate and reliable electrophysiological data for subsequent comparative analysis.

[0017] Specifically, in step S3, the activity comprehensive index (PAI) is calculated by the following formula:

[0018]

[0019] wherein VD pterygium and FI pterygium are the vascular density and blood flow index of the pterygium area; VD normal and FI normal are the vascular density and blood flow index of the normal bulbar conjunctiva control area; RPD pterygium and RPD normalThe resting transmembrane potential difference of the pterygium region and the normal conjunctival control region, respectively; w1, w2 and w3 are preset weight coefficients.

[0020] In this scheme, the calculation step (S3) of the activity comprehensive index (PAI) is performed by the above specific weighted linear model. The above calculation model divides the vascular density and blood flow index of the pterygium region by the corresponding values of the normal control region respectively to obtain the normalized relative microcirculation parameters; at the same time, the absolute difference of the resting transmembrane potential difference between the pterygium region and the normal control region is calculated. Finally, the three normalized parameters are multiplied by the respective preset weight coefficients (w1, w2, w3) and summed up. The technical effects of this calculation method are reflected in many aspects: first, by comparing with itself normal tissue and calculating the ratio or difference, the individual physiological differences that may exist are effectively eliminated, making the calculation result more horizontally comparable; second, taking the absolute value of the potential difference ensures that whether the potential deviation is positive or negative, as long as the deviation amplitude is large, it is considered as the manifestation of enhanced activity, which is consistent with the characteristics of biological phenomena; finally, the weight coefficient is introduced, which allows the importance of different parameters in evaluating the activity to be adjusted and optimized according to the results of large-scale clinical data statistical analysis, so that the finally constructed PAI model can more accurately reflect the comprehensive biological activity of pterygium and establish a stronger correlation with clinical prognosis (such as progression speed or postoperative recurrence risk).

[0021] Preferably, the biological electric parameter acquisition step of step S2 further comprises acquiring a biological electric signal stabilization time (ST), the biological electric signal stabilization time (ST) being the time required for the fluctuation amplitude of the measured potential signal to stabilize within a preset threshold from the moment the measurement electrode probe contacts the tissue surface;

[0022] And in step S3, the calculation of the activity comprehensive index (PAI) further comprises the process of comparing and integrating the biological electric signal stabilization time (ST) of the pterygium region and the normal conjunctival control region.

[0023] Specifically, the acquisition of the biological electric signal stabilization time (ST) comprises: triggering the timing when the measurement electrode probe contacts the tissue surface, and calculating the signal fluctuation index in a sliding time window in real time; when the signal fluctuation index first continuously falls below a preset stabilization criterion threshold, stop timing, and record the timing duration as the biological electric signal stabilization time (ST); wherein the signal fluctuation index is the standard deviation or peak-to-peak value of the potential signal in the sliding time window.

[0024] Specifically, in this scheme, the biological electrical parameter acquisition step (S2) further introduces a dynamic parameter, the biological electrical signal stabilization time (ST), in addition to measuring the static RPD value. The definition of the biological electrical signal stabilization time (ST) is the time required for the fluctuation amplitude of the measured potential signal to stabilize within a preset threshold from the moment the electrode probe contacts the tissue surface. The specific acquisition process is as follows: trigger the timer at the moment the probe contacts the tissue, and at the same time, the system collects the potential signal at a high sampling rate and calculates the signal fluctuation index (such as standard deviation or peak-to-peak value) in a sliding time window in real time; when the fluctuation index first continuously falls below a preset stabilization criterion threshold, the system stops timing and records this time period as ST. Active pterygium tissue is often accompanied by pathological changes such as cell edema and ion microenvironment disorder, which can slow down the process of establishing a stable electrochemical interface between the electrode and the tissue. Therefore, the technical effect of this technical solution is that it extracts new information reflecting the dynamic stability of the tissue micro-interface from a single measurement without increasing additional hardware and complex operations. As a supplementary dynamic indicator, ST can indirectly reflect the metabolic activity and microenvironment stability of the tissue, and when combined with the static VD, FI, and RPD parameters, it can provide a more comprehensive and stereoscopic characterization of the biological activity of pterygium, especially in improving the recognition sensitivity of early or low-grade active lesions.

[0025] Specifically, in the step S3, the calculation formula of the activity comprehensive index (PAI) is further set as:

[0026]

[0027] wherein ST pterygium and ST normal are the biological electrical signal stabilization times of the pterygium area and the normal conjunctival control area respectively, and w4 is a newly added preset weight coefficient.

[0028] It can be understood that based on the above technical solution introducing the ST parameter, the calculation formula of the activity comprehensive index (PAI) is also optimized accordingly. The new formula adds a fourth weighted term, i.e., the ratio of the ST of the pterygium area to the ST of the normal control area multiplied by its corresponding weight coefficient w4, based on the original three-parameter model. The technical effect of this technical solution is that it formally integrates the dynamic information reflecting the "potential response speed" of the tissue into the quantitative evaluation model. By weighting the four-dimensional parameters (blood flow density, blood flow velocity, static potential, and dynamic response), the PAI constructed can more comprehensively and reliably evaluate the biological activity of pterygium, reducing the misjudgment that may be caused by insufficient single-dimensional information, thereby making the final grading result more reliable.

[0029] Preferably, the process of acquiring the bioelectric signal steady time (ST) further comprises acquiring a steady time change rate (STCR), and the step of acquiring the steady time change rate (STCR) is:

[0030] guiding the subject to keep open eyes after one blink;

[0031] repeating the measurement of the bioelectric signal steady time (ST) at at least two different time points during the open eye state for the same measurement point of the pterygium region and the same measurement point of the normal bulbar conjunctiva control region respectively to obtain respective time series data;

[0032] and calculating a steady time change rate (STCR) based on the time series data, wherein the steady time change rate (STCR) is obtained by linear regression fitting of the time series data points to obtain a slope, or by calculating the difference between the bioelectric signal steady time (ST) of the preset end time point and the starting time point and then dividing by the time interval.

[0033] Specifically, in this scheme, on the basis of acquiring ST, the steady time change rate (STCR) is further acquired. This step takes advantage of the physiological process of natural evaporation of the tear film during the open eye state as a kind of mild, standardized physiological stimulation. The specific operation is as follows: after guiding the subject to complete one blink to form a fresh tear film and keep open eyes, then repeating the measurement of ST at at least two different time points (such as 2 seconds and 12 seconds) during the open eye state for the same measurement point, thereby obtaining a time series data of ST. Based on the sequence data, the slope is obtained by linear regression fitting, or the difference between the ST values of the first and last time points is calculated and then divided by the time interval to obtain the STCR. A healthy tissue with strong physiological steady state maintenance ability is not sensitive to the slight osmotic pressure changes caused by tear film evaporation, and the STCR tends to be zero; while an active and fragile pterygium tissue has poor steady state regulation ability, and the ST value will change more significantly over time, resulting in an increase in the absolute value of the STCR. Therefore, the technical effect of this technical scheme lies in that it reveals the electro-physiological steady state maintenance ability of the tissue when facing a microenvironment disturbance, i.e. the "stress resilience", through a non-invasive endogenous stimulation test. This is a more in-depth dynamic functional index than single ST measurement, which can effectively identify those "latent high activity" cases with weak steady state regulation function and high risk of progression, which are not obvious in static or quasi-dynamic measurement.

[0034] Further, in the step S3, the calculation of the activity comprehensive index (PAI) further comprises a process of comparing and integrating the stable time change rate (STCR) of the pterygium area and the normal conjunctival control area. More specifically, the calculation formula of the activity comprehensive index (PAI) is further set as:

[0035]

[0036] wherein STCR pterygium and STCR normal are the stable time change rates of the pterygium area and the normal conjunctival control area respectively, and w5 is a newly added preset weight coefficient

[0037] That is, this scheme integrates the newly acquired dynamic stress parameter STCR into the calculation of PAI. The final PAI calculation formula adds a fifth weighted term to the four-parameter model, which is the absolute difference between the STCR of the pterygium area and the normal control area multiplied by its weight coefficient w5. The technical effect of this technical scheme is that it constructs a highly comprehensive five-dimensional evaluation model containing four aspects of "perfusion status", "resting potential", "interface stability" and "stress response ability". This final optimized PAI can depict the biological characteristics of pterygium with unprecedented comprehensiveness and depth, greatly improving the sensitivity and specificity of the grading method, and providing the strongest objective basis for realizing the precise typing of pterygium and the truly personalized treatment decision (such as the selection of surgical timing, the development of adjuvant therapy scheme, and the intensification of postoperative management, etc.).

[0038] The technical effect of the pterygium grading method based on microcirculation and bioelectricity combined detection of the application is that: first, the method converts the qualitative description of the pterygium congestion degree and hypertrophy degree, which is traditionally dependent on the experience of clinicians, into objective data that can be accurately measured and repeated, by introducing standardized instruments such as OCTA and bioelectricity amplifiers to obtain parameters such as blood vessel density, blood flow index and resting transmembrane potential difference, which can effectively improve the objectivity and consistency of the evaluation. Secondly, the scheme creatively uses a self-control design, that is, using the healthy bulbar conjunctiva of the same eye as a reference standard. This design effectively eliminates individual differences between patients (such as the influence of factors such as basal blood pressure and age on ocular surface microcirculation and electrophysiological state) by calculating the relative change rate or difference, so that the measurement results can more specifically reflect the pathophysiological changes of the pterygium itself, significantly improving the accuracy and reliability of the evaluation. Thirdly, the application does not stop at single-dimensional detection, but combines microcirculation parameters reflecting tissue "blood supply" with bioelectricity parameters reflecting tissue "metabolism" to construct a multi-dimensional evaluation model. The fusion of this multi-source information can more comprehensively and deeply depict the biological behavior of the pterygium, for example, for an early progressive pterygium with insignificant vascular proliferation but active abnormal metabolism, the method can identify it by abnormal changes in bioelectricity parameters, thereby improving the sensitivity and comprehensiveness of the evaluation. Finally, by constructing the activity comprehensive index (PAI) and using it for grading, the method converts complex multi-dimensional biological data into an intuitive, single score and grade, greatly simplifying the complexity of clinical interpretation and providing a clear and direct reference for doctors. Therefore, the technical effect ultimately realized by the application is to provide an objective, accurate, comprehensive and easy-to-clinically-apply pterygium activity grading method, which can effectively predict the progression trend and postoperative recurrence risk of pterygium, and provide a new technical means for realizing personalized precision treatment. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description.

[0040] Figure 1 is a flow chart of the implementation method of the application. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical scheme and advantages of the application more clear, the following will further describe the application with specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the application, and are not used to limit the application.

[0042] Example 1

[0043] AsFigure 1 As shown, the embodiment discloses a pterygium grading method based on microcirculation and bioelectricity combined detection, mainly including steps S1-microcirculation parameter acquisition step, step S2-bioelectricity parameter acquisition step; step S3-active comprehensive index calculation step; step S4-grading step.

[0044] Specifically, step S1 performs the acquisition step of microcirculation parameters, which aims to quantify the blood perfusion state of pterygium tissue, because angiogenesis is a key pathophysiological link in the occurrence and development process of pterygium, and its perfusion level is directly related to the metabolic demand and proliferation potential of the tissue. In specific operation, first, the region of the eye to be measured needs to be accurately positioned, and two key measurement regions are clearly divided: one is the pterygium lesion tissue itself, in order to ensure the representativeness of the data, usually the region with more abundant blood vessels and thicker tissue in the body is selected; the second is the normal bulbar conjunctiva control region on the same eye, which should be healthy and not invaded by pterygium, such as the conjunctiva in the temporal superior or nasal superior quadrant. The purpose of setting its own control is to effectively exclude the differences in ocular surface microcirculation baseline level caused by individual differences (such as age, baseline blood pressure, systemic disease, etc.), so that the subsequent comparative analysis can more accurately reflect the changes specific to the local pathological state of pterygium. After determining the measurement region, appropriate non-invasive ocular surface microcirculation imaging technology known to those skilled in the art can be used to scan and collect data on the above two regions. By post-processing and analyzing the collected images or signals, at least two core microcirculation parameters, namely vascular density (VD) and blood flow index (FI), can be quantitatively extracted. Among them, vascular density (VD) objectively reflects the distribution density of microvascular network per unit area, while blood flow index (FI) is a relative index related to blood cell flow rate or blood flow per unit time. This step finally obtains the vascular density value and blood flow index value of the pterygium region, as well as the vascular density value and blood flow index value of the normal bulbar conjunctiva control region, which together constitute the first dimension of evaluating pterygium activity.

[0045] After obtaining the microcirculation parameters, step S2 is performed to obtain bioelectricity parameters of the same pterygium area and normal conjunctival control area. Pterygium is an abnormal proliferative tissue, and its cell metabolism, ion exchange, and membrane potential and other electrophysiological activity states are significantly different from those of normal conjunctival epithelial cells. This step aims to capture the differences in such electrophysiological states in a non-invasive manner. During the specific measurement, a measurement system including a measurement electrode and a reference electrode is constructed. A measurement electrode probe with good biocompatibility with the human body is gently placed on the surface of the tissue to be measured, and a reference electrode is placed on the body at another relatively electrically neutral position (such as the earlobe or forehead skin) to establish a stable potential reference. Through a high-precision bioelectricity signal acquisition device, the potential difference between the measurement electrode and the reference electrode is measured and recorded, and this potential difference is defined as the resting transmembrane potential difference (RPD) of the measurement point. This operation is repeated to obtain the resting transmembrane potential difference (RPD) of the pterygium area and the resting transmembrane potential difference (RPD) of the normal conjunctival control area, respectively. This parameter reflects the macroscopic electrophysiological characteristics of the tissue in the resting state and constitutes a second dimension independent of microcirculation perfusion for evaluating pterygium activity.

[0046] After the above two steps are completed and at least three parameters of microcirculation and bioelectricity are obtained, step S3 is performed to enter the calculation step of the activity comprehensive index. This step aims to integrate the multi-source and heterogeneous biological measurement data obtained in the foregoing steps through a preset mathematical model to generate a single quantitative index that can fully characterize the biological activity of pterygium, i.e., the activity comprehensive index (Pterygium Activity Index, PAI). This calculation process first includes the comparison and integration of the parameters of the pterygium area and the normal conjunctival control area. For example, to eliminate individual absolute value differences and highlight the relative degree of pathological changes, the model can first compare (such as calculating the ratio) the vascular density (VD) and blood flow index (FI) of the pterygium area with the values of the corresponding normal control area, and compare (such as calculating the absolute value of the difference) the resting transmembrane potential difference (RPD) of the pterygium area with the value of the normal control area. Subsequently, through a preset weighted model, these compared and standardized parameter components are combined linearly or nonlinearly. The weight coefficients in the model are determined in advance based on the previous clinical data statistical analysis or machine learning training, and the weighted model can reflect the relative importance of different physiological parameters in the comprehensive evaluation of pterygium activity. Through such calculation, a dimensionless PAI value is finally obtained. The establishment of this index can condense complex biological information into a direct scoring technique, greatly simplifying the complexity of clinical interpretation.

[0047] Finally, the method of the present embodiment performs a classification step S4 according to the calculated PAI value. This step maps the continuous PAI value interval into discrete, pre-set at least two biological activity levels by setting one or more pre-set classification threshold values with clinical statistical significance. For example, a threshold value T1 can be set, and when the calculated PAI value is less than or equal to T1, the pterygium is classified as "I level (static type)"; when the PAI value is greater than T1, it is classified as "II level (progressive type)". Of course, more thresholds can be set to achieve more refined classification, such as "highly invasive type" level. Through this classification step, the method of the present application finally outputs a clear and explicit activity level judgment result. This result overcomes the ambiguity of traditional morphological description, and provides objective and quantitative decision support for clinicians in formulating treatment plans, such as deciding the timing of surgery, choosing the surgical approach, predicting the risk of postoperative recurrence, and planning postoperative medication strategies, thereby enabling personalized and precise treatment of pterygium.

[0048] Embodiment Two

[0049] The present embodiment further provides more specific and preferred technical implementation schemes for the microcirculation parameter acquisition step and the bioelectric parameter acquisition step in the framework of the method disclosed in Embodiment One, as follows:

[0050] In a specific implementation process, in order to realize the accurate quantification of the pterygium tissue microcirculation state, the embodiment preferably adopts optical coherence tomography angiography (OCTA) as the means for acquiring the microcirculation parameters. Before detection, first, the subject's eye surface is locally anesthetized with propoxycaine hydrochloride eye drops to improve the patient's comfort during the detection process and reduce artifacts caused by eye movement. Subsequently, the patient is guided to fix his head on the chin and forehead supports of the OCTA device (for example, a swept source-based OCTA system), and is instructed to fix his gaze on the fixation target inside the device. The operator first locates and selects the area with more dense blood vessels at the head or body of the pterygium as the lesion tissue measurement area, and selects a healthy conjunctiva area (such as the upper temporal conjunctiva) in the same eye as the normal conjunctiva control area. For these two areas, the device's blood vessel imaging scanning mode is enabled, the scanning range (for example, 6mm x 6mm) is set, and the scanning operation is performed. The built-in analysis software in the device, for example, using the split-spectrum amplitude-decorrelation angiography (SSADA) algorithm, can automatically process the collected three-dimensional data to generate en-face blood vessel imaging images of the corresponding areas. Based on the blood vessel imaging images, the software can automatically calculate and output two key quantitative indicators: vessel density (VD), which is defined as the percentage of total pixel area occupied by blood vessel pixels in the selected area; and flow index (FI), which is a comprehensive index related to blood flow signal intensity and range, which can reflect the relative blood flow per unit area. Through the above operation, the VD and FI values of the pterygium area and the normal control area can be obtained non-invasively and with high resolution. This implementation based on OCTA technology converts the traditional subjective evaluation of pterygium "hyperemia degree" in clinical practice into objective and repeatable quantitative data. The technical effect is that it greatly improves the accuracy of evaluation, and can distinguish blood vessel network information at different depths through layered imaging capability, providing a richer dimension for in-depth understanding of the pathophysiology of pterygium, and thus providing high-quality input data for the calculation of the subsequent activity comprehensive index.

[0051] After the collection of microcirculation parameters, the bioelectric parameters of the same measurement area are obtained. In this embodiment, a high-precision microelectrode measurement system is preferably used to complete this step, which is composed of a measurement electrode, a reference electrode, and a bio-signal acquisition and analysis device. Specifically, the measurement electrode can be a silver chloride (Ag / AgCl) electrode with a tip diameter of 0.5 mm, and the reference electrode is a conventional Ag / AgCl disc electrode for the skin surface. The bio-signal acquisition and analysis device can be directly realized by using the conventional electromyography / evoked potential system (EMG / EP System) in the hospital's neurology or rehabilitation department, which itself integrates the required high-input impedance bio-signal preamplifier and data acquisition and analysis system. In actual operation, the reference electrode is first pasted on the ipsilateral earlobe of the subject through conductive paste to establish a stable zero potential reference point. Then, the lead wires of the measurement electrode and the reference electrode are connected to the signal input channels of the electromyography / evoked potential system. The system is set to a direct current (DC) coupling recording mode to ensure that the static direct current potential of the tissue surface can be stably measured, rather than the alternating current (AC) signal commonly used in electromyography. The collection parameters can be set as follows: sampling frequency 1000 Hz, filter set to 0.05-30 Hz band-pass filter, or a low-pass filter with a cutoff frequency of 0.5 Hz is applied to filter out high-frequency noise and interference, so as to stably extract the resting potential signal. Under the same local anesthetic effect as the aforementioned OCTA detection, the operator holds the measurement electrode probe with its tip gently and vertically touching the pre-selected pterygium tissue surface, and observes the recorded potential value on the system screen. When the signal is stable (e.g., fluctuation less than 0.1 mV within 3 seconds), the stable voltage value is recorded as the resting transmembrane potential difference (RPD) of that point. Subsequently, the measurement electrode probe is moved to the normal bulbar conjunctiva control area surface in the same way to measure and obtain the RPD value of the normal tissue. To ensure the reliability of the data, each measurement area can be measured three times and the average value is taken. By using the existing clinical conventional equipment to obtain the bioelectric parameters, the ion pump function, cell membrane permeability, and overall metabolic activity at the tissue cell level are directly reflected, and the technical effect is that it not only ensures the implementability and easy popularization of the method of the present application, but also provides a completely independent biological evaluation dimension from blood perfusion. This dimension can detect early activity changes of pterygium at the molecular and cellular levels, which may occur before significant changes in blood vessel morphology. Therefore, by including this electrophysiological indicator in the evaluation system, the sensitivity and forward-looking of the grading method can be significantly improved, and the judgment of the biological activity of pterygium is more comprehensive.

[0052] Embodiment Three

[0053] The embodiment is based on the embodiment one and embodiment two, and the specific calculation steps of the activity comprehensive index are described in detail. After obtaining the vascular density value (VD pterygium ), blood flow index value (VD pterygium ), resting transmembrane potential difference value (RPD pterygium ) of the pterygium area and the vascular density value (VD normal ), blood flow index value (FI normal ), resting transmembrane potential difference value (RPD normal ) of the normal conjunctival control area by the method described in the foregoing embodiments, the method of the present application enters the data integration and index calculation link.

[0054] The core of this step is to integrate and calculate the obtained multi-source physiological and electrophysiological parameters by a preset mathematical model to obtain an activity comprehensive index (PAI) which can quantitatively and comprehensively reflect the biological activity of the pterygium. The specific formula of the calculation is as follows:

[0055]

[0056] In the formula, PAI is the activity comprehensive index; VD pterygium is the vascular density value of the pterygium area, VD normal is the vascular density value of the normal conjunctival control area; FI pterygium is the blood flow index value of the pterygium area, FI normal is the blood flow index value of the normal conjunctival control area; RPD pterygium is the resting transmembrane potential difference value of the pterygium area, RPD normal is the resting transmembrane potential difference value of the normal conjunctival control area; w1, w2 and w3 are preset weight coefficients, and satisfy w1+w2+w3=1.

[0057] In the formula, the vascular density ratio and the blood flow index ratio of the pterygium area and the normal conjunctival control area are calculated to realize the standardization of the microcirculation parameters. The technical effect of this ratio calculation by self-control is that the universal influence of individual factors such as heart rate, blood pressure on the absolute value of the ocular surface microcirculation can be effectively filtered out, so that the two ratios can more purely reflect the relative change degree of the vascular proliferation and blood perfusion driven by the local pathological process of the pterygium relative to its own healthy baseline. At the same time, the absolute difference (|RPD pterygium -RPD normal|), the bioelectric parameters are quantitatively processed. Considering that the potential of healthy bulbar conjunctival tissue is usually in a relatively stable interval, the size of the absolute difference is directly related to the difference degree of the electrophysiological characteristics of the diseased tissue and the normal tissue, and is irrelevant to the specific direction of the potential change. The technical effect of this processing is that it converts the electrophysiological state change of the tissue into a positive value that can stably represent the pathological deviation degree, simplifying the construction and interpretation of the subsequent model. The weight coefficients W1, W2 and W3 in the formula are determined in advance based on the correlation between the parameters and the gold standard such as the recurrence rate after pterygium surgery, the histopathological proliferation index, and the like, which is modeled and optimized by a large number of retrospective statistical analysis of clinical case data, such as multivariate linear regression analysis or machine learning algorithm. For example, in a specific setting, the weight coefficients can be determined as W1 = 0.4, W2 = 0.3, and W3 = 0.3. Through the construction of such a weighted linear model, the final technical effect is that it can reasonably weight the different physiological indicators according to their actual contribution to reflecting the overall biological activity of pterygium, so as to organically integrate the multi-source and heterogeneous biological information into a more stable structure and more comprehensive quantitative score. Compared with any single parameter, the finally generated PAI value can more accurately and reliably represent the inherent proliferation potential and invasive activity of pterygium, providing a reliable basis for subsequent objective grading.

[0058] More specifically, the present embodiment selects three pterygium patients (labeled as case A, case B and case C, respectively) as examples. The operator first performs non-invasive detection of the microcirculation parameters and bioelectric parameters of the affected eye of each patient according to the method described in embodiment two, and obtains the original measurement data of each parameter of the pterygium area and the normal bulbar conjunctival control area. Subsequently, according to the calculation formula disclosed in embodiment three, and using the preset weight coefficients (set as W1 = 0.4, W2 = 0.3, W3 = 0.3), the data of each patient is processed to calculate the corresponding activity comprehensive index (PAI). All the original data and calculation results are summarized in Table 1 below.

[0059] Table 1 Example of clinical case data collection

[0060] Case identification VD_p (%) VD_n (%) FI_p (a.u.) FI_n (a.u.) RPD_p (mV) RPD_n (mV) Case A 21.5 19.8 0.28 0.25 -18.2 -17.5 Case B 32.6 18.5 0.45 0.22 -22.5 -16.8 Case C 40.1 19.1 0.58 0.24 -25.8 -17.1

[0061] (Table, the symbol of the case is a simplified representation, specifically, VD_p is VD pterygium , VD_n is VD normal , FI_p is FI pterygium , FI_n is FI normal , RPD_p is RPD pterygium , RPD_n is RPD normal ).

[0062] Taking case B as an example, the PAI value is calculated as follows: PAI = 0.4 x (32.6 / 18.5) + 0.3 x (0.45 / 0.22) + 0.3 x |-22.5 - (-16.8)| = 0.4 x 1.76 + 0.3 x 2.05 + 0.3 x 5.7 = 0.704 + 0.615 + 1.71 = 2.629, approximately equal to 2.63. In the same way, the PAI value of case A is calculated as 1.00, and the PAI value of case C is calculated as 3.99.

[0063] After the calculation of the activity comprehensive index is completed, the method of the present application enters the final grading step. This step is based on a preset grading standard with clinical statistical significance, which maps the continuous PAI value interval to discrete biological activity levels. In this embodiment, the grading standard is set as follows:

[0064] I level (static type): PAI ≤ 1.5

[0065] II level (progressive type): 1.5 < PAI ≤ 3.0

[0066] III level (high activity type): PAI > 3.0

[0067] According to this grading standard, the three cases in Table 1 are graded as follows:

[0068] Case A: The calculated PAI value is 1.00, which is less than or equal to 1.5, so the biological activity level of the pterygium is determined to be I level (static type);

[0069] Case B: The calculated PAI value is 2.63, which is greater than 1.5 and less than or equal to 3.0, so the biological activity level of the pterygium is determined to be II level (progressive type);

[0070] Case C: The calculated PAI value is 3.99, which is greater than 3.0, so the biological activity level of the pterygium is determined to be III level (high activity type).

[0071] Through the above complete implementation process, the present application successfully converts the clinical ambiguous, subjective morphological observation of whether the pterygium is active into an objective, quantitative and repeatable grading result. The technical effect is to provide a clear decision basis for clinicians: for case A, a patient of grade I, conservative observation or drug treatment can be taken; for case B, a patient of grade II, it is suggested that the lesion is in the progressive stage, surgical intervention should be considered, and postoperative recovery should be closely observed; and for case C, a patient of grade III, it is indicated that it has a high proliferation and invasion potential, which is not only a strong indication for surgery, but also suggests that auxiliary treatment (such as mitomycin C or amniotic membrane transplantation) may need to be combined in the development of surgical plan to reduce the risk of postoperative recurrence. Thus, the present embodiment provides a strong technical support for realizing the precise and individualized diagnosis and treatment of pterygium by constructing a complete technical closed loop from multi-dimensional biological parameter detection to standardized index calculation and then to objective grading.

[0072] In addition, more specifically, the preset grading standard in the present embodiment, i.e. the set of classification thresholds of "grade I (static type): PAI≤1.5", "grade II (progressive type): 1.5<PAI≤3.0" and "grade III (high activity type): PAI>3.0", is objectively established through prospective clinical research and statistical analysis, thereby ensuring the scientificity, reliability and clinical applicability of the grading method of the present application. The execution process is as follows:

[0073] The establishment of this grading standard first involves a prospective clinical cohort study, which enrolls patients with primary pterygium who have clear surgical indications, for example, 200 patients are enrolled. Before all enrolled patients undergo pterygium excision combined with autologous corneal limbal stem cell transplantation surgery, the microcirculation and bioelectricity of each patient are detected according to the method described in Embodiment II, and the preoperative active comprehensive index (PAI) of each patient is calculated according to the formula in Embodiment III. After the determination of the preoperative PAI value is completed, all patients receive standardized surgical treatment and enter a postoperative follow-up period of at least 12 months. During the follow-up period, patients are regularly examined under a slit lamp microscope, and whether pterygium recurs is determined according to internationally recognized standards (for example, defined as any fibrovascular tissue growing into the transparent corneal area from the bed edge of the corneal graft bed after surgery). After the end of the 12-month follow-up period, the entire cohort is divided into two groups according to the final clinical outcome of the patients: the recurrence group and the non-recurrence group. At this time, the core task of the study is to analyze the correlation between the preoperative PAI value and the postoperative recurrence of the clinical "gold standard" event using statistical tools, and to find the best PAI threshold value that can effectively predict the risk of recurrence. This embodiment uses Receiver Operating Characteristic curve (ROC curve) analysis to complete this task. The specific operation is as follows: the preoperative PAI value of all patients is taken as the test variable, and whether they recur after surgery (yes = 1, no = 0) is taken as the state variable, and the ROC curve is drawn. The ROC curve can directly show the relationship between the sensitivity (true positive rate) and the specificity (1-false positive rate) of the PAI value at different cutoff points (i.e., threshold values) in distinguishing the recurrence group from the non-recurrence group.

[0074] Through ROC curve analysis, the area under the curve (AUC) is first calculated. The closer the AUC value is to 1, the higher the diagnostic value of PAI as a predictive indicator. In the study, if a statistically significant high AUC value (for example, AUC > 0.85) is obtained, it indicates that PAI can effectively distinguish between patients with high recurrence risk and patients with low recurrence risk. Subsequently, in order to determine the best single diagnostic threshold, the principle of maximizing Youden's Index (Youden's Index = sensitivity + specificity - 1) is adopted. On the ROC curve, the PAI value corresponding to the point with the maximum Youden's Index is the best critical point for distinguishing recurrence from non-recurrence. After calculation, it is determined that the best critical value is PAI ≈ 3.0. Therefore, the present application defines PAI > 3.0 as "grade III (high active type)", and its clinical significance is that patients with a preoperative PAI value exceeding this threshold have a significantly increased risk of postoperative recurrence.

[0075] In order to further stratify the patient population with PAI value below 3.0, to distinguish the "quiescent" with little proliferative activity and the "progressive" with certain proliferative potential, the present embodiment combines clinical observation data and the distribution characteristics of PAI values of patients in the non-recurrence group. By analyzing the PAI value distribution of pterygium patients who clinically exhibit long-term stability, sparse blood vessels, and thin tissue in the typical "quiescent" state, it is found that the PAI values of most of them are concentrated below 1.5. At the same time, in the non-recurrence cohort, the PAI values also exhibit skew distribution, and the 75th percentile or a low-risk cut-off point calculated based on the distribution model also falls near 1.5. Therefore, PAI = 1.5 is selected as the second threshold for distinguishing "Class I (quiescent)" and "Class II (progressive)". This threshold allows the grading system to more finely identify patients who, although currently do not belong to the highest risk level, have shown clear biological activity (1.5 < PAI ≤ 3.0) in an intermediate state.

[0076] The above grading criteria are not subjectively set, but are the result of rigorous clinical cohort studies, which associate the quantitative indicator (PAI) proposed by the present application with the recognized, objective clinical hard endpoint (postoperative recurrence), and use existing mature statistical methods (ROC curve analysis, etc.) for data mining and threshold optimization. The technical effect lies in ensuring the clinical effectiveness and predictive value of the grading results, so that clinical decisions based on this grading (such as the choice of surgical timing, the application of adjuvant therapy, etc.) are based on evidence-based medicine.

[0077] Embodiment Four

[0078] The present embodiment, based on the foregoing embodiments, provides a preferred implementation for further improving the evaluation dimension and sensitivity of the grading method described in the present application. The core of this method is to deepen the biological electrical parameter acquisition step (S2), without adding additional hardware devices, to simultaneously acquire a new dynamic response parameter - biological electrical signal stabilization time (ST), and to optimize the activity comprehensive index calculation step (S3) accordingly, so as to help achieve a more comprehensive evaluation of pterygium biological activity, as follows:

[0079] In the preferred embodiment, the bioelectric parameter acquisition step (S2) acquires the bioelectric signal stabilization time (ST) synchronously in addition to measuring the static resting potential difference (RPD). The bioelectric signal stabilization time (ST) herein is defined as the time required for the fluctuation amplitude of the measured potential signal to stabilize within a certain preset threshold since the moment the electrode probe contacts the tissue surface. The introduction of this parameter is based on the technical foundation that when the measuring electrode contacts the biological tissue, the electrode-tissue interface formed needs a short process to reach electrochemical equilibrium, at which time the recorded potential signal will tend to be stable. The length of this process, i.e. ST, is not only related to the response characteristics of the measuring system itself, but also reflects the physicochemical characteristics of the microenvironment of the tissue in a deeper level. Compared with normal conjunctival tissue, actively proliferating pterygium tissue is often accompanied by pathophysiological characteristics such as tissue edema, disorder of extracellular fluid ion composition, and changes in cell membrane permeability, all of which will lead to a more complex and unstable electrochemical environment of the electrode-tissue interface, thereby significantly prolonging the time required for the signal to reach steady state. Therefore, by accurately quantifying ST, the biological activity of pterygium can be evaluated from a completely new dimension reflecting the dynamic stability of the tissue interface.

[0080] To achieve the accurate acquisition of the stable time (ST) of bioelectric signals, the present embodiment further requires the software function of the bio-signal acquisition and analysis device (such as an electromyography / evoked potential instrument system) described in Embodiment 2. The software system needs to have the ability of event-triggered timing and real-time data stream analysis. Specifically, when the measurement electrode probe contacts the tissue surface, the system can automatically identify the contact event by monitoring the mutation of the potential signal (for example, the change amount of the signal amplitude within 1 millisecond exceeds a preset noise threshold), and use it as the timing starting point. After the timing starts, the system continuously acquires the potential signal at a high sampling rate (for example, 1000 Hz), and can calculate the signal fluctuation index in a sliding short time window (for example, 100 milliseconds) in real time. In the present embodiment, the standard deviation (SD) of the potential signal in the sliding time window is preferably used as the fluctuation index. A stability criterion threshold is preset in the system, which can be scientifically determined according to the natural fluctuation range of the signal after stability of the normal conjunctiva of healthy people measured by a large number of previous experimental measurements, for example, it can be set as SD < 5 μV. When the real-time calculated signal fluctuation index first continuously falls below the preset stability criterion threshold (for example, the SD values of the three consecutive sliding windows are all less than 5 μV), the system determines that the signal has reached a stable state, and automatically stops timing. The time period from the contact moment to the timing stop is accurately recorded as the stable time (ST) of the bioelectric signal at the measurement point. After determining the signal stability, the system continues to record a fixed time length of stable signal (for example, 2 seconds), and performs time averaging on the data segment to calculate the resting transmembrane potential difference (RPD) at the point. Through this measurement protocol, when a single measurement operation is performed on the same point of the pterygium area and the normal conjunctiva control area, the (ST pterygium ,RPD pterygium ) and (ST normal ,RPD normal ) two groups of data can be obtained synchronously.

[0081] After obtaining all the parameters including the stable time (ST) of bioelectric signals, the present embodiment optimizes the activity comprehensive index calculation step (S3) accordingly. In line with the processing method of microcirculation parameters and static potential parameters, the newly obtained ST parameter is first standardized, that is, the ST ratio of the pterygium area to the normal conjunctiva control area is calculated to eliminate individual differences and highlight the relative degree of pathological changes. Subsequently, the standardized ST parameter is integrated into the original weighted model to form an activity comprehensive index (PAI) with enhanced dimension. Its calculation formula is further set as:

[0082]

[0083] In the formula, ST pterygiumand ST normal The bioelectric signal stable time of pterygium area and normal bulbar conjunctiva control area respectively, and W4 is a new weight coefficient. Each weight coefficient (W1, W2, W3, W4) is also determined by regression analysis or statistical methods such as analytic hierarchy process through large sample data, and meets W1+W2+W3+W4=1. In this embodiment, a set of preferred weight coefficients can be set as: W1=0.25, W2=0.35, W3=0.20, and W4=0.2.

[0084] In order to make the technical solutions of the present application easier to understand, a patient (patient 4) with a pterygium clinically showing "deceptively quiet" (i.e. "false quiescence") is exemplified by combining the data in Table 1 of Example 3 and supplementing the ST parameter.

[0085] The pterygium of this patient is thin and membranous under slit lamp observation, and the vascular structure is not very rich, which is often judged as non-active period by clinical experience. The detection by the method of the present application obtains the parameters as shown in the following table:

[0086] Table 2: Measurement values of multi-dimensional parameters of patient 4

[0087] Parameter Pterygium area (p) Normal bulbar conjunctiva control area (n) Vessel density VD (mm / mm2) 2 )]> 180.5 160.1 Blood flow index FI (AU) 180.5 0.5 Resting potential RPD (mV) -48.0 -55.0 Steady time ST (ms) 550 -55.0

[0088] Based on the data in Table 2, the activity comprehensive index (PAI) of patient 4 is calculated

[0089] 1. Calculate the standardized ratio or difference of each parameter:

[0090]

[0091] Resting potential difference absolute value = |RPD pterygium -RPD normal | = |-48.0 - (-55.0) | = 7.0 mV

[0092]

[0093] 2. Substitute the PAI calculation formula of the embodiment with dimension enhancement:

[0094] PAI = 0.25 × 1.13 + 0.35 × 1.60 + 0.20 × 7.0 + 0.20 × 3.67 ≈ 2.98

[0095] In the grading system of the present application, if the grading threshold (established based on large sample data) is set as: Grade I (PAI < 2.0), Grade II (2.0≤PAI<4.0), Grade III (PAI≥4.0). Then the PAI value of patient 4 is 2.98, which should be objectively evaluated as Grade II (moderate activity level).

[0096] Technical effect analysis:

[0097] If the ST parameter introduced in this embodiment is not used, only the three-parameter model in Example Three (assuming weights W1=0.3, W2=0.4, W3=0.3) is used, then the PAI_3 of this patient is 0.3x1.13+0.4x1.60+0.3x7.0=0.339+0.64+2.1=3.079. The result of this three-parameter model will also evaluate it as a moderate activity level. However, in this case, the ST ratio is as high as 3.67, which is the most significant deviation from the normal value among all parameters, and it strongly indicates that there is significant instability in the electrochemical level of the pterygium tissue microenvironment, which is an early signal of potential high proliferation activity. The four-dimensional PAI model assigns a weight (W4=0.20) to the ST parameter, so that this "hidden" activity information can be effectively expressed in the final comprehensive score.

[0098] For another type of case, the VD, FI and RPD indicators may be abnormally significant, but the ST difference is not large, and the four-dimensional model can also make an objective conclusion by weight allocation. Therefore, by introducing the ST dynamic response parameter, the technical effect lies in significantly improving the diagnostic sensitivity and comprehensiveness of the grading method. It enables the present application to identify those "false quiescence" or early active pterygiums that are not yet typical in traditional morphological or blood flow indicators, providing key and objective quantitative basis for earlier clinical intervention or developing more forward-looking surgical and postoperative management plans (e.g., choosing stronger anti-proliferation drugs). This makes the final PAI score more robust and more resistant to interference, so as to more reliably distinguish pterygiums of different activity states.

[0099] Example Five

[0100] The embodiment provides a deeper preferred embodiment based on the method framework disclosed in the foregoing embodiment. The embodiment aims to further improve the evaluation of pterygium biological activity from the level of static properties and quasi-dynamic response inherent to the tissue to the dimension of dynamic stress response and steady state maintenance ability under continuous microenvironment disturbance. The core of the embodiment is the innovative process design of the bioelectric parameter acquisition step. By introducing a standardized excitation test based on the natural physiological process of the ocular surface, a new high-order dynamic parameter, the stable time change rate (STCR), is obtained and integrated into the calculation model of the activity comprehensive index (PAI), thereby realizing the most comprehensive and profound quantitative characterization of the biological behavior of pterygium.

[0101] In the embodiment, the microcirculation parameters are acquired in the same way as in the foregoing embodiment, i.e., the blood vessel density (VD) and blood flow index (FI) of the pterygium area and the normal bulbar conjunctiva control area are acquired by using optical coherence tomography blood flow imaging (OCTA) and the like. The improvement of the embodiment mainly focuses on the acquisition process of the bioelectric parameter and the construction method of the activity comprehensive index.

[0102] Specifically, the bioelectric parameter acquisition step is reengineered in the embodiment. The technical principle is to actively use an inevitable physiological phenomenon of the ocular surface, tear film evaporation, as a standardized, mild, and endogenous physiological excitation source. During the open-eye state of the subject, the tear film of the ocular surface will gradually thin due to evaporation, causing a slight but continuous increase in local osmotic pressure. This progressive change in osmotic pressure constitutes a natural physiological function test for ocular surface tissue cells. A physiologically functional and steady-state maintenance capable tissue, such as normal bulbar conjunctiva, can effectively work ion pumps and ion channels on the cell membrane to actively regulate ion transmembrane transport to resist this slight osmotic pressure fluctuation, thereby maintaining the relative stability of the electro-physiological environment. On the contrary, a pterygium tissue in an active proliferation state often has altered cell membrane permeability, and the ion regulation function may be in a sub-health or decompensated state, and the electro-physiological steady state system is more fragile. Therefore, when facing the same continuous osmotic pressure micro-stimulation, the instability of the electrochemical interface of the pterygium tissue will be amplified. This instability can be reflected by the significant change in the stable time (ST) of the bioelectric signal over time. The embodiment accurately quantifies this change trend, i.e., calculates the stable time change rate (STCR), thereby obtaining a key indicator that can directly reflect the steady state regulation ability and stress vulnerability of the tissue.

[0103] To achieve the above-mentioned purpose, the specific operation process of the embodiment is as follows: first, guide the subject to complete a natural and complete blinking action. The purpose of this operation is to coat the entire eyeball surface, including the pterygium and normal conjunctival surface, with a layer of fresh and uniform thickness tear film, so as to standardize all the initial state (t=0) measurements to a relatively consistent physiological baseline. After the completion of the blinking, the subject is required to keep the eyes naturally open and gaze at a fixed target in front to minimize eye movement.

[0104] Subsequently, the measurement system software automatically starts timing from the moment when the subject's blinking ends. The operator needs to hold the microelectrode probe with the aid of magnification equipment such as a slit lamp, and perform rapid and repeated bioelectric signal stabilization time (ST) measurements on the same preset measurement point. In order to capture different stages of the tear film from complete to gradually unstable, the measurement protocol presets at least two different time points. In a preferred scheme, measurements are taken at three time points: 2 seconds (t1), 7 seconds (t2) and 12 seconds (t3) after opening the eyes. When each preset time point is reached, the operator quickly and gently contacts the probe tip to the preset measurement point and completes a complete ST measurement according to the method defined in the foregoing embodiment, i.e. timing starts from the moment of probe contact, and stops when the fluctuation amplitude of the measured potential signal (for example, represented by the signal standard deviation in the sliding time window) first lasts below the preset stabilization criterion threshold, and the time length is recorded. By performing three such rapid measurements on the same point of the pterygium, a time series data of ST values is obtained: ST_pterygium(t1), ST_pterygium(t2), ST_pterygium(t3). After completing the sequence measurement of the pterygium area, the subject is allowed to rest and normally blink, and then the same operation process is repeated on the control area of the normal conjunctival surface to obtain the time series data of ST values of the normal tissue: ST_normal(t1), ST_normal(t2), ST_normal(t3).

[0105] After obtaining the time series data, the stable time change rate (STCR) that can quantify the dynamic change trend is calculated. The calculation method can adopt one of the following two methods: one is a linear regression fitting method, taking the measurement time point (t) as the independent variable and the corresponding ST value as the dependent variable, performing linear regression analysis on the data points of the time series, and the slope of the fitting straight line is defined as the STCR. This method integrates the information of all measurement points, and the result is more stable. The other is a simplified difference calculation method, which calculates the difference between the preset end time point (such as t3) and the starting time point (such as t1) of the bioelectric signal stable time (ST), and then divides by the corresponding time interval, and the calculation formula is: STCR = [ST(t3) - ST(t1)] / (t3-t1). Through this step, the stable time change rate STCR_pterygium of the pterygium area and the stable time change rate STCR_normal of the normal conjunctiva control area are finally calculated respectively

[0106] Next, in the active comprehensive index (PAI) calculation step, the newly obtained dynamic stress parameter STCR is further integrated into the calculation model. In order to eliminate the baseline differences between individuals and highlight the abnormal degree of response of the diseased tissue, the absolute difference between the stable time change rates (STCR) of the pterygium area and the normal conjunctiva control area, i.e. |STCR_pterygium-STCR_normal|, is preferably used as one of the input parameters of the model. Finally, a more comprehensive active comprehensive index (PAI) calculation formula is constructed, which includes five dimensions:

[0107]

[0108] where STCR_pterygium and STCR_normal are the stable time change rates of the pterygium area and the normal conjunctiva control area respectively, and w5 is a new preset weight coefficient also determined by regression analysis of large sample clinical data or other statistical methods, and its value reflects the relative contribution of the "dynamic stress response ability" dimension in the comprehensive evaluation. pterygium and STCR normal are the stable time change rates of the pterygium area and the normal conjunctiva control area respectively, and w5 is a new preset weight coefficient also determined by regression analysis of large sample clinical data or other statistical methods, and its value reflects the relative contribution of the "dynamic stress response ability" dimension in the comprehensive evaluation.

[0109] The weight coefficients (w1, w2, w3, w4, w5) are also determined by regression analysis of large sample data or statistical methods such as analytic hierarchy process, and satisfy w1+w2+w3+w4+w5=1. In this embodiment, a set of preferred weight coefficients can be set as: w1=0.25, w2=0.15, w3=0.25, w4=0.15, w5=0.20.

[0110] In addition, the establishment of grading criteria. Since the active comprehensive index (PAI) of the present embodiment is a brand-new model containing five-dimensional parameters, the numerical range and distribution characteristics of its calculation results are essentially different from those of the four-dimensional model in the aforementioned embodiments. Therefore, a set of objective grading criteria matching the five-dimensional model must be re-established. The establishment process of the grading criteria follows the same scientific method as the aforementioned embodiments. That is, first, a large-scale and diversified pterygium case cohort is collected, and the complete five-dimensional parameter detection scheme described in the present embodiment is used for each patient to calculate its PAI value. At the same time, long-term clinical follow-up is performed on all cases to obtain their clear clinical outcomes, such as postoperative recurrence, disease progression rate, etc. Then, statistical methods such as receiver operating characteristic (ROC) curve analysis are used to correlate PAI values with clinical outcomes to determine the critical threshold value that can best divide different activity levels (e.g., low, medium, and high activity).

[0111] In the present embodiment, the following grading criteria are established for the five-dimensional PAI model by the above method:

[0112] Grade I (low activity): PAI ≤ 2.5

[0113] Grade II (medium activity): 2.5 < PAI ≤ 5.0

[0114] Grade III (high activity): PAI > 5.0

[0115] Calculation and grading examples

[0116] To more clearly illustrate the technical solutions of the present embodiment, the dynamic parameter measurement and PAI calculation process of the present embodiment are supplemented by taking patient C in Table 1 of the aforementioned Example 3 as an example.

[0117] First, the basic parameters of case C are accurately retrieved from Table 1:

[0118] VD pterygium = 40.1 (%), VD normal = 19.1 (%)

[0119] FI pterygium = 0.58 (a.u.), FI normal = 0.24 (a.u.)

[0120] RPD pterygium = -25.8 (mV), RPD normal = -17.1 (mV)

[0121] Then, the biological electrical signal stable time (ST) of case C was measured according to the method described in Example 4. In order to keep the unit consistent with the previous examples, the unit of ST in this example was unified as millisecond (ms). The baseline value of case C at t1=2s was measured as:

[0122] ST pterygium =2100(ms), ST normal =1000(ms)

[0123] Next, according to the dynamic measurement process of this example, case C was measured to obtain the following time series data (all in ms):

[0124] The stable time (ST) sequence of the pterygium area:

[0125] At t1=2s, ST_pterygium(t1)=2100ms

[0126] At t2=7s, ST_pterygium(t2)=3000ms

[0127] At t3=12s, ST_pterygium(t3)=4200ms

[0128] The stable time (ST) sequence of the normal conjunctival control area:

[0129] At t1=2s, ST_normal(t1)=1000ms

[0130] At t2=7s, ST_normal(t2)=1000ms

[0131] At t3=12s, ST_normal(t3)=1100ms

[0132] 1. Calculate the stable time change rate (STCR)

[0133] Using the simplified difference calculation method, the unit is ms / s:

[0134] STCR pterygium =[ST_pterygium(t3)-ST_pterygium(t1)] / (t3-t1)= (4200-2100) / (12-2)=2100 / 10=210ms / s

[0135] STCR normal =[ST_normal(t3)-ST_normal(t1)] / (t3-t1)= (1100-1000) / (12-2)=100 / 10=10ms / s

[0136] 2. Calculate the five-dimension activity comprehensive index (PAI)

[0137] The calculation is performed using the aforementioned preferred weight coefficients and scaling transformation coefficients:

[0138] w1=0.25, w2=0.15, w3=0.25, w4=0.15, w5=0.20.

[0139] Substitute all parameters into the PAI calculation formula of this embodiment containing five dimensions:

[0140] PAI=0.25x(40.1 / 19.1)+0.15x(0.58 / 0.24)+0.25x|-25.8-(-17.1)|+0.15x(2100 / 1000)+0.20x(210 / 10)≈7.578.

[0141] 3. Perform grading

[0142] Compare the calculated PAI value (7.578) of case C with the pre-established five-dimension grading standard. Since 7.578>5.0, the PAI value of this case falls into the III-grade (high activity) interval. Therefore, case C is objectively determined as a III-grade (high activity) pterygium.

[0143] The technical effect of this embodiment lies in that by introducing the high-order dynamic parameter of stable time change rate (STCR), the sensitivity and specificity of the grading method are greatly improved. This method can accurately identify a special class of "latent high activity" pterygium. This class of pterygium may not appear active on conventional static parameters (such as VD, RPD) or even a single ST measurement, but its internal steady-state regulation mechanism has been damaged. Only after a sustained and mild physiological challenge, its inherent vulnerability will be exposed through an abnormally high STCR value. This has decisive value for screening cases that appear "static" on the surface but actually have a high recurrence risk. In addition, the STCR parameter also provides more refined guidance for clinical treatment. For example, a pterygium with a high STCR value indicates that it is highly sensitive to changes in the ocular surface microenvironment, which means that in addition to conventional anti-inflammatory treatment, more emphasis should be placed on lubrication and protection of the ocular surface when developing postoperative medication strategies, and artificial tears that can maintain the stability of the ocular surface osmotic pressure should be preferred to reduce external factors that may induce postoperative recurrence. In summary, this embodiment establishes a multi-dimensional comprehensive evaluation system covering "blood perfusion", "resting potential", "interface stability" and "stress resilience", providing strong technical support for achieving precise typing and personalized treatment of pterygium.

Claims

1. A method for grading pterygium based on combined detection of microcirculation and bioelectricity, characterized in that, Includes the following steps: S1. Microcirculation parameter acquisition steps: Acquire the microcirculation parameters of the pterygium region to be tested and the normal bulbar conjunctiva control region of the same affected eye. The microcirculation parameters include at least vascular density (VD) and blood flow index (FI). S2. Bioelectric parameter acquisition steps: Measure the bioelectric parameters of the pterygium region and the normal bulbar conjunctiva control region. The bioelectric parameters are the resting transmembrane potential difference (RPD) relative to the same reference electrode. S3. Activity Comprehensive Index Calculation Step: Based on the microcirculation parameters obtained in step S1 and the bioelectric parameters obtained in step S2, the Activity Comprehensive Index (PAI) of the pterygium is calculated through a preset weighted model. The calculation of the Activity Comprehensive Index (PAI) includes a process of comparing and integrating the vascular density (VD), blood flow index (FI), and resting transmembrane potential difference (RPD) of the pterygium region and the normal bulbar conjunctival control region. S4. Grading step: Based on the value of the Comprehensive Activity Index (PAI) calculated in step S3, the pterygium is divided into at least two preset bioactivity levels.

2. The pterygium grading method based on combined detection of microcirculation and bioelectricity according to claim 1, characterized in that, In step S1, optical coherence tomography (OCTA) or laser speckle flow imaging (LSCI) is used to scan the pterygium region and the normal bulbar conjunctiva control region to obtain the microcirculation parameters.

3. The pterygium grading method based on combined detection of microcirculation and bioelectricity according to claim 1, characterized in that, In step S2, the measurement is performed using a contact measurement electrode probe and a reference electrode placed on the skin surface away from the eye, and the potential difference between the measurement electrode probe and the reference electrode is recorded by a bioelectric amplifier.

4. The pterygium grading method based on combined detection of microcirculation and bioelectricity according to claim 1, characterized in that, In step S3, the Activity Composite Index (PAI) is calculated using the following formula: Among them, VD pterygium and FI pterygium Vascular density and blood flow index of the pterygium region; VD normal and FI normal The vascular density and blood flow index of the normal bulbar conjunctiva control area; RPD pterygium and RPD normal The values ​​represent the resting transmembrane potential difference between the pterygium region and the normal bulbar conjunctiva control region, respectively; w1, w2, and w3 are preset weighting coefficients.

5. The pterygium grading method based on combined detection of microcirculation and bioelectricity according to claim 1, characterized in that, The bioelectric parameter acquisition step in step S2 further includes acquiring the bioelectric signal stabilization time (ST), which is the time required for the fluctuation amplitude of the measured potential signal to stabilize within a preset threshold from the moment the measuring electrode probe contacts the tissue surface. Furthermore, in step S3, the calculation of the Activity Composite Index (PAI) also includes a process of comparing and integrating the bioelectrical signal stabilization time (ST) of the pterygium region and the normal bulbar conjunctival control region.

6. The pterygium grading method based on combined detection of microcirculation and bioelectricity according to claim 5, characterized in that, The acquisition of the bioelectric signal stabilization time (ST) includes: triggering timing when the measuring electrode probe contacts the tissue surface, and calculating the signal volatility index within a sliding time window in real time; stopping timing when the signal volatility index is continuously lower than a preset stability criterion threshold for the first time, and recording the timing duration as the bioelectric signal stabilization time (ST); wherein, the signal volatility index is the standard deviation or peak-to-peak value of the potential signal within the sliding time window.

7. The pterygium grading method based on combined detection of microcirculation and bioelectricity according to claim 5, characterized in that, In step S3, the formula for calculating the Activity Composite Index (PAI) is further set as follows: Among them, ST pterygium and ST n*rmal The values ​​represent the bioelectrical signal stabilization time in the pterygium region and the normal bulbar conjunctiva control region, respectively, with w4 being a newly added preset weighting coefficient.

8. The pterygium grading method based on combined detection of microcirculation and bioelectricity according to claim 5, characterized in that, The process of acquiring the steady-state time (ST) of the bioelectric signal further includes acquiring the steady-state time change rate (STCR), and the step of acquiring the steady-state time change rate (STCR) is as follows: Instruct subjects to keep their eyes open after completing one blink; At at least two different time points during the eye-opening state, the time to steady-state (ST) of the bioelectrical signal was repeatedly measured at the same measurement point in the pterygium region and the same measurement point in the normal bulbar conjunctiva control region to obtain their respective time-series data; Based on the time series data, the steady-state time rate of change (STCR) is calculated. The steady-state time rate of change (STCR) is obtained by performing linear regression fitting on the time series data points to obtain the slope, or by calculating the difference between the steady-state time (ST) of the bioelectric signal at the preset end time point and the start time point and then dividing it by the time interval.

9. The pterygium grading method based on combined detection of microcirculation and bioelectricity according to claim 8, characterized in that, In step S3, the calculation of the Activity Composite Index (PAI) further includes a process of comparing and integrating the steady-time rate of change (STCR) of the pterygium region and the normal bulbar conjunctival control region.

10. The pterygium grading method based on combined detection of microcirculation and bioelectricity according to claim 9, characterized in that, The formula for calculating the Activity Composite Index (PAI) is further set as follows: Among them, STCR pterygium and STCR normal The values ​​represent the rate of change over the steady-state time in the pterygium region and the normal bulbar conjunctiva control region, respectively, with w5 being a newly added preset weighting coefficient.

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