Laser irradiation progress prediction method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a laser irradiation progress prediction method and device, equipment and a storage medium, and relates to the technical field of medical treatment. The method comprises the following steps: acquiring various physiological parameters when a target part is subjected to laser irradiation; the physiological parameters comprise impedance of nucleus pulposus tissue in the target part, temperature distribution in the target part, pressure in the nucleus pulposus tissue and a backscattered light signal with a preset wavelength; the multiple physiological parameters are input into a first model, and the first model determines weight coefficients corresponding to the various physiological parameters according to the temperature distribution in the target part and the current target stage where laser irradiation is located according to the target stage; each physiological parameter has a corresponding weight coefficient in each stage; the first model outputs a prediction result of whether laser irradiation reaches a preset progress or not according to the various physiological parameters and the corresponding weight coefficients. According to the invention, the prediction of whether the laser irradiation progress reaches the preset progress is realized, and the prediction precision and the effectiveness of laser irradiation are improved.

Description

Technical Field

[0001] This application relates to the field of medical technology, and more specifically, to a method, apparatus, device, and storage medium for predicting the progress of laser irradiation. Background Technology

[0002] Percutaneous Laser Disc Repair (PLDR) is a minimally invasive technique that upgrades traditional percutaneous laser disc decompression. It uses a 970nm semiconductor low-energy laser to gently thermoplasticize and thermocapillary effect the herniated nucleus pulposus while injecting isotonic or hypertonic saline solution. This repairs the annulus fibrosus, reduces the size of the herniation, and relieves nerve root compression, rather than simply vaporizing the tissue.

[0003] However, the relevant technologies have the problem of not being able to accurately predict whether laser irradiation has reached the preset progress. Summary of the Invention

[0004] This application provides a method, apparatus, device, and storage medium for predicting the progress of laser irradiation, which solves the technical problem that it is difficult to accurately predict whether laser irradiation has reached a preset progress.

[0005] According to a first aspect of the embodiments of this application, a method for predicting the progress of laser irradiation is provided, the method comprising: Multiple physiological parameters are acquired when laser irradiation is applied to the target area. These physiological parameters include the impedance of the nucleus pulposus tissue within the target area, the temperature distribution within the target area, the pressure within the nucleus pulposus tissue, and the backscattered light signal at a preset wavelength. Multiple physiological parameters are input into a pre-trained first model. The first model determines the current target stage of laser irradiation based on the temperature distribution within the target area, and determines the corresponding weight coefficients for various physiological parameters based on the target stage. Each physiological parameter has a corresponding weight coefficient in each stage. The first model outputs a prediction result on whether laser irradiation has reached the preset progress based on various physiological parameters and corresponding weighting coefficients. The first model is trained through supervised learning using multiple training samples. The training samples are various physiological parameters of the target area when laser irradiation is performed, and the training label is whether the laser irradiation has reached the preset progress.

[0006] In one possible implementation Laser irradiation includes three stages: the first stage, the second stage, and the third stage. When the target stage is the first stage, the temperature distribution is in the first temperature range, and the weighting coefficient of the temperature distribution is the largest. When the target stage is the second stage, the temperature distribution is in the second temperature range, and the weighting coefficient of the temperature distribution is less than that in the first stage. The weighting coefficients of the impedance of the nucleus pulposus and the backscattered light signal are both greater than those in the first stage. When the target stage is the third stage, the temperature distribution is in the third temperature range, and the weighting coefficients of the pressure and impedance of the nucleus pulposus are both greater than those in the second stage. The first temperature range is smaller than the second temperature range, and the second temperature range is smaller than the third temperature range.

[0007] In another possible implementation, if it is determined that the parameter values ​​of multiple physiological parameters satisfy the first condition, then the multiple physiological parameters are input into the first model; The first condition includes at least one of the following: The impedance of the nucleus pulposus tissue is within the first threshold range; The temperature of various tissues within the target area does not exceed the corresponding first temperature threshold. The change in intensity or spectral characteristics of the backscattered light signal per unit time shall not exceed the corresponding change threshold.

[0008] In another possible implementation, if the values ​​of multiple physiological parameters are determined to satisfy the first condition, then the laser power of the laser is reduced. The first condition includes: The impedance of the nucleus pulposus tissue is within the first threshold range; The temperature of various tissues within the target area does not exceed the corresponding first temperature threshold. The change in intensity or spectral characteristics of the backscattered light signal per unit time shall not exceed the corresponding change threshold.

[0009] In yet another possible implementation, the laser is turned off if it is determined that there is at least one type of tissue with a temperature greater than the second temperature threshold; the second temperature threshold is greater than the first temperature threshold. If it is determined that the temperature of at least one type of tissue in the target area is between a first temperature threshold and a second temperature threshold, then the first temperature difference between the temperature of at least one type of tissue and the first temperature threshold is obtained. For each type of tissue, determine the total laser power adjustment value required for the tissue based on the first temperature difference and the laser power adjustment value required per unit temperature difference. The maximum value of the total laser power adjustment is taken as the target adjustment value, and the laser power of the laser is reduced based on the target adjustment value; the difference between the laser power before reduction and the laser power after reduction is the target adjustment value.

[0010] In another possible implementation, if the predicted result is that the laser irradiation reaches the preset progress, then the laser irradiation is stopped. If the prediction result is that the laser irradiation has not reached the preset progress, then the laser irradiation of the target area will continue.

[0011] According to a second aspect of the embodiments of this application, a prediction system is provided, the prediction system comprising: a processor, a data acquisition device, a laser, and a display screen; The processor is used to execute the aforementioned method for predicting the progress of laser irradiation.

[0012] The data acquisition device is used to collect multiple physiological parameters in real time. A laser is used to irradiate a target area. A display screen is used to show the prediction results and set the laser parameters.

[0013] According to a third aspect of the embodiments of this application, an electronic device is provided, the electronic device including a memory, a processor and a computer program stored in the memory, wherein the processor executes the program to implement the steps of the method provided in the first aspect.

[0014] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps of the method provided in the first aspect.

[0015] According to a fifth aspect of the present application, a computer program product is provided, the computer program product including computer instructions stored in a computer-readable storage medium, wherein when a processor of a computer device reads the computer instructions from the computer-readable storage medium, the processor executes the computer instructions, causing the computer device to perform steps implementing the method provided in the first aspect.

[0016] The beneficial effects of the technical solutions provided in this application are: The laser irradiation progress prediction method provided in this application acquires various physiological parameters during laser irradiation of a target area, enabling real-time monitoring of the target area's physiological state during the irradiation process. These physiological parameters are input into a first model, which determines the current target stage of the laser irradiation based on the temperature distribution within the target area. The model then determines the corresponding weight coefficients for each physiological parameter based on the target stage. This allows for dynamic adjustment of the weight coefficients of each physiological parameter before performing a pre-defined progress analysis. Consequently, the first model can analyze whether the pre-defined progress has been reached based on the importance of each physiological parameter at the current stage during prediction, providing strong data support for subsequent analysis.

[0017] The first model outputs a prediction result on whether laser irradiation has reached the preset progress based on various physiological parameters and corresponding weight coefficients. Since the first model is trained by supervised learning from multiple training samples, and the training samples are various physiological parameters of the target area when laser irradiation is performed, with the training label being whether the laser irradiation has reached the preset progress, after inputting multiple physiological parameters into the first model, the prediction result on whether the laser irradiation has reached the preset progress can be obtained from the output of the first model. This enables real-time determination of whether the preset progress of laser irradiation has been reached during the laser irradiation process. The first model analyzes whether the preset progress has been reached based on multiple physiological parameters and corresponding weight coefficients, avoiding the use of the same analysis strategy to analyze multiple physiological parameters throughout the entire laser irradiation process. It effectively combines the current stage of laser irradiation and performs multi-dimensional comprehensive analysis based on the weight information of each physiological parameter, effectively reducing the risk of misjudgment caused by a single parameter and a single analysis strategy, achieving a refined judgment of the preset progress, and improving the accuracy and effectiveness of the preset progress prediction of laser irradiation. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below.

[0019] Figure 1 A schematic diagram of the system architecture for the method of predicting laser irradiation progress provided in the embodiments of this application; Figure 2 A flowchart illustrating a method for predicting laser irradiation progress provided in an embodiment of this application; Figure 3 A flowchart illustrating another method for predicting laser irradiation progress provided in an embodiment of this application; Figure 4 A schematic flowchart illustrating the laser power reduction method in a laser irradiation progress prediction method provided in this application embodiment; Figure 5 A flowchart illustrating another method for predicting the progress of laser irradiation provided in this application embodiment; Figure 6 This is a schematic diagram of the structure of a laser irradiation system provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of a catheter provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of a prediction system provided in an embodiment of this application; Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0020] The embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the embodiments described below with reference to the accompanying drawings are exemplary descriptions for explaining the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions of the embodiments of this application.

[0021] Those skilled in the art will understand that, unless otherwise stated, the singular forms “a,” “an,” and “the” used herein may also include the plural forms. It should be further understood that the terms “comprising” and “including” as used in embodiments of this application mean that the corresponding feature can be implemented as the presented feature, information, data, step, operation, element, and / or component, but do not exclude implementation as other features, information, data, step, operation, element, component, and / or combinations thereof supported by the art. It should be understood that when we say that an element is “connected” or “coupled” to another element, the one element can be directly connected or coupled to the other element, or it can mean that the one element and the other element establish a connection relationship through an intermediate element. Furthermore, “connected” or “coupled” as used herein can include wireless connection or wireless coupling. The term “and / or” as used herein indicates at least one of the items defined by the term; for example, “A and / or B” can be implemented as “A,” or as “B,” or as “A and B.”

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0023] The relevant technologies are explained below: In related technologies, during laser irradiation, the determination of whether the laser irradiation has reached the preset progress relies on fixed parameters or the operator's extensive experience, which leads to problems of inaccurate and inconsistent progress judgment.

[0024] In related technologies, the true state of tissue within the target area during laser irradiation is usually determined by monitoring a single physiological parameter, which suffers from the problem of limited data.

[0025] To address at least one of the aforementioned technical problems or areas requiring improvement in related technologies, this application proposes a method for predicting the progress of laser irradiation. This method acquires multiple physiological parameters during laser irradiation of a target area, enabling real-time monitoring of the physiological state of the target area during laser irradiation. These physiological parameters are input into a first model, which is trained using supervised learning from multiple training samples. The training samples consist of multiple physiological parameters during laser irradiation of the target area, and the training labels indicate whether the laser irradiation has reached a preset progress. Therefore, after inputting these physiological parameters into the first model, a prediction result indicating whether the laser irradiation has reached the preset progress can be obtained. This allows for real-time determination of whether the preset progress of laser irradiation has been reached during the laser irradiation process, and improves the accuracy and effectiveness of predicting the preset progress of laser irradiation by using multiple physiological parameters during laser irradiation.

[0026] The technical solutions of this application and their effects are described below through several exemplary embodiments. It should be noted that the following embodiments can be referenced, borrowed from, or combined with each other. Identical terms, similar features, and similar implementation steps in different embodiments will not be repeated.

[0027] Figure 1 This is a schematic diagram of the system architecture for a method to predict the progress of laser irradiation provided in an embodiment of this application. The system architecture includes a prediction system 120 and a server 140.

[0028] The prediction system 120 is equipped with and runs an application program that predicts the progress of laser irradiation. The prediction system 120 is used to acquire various physiological parameters when laser irradiating a target area, input the various physiological parameters into a pre-trained first model, and obtain a prediction result output by the first model as to whether the laser irradiation has reached the preset progress.

[0029] The prediction system 120 is connected to the server 140 via a wireless or wired network.

[0030] Server 140 includes at least one of a single server, multiple servers, a cloud computing platform, and a virtualization center. Illustratively, server 140 includes a processor 144 and a memory 142, the memory 142 including a display module 1421, a control module 1422, and a receiving module 1423. Server 140 provides background services for the application of the method. Optionally, server 140 undertakes the primary computational work, and prediction system 120 undertakes secondary computational work; or, server 140 undertakes secondary computational work, and prediction system 120 undertakes primary computational work; or, server 140 and prediction system 120 collaborate on computation using a distributed computing architecture.

[0031] This application provides a method for predicting the progress of laser irradiation, such as... Figure 2 As shown, the method includes: S101 acquires various physiological parameters when laser irradiating the target area.

[0032] In the embodiments of this application, the target area refers to the area currently being irradiated with laser. The target area is a part of the human body. For example, laser irradiation can be used to remove a herniated intervertebral disc, to precisely cut muscles, fat and other tissues, to remove tumors, or to remove decayed tooth tissue.

[0033] In the embodiments of this application, physiological parameters refer to the physiological parameters of the target site, such as the current temperature, pressure, impedance, and other parameters that can characterize the physiological state of the target site.

[0034] In this embodiment of the application, the physiological parameters include the impedance of the nucleus pulposus tissue in the target area, the temperature distribution in the target area, the pressure in the nucleus pulposus tissue, and the backscattered light signal of a preset wavelength.

[0035] In this embodiment, when the target site is the intervertebral disc, the impedance of the nucleus pulposus tissue within the target site is used to reflect changes in the water content and ionic conductivity of the nucleus pulposus tissue. When the nucleus pulposus tissue vaporizes or dehydrates, the impedance increases significantly. During laser irradiation of the intervertebral disc, the hydration of the disc affects the laser propagation effect. If the nucleus pulposus has a low water content (i.e., high impedance), the laser energy may not be effectively transmitted to the deeper layers of the intervertebral disc, affecting the laser irradiation effect.

[0036] In this embodiment, by acquiring the temperature distribution of the nucleus pulposus tissue within the target area, the propagation, absorption, and conversion of laser energy within the intervertebral disc can be determined in real time. Different tissues have varying tolerances to temperature changes. Increased intervertebral disc temperature can lead to accelerated metabolism, fibrosis, and collagen remodeling in tissue cells. However, excessively high temperatures may cause tissue overheating, resulting in cell damage or necrosis. During laser irradiation, the temperature within the intervertebral disc needs to be precisely controlled within a safe range. Real-time acquisition of the temperature distribution can help monitor for safety risks during laser irradiation of the intervertebral disc and determine whether the laser irradiation effect is insufficient.

[0037] In this embodiment of the application, laser irradiation of the intervertebral disc can heat and evaporate the nucleus pulposus tissue, thereby reducing the volume of the nucleus pulposus tissue and reducing the pressure inside the nucleus pulposus tissue. The reduction in pressure inside the nucleus pulposus tissue helps to relieve the pressure on the intervertebral disc. By obtaining real-time monitoring of the pressure inside the nucleus pulposus tissue, the decompression effect of laser irradiation on the nucleus pulposus tissue can be demonstrated.

[0038] In this embodiment, by analyzing the intensity or spectral characteristics of the backscattered light signal at a preset wavelength, it is possible to infer whether carbonization has occurred in the intervertebral disc (carbonization can cause drastic changes in scattering characteristics), and the power of the laser can be adjusted in a timely manner to avoid unnecessary tissue damage.

[0039] In this embodiment of the application, during the process of irradiating the target area with a laser, the physiological parameters of the tissue inside the target area are collected, thereby realizing real-time monitoring of the true physiological state of the tissue inside the target area and obtaining the state changes of the tissue inside the target area.

[0040] In this embodiment, during laser irradiation of the target area, the impedance of the nucleus pulposus tissue, the temperature distribution within the target area, the pressure within the nucleus pulposus tissue, and the backscattered light signal of a preset wavelength are acquired in real time. This enables real-time detection of the laser irradiation process from multiple dimensions. The tissue impedance, temperature distribution, pressure, and backscattered light signal of a specific wavelength are synchronously collected and fused as a comprehensive basis for judging the tissue state. This provides a more accurate result to help the first model predict whether the preset progress has been reached. Furthermore, through multi-parameter fusion sensing technology, the first model can cross-verify the changes in tissue state from multiple dimensions, including electrical, thermal, mechanical, and optical aspects. This enables accurate and objective judgment of whether the laser irradiation has reached the preset progress (such as ideal decompression or moderate denaturation), avoiding misjudgment based on a single signal.

[0041] S102, inputs multiple physiological parameters into the pre-trained first model. The first model determines the current target stage of laser irradiation based on the temperature distribution within the target area, and determines the corresponding weight coefficients of various physiological parameters based on the target stage.

[0042] In this embodiment, the laser irradiation of the target area involves multiple stages, each with a different purpose and temperature range. Therefore, the current target stage of the laser irradiation can be determined based on the temperature distribution within the target area. In this embodiment, each physiological parameter has a corresponding weighting coefficient at each stage. Since the purpose of laser irradiation differs at each stage, and multiple physiological parameters are acquired each time, with varying importance at different stages, a pre-established weighting coefficient for each physiological parameter at each stage is used. After determining the current stage based on the temperature distribution, the weighting coefficients for each physiological parameter are determined according to the target stage. This allows for the determination of the importance of different physiological parameters based on the weighting coefficients when predicting whether a preset progress has been reached, thereby improving prediction accuracy.

[0043] S103, the first model outputs a prediction result on whether laser irradiation has reached the preset progress based on various physiological parameters and corresponding weighting coefficients.

[0044] In this embodiment of the application, when the first model predicts whether laser irradiation has reached a preset progress based on the input physiological parameters, it determines the importance of the physiological parameter in the target progress according to the weight coefficient corresponding to the physiological parameter. Based on the importance of each physiological parameter, it predicts whether laser irradiation has reached the preset progress from multiple dimensions. For example, if the current target stage temperature has the highest weight coefficient, then the temperature distribution in the target area will dominate the prediction process, while other physiological parameters will be auxiliary parameters in the prediction process.

[0045] In this embodiment of the application, the first model is trained by supervised learning using multiple training samples. The training samples are various physiological parameters of the target area when laser irradiation is performed, and the training label is whether the corresponding laser irradiation has reached a preset progress.

[0046] In this embodiment of the application, before training the first model, a large number of physiological parameters of various samples collected when the target part is irradiated by laser are obtained. These physiological parameters are used as training samples, and whether the corresponding physiological parameters of the various samples have reached a preset progress is used as training labels to train the first model. For example, the first model is a convolutional neural network (CNN) or a long short-term memory network (LSTM). The goal of the first model is to identify the various physiological parameters a moment before the laser irradiation reaches the preset progress. That is, based on the input of various physiological parameters, it is determined whether the preset progress of laser irradiation has been reached.

[0047] In the embodiments of this application, the first model is a machine learning-based model. During the training process of the first model, a machine learning model (such as support vector machine SVM, random forest or neural network) is constructed and trained.

[0048] In this embodiment of the application, since the trained first model can determine the moment before the laser irradiation of the target part reaches the preset progress based on a variety of physiological parameters in the current state, the prediction result output by the first model is obtained.

[0049] Based on the above embodiments, as an optional embodiment, if the predicted result is that the laser irradiation has reached the preset progress, then the laser irradiation is stopped; if the predicted result is that the laser irradiation has not reached the preset progress, then the laser irradiation of the target area continues.

[0050] In this embodiment of the application, if the prediction result is that the laser irradiation has reached the preset progress, it means that the current collection of various physiological parameters indicates that the laser irradiation of the target area has reached the preset effect at the moment before, and therefore, the laser irradiation of the target area is stopped.

[0051] In this embodiment of the application, if the prediction result is that the laser irradiation has not reached the preset progress, it means that the current collection of various physiological parameters indicates that the laser irradiation of the target area has not yet reached the preset effect. Therefore, it is necessary to continue to irradiate the target area with laser so that the target area can reach the preset effect.

[0052] In this embodiment of the application, during the laser irradiation of the target area, multiple physiological parameters are collected in real time to continuously predict whether the laser irradiation has reached the preset progress, until it is determined that the laser irradiation has reached the preset progress, at which point the laser irradiation and the collection of multiple physiological parameters are stopped.

[0053] The laser irradiation progress prediction method provided in this application acquires various physiological parameters during laser irradiation of a target area, enabling real-time monitoring of the target area's physiological state during the irradiation process. Multiple physiological parameters are input into a first model. Based on the temperature distribution within the target area, the first model determines the current target stage of the laser irradiation and assigns weight coefficients to various physiological parameters according to the target stage. This allows for dynamic adjustment of the weight coefficients of each physiological parameter before performing a pre-defined progress analysis. Consequently, the first model can analyze whether the pre-defined progress has been achieved based on the importance of each physiological parameter at the current stage during prediction, providing strong data support for subsequent analysis.

[0054] The first model outputs a prediction result on whether laser irradiation has reached the preset progress based on various physiological parameters and corresponding weight coefficients. Since the first model is trained by supervised learning from multiple training samples, and the training samples are various physiological parameters of the target area when laser irradiation is performed, with the training label being whether the laser irradiation has reached the preset progress, after inputting multiple physiological parameters into the first model, the prediction result on whether the laser irradiation has reached the preset progress can be obtained from the output of the first model. This enables real-time determination of whether the preset progress of laser irradiation has been reached during the laser irradiation process. The first model analyzes whether the preset progress has been reached based on multiple physiological parameters and corresponding weight coefficients, avoiding the use of the same analysis strategy to analyze multiple physiological parameters throughout the entire laser irradiation process. It effectively combines the current stage of laser irradiation and performs multi-dimensional comprehensive analysis based on the weight information of each physiological parameter, effectively reducing the risk of misjudgment caused by a single parameter and a single analysis strategy, achieving a refined judgment of the preset progress, and improving the accuracy and effectiveness of the preset progress prediction of laser irradiation.

[0055] In this application embodiment, a method for predicting laser irradiation progress is provided, such as... Figure 3 As shown, the specific process is as follows: S201, acquires various physiological parameters when laser irradiating the target area; S202, input multiple physiological parameters into the pre-trained first model to obtain the prediction result of whether the laser irradiation has reached the preset progress output by the first model; S203, determine whether the prediction result is that the preset progress has been reached. If yes, proceed to step S204; otherwise, proceed to step S201. S204, Stop laser irradiation of the target area.

[0056] In the embodiments of this application, before inputting multiple physiological parameters into the first model, the multiple physiological parameters are filtered, amplified, and converted from digital to analog. Parameters with different physical dimensions (such as ohms, degrees Celsius, Pascals, and voltage values) are timestamped and normalized to form a unified and standardized multidimensional data stream.

[0057] Based on the above embodiments, as an optional embodiment, laser irradiation includes a first stage, a second stage, and a third stage. The first temperature range is smaller than the second temperature range, and the second temperature range is smaller than the third temperature range. When the target stage is the first stage, the temperature distribution is within the first temperature range, and the weighting coefficient of the temperature distribution is the largest.

[0058] In the embodiments of this application, the core objective of the first stage of laser irradiation is to achieve uniform preheating of the tissue in the target area, thereby laying the foundation for subsequent laser irradiation. Since the first stage is the preheating stage in the laser irradiation process, the corresponding temperature range is the smallest and the weighting coefficient corresponding to the temperature distribution is the largest. That is, the temperature distribution is the most important basis for prediction and judgment at this time, while other physiological parameters are used as auxiliary references for prediction and judgment.

[0059] In this embodiment, the first temperature range can be 0-50 degrees. When the laser irradiation of the current target stage is detected as the first stage based on the temperature distribution, the weight allocation mechanism inside the first model will automatically set the weight of temperature-related features (such as temperature gradient and temperature change rate) to the highest. At this time, even if the impedance or optical parameters of the nucleus pulposus tissue fluctuate slightly, the output of the first model is mainly driven by the temperature-related parameters.

[0060] In this embodiment of the application, when the target stage is the second stage, the temperature distribution is in the second temperature range, the weighting coefficient of the temperature distribution is less than the weighting coefficient in the first stage, and the weighting coefficients of the impedance of the nucleus pulposus and the backscattered light signal are both greater than the weighting coefficients in the first stage.

[0061] In the embodiments of this application, the core objective of the second stage of laser irradiation is to maximize the therapeutic effect while ensuring safety. In the second stage, the weighting coefficient corresponding to the temperature distribution is appropriately reduced, and the weighting coefficients of the impedance of the nucleus pulposus tissue and the backscattered light signal are significantly improved compared to the first stage.

[0062] In this embodiment, the second temperature range can be 50-70 degrees Celsius. When the currently acquired temperature distribution falls within this range, it indicates that the formal treatment zone has been entered. The weighting mechanism of the first model automatically adjusts, appropriately reducing the weight of the temperature distribution while maximizing the weight of electrical characteristics (such as impedance change rate) and optical characteristics (such as backscattered light signals). The first model then focuses more on the coordinated change pattern of impedance and temperature, as well as the tissue structure changes reflected by the optical signals, thereby making a more accurate judgment on whether the current stage has reached the preset progress.

[0063] In this embodiment of the application, when the target stage is the third stage, the temperature distribution is in the third temperature range. The weighting coefficients of the pressure and impedance of the nucleus pulposus are both greater than the weighting coefficients in the second stage. That is to say, the change in the impedance of the nucleus pulposus in the second stage becomes the key indicator of whether the current reaction has reached the preset progress. The first model closely monitors the rate of increase of the impedance of the nucleus pulposus and performs a collaborative analysis of the rate of increase of the temperature.

[0064] In the embodiments of this application, when in the third stage, it indicates that the treatment is approaching the end point and the tissue state is changing drastically. Any energy overshoot may cause irreversible damage. Therefore, the core objective at this time is to ensure that no tissue is subjected to irreversible damage. As a result, the weighting coefficients of the pressure and impedance within the nucleus pulposus are increased to the highest level.

[0065] In this embodiment, the third temperature range can be 70-100 degrees. The weighting mechanism of the first model will further tilt the decision focus towards mechanical characteristics (such as the rate of pressure change in the nucleus pulposus) and thermal accumulation characteristics (the impedance of the nucleus pulposus). At this time, the first model will become very sensitive to the slight changes in the above parameters. Once a synergistic feature that indicates tissue overshoot or damage (i.e., a sudden increase in pressure accompanied by abnormal impedance) is detected, the prediction result output by the first model will trigger corresponding protective measures even if the temperature has not reached the hard threshold.

[0066] It should be noted that the embodiments of this application do not specifically limit the first temperature range, the second temperature range and the third temperature range. The first temperature range, the second temperature range and the third temperature range mentioned above can be determined according to the actual situation of the target part.

[0067] In the above scheme, the first model dynamically adjusts the weight coefficients of each physiological parameter according to the current target stage of laser irradiation, thereby improving the laser irradiation process from a single preset progress judgment to a refined control of the entire process. This significantly improves the accuracy and safety of laser irradiation treatment. Based on the characteristics of different stages, different physiological parameters are used as the main references at different stages during the preset progress judgment process, making the physiological parameter analysis more consistent with the actual situation and making the preset progress judgment more reliable and accurate.

[0068] Based on the above embodiments, as an optional embodiment, if it is determined that the parameter values ​​of multiple physiological parameters meet the first condition, then the multiple physiological parameters are input into the first model; The first condition includes at least one of the following: The impedance of the nucleus pulposus tissue is within the first threshold range; The temperature of various tissues within the target area does not exceed the corresponding first temperature threshold. The change in intensity or spectral characteristics of the backscattered light signal per unit time shall not exceed the corresponding change threshold.

[0069] In this embodiment of the application, before inputting the currently acquired multiple physiological parameters into the first model, it is also necessary to determine whether there is a safety risk in the current laser irradiation based on the multiple physiological parameters, that is, to determine whether continuing laser irradiation will cause unnecessary damage to the body. When it is determined that the parameter values ​​of multiple physiological parameters meet the first condition, it means that continuing laser irradiation according to the current trend will not cause unnecessary damage to the body. Therefore, multiple physiological parameters are input into the first model to determine whether laser irradiation can reach the preset progress.

[0070] In this embodiment of the application, if any of the first conditions is not met, it indicates that there is a risk in continuing laser irradiation. Therefore, inputting multiple physiological parameters into the first model requires that each of the first conditions be met.

[0071] In this embodiment, if the impedance of the nucleus pulposus is too high, there is a possibility of carbonization of the nucleus pulposus. Carbonization will hinder the further penetration of laser energy, reduce the efficiency of subsequent treatment, and may trigger an inflammatory response due to the generation of carbon particles. If the impedance is too high, it means that the water content of the nucleus pulposus is reduced. Reduced water content will cause the nucleus pulposus to become harder, and hardened tissue will affect the treatment effect of laser. If the impedance of the nucleus pulposus is too low, it means that the nucleus pulposus is not currently being effectively treated by laser, resulting in poor treatment effect. Therefore, multiple physiological parameters will only be input into the first model when the impedance of the nucleus pulposus is within the first threshold range.

[0072] In the embodiments of this application, different tissues have different tolerances to temperature changes. Increased temperature in the intervertebral disc can lead to accelerated metabolism of tissue cells, fibrosis, collagen remodeling, and other changes. However, if the temperature is too high, it may cause tissue overheating, resulting in cell damage or necrosis. Therefore, the temperature of various tissues in the target area needs to be no greater than the corresponding first temperature threshold to ensure that continued laser irradiation will not lead to tissue necrosis.

[0073] In this embodiment, when the laser irradiates the carbonized region, most of the light energy is instantly absorbed and converted into heat energy, with almost no light being reflected or scattered back. Therefore, the intensity of the backscattered light decreases sharply. If the change in the intensity or spectral characteristics of the backscattered light signal per unit time exceeds a corresponding threshold, it indicates the possibility of carbonization in the nucleus pulposus tissue. Carbonization hinders further penetration of laser energy, reduces subsequent treatment efficiency, and may trigger an inflammatory response due to the generation of carbon particles, posing a safety risk. Therefore, it is necessary to input multiple physiological parameters into the first model when the change in the intensity or spectral characteristics of the backscattered light signal per unit time does not exceed the corresponding threshold.

[0074] In the above scheme, before inputting the various physiological parameters currently acquired into the first model, it is first determined whether the parameter values ​​of the physiological parameters meet the first condition. If the first condition is met, it means that there is no safety risk in the current laser treatment. Therefore, the parameter values ​​of the physiological parameters can be input into the first model to continue to judge whether the preset progress has been reached. This avoids the continuous use of laser to irradiate the target area when there is a safety risk, and effectively avoids unnecessary damage to the tissue of the target area.

[0075] Based on the above embodiments, as an optional embodiment, if it is determined that the parameter values ​​of multiple physiological parameters do not meet the first condition, the laser power of the laser is reduced; The first condition includes at least one of the following: The impedance of the nucleus pulposus tissue is within the first threshold range; The temperature of various tissues within the target area does not exceed the corresponding first temperature threshold. The change in intensity or spectral characteristics of the backscattered light signal per unit time shall not exceed the corresponding change threshold.

[0076] In this embodiment of the application, the laser is used to emit laser light to irradiate the target area. Reducing the laser power can be done by reducing the laser power appropriately while ensuring that the laser irradiation continues, or it can be done by directly reducing the laser power to 0, that is, turning off the laser.

[0077] In this embodiment, if at least one of the acquired physiological parameters does not meet the first condition, it indicates a safety risk in continuing laser irradiation of the target area. Therefore, laser irradiation of the target area is stopped or the laser irradiation power is reduced before substantial bodily harm is caused, thus avoiding unnecessary damage to the target area. In this embodiment, the first condition can be adaptively adjusted according to the current stage of laser irradiation. That is, before inputting physiological parameters into the first model, the current stage is determined based on the currently acquired temperature distribution, thereby determining the first condition corresponding to the current stage.

[0078] In this application embodiment, when the current stage is in the first stage, the first condition can be composed of the temperature distribution of each tissue in the target site not being greater than the corresponding first temperature threshold and the impedance of the nucleus pulposus tissue being within the first threshold range.

[0079] In this embodiment of the application, when the current stage is the second stage, the first condition includes: the rate of increase of impedance of the nucleus pulposus tissue is not greater than a preset rate of increase of impedance, the rate of increase of temperature is not greater than a preset rate of increase of temperature, and the change value of the spectral characteristics of backscattered light per unit time is not greater than the corresponding change threshold. For example, if the impedance of the nucleus pulposus tissue increases rapidly while the temperature increases slowly, it may indicate that the laser currently irradiating the target site is effectively used for tissue protein denaturation rather than simply generating heat. The above changes are the ideal treatment state. At the same time, the first model will also refer to the spectral changes of backscattered light to ensure that the tissue structure is undergoing the expected change. The stable change of internal pressure of the nucleus pulposus tissue serves as evidence of the stability of the treatment process. Therefore, when the above first condition is met, multiple physiological parameters are input into the first model to determine the preset progress. When the above first condition is not met, the laser power is reduced.

[0080] In this embodiment of the application, when the current stage is the third stage, the first condition can be that the temperature of various tissues in the target area is not greater than the corresponding first temperature threshold. That is, if the temperature of any type of tissue is greater than the preset first temperature threshold, the laser power will be reduced to 0.

[0081] In this embodiment, since excessive changes in the internal pressure and impedance of the nucleus pulposus tissue per unit time are considered precursors to tissue vaporization or carbonization, in the third stage, the first condition can also be that the rate of change of the internal pressure and impedance of the nucleus pulposus tissue per unit time is not greater than the corresponding threshold. That is, if any one of the contents of the first condition is not met, the laser power needs to be adjusted. For example, if the pressure inside the nucleus pulposus tissue increases too much per unit time, even if the temperature is still within a safe range, it will be determined that the first condition is not met, and the laser power will be reduced immediately. At the same time, a sudden decrease in the intensity of backscattered light may indicate a change in tissue structure.

[0082] In the above scheme, after obtaining multiple physiological parameters, if it is determined that the value of one of the physiological parameters does not meet the first condition, it indicates that there is a safety risk in the current laser irradiation process. In this case, the laser is immediately turned off, or the laser power is reduced to avoid irreversible damage to the tissues in the lumbar disc. Through this multi-parameter, multi-level cross-constraint and verification, the system ensures that the risk of tissue damage is minimized while achieving the therapeutic effect.

[0083] In this embodiment, the laser primarily irradiates the target area using a high-power, short-pulse evaporation mode. The evaporation mode of the laser needs to be switched when the following conditions occur: When the temperature approaches the first temperature threshold, in order to prevent tissue overheating and carbonization, the laser mode is switched to low-power continuous mode. When impedance suddenly increases (indicating tissue vaporization or carbonization), switch the laser from evaporation mode, which is used to quickly remove the protruding nucleus pulposus, to low-power thermoplastic mode, which is used for gentle thermoplastic repair of the annulus fibrosus. When the intracavitary pressure drops significantly (the pressure reduction target has been reached), in order to prevent excessive suction from causing damage to the intervertebral disc structure, stop the laser or switch to low-power maintenance mode. When the treatment phase changes (e.g., from decompression phase to tissue remodeling phase), the laser is stopped and the mode is switched according to the prediction results of the first model.

[0084] Based on the above embodiments, as an optional embodiment, a method for reducing laser power is provided, such as... Figure 4 As shown, the specific content is as follows: S301, determine that the values ​​of multiple physiological parameters do not meet the first condition; S302-1, If ​​it is determined that there is at least one type of tissue with a temperature greater than the second temperature threshold, then turn off the laser; S302-2, if it is determined that the temperature of at least one type of tissue in the target area is between a first temperature threshold and a second temperature threshold, then obtain the first temperature difference between the temperature of at least one type of tissue and the first temperature threshold. S303, for the first temperature difference and the laser power adjustment value required per unit temperature difference for each type of tissue, determine the total laser power adjustment value required for the tissue; S304, take the maximum value of the total laser power adjustment value as the target adjustment value, and reduce the laser power of the laser based on the target adjustment value; the difference between the laser power before reduction and the laser power after reduction is the target adjustment value.

[0085] In embodiment S301 of this application, after determining that the first condition is not met, it is also necessary to classify the risk level of the specific physiological parameters in order to provide a laser power reduction method that is more suitable for the current situation.

[0086] In S302-1 of this application embodiment, each type of tissue has its corresponding second temperature threshold. Since the second temperature threshold is greater than the first temperature threshold, the target tissue does not pose a safety risk when the temperature is less than the first temperature threshold. Therefore, based on the temperature of the tissue, it is divided into three risk levels: no risk when the temperature is below the first temperature threshold, high risk when the temperature is above the second temperature threshold, and low risk when the temperature is between the first and second temperature thresholds. Therefore, if the temperature of at least one type of tissue is greater than the second temperature threshold, it means that the current safety risk level of that type of tissue in the target area is the highest. Therefore, it is necessary to immediately stop laser irradiation of the target area.

[0087] In S302-2 of this application embodiment, when it is determined that the temperature of at least one type of tissue in the target area is between the first temperature threshold and the second temperature threshold, it indicates that the current risk level is low, and unnecessary damage to the tissue can be avoided by reducing the laser power. Therefore, at least one type of tissue with a temperature between the first temperature threshold and the second temperature threshold is first determined, and for each type of tissue, the first temperature difference between the tissue and the corresponding first temperature threshold is obtained.

[0088] In S303 of this application embodiment, a unit temperature difference refers to a temperature rise of one unit (usually 1 degree Celsius) in a tissue. Since the laser power adjustment value required for a unit temperature difference is different for each type of tissue, for example, the laser power required for skin tissue to rise by 1°C is 10 watts, and that required for adipose tissue is 15 watts. Therefore, for each type of tissue, the total laser power adjustment value required for that type of tissue is determined based on the first temperature difference of that type of tissue and the corresponding laser power adjustment value required for a unit temperature difference.

[0089] In S304 of this application embodiment, after obtaining the total laser power adjustment value for each type of tissue, all the total laser power adjustment values ​​are sorted. Since it is necessary to ensure that all tissues in the target area are not damaged by high temperature, the value with the largest total laser power adjustment value is selected as the target adjustment value. Based on the target adjustment value, the current laser power is reduced so that the difference between the laser power before reduction and the laser power after reduction is the target adjustment value.

[0090] In the above scheme, the potential risks to the target area during laser irradiation are divided into three levels. When the temperature of the tissue exceeds the corresponding second temperature threshold, it indicates a high-risk state, and the laser is directly turned off. When the temperature of the tissue is between the first and second temperature thresholds, it indicates a low-risk state, and the risk can be eliminated by adjusting the laser power. During the reduction of laser power, the total laser power adjustment value for each tissue in the target area is determined based on the first temperature difference of the tissue and the laser power adjustment required per unit temperature deviation. Since the intervertebral disc involves multiple types of tissues, it is necessary to ensure that all tissues are not damaged. Therefore, the maximum total laser power value is selected as the target adjustment value to adjust the laser power. This ensures that the laser continues to operate as much as possible while addressing the existing safety risks. The laser power is dynamically calculated and adjusted based on real-time temperature to ensure that the laser irradiation process is always within a safe range.

[0091] In this embodiment, when the first stage is in progress, if the temperature of a certain tissue in the target area is detected to be too high or too low, since impedance is closely related to tissue water content, and water content will directly affect the heat conduction effect, for example, if the temperature of a certain area is detected to rise too slowly, the impedance of the tissue in that area will be checked accordingly (a high impedance means dehydration or fibrosis). Therefore, the impedance of the nucleus pulposus tissue is referenced simultaneously to determine whether the laser needs to be adjusted. When it is determined to adjust the laser power, the adjustment range will also refer to the intensity of the backscattered light signal to avoid local overheating due to power sudden change. At the same time, the internal pressure of the tissue is monitored for safety to ensure that the pressure generated by the thermal effect is within a safe range. Throughout the process, the uniformity of temperature is the ultimate goal. With the assistance of electrical and optical parameters, the laser energy is finely and smoothly adjusted, and finally the physical output of power is completed by the actuator.

[0092] In this embodiment, when the first model processes multiple physiological parameters in the second stage, if the predicted progress has not been reached, the first model will not blindly adjust the laser power. Instead, based on the impedance of the nucleus pulposus tissue and the feedback of the backscattered light signal, it will fine-tune the duty cycle or frequency of the laser pulse to continue treatment with a better energy transfer method. Simultaneously, the current coordination status will be displayed to the operator via a screen. This embodiment provides a flowchart of a method for predicting the progress of laser irradiation, as shown below. Figure 5 As shown, the specific content is as follows: S401, acquires various physiological parameters when laser irradiating the target area; S402, determine whether the values ​​of multiple physiological parameters meet the first condition. If yes, proceed to step S403; if no, proceed to step S406. S403, input multiple physiological parameters into the first model to obtain the prediction results output by the first model; S404, determine whether the prediction result has reached the preset progress. If yes, proceed to S405; otherwise, proceed to step S401. S405, Stop laser irradiation of the target area; S406, determine whether there is at least one type of tissue with a temperature greater than the second temperature threshold. If yes, proceed to S405; otherwise, proceed to step S407. S407, Obtain a first temperature difference between the temperature of at least one type of tissue and a first temperature threshold; S408, for each type of tissue, for the first temperature difference and the laser power adjustment value required per unit temperature difference, determine the total laser power adjustment value required for the tissue; S409: The maximum value of the total laser power adjustment value is used as the target adjustment value, and the laser power of the laser is reduced based on the target adjustment value.

[0093] The laser irradiation progress prediction method provided in this application adopts a multi-physiological parameter fusion sensing technology (tissue impedance, multi-path temperature, pressure, optical feedback). The system can cross-verify the state changes of tissue in the target area from multiple dimensions of electrical, thermal, mechanical and optical, thereby achieving accurate and objective judgment of the preset progress (such as ideal decompression, moderate denaturation) and avoiding misjudgment based on a single signal.

[0094] By establishing a progress prediction model based on machine learning, the system can learn and identify multi-parameter feature patterns before laser irradiation reaches the preset progress, thus enabling it to predictively and automatically stop treatment when the preset progress is reached. This achieves a leap from "reactive" control to "predictive" control, significantly improving the anticipation and accuracy of the control.

[0095] Because a complete "monitoring-analysis-decision-control" closed loop has been constructed, the laser output can be automatically adjusted based on real-time feedback, thereby standardizing the laser irradiation process, greatly reducing the reliance on the operator's personal experience, and ensuring the consistency of laser irradiation effects among different patients and different operators.

[0096] In this application embodiment, a laser irradiation system is provided, such as Figure 6 As shown, the laser irradiation system is used to collect various physiological parameters during the laser irradiation process in real time, and to use intelligent algorithms to determine whether the laser irradiation has reached the preset progress and control the laser output, so as to achieve precise, automated and standardized laser irradiation of the target area.

[0097] In this embodiment, the laser irradiation system comprises a multi-parameter sensing module (1), a signal processing and data fusion unit (2), an intelligent judgment core (3), a closed-loop control decision unit (4), a laser energy output control module (5), an actuator (6), and a human-machine interface (7). The multi-parameter sensing module (1) is connected to the signal processing and data fusion unit (2) via a cable and is responsible for collecting raw physiological signals. The signal processing and data fusion unit (2) is electrically connected to the intelligent endpoint judgment core (3) and is responsible for transmitting the processed standardized data to the intelligent judgment core (3). The output of the intelligent judgment core (3) is connected to the closed-loop control decision unit (4). The output of the closed-loop control decision unit (4) is connected to the laser energy output control module (5). The laser energy output control module (5) controls the working state of the actuator (6) via a control line. The human-machine interface (7) is connected to each main unit in the system and is used to display the status and set parameters.

[0098] The laser irradiation system aims to achieve precision, automation, and standardization of intervertebral disc laser irradiation by sensing various physiological parameters in real time during the laser irradiation process, using intelligent algorithms to determine whether the preset progress of laser irradiation has been reached, and automatically controlling the laser output.

[0099] In this embodiment, the multi-parameter sensing module (1) is placed at the tip of the catheter and extends into the nucleus pulposus of the intervertebral disc as the catheter extends, responsible for real-time, in-situ acquisition of various physiological parameters. The multi-parameter sensing module (1) includes: a laser emitting fiber for transmitting laser light; an impedance measuring electrode pair consisting of two microelectrodes that measure the impedance of the tissue under low-frequency current to reflect changes in tissue water content and ionic conductivity. The impedance increases significantly when the tissue vaporizes or dehydrates; a miniature temperature sensor using multiple (e.g., four) thermocouples or fiber optic temperature sensors distributed at a certain spacing around the laser fiber to measure the temperature field distribution of the target site rather than a single point temperature, thereby monitoring the heat diffusion range; a pressure sensor diaphragm located on the side of the catheter to sense pressure changes inside the nucleus pulposus tissue and monitor the decompression effect; and a receiving fiber for receiving laser light of a specific wavelength reflected from the tissue. By analyzing the intensity or spectral characteristics of the backscattered light, it can be inferred whether the tissue has carbonized (carbonization causes a drastic change in scattering characteristics). The above sensor elements are integrated and packaged in the main body of the catheter and isolated from the internal perfusion channel to prevent interference. A schematic diagram of the catheter is shown below. Figure 7 As shown.

[0100] In this embodiment of the application, the signal processing and data fusion unit (2) is used to filter, amplify, and convert the acquired raw signal into an analog-to-digital signal, and to perform timestamp alignment and normalization processing on parameters of different physical dimensions (ohms, degrees Celsius, Pascals, voltage values) to form a unified and standardized multidimensional data stream.

[0101] In this embodiment, the intelligent judgment core (3) is used to determine whether the laser irradiation of the target part has reached the preset progress based on the multidimensional data stream input by the signal processing and data fusion unit (2). It internally stores or runs a trained machine learning model online. In predicting whether the preset progress has been reached, the model receives a continuous data stream (multiple physiological parameters) from the signal processing and data fusion unit (2), and the model outputs a score between 0 and 1. When the score exceeds the preset threshold (e.g., 0.95), it indicates that the prediction result is that the laser irradiation has reached the preset progress. When the score does not exceed the preset threshold, it indicates that the prediction result is that the laser irradiation has not reached the preset progress.

[0102] In this embodiment, the closed-loop control decision unit (4) is used to issue a "stop laser irradiation" command to the laser energy output control module (5) if the prediction result is determined to be that the preset progress has been reached, based on the prediction result output by the intelligent judgment core (3) and the preset logic. In addition, the unit also runs a dynamic safety protection subroutine: for example, if any temperature sensor reading exceeds 70°C, or the tissue impedance jumps instantaneously (indicating possible carbonization), the laser energy output control module (5) is instructed to reduce the laser power or suspend the output.

[0103] The laser energy output control module (5) and actuator (6) are used to precisely control the laser power of the irradiated laser and execute the instructions of the closed-loop control decision unit (4). This module can be a programmable laser power controller. The actuator (6) can be a semiconductor laser or an Nd:YAG laser with wavelengths such as 970nm or 1470nm.

[0104] In this embodiment, before laser irradiation of the target area, the doctor initializes the system, sets parameters, and selects the corresponding laser irradiation mode through the human-computer interaction interface (7). The system performs a self-check, loads the corresponding model and parameters, inserts the catheter, and, guided by real-time images, inserts the integrated sensor catheter into the target area (such as the intervertebral disc target area). After the doctor confirms, the actuator (6) starts to output laser according to the initial parameters. The multi-parameter sensing module (1) starts to synchronously and in real-time collect tissue impedance, multi-point temperature, intracavitary pressure, and backscattered light signals. The signal processing and data fusion unit (2) processes and fuses the collected raw signals to generate standardized multi-dimensional data frames. The intelligent judgment core (3) inputs the real-time data frames into the trained machine learning model, calculates and outputs the prediction result of whether the preset progress has been reached. The closed-loop control decision unit (4) determines whether the prediction result is that the preset progress has been reached. If not, it continues to collect signals; if so, it terminates the laser output and ends the laser irradiation. The system prompts that the laser irradiation is complete, and the doctor removes the catheter.

[0105] This application provides a prediction system, such as... Figure 8 As shown, the prediction system 80 may include: a processor 801, a data acquisition device 802, a laser 803, and a display screen 804. Specifically, processor 801 is used to execute the above-mentioned method for predicting the progress of laser irradiation.

[0106] The data acquisition device 802 is used to collect multiple physiological parameters in real time; Laser 803 is used for laser irradiation of target areas; Display screen 804 is used to display prediction results and set laser parameters.

[0107] The prediction system provided in this application acquires various physiological parameters during laser irradiation of a target area, enabling real-time monitoring of the target area's physiological state during the irradiation process. Multiple physiological parameters are input into a first model. Based on the temperature distribution within the target area, the first model determines the current target stage of the laser irradiation and assigns weight coefficients to various physiological parameters according to the target stage. This allows for dynamic adjustment of the weight coefficients of each physiological parameter before performing a pre-defined progress analysis. Consequently, the first model can analyze whether a pre-defined progress has been reached based on the importance of each physiological parameter at the current stage during prediction, providing strong data support for subsequent analysis.

[0108] The first model outputs a prediction result on whether laser irradiation has reached the preset progress based on various physiological parameters and corresponding weight coefficients. Since the first model is trained by supervised learning from multiple training samples, and the training samples are various physiological parameters of the target area when laser irradiation is performed, with the training label being whether the laser irradiation has reached the preset progress, after inputting multiple physiological parameters into the first model, the prediction result on whether the laser irradiation has reached the preset progress can be obtained from the output of the first model. This enables real-time determination of whether the preset progress of laser irradiation has been reached during the laser irradiation process. The first model analyzes whether the preset progress has been reached based on multiple physiological parameters and corresponding weight coefficients, avoiding the use of the same analysis strategy to analyze multiple physiological parameters throughout the entire laser irradiation process. It effectively combines the current stage of laser irradiation and performs multi-dimensional comprehensive analysis based on the weight information of each physiological parameter, effectively reducing the risk of misjudgment caused by a single parameter and a single analysis strategy, achieving a refined judgment of the preset progress, and improving the accuracy and effectiveness of the preset progress prediction of laser irradiation. The apparatus in this application embodiment can execute the method provided in this application embodiment, and the implementation principle is similar. The actions performed by each module in the apparatus of each embodiment of this application correspond to the steps in the method of each embodiment of this application. For detailed functional descriptions of each module of the apparatus, please refer to the descriptions in the corresponding methods shown above, which will not be repeated here.

[0109] Furthermore, the data acquisition device includes: Impedance measurement electrode pair, used to acquire the impedance of nucleus pulposus tissue in the target area; Miniature temperature sensors are used to collect the temperature within a target area; A pressure sensor diaphragm is used to collect pressure within the nucleus pulposus tissue; The receiving optical fiber is used to collect backscattered light signals at a preset wavelength.

[0110] In one possible implementation Laser irradiation includes three stages: the first stage, the second stage, and the third stage. When the target stage is the first stage, the temperature distribution is in the first temperature range, and the weighting coefficient of the temperature distribution is the largest. When the target stage is the second stage, the temperature distribution is in the second temperature range, and the weighting coefficient of the temperature distribution is less than that in the first stage. The weighting coefficients of the impedance of the nucleus pulposus and the backscattered light signal are both greater than those in the first stage. When the target stage is the third stage, the temperature distribution is in the third temperature range, and the weighting coefficients of the pressure and impedance of the nucleus pulposus are both greater than those in the second stage. The first temperature range is smaller than the second temperature range, and the second temperature range is smaller than the third temperature range.

[0111] In another possible implementation, if it is determined that the parameter values ​​of multiple physiological parameters satisfy the first condition, then the multiple physiological parameters are input into the first model; The first condition includes at least one of the following: The impedance of the nucleus pulposus tissue is within the first threshold range; The temperature of various tissues within the target area does not exceed the corresponding first temperature threshold. The change in intensity or spectral characteristics of the backscattered light signal per unit time shall not exceed the corresponding change threshold.

[0112] In another possible implementation, if the values ​​of multiple physiological parameters are determined to satisfy the first condition, then the laser power of the laser is reduced. The first condition includes: The impedance of the nucleus pulposus tissue is within the first threshold range; The temperature of various tissues within the target area does not exceed the corresponding first temperature threshold. The change in intensity or spectral characteristics of the backscattered light signal per unit time shall not exceed the corresponding change threshold.

[0113] In yet another possible implementation, the laser is turned off if it is determined that there is at least one type of tissue with a temperature greater than the second temperature threshold; the second temperature threshold is greater than the first temperature threshold. If it is determined that the temperature of at least one type of tissue in the target area is between a first temperature threshold and a second temperature threshold, then the first temperature difference between the temperature of at least one type of tissue and the first temperature threshold is obtained. For each type of tissue, determine the total laser power adjustment value required for the tissue based on the first temperature difference and the laser power adjustment value required per unit temperature difference. The maximum value of the total laser power adjustment is taken as the target adjustment value, and the laser power of the laser is reduced based on the target adjustment value; the difference between the laser power before reduction and the laser power after reduction is the target adjustment value.

[0114] In another possible implementation, if the predicted result is that the laser irradiation reaches the preset progress, then the laser irradiation is stopped. If the prediction result is that the laser irradiation has not reached the preset progress, then the laser irradiation of the target area will continue.

[0115] This application provides an electronic device (computer device / equipment / system) including a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of a laser irradiation progress prediction method, which can achieve the following compared to related technologies: By acquiring various physiological parameters during laser irradiation of the target area, real-time monitoring of the target area's physiological state is achieved. These parameters are input into a first model, which determines the current target stage of the laser irradiation based on the temperature distribution within the target area. The model then determines the corresponding weight coefficients for each physiological parameter based on the target stage. This allows for dynamic adjustment of the weight coefficients of each physiological parameter before performing a pre-defined progress analysis. Consequently, the first model can analyze whether the pre-defined progress has been achieved based on the importance of each physiological parameter at the current stage during prediction, providing strong data support for subsequent analysis.

[0116] The first model outputs a prediction result on whether laser irradiation has reached the preset progress based on various physiological parameters and corresponding weight coefficients. Since the first model is trained by supervised learning from multiple training samples, and the training samples are various physiological parameters of the target area when laser irradiation is performed, with the training label being whether the laser irradiation has reached the preset progress, after inputting multiple physiological parameters into the first model, the prediction result on whether the laser irradiation has reached the preset progress can be obtained from the output of the first model. This enables real-time determination of whether the preset progress of laser irradiation has been reached during the laser irradiation process. The first model analyzes whether the preset progress has been reached based on multiple physiological parameters and corresponding weight coefficients, avoiding the use of the same analysis strategy to analyze multiple physiological parameters throughout the entire laser irradiation process. It effectively combines the current stage of laser irradiation and performs multi-dimensional comprehensive analysis based on the weight information of each physiological parameter, effectively reducing the risk of misjudgment caused by a single parameter and a single analysis strategy, achieving a refined judgment of the preset progress, and improving the accuracy and effectiveness of the preset progress prediction of laser irradiation.

[0117] In one alternative embodiment, an electronic device is provided, such as Figure 9 As shown, Figure 9 The illustrated electronic device 4000 includes a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, for example, via a bus 4002. Optionally, the electronic device 4000 may further include a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 4004 is not limited to one type, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of this application.

[0118] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 4001 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0119] Bus 4002 may include a pathway for transmitting information between the aforementioned components. Bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 4002 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 9 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0120] The memory 4003 may be ROM (Read Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, other magnetic storage devices, or any other medium capable of carrying or storing computer programs and capable of being read by a computer, without limitation herein.

[0121] The memory 4003 is used to store computer programs that execute the embodiments of this application, and the execution is controlled by the processor 4001. The processor 4001 is used to execute the computer programs stored in the memory 4003 to implement the steps shown in the foregoing method embodiments.

[0122] The electronic device package may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 9 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments disclosed herein.

[0123] This application provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program can implement the steps and corresponding content of the aforementioned method embodiments. Compared with the prior art, it can achieve the following: By acquiring various physiological parameters during laser irradiation of the target area, real-time monitoring of the target area's physiological state is achieved. These parameters are input into a first model, which determines the current target stage of the laser irradiation based on the temperature distribution within the target area. The model then determines the corresponding weight coefficients for each physiological parameter based on the target stage. This allows for dynamic adjustment of the weight coefficients of each physiological parameter before performing a pre-defined progress analysis. Consequently, the first model can analyze whether the pre-defined progress has been achieved based on the importance of each physiological parameter at the current stage during prediction, providing strong data support for subsequent analysis.

[0124] The first model outputs a prediction result on whether laser irradiation has reached a preset progress based on various physiological parameters and corresponding weight coefficients. Since the first model is trained through supervised learning using multiple training samples, and these training samples consist of various physiological parameters during laser irradiation of the target area, with the training label indicating whether the laser irradiation has reached a preset progress, inputting multiple physiological parameters into the first model yields a prediction result indicating whether the laser irradiation has reached a preset progress. This allows for real-time determination of whether the preset progress has been reached during laser irradiation of the target area. The first model analyzes whether the preset progress has been reached based on multiple physiological parameters and corresponding weight coefficients, avoiding the use of the same analysis strategy for multiple physiological parameters throughout the entire laser irradiation process. It effectively combines the current stage of laser irradiation with multi-dimensional comprehensive analysis based on the weight information of each physiological parameter, effectively reducing the risk of misjudgment caused by a single parameter or analysis strategy. This achieves refined judgment of the preset progress and improves the accuracy and effectiveness of predicting the preset progress of laser irradiation. It should be noted that the computer-readable medium described above can be a computer-readable signal medium, a computer-readable medium, or any combination of the two. Computer-readable storage media can be, for example—but not limited to—electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium that can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0125] This application also provides a computer program product, including a computer program that, when executed by a processor, can implement the steps and corresponding content of the aforementioned method embodiments. Compared with the prior art, it can achieve: By acquiring various physiological parameters during laser irradiation of the target area, real-time monitoring of the target area's physiological state is achieved. These parameters are input into a first model, which determines the current target stage of the laser irradiation based on the temperature distribution within the target area. The model then determines the corresponding weight coefficients for each physiological parameter based on the target stage. This allows for dynamic adjustment of the weight coefficients of each physiological parameter before performing a pre-defined progress analysis. Consequently, the first model can analyze whether the pre-defined progress has been achieved based on the importance of each physiological parameter at the current stage during prediction, providing strong data support for subsequent analysis.

[0126] The first model outputs a prediction result on whether laser irradiation has reached the preset progress based on various physiological parameters and corresponding weight coefficients. Since the first model is trained by supervised learning from multiple training samples, and the training samples are various physiological parameters of the target area when laser irradiation is performed, with the training label being whether the laser irradiation has reached the preset progress, after inputting multiple physiological parameters into the first model, the prediction result on whether the laser irradiation has reached the preset progress can be obtained from the output of the first model. This enables real-time determination of whether the preset progress of laser irradiation has been reached during the laser irradiation process. The first model analyzes whether the preset progress has been reached based on multiple physiological parameters and corresponding weight coefficients, avoiding the use of the same analysis strategy to analyze multiple physiological parameters throughout the entire laser irradiation process. It effectively combines the current stage of laser irradiation and performs multi-dimensional comprehensive analysis based on the weight information of each physiological parameter, effectively reducing the risk of misjudgment caused by a single parameter and a single analysis strategy, achieving a refined judgment of the preset progress, and improving the accuracy and effectiveness of the preset progress prediction of laser irradiation. The terms "first," "second," "third," "fourth," "1," "2," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in a sequence other than that shown in the illustrations or text descriptions.

[0127] It should be understood that although arrows indicate various operation steps in the flowcharts of this application's embodiments, the order in which these steps are implemented is not limited to the order indicated by the arrows. Unless explicitly stated herein, in some implementation scenarios of this application's embodiments, the implementation steps in each flowchart can be executed in other orders as required. Furthermore, some or all steps in each flowchart, based on the actual implementation scenario, may include multiple sub-steps or multiple stages. Some or all of these sub-steps or stages can be executed at the same time, and each sub-step or stage can also be executed at different times. In scenarios where execution times differ, the execution order of these sub-steps or stages can be flexibly configured according to requirements, and this application's embodiments do not limit this.

[0128] The above are only optional implementation methods for some implementation scenarios of this application. It should be noted that for those skilled in the art, other similar implementation methods based on the technical concept of this application, without departing from the technical concept of this application, also fall within the protection scope of the embodiments of this application.

Claims

1. A method for predicting the progress of laser irradiation, characterized in that, include: To obtain various physiological parameters when laser irradiating a target area; The various physiological parameters include the impedance of the nucleus pulposus tissue in the target area, the temperature distribution in the target area, the pressure in the nucleus pulposus tissue, and the backscattered light signal of a preset wavelength; The various physiological parameters are input into a pre-trained first model. The first model determines the current target stage of the laser irradiation based on the temperature distribution within the target area, and determines the corresponding weight coefficients for various physiological parameters based on the target stage. Each physiological parameter has a corresponding weight coefficient in each stage. The first model outputs a prediction result on whether laser irradiation has reached the preset progress based on various physiological parameters and corresponding weighting coefficients. The first model is trained through supervised learning using multiple training samples. The training samples are various physiological parameters of the target area when laser irradiation is performed, and the training label is whether the laser irradiation has reached a preset progress.

2. The method according to claim 1, characterized in that, The laser irradiation includes a first stage, a second stage, and a third stage; When the target stage is the first stage, the temperature distribution is within the first temperature range, and the weighting coefficient of the temperature distribution is the largest. When the target stage is the second stage, the temperature distribution is in the second temperature range, the weighting coefficient of the temperature distribution is less than the weighting coefficient in the first stage, and the weighting coefficients of the impedance of the nucleus pulposus and the backscattered light signal are both greater than the weighting coefficients in the first stage. When the target stage is the third stage, the temperature distribution is in the third temperature range, and the weighting coefficients of the pressure in the nucleus pulposus and the impedance of the nucleus pulposus are both greater than the weighting coefficients in the second stage. Wherein, the first temperature range is smaller than the second temperature range, and the second temperature range is smaller than the third temperature range.

3. The method according to claim 1, characterized in that, The step of inputting the multiple physiological parameters into a pre-trained first model includes: If it is determined that the values ​​of the multiple physiological parameters satisfy the first condition, then the multiple physiological parameters are input into the first model; The first condition includes at least one of the following: The impedance of the nucleus pulposus tissue is within the first threshold range; The temperature of various tissues within the target area is not greater than the corresponding first temperature threshold. The change in intensity or spectral characteristics of the backscattered light signal per unit time is not greater than the corresponding change threshold.

4. The method according to claim 1, characterized in that, The process of acquiring various physiological parameters during laser irradiation of the target area further includes: If it is determined that the values ​​of the various physiological parameters do not meet the first condition, then the laser power of the laser is reduced. The first condition includes at least one of the following: The impedance of the nucleus pulposus tissue is within the first threshold range; The temperature of various tissues within the target area is not greater than the corresponding first temperature threshold. The change in intensity or spectral characteristics of the backscattered light signal per unit time is not greater than the corresponding change threshold.

5. The method according to claim 4, characterized in that, If it is determined that the parameter values ​​of the multiple physiological parameters meet the first condition, then reducing the laser power of the laser includes: If it is determined that at least one type of tissue has a temperature greater than the second temperature threshold, then the laser is turned off; the second temperature threshold is greater than the first temperature threshold. If it is determined that the temperature of at least one type of tissue in the target area is between the first temperature threshold and the second temperature threshold, then the first temperature difference between the temperature of the at least one type of tissue and the first temperature threshold is obtained; For each type of tissue, determine the total laser power adjustment value required for the tissue based on the first temperature difference and the laser power adjustment value required per unit temperature difference. The maximum value of the total laser power adjustment is taken as the target adjustment value, and the laser power of the laser is reduced based on the target adjustment value; the difference between the laser power before reduction and the laser power after reduction is the target adjustment value.

6. The method according to claim 1, characterized in that, The prediction result regarding whether the output laser irradiation has reached the preset progress also includes: If the predicted result is that the laser irradiation has reached the preset progress, then the laser irradiation will be stopped. If the prediction result indicates that the laser irradiation has not reached the preset progress, then the laser irradiation of the target area will continue.

7. A prediction system, comprising a processor, a data acquisition device, a laser, and a display screen; The processor is configured to execute the laser irradiation progress prediction method as described in any one of claims 1-6; The acquisition device is used to collect multiple physiological parameters in real time; The laser is used to irradiate the target area with laser light; The display screen is used to display the prediction results and set the parameters of the laser.

8. The system according to claim 7, characterized in that, The data acquisition device includes: Impedance measurement electrode pair, used to acquire the impedance of nucleus pulposus tissue in the target area; Miniature temperature sensors are used to collect the temperature within a target area; A pressure sensor diaphragm is used to collect pressure within the nucleus pulposus tissue; The receiving optical fiber is used to collect backscattered light signals at a preset wavelength.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the method according to any one of claims 1-6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1-6.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1-6.

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