Glioma 1p / 19q chromosome co-deletion detection method and device
Through the combination of Raman spectroscopy technology and classification model, the co-deletion status of glioma 1p/19q chromosomes is quickly and accurately detected, solving the problems of high detection costs and long time in the existing technology, and achieving low-cost and efficient detection Effect.
Patent Information
- Application Number
- CN202411535023.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-30
- Publication Date
- 2025-02-18
AI Technical Summary
In the prior art, the detection cost of glioma 1p/19q chromosome co-deletion is high and time-consuming, and there is a lack of efficient detection methods and means.
Raman spectroscopy technology was used to scan the tissue samples of glioma to be tested, and Raman spectroscopy data was obtained and feature extraction was performed. The classification prediction value was calculated using the trained classification model to assist in determining the co-deletion status of 1p/19q chromosomes.
The low-cost and rapid detection of glioma 1p/19q chromosome co-deletion status is achieved, which can partially replace the high-cost tumor gene detection and analysis function.
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Figure CN119470385A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of Raman spectroscopy detection, and in particular to a method and device for detecting 1p / 19q chromosome co-deletion in glioma. Background Art
[0002] Gliomas are the most common primary malignant brain tumors, accounting for 40%-50% of brain tumors and 70% of primary malignant brain tumors. They have short survival, high disability rate, poor therapeutic effect, and large heterogeneity of different molecular subtypes of gliomas. The combined deletion of the short arm of chromosome 1 (1p) and the long arm of chromosome 19 (19q) is an important molecular marker of gliomas (especially oligodendrogliomas), which is of great significance in pathological diagnosis, evaluation of the efficacy of radiotherapy and chemotherapy, and prediction of clinical prognosis.
[0003] However, the detection of 1p / 19q chromosome co-deletion generally uses tissue section samples for fluorescence hybridization detection or extracts the genome for in vitro amplification, which is costly and time-consuming, and is not conducive to the patient's entire treatment process. Currently, there is no alternative efficient detection method and means. Summary of the invention
[0004] The purpose of the present application is to provide a method and device for detecting glioma 1p / 19q chromosome co-deletion, which can realize low-cost and rapid detection of glioma 1p / 19q chromosome co-deletion status.
[0005] To achieve the above objectives, this application provides the following solutions.
[0006] In a first aspect, the present application provides a method for detecting glioma 1p / 19q chromosome co-deletion, comprising: performing Raman spectroscopy scanning on a glioma tissue sample to be tested to obtain Raman spectroscopy data; preprocessing the Raman spectroscopy data to obtain normalized Raman spectroscopy data; extracting the intensity value at the characteristic displacement from the normalized Raman spectroscopy data; the characteristic displacement includes a Raman displacement of 502 cm -1 、683cm -1 、1161cm -1 、1166cm -1 、1566cm -1 、1571cm -1 、2874cm -1 、2899cm -1 、2903cm -1 、3004cm -1 、3140cm -1 、3144cm -1 、3172cm -1 、3192cm -1 、3268cm -1、3308cm -1 、3367cm -1 、3382cm -1 、3486cm -1 and 3494cm -1 ; Input the intensity value at the characteristic displacement into the classification model to calculate the classification prediction value; the classification model is a multivariate linear equation of the classification prediction value and the intensity value at the characteristic displacement; the classification prediction value is used to assist in determining the 1p / 19q chromosome co-deletion state of the glioma tissue sample to be tested; the 1p / 19q chromosome co-deletion state includes 1p / 19q chromosome co-deletion positive and 1p / 19q chromosome co-deletion negative.
[0007] Optionally, the Raman spectrum data is preprocessed to obtain normalized Raman spectrum data, including: removing fluorescence background from the Raman spectrum data to obtain Raman spectrum data with fluorescence background removed; smoothing and denoising the Raman spectrum data with fluorescence background removed to obtain smoothed and denoised Raman spectrum data; and normalizing the smoothed and denoised Raman spectrum data to obtain normalized Raman spectrum data.
[0008] Optionally, the classification model is determined based on a LASSO regression algorithm; the process of determining the classification model includes: obtaining a number of Raman spectrum samples marked with 1p / 19q chromosome co-deletion status, and preprocessing and extracting characteristic spectrum information to construct a sample data set; the sample data set includes characteristic spectrum information and 1p / 19q chromosome co-deletion status corresponding to a number of normalized Raman spectrum samples; the characteristic spectrum information includes intensity values at a number of Raman shifts; the 1p / 19q chromosome co-deletion status includes 1 and 0, wherein 1 indicates that 1p / 19q chromosome co-deletion is positive, and 0 indicates that 1p / 19q chromosome co-deletion is negative; a linear regression model is constructed with the 1p / 19q chromosome co-deletion status as the target variable and the characteristic spectrum information as the characteristic variable; according to the sample data set, a 5-fold cross validation is used to determine the optimal regularization parameter value, and based on the optimal regularization parameter value, the linear regression model is trained using the LASSO regression algorithm to gradually reduce the coefficient of the irrelevant Raman shift in the linear regression model to zero, and the characteristic shift and classification model are screened.
[0009] Optionally, the classification model is expressed as: y=0.6647+(-0.2678×I 502 )+(-0.0599×I 683 )+0.1346×I 1161 +0.1769×I 1166 +(-0.0920×I 1566 )+(-0.2460×I1571 )+(-0.3546×I 2874 )+(-0.0333×I 2899 )+(-0.0551×I 2903 )+(-0.2218×I 3004 )+0.1193×I 3140 +0.0900×I 3144 +0.1882×I 3172 +0.0526×I 3192 +0.0237×I 3268 +0.0300×I 3308 +(-0.5208×I 3367 )+(-0.0340×I 3382 )+0.0402×I 3486 +0.0323×I 3494 ; Wherein, y represents the classification prediction value. When y≥0.5, it is judged as a glioma with positive 1p / 19q chromosome co-deletion, and when y<0.5, it is judged as a glioma with negative 1p / 19q chromosome co-deletion; I 502 Indicates the Raman shift of 502 cm -1 The intensity value at I 683 Indicates the Raman shift of 683cm -1 The intensity value at I 1161 Indicated at Raman shift 1161cm -1 The intensity value at I 1166 Indicates that the Raman shift is 1166cm -1 The intensity value at I 1566 Indicates the Raman shift of 1566cm -1 The intensity value at I 1571 Indicates that the Raman shift is 1571cm -1 The intensity value at I 2874 Indicated at Raman shift 2874cm -1 The intensity value at I 2899 Indicates the Raman shift of 2899 cm -1 The intensity value at I 2903 Indicated at Raman shift 2903cm -1 The intensity value at I 3004 Indicates the Raman shift of 3004cm -1 The intensity value at I 3140 Indicates the Raman shift of 3140 cm -1 The intensity value at I 3144 Indicates that the Raman shift is 3144cm -1 The intensity value at I 3172 Indicated at Raman shift 3172cm -1The intensity value at I 3192 Indicated at Raman shift 3192cm -1 The intensity value at I 3268 Indicates that the Raman shift is 3268cm -1 The intensity value at I 3308 Indicates that the Raman shift is 3308cm -1 The intensity value at I 3367 Indicates that the Raman shift is 3367cm -1 The intensity value at I 3382 Indicated at Raman shift 3382cm -1 The intensity value at I 3486 Indicates that the Raman shift is 3486cm -1 The intensity value at I 3494 Indicates that the Raman shift is 3494cm -1 The intensity value at .
[0010] Optionally, the Raman spectrum data is processed to remove the fluorescence background to obtain the Raman spectrum data with the fluorescence background removed, including: using an adaptive iterative reweighted penalized least squares method to process the Raman spectrum data to remove the fluorescence background to obtain the Raman spectrum data with the fluorescence background removed.
[0011] Optionally, performing smoothing and denoising processing on the Raman spectrum data from which the fluorescence background is removed to obtain smoothed and denoised Raman spectrum data includes: performing smoothing and denoising processing on the Raman spectrum data from which the fluorescence background is removed using a Savitzky-Golay smoothing algorithm to obtain smoothed and denoised Raman spectrum data.
[0012] Optionally, normalizing the smoothed and denoised Raman spectrum data to obtain normalized Raman spectrum data includes: normalizing the smoothed and denoised Raman spectrum data using a maximum-minimum normalization algorithm to obtain normalized Raman spectrum data.
[0013] In a second aspect, the present application provides a glioma 1p / 19q chromosome co-deletion detection device, which adopts the above-mentioned glioma 1p / 19q chromosome co-deletion detection method, including: a laser, used to emit laser to the glioma tissue sample to be tested; a spectrometer, used to collect Raman light scattered by the glioma tissue sample to be tested, to obtain Raman spectrum data, to pre-process the Raman spectrum data to obtain normalized Raman spectrum data, to extract the intensity value at the characteristic displacement from the normalized Raman spectrum data, and to input the intensity value at the characteristic displacement into a classification model to calculate a classification prediction value.
[0014] Optionally, the glioma 1p / 19q chromosome co-deletion detection device further includes: an optical microscopy platform for placing the glioma tissue sample to be tested, and adjusting the position and height of the glioma tissue sample to be tested.
[0015] Optionally, the glioma 1p / 19q chromosome co-deletion detection device also includes: a display connected to the spectrometer, for displaying the classification prediction value and the auxiliary determination result; the auxiliary determination result is determined based on the classification prediction value.
[0016] Optionally, the glioma 1p / 19q chromosome co-deletion detection device also includes: an optical fiber probe, which is respectively connected to the laser and the spectrometer, and is used to transmit the laser emitted by the laser to the surface of the glioma tissue sample to be tested, and transmit the Raman light scattered by the surface of the glioma tissue sample to be tested to the spectrometer.
[0017] Optionally, the excitation wavelength of the laser is 532 nm, and the integration time is 1 to 3 seconds.
[0018] According to the specific embodiments provided by the present application, the present application discloses the following technical effects: The present application provides a method and device for detecting 1p / 19q chromosome co-deletion in glioma, firstly, a Raman spectrum scan is performed on the glioma tissue sample to be tested to obtain Raman spectrum data, then the Raman spectrum data is preprocessed and feature extracted to obtain the intensity value at the characteristic displacement, and finally the intensity value at the characteristic displacement is input into a pre-trained classification model to calculate the classification prediction value to assist in determining the 1p / 19q chromosome co-deletion state of the glioma tissue sample to be tested. Compared with the prior art, the present application utilizes Raman spectroscopy technology, performs Raman spectroscopy analysis on the glioma tissue sample to be tested, and combines the trained classification model to achieve low-cost and rapid detection of the 1p / 19q chromosome co-deletion state of glioma, which can partially replace the high-cost tumor gene detection and analysis function. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0020] Figure 1 A flow chart of the method for detecting glioma 1p / 19q chromosome co-deletion provided in this application.
[0021] Figure 2The present application provides a displacement feature weight map for predicting the co-deletion state of 1p / 19q chromosomes in gliomas using Raman spectroscopy.
[0022] Figure 3 This is a graph showing the predictive performance curve of the 1p / 19q chromosome co-deletion status of the classification model provided in this application.
[0023] Figure 4 This is a structural diagram of the glioma 1p / 19q chromosome co-deletion detection device provided in this application.
[0024] Reference numerals: laser-1, spectrum analyzer-2, display-3, optical microscopy platform-4. DETAILED DESCRIPTION
[0025] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0026] The present application provides a simple, efficient and accurate method and device for detecting glioma 1p / 19q chromosome co-deletion, which provides a new technical means for the auxiliary diagnosis and treatment of brain glioma. The method uses Raman spectroscopy technology to identify the 1p / 19q chromosome co-deletion state by performing Raman spectroscopy analysis on the glioma tissue sample to be tested, thereby realizing the rapid detection of glioma with 1p / 19q chromosome co-deletion and guiding the formulation of treatment plans.
[0027] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.
[0028] like Figure 1 As shown, the method for detecting glioma 1p / 19q chromosome co-deletion provided in the present application includes the following steps S1 to S4.
[0029] Step S1: Perform Raman spectrum scanning on the glioma tissue sample to be tested to obtain Raman spectrum data.
[0030] Among them, the glioma tissue samples to be tested can be collected directly during the operation without any slicing processing. Tissue fragments with a long diameter of about 2 to 20 mm can be taken and placed on a glass slide.
[0031] Exemplarily, a Raman spectrum excitation device (such as a laser with an excitation wavelength of 532 nm) is used to perform Raman spectrum scanning on the glioma tissue sample to be tested, and a spectrum analyzer is used to collect Raman spectrum data. The integration time of the Raman spectrum scanning is controlled to be 1 to 3 seconds.
[0032] Step S2: preprocessing the Raman spectrum data to obtain normalized Raman spectrum data.
[0033] Exemplarily, the Raman spectrum data is first processed to remove the fluorescence background to obtain the Raman spectrum data with the fluorescence background removed; secondly, the Raman spectrum data with the fluorescence background removed is smoothed and denoised to obtain the smoothed and denoised Raman spectrum data; finally, the smoothed and denoised Raman spectrum data is normalized to obtain the normalized Raman spectrum data.
[0034] Preferably, the fluorescence background removal process uses Adaptive Iterative Re-weighted Penalized Least Squares (airPLS).
[0035] Preferably, the smoothing and noise reduction process adopts the Savitzky-Golay smoothing algorithm, and the Python function name is savgol_filter.
[0036] Preferably, the normalization process adopts the maximum-minimum normalization algorithm. The formula is: x'=(x-min(x)) / (max(x)-min(x)); wherein x' is the normalized Raman spectrum data, x is the smoothed and denoised Raman spectrum data, min(x) is the minimum value of the smoothed and denoised Raman spectrum data, and max(x) is the maximum value of the smoothed and denoised Raman spectrum data.
[0037] Step S3: Extract the intensity value at the characteristic shift from the normalized Raman spectrum data. The characteristic shift includes the Raman shift of 502 cm -1 、683cm -1 、1161cm -1 、1166cm -1 、1566cm -1 、1571cm -1 、2874cm -1 、2899cm -1 、2903cm -1 、3004cm -1 、3140cm -1 、3144cm -1 、3172cm -1 、3192cm -1 、3268cm-1 、3308cm -1 、3367cm -1 、3382cm -1 、3486cm -1 and 3494cm -1 .
[0038] Step S4: Input the intensity value at the characteristic displacement into the classification model, and calculate the classification prediction value. The classification model is a multivariate linear equation of the classification prediction value and the intensity value at the characteristic displacement. The classification prediction value is used to assist in determining the 1p / 19q chromosome co-deletion state of the glioma tissue sample to be tested. The 1p / 19q chromosome co-deletion state includes 1p / 19q chromosome co-deletion positive and 1p / 19q chromosome co-deletion negative. Among them, the classification model is determined using machine learning or pattern recognition algorithms.
[0039] For example, the classification model is based on the least absolute shrinkage and selection operator. The method is to determine the co-deletion status of chromosome 1p / 19q by using a linear regression operator (LASSO) regression algorithm, and the determination process includes: obtaining a number of Raman spectrum samples annotated with the co-deletion status of chromosome 1p / 19q, pre-processing and extracting characteristic spectrum information to construct a sample data set; the sample data set includes characteristic spectrum information and the co-deletion status of chromosome 1p / 19q corresponding to a number of normalized Raman spectrum samples; the characteristic spectrum information includes intensity values at a number of Raman shifts; the co-deletion status of chromosome 1p / 19q includes 1 and 0, wherein 1 indicates that chromosome 1p / 19q is co-deletion positive, and 0 indicates that chromosome 1p / 19q is co-deletion negative; a linear regression model is constructed with the co-deletion status of chromosome 1p / 19q as the target variable and the characteristic spectrum information as the characteristic variable; according to the sample data set, a 5-fold cross validation is used to determine the optimal regularization parameter value, and based on the optimal regularization parameter value, a LASSO regression algorithm is used to train the linear regression model, the coefficient of the irrelevant Raman shift in the linear regression model is gradually reduced to zero, and the characteristic shift and classification model are screened out.
[0040] In this embodiment, based on the spectral data of 681 cases of 155 patients retrospectively included for training (including 273 cases with positive 1p / 19q chromosome co-deletion and 408 cases with negative 1p / 19q chromosome co-deletion), the LASSO regression algorithm was used for 5-fold cross validation, and the optimal regularization parameter λ (0.0035) value was selected to gradually reduce the coefficient of the irrelevant Raman shift to zero, and finally 20 characteristic shifts were selected, such as Figure 2 shown.
[0041] When using the LASSO regression algorithm, first define its cost function expression as: Among them, n is the number of samples, p is the number of features, and y i is the observed value of the i-th sample, x ij is the jth feature of the i-th sample, β is the regression coefficient, β j is the regression coefficient of the jth feature, β0 is the initial value of the regression coefficient, and λ is the regularization parameter used to control the strength of regularization. While minimizing the cost function, a set of regression coefficients corresponding to each feature is obtained, so that the predicted value is closest to the actual observed value.
[0042] The parameters of the machine learning model were optimized to predict the co-deletion status of 1p / 19q chromosomes in gliomas. The area under the receiver operating characteristic curve (ROC) of the trained classification model was as high as 85.5%, and the sensitivity was as high as 80.0%. Figure 3 shown.
[0043] In the process of spectral feature screening using the LASSO regression algorithm, the possible main characteristic peaks involved are as follows.
[0044] 502cm -1 : This peak position is affected by the stretching of the SS disulfide bond of protein or cysteine.
[0045] 683cm -1 : This peak position may be affected by the cyclic respiration of tryptophan, and may also involve the effects of lipids such as cholesterol and phospholipids.
[0046] 1161~1166cm -1 : A variety of substances may form peaks here, such as carotenoids, aromatic compounds (CH bending vibration or CC stretching vibration of aromatic rings), etc.
[0047] 1566~1571cm -1 : The peak position in this region may correspond to the characteristic vibration of tryptophan, which is the synthetic precursor of many biologically active molecules.
[0048] 2874~3004cm -1 : The peak position in this region corresponds to the stretching vibration of the CH bond in the protein methyl group.
[0049] 3140~3192cm -1 :The peak position in this region is related to the Amide B group and involves the stretching of the free NH bond.
[0050] 3268~3494cm -1:The peak in this area is likely to come from the hydroxyl (OH) effect of water molecules.
[0051] Specifically, the expression of the classification model is: y = 0.6647 + (-0.2678 × I 502 )+(-0.0599×I 683 )+0.1346×I 1161 +0.1769×I 1166 +(-0.0920×I 1566 )+(-0.2460×I 1571 )+(-0.3546×I 2874 )+(-0.0333×I 2899 )+(-0.0551×I 2903 )+(-0.2218×I 3004 )+0.1193×I 3140 +0.0900×I 3144 +0.1882×I 3172 +0.0526×I 3192 +0.0237×I 3268 +0.0300×I 3308 +(-0.5208×I 3367 )+(-0.0340×I 3382 )+0.0402×I 3486 +0.0323×I 3494 .
[0052] Wherein, y represents the classification prediction value. When y≥0.5, it is judged as a glioma with positive 1p / 19q chromosome co-deletion, and when y<0.5, it is judged as a glioma with negative 1p / 19q chromosome co-deletion. I represents the normalized intensity value at the Raman shift, hereinafter referred to as the intensity value. I 502 Indicates the Raman shift of 502 cm -1 The intensity value at I 683 Indicates the Raman shift of 683cm -1 The intensity value at I 1161 Indicated at Raman shift 1161cm -1 The intensity value at I 1166 Indicates that the Raman shift is 1166cm -1 The intensity value at I 1566 Indicates the Raman shift of 1566cm -1 The intensity value at I 1571 Indicates that the Raman shift is 1571cm -1 The intensity value at I 2874 Indicated at Raman shift 2874cm -1 The intensity value at I2899 Indicates the Raman shift of 2899 cm -1 The intensity value at I 2903 Indicated at Raman shift 2903cm -1 The intensity value at I 3004 Indicates the Raman shift of 3004cm -1 The intensity value at I 3140 Indicates the Raman shift of 3140cm -1 The intensity value at I 3144 Indicates that the Raman shift is 3144cm -1 The intensity value at I 3172 Indicated at Raman shift 3172cm -1 The intensity value at I 3192 Indicated at Raman shift 3192cm -1 The intensity value at I 3268 Indicates that the Raman shift is 3268cm -1 The intensity value at I 3308 Indicates that the Raman shift is 3308cm -1 The intensity value at I 3367 Indicates that the Raman shift is 3367cm -1 The intensity value at I 3382 Indicated at Raman shift 3382cm -1 The intensity value at I 3486 Indicates that the Raman shift is 3486cm -1 The intensity value at I 3494 Indicates that the Raman shift is 3494cm -1 The intensity value at .
[0053] like Figure 4 As shown, the glioma 1p / 19q chromosome co-deletion detection device provided by the present application includes: a laser 1 and a spectrum analyzer 2. Among them, the laser 1 is used to emit laser light to the glioma tissue sample to be tested; the spectrum analyzer 2 is used to collect Raman light scattered by the glioma tissue sample to be tested, obtain Raman spectrum data, pre-process the Raman spectrum data to obtain normalized Raman spectrum data, extract the intensity value at the characteristic displacement from the normalized Raman spectrum data, and input the intensity value at the characteristic displacement into the classification model to calculate the classification prediction value.
[0054] Preferably, the excitation wavelength of the laser 1 is 532 nm, and the integration time is 1 to 3 seconds.
[0055] Furthermore, the above-mentioned glioma 1p / 19q chromosome co-deletion detection device further comprises: an optical microscopic platform 4. The optical microscopic platform 4 is used to place the glioma tissue sample to be tested, and to adjust the position and height of the glioma tissue sample to be tested.
[0056] Furthermore, the above-mentioned glioma 1p / 19q chromosome co-deletion detection device further includes: a display 3. The display 3 is connected to the spectrum analyzer 2 and is used to display the classification prediction value and the auxiliary determination result; the auxiliary determination result is determined based on the classification prediction value.
[0057] Furthermore, the above-mentioned glioma 1p / 19q chromosome co-deletion detection device also includes: an optical fiber probe. The optical fiber probe is connected to the laser 1 and the spectrum analyzer 2 respectively, and is used to transmit the laser emitted by the laser 1 to the surface of the glioma tissue sample to be tested, and transmit the Raman light scattered by the surface of the glioma tissue sample to be tested to the spectrum analyzer 2.
[0058] The glioma 1p / 19q chromosome co-deletion detection method and device provided in the present application have the following advantages.
[0059] 1. Fast: Using Raman spectroscopy technology, the detection time is short and the results are rapid.
[0060] 2. Accurate: Analyze the characteristic spectral information to accurately identify the co-deletion status of 1p / 19q chromosomes.
[0061] 3. Non-destructive: No additional processing or staining of tissue samples is required, maintaining the integrity of the samples.
[0062] 4. Simple: easy to operate, no need for complicated experimental conditions and professional skills.
[0063] In summary, the present application provides a method and device for detecting 1p / 19q chromosome co-deletion in glioma, which has the advantages of being fast, accurate, and non-destructive. It can be used as a supplementary means of genetic testing and is suitable for clinical medicine and scientific research fields.
[0064] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0065] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.
Claims
1. A method for detecting 1p / 19q chromosome co-deletion in glioma, characterized in that: include: Performing Raman spectrum scanning on the glioma tissue sample to be tested to obtain Raman spectrum data; Preprocessing the Raman spectrum data to obtain normalized Raman spectrum data; Extract the intensity value at the characteristic shift from the normalized Raman spectrum data; the characteristic shift includes the Raman shift 502cm -1 、683cm -1 、1161cm -1 、1166cm -1 、1566cm -1 、1571cm -1 、2874cm -1 、2899cm -1 、2903cm -1 、3004cm -1 、3140cm -1 、3144cm -1 、3172cm -1 、3192cm -1 、3268cm -1 、3308cm -1 、3367cm -1 、3382cm -1 、3486cm -1 and 3494cm -1 ; The intensity value at the characteristic displacement is input into the classification model to calculate the classification prediction value; the classification model is a multivariate linear equation of the classification prediction value and the intensity value at the characteristic displacement; the classification prediction value is used to assist in determining the 1p / 19q chromosome co-deletion state of the glioma tissue sample to be tested; the 1p / 19q chromosome co-deletion state includes 1p / 19q chromosome co-deletion positive and 1p / 19q chromosome co-deletion negative.
2. The method for detecting glioma 1p / 19q chromosome co-deletion according to claim 1, characterized in that: Preprocessing the Raman spectrum data to obtain normalized Raman spectrum data includes: Performing fluorescence background removal processing on the Raman spectrum data to obtain Raman spectrum data with fluorescence background removed; Performing smoothing and noise reduction processing on the Raman spectrum data after the fluorescence background is removed to obtain smoothed and noise-reduced Raman spectrum data; The smoothed and denoised Raman spectrum data is normalized to obtain normalized Raman spectrum data.
3. The method for detecting glioma 1p / 19q chromosome co-deletion according to claim 1, characterized in that: The classification model is determined based on the LASSO regression algorithm; the determination process of the classification model includes: Acquire several Raman spectrum samples marked with 1p / 19q chromosome co-deletion status, perform preprocessing and extract characteristic spectrum information, and construct a sample data set; the sample data set includes characteristic spectrum information and 1p / 19q chromosome co-deletion status corresponding to several normalized Raman spectrum samples; the characteristic spectrum information includes intensity values at several Raman shifts; the 1p / 19q chromosome co-deletion status includes 1 and 0, wherein 1 indicates that 1p / 19q chromosome co-deletion is positive, and 0 indicates that 1p / 19q chromosome co-deletion is negative; A linear regression model is constructed using the 1p / 19q chromosome co-deletion state as the target variable and the characteristic spectral information as the characteristic variable; According to the sample data set, a 5-fold cross validation is used to determine the optimal regularization parameter value, and based on the optimal regularization parameter value, the linear regression model is trained using a LASSO regression algorithm, the coefficient of the unrelated Raman shift in the linear regression model is gradually reduced to zero, and the characteristic shift and classification model are screened.
4. The method for detecting glioma 1p / 19q chromosome co-deletion according to claim 1, characterized in that: The expression of the classification model is: and=0.6647+(-0.2678×I 502 )+(-0.0599×I 683 )+0.1346×I 1161 +0.1769×I 1166 +(-0.0920×I 1566 )+(-0.2460×I 1571 )+(-0.3546×I 2874 )+(-0.0333×I 2899 )+(-0.0551×I 2903 )+(-0.2218×I 3004 )+0.1193×I 3140 +0.0900×I 3144 +0.1882×I 3172 +0.0526×I 3192 +0.0237×I 3268 +0.0300×I 3308 +(-0.5208×I 3367 )+(-0.0340×I 3382 )+0.0402×I 3486 +0.0323×I 3494 ; Wherein, y represents the classification prediction value. When y≥0.5, it is judged as a glioma with positive 1p / 19q chromosome co-deletion, and when y<0.5, it is judged as a glioma with negative 1p / 19q chromosome co-deletion. 502 Indicates the Raman shift of 502 cm -1 The intensity value at I 683 Indicates the Raman shift of 683cm -1 The intensity value at I 1161 Indicated at Raman shift 1161cm -1 The intensity value at I 1166 Indicates that the Raman shift is 1166cm -1 The intensity value at I 1566 Indicates the Raman shift of 1566cm -1 The intensity value at I 1571 Indicates that the Raman shift is 1571cm -1 The intensity value at I 2874 Indicated at Raman shift 2874cm -1 The intensity value at I 2899 Indicates the Raman shift of 2899 cm -1 The intensity value at I 2903 Indicated at Raman shift 2903cm -1 The intensity value at I 3004 Indicates the Raman shift of 3004cm -1 The intensity value at I 3140 Indicates the Raman shift of 3140cm -1 The intensity value at I 3144 Indicates that the Raman shift is 3144cm -1 The intensity value at I 3172 Indicated at Raman shift 3172cm -1 The intensity value at I 3192 Indicated at Raman shift 3192cm -1 The intensity value at I 3268 Indicates that the Raman shift is 3268cm -1 The intensity value at I 3308 Indicates that the Raman shift is 3308cm -1 The intensity value at I 3367 Indicates that the Raman shift is 3367cm -1 The intensity value at I 3382 Indicated at Raman shift 3382cm -1 The intensity value at I 3486 Indicates that the Raman shift is 3486cm -1 The intensity value at I 3494 Indicates that the Raman shift is 3494cm -1 The intensity value at .
5. The method for detecting glioma 1p / 19q chromosome co-deletion according to claim 2, characterized in that: Adopting adaptive iterative reweighted penalty least squares method to remove fluorescence background from the Raman spectrum data; The Savitzky-Golay smoothing algorithm is used to perform smoothing and noise reduction processing on the Raman spectrum data after removing the fluorescence background; and the maximum and minimum normalization algorithm is used to perform normalization processing on the smoothed and noise-reduced Raman spectrum data.
6. A device for detecting glioma 1p / 19q chromosome co-deletion, using the glioma 1p / 19q chromosome co-deletion detection method according to claim 1, characterized in that: include: A laser, used for emitting laser light to the glioma tissue sample to be tested; The spectrum analyzer is used to collect Raman light scattered by the glioma tissue sample to be tested to obtain Raman spectrum data, pre-process the Raman spectrum data to obtain normalized Raman spectrum data, extract the intensity value at the characteristic displacement from the normalized Raman spectrum data, and input the intensity value at the characteristic displacement into a classification model to calculate a classification prediction value.
7. The glioma 1p / 19q chromosome co-deletion detection device according to claim 6, characterized in that: Also includes: The optical microscopy platform is used to place the glioma tissue sample to be tested, and to adjust the position and height of the glioma tissue sample to be tested.
8. The glioma 1p / 19q chromosome co-deletion detection device according to claim 6, characterized in that: Also includes: A display, connected to the spectrum analyzer, for displaying the classification prediction value and the auxiliary determination result; The auxiliary determination result is determined based on the classification prediction value.
9. The glioma 1p / 19q chromosome co-deletion detection device according to claim 6, characterized in that: Also includes: The optical fiber probe is connected to the laser and the spectrum analyzer respectively, and is used to transmit the laser light emitted by the laser to the surface of the glioma tissue sample to be tested, and transmit the Raman light scattered by the surface of the glioma tissue sample to be tested to the spectrum analyzer.
10. The glioma 1p / 19q chromosome co-deletion detection device according to claim 6, characterized in that: The excitation wavelength of the laser is 532 nm, and the integration time is 1 to 3 seconds.