Method and apparatus for detecting chromosome 1p / 19q co-deletion in glioma

Abstract

The present application relates to the field of Raman spectroscopic detection. Disclosed are a method and apparatus for detecting chromosome 1p / 19q co-deletion in glioma. The method comprises: performing Raman spectroscopic scanning on a glioma tissue sample to be subjected to detection, in order to obtain Raman spectral data; preprocessing the Raman spectral data, in order to obtain normalized Raman spectral data; extracting intensity values at characteristic shifts from the normalized Raman spectral data; and inputting the intensity values at the characteristic shifts into a classification model to calculate a classification prediction value, which is used for assisting with the determination of the chromosome 1p / 19q co-deletion state of said glioma tissue sample. The present application can realize the low-cost and rapid detection of the chromosome 1p / 19q co-deletion state in gliomas.

Description

A method and device for detecting 1p / 19q chromosomal co-deletion in gliomas.

[0001] This application claims priority to Chinese Patent Application No. 202411535023.2, filed on October 30, 2024, entitled "A Method and Apparatus for Detecting Co-deletion of Glioma Chromosome 1p / 19q", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of Raman spectroscopy detection, and in particular to a method and apparatus for detecting glioma 1p / 19q chromosome co-deletion. Background Technology

[0003] Gliomas are the most common primary malignant brain tumors, accounting for 40%-50% of all brain tumors and 70% of all primary malignant brain tumors. They are characterized by short survival, high disability rates, and poor treatment outcomes. Different molecular subtypes of gliomas exhibit significant heterogeneity. The combined deletion of the short arm (1p) and long arm (19q) of chromosome 19 is an important molecular marker for gliomas (especially oligodendrogliomas), playing a crucial role in pathological diagnosis, evaluation of radiotherapy and chemotherapy efficacy, and clinical prognosis prediction. Oligodendrogliomas with combined 1p / 19q deletions grow more slowly and are more sensitive to chemotherapy. Current treatment guidelines recommend testing for the 1p / 19q combined deletion status in oligodendrogliomas. Treatment with temozolomide or radiotherapy alone prolongs progression-free survival in patients with oligodendrogliomas exhibiting combined 1p / 19q deletion. For asymptomatic oligodendroglioma patients with combined 1p / 19q deletion, tumor growth is slow and overall survival is long, leading some physicians to opt for clinical observation. For symptomatic patients, treatment outcomes are better, with improved symptoms and quality of life.

[0004] However, the detection of 1p / 19q chromosome co-deletion typically involves fluorescent hybridization of tissue sections or in vitro amplification of the genome, which is costly and time-consuming, hindering the patient's overall treatment process. Currently, there is no alternative, highly efficient detection method or technique. Summary of the Invention

[0005] The purpose of this application is to provide a method and device for detecting 1p / 19q chromosome co-deletion in gliomas, which can achieve low-cost and rapid detection of 1p / 19q chromosome co-deletion status in gliomas.

[0006] To achieve the above objectives, this application provides the following solution.

[0007] In a first aspect, this application provides a method for detecting 1p / 19q chromosomal co-deletion in gliomas, comprising: performing Raman spectroscopy on a glioma tissue sample to be tested to obtain Raman spectral data; preprocessing the Raman spectral data to obtain normalized Raman spectral data; and extracting intensity values ​​at characteristic shifts from the normalized Raman spectral data; wherein the characteristic shifts include a Raman shift of 502 cm⁻¹. -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 feature displacement is input into the classification model to calculate the classification prediction value. The classification model is a multivariate linear equation relating the classification prediction value and the intensity value at the feature displacement. The classification prediction value is used to assist in determining the 1p / 19q chromosome co-deletion status of the glioma tissue sample to be tested. The 1p / 19q chromosome co-deletion status includes 1p / 19q chromosome co-deletion positive and 1p / 19q chromosome co-deletion negative. If the classification prediction value is greater than or equal to a predetermined threshold, the 1p / 19q chromosome co-deletion status is determined to be positive; and if the classification prediction value is less than the predetermined threshold, the 1p / 19q chromosome co-deletion status is determined to be negative.

[0008] In one exemplary embodiment, preprocessing the Raman spectral data to obtain normalized Raman spectral data includes: removing fluorescence background from the Raman spectral data to obtain Raman spectral data with removed fluorescence background; smoothing and denoising the Raman spectral data with removed fluorescence background to obtain smoothed and denoised Raman spectral data; and normalizing the smoothed and denoised Raman spectral data to obtain normalized Raman spectral data.

[0009] In an exemplary embodiment, the classification model is determined based on the LASSO regression algorithm. The process of determining the classification model includes: acquiring several Raman spectral samples labeled with 1p / 19q chromosome co-deletion states, preprocessing them, and extracting feature spectral information to construct a sample dataset; the sample dataset includes feature spectral information corresponding to several normalized Raman spectral samples and 1p / 19q chromosome co-deletion states; the feature spectral information includes intensity values ​​at several Raman shifts; the 1p / 19q chromosome co-deletion states include 1 and 0, where 1 represents a positive 1p / 19q chromosome co-deletion and 0 represents a negative 1p / 19q chromosome co-deletion; using the 1p / 19q chromosome co-deletion states as the target variable and the feature spectral information as the feature variable, a linear regression model is constructed; based on the sample dataset, 5-fold cross-validation is used to determine the optimal regularization parameter value, and based on the optimal regularization parameter value, the LASSO regression algorithm is used to train the linear regression model, gradually reducing the coefficients of irrelevant Raman shifts in the linear regression model to zero, and selecting the feature shifts and the classification model.

[0010] In an exemplary embodiment, the expression for 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 Where y represents the classification prediction value; when y ≥ 0.5, it is classified as a glioma positive for 1p / 19q chromosome co-deletion; when y < 0.5, it is classified as a glioma negative for 1p / 19q chromosome co-deletion. 502This indicates a Raman displacement of 502 cm. -1 Intensity value at; I 683 This indicates a Raman displacement of 683 cm. -1 Intensity value at; I 1161 This indicates a Raman displacement of 1161 cm. -1 Intensity value at; I 1166 This indicates a Raman displacement of 1166 cm. -1 Intensity value at; I 1566 This indicates a Raman displacement of 1566 cm. -1 Intensity value at; I 1571 This indicates a Raman displacement of 1571 cm. -1 Intensity value at; I 2874 This indicates a Raman displacement of 2874 cm. -1 Intensity value at; I 2899 This indicates a Raman displacement of 2899 cm. -1 Intensity value at; I 2903 This indicates a Raman displacement of 2903 cm. -1 Intensity value at; I 3004 This indicates a Raman displacement of 3004 cm. -1 Intensity value at; I 3140 This indicates a Raman displacement of 3140 cm. -1 Intensity value at; I 3144 This indicates a Raman displacement of 3144 cm. -1 Intensity value at; I 3172 This indicates a Raman displacement of 3172 cm. -1 Intensity value at; I 3192 This indicates a Raman displacement of 3192 cm. -1 Intensity value at; I 3268 This indicates a Raman displacement of 3268 cm. -1 Intensity value at; I 3308 This indicates a Raman displacement of 3308 cm. -1 Intensity value at; I 3367 This indicates a Raman displacement of 3367 cm. -1 Intensity value at; I 3382 This indicates a Raman displacement of 3382 cm. -1 Intensity value at; I 3486 This indicates a Raman displacement of 3486 cm. -1 Intensity value at; I 3494 This indicates a Raman displacement of 3494 cm. -1 The intensity value at that location.

[0011] In one exemplary embodiment, removing the fluorescence background from the Raman spectral data to obtain Raman spectral data with removed fluorescence background includes: performing fluorescence background removal processing on the Raman spectral data using an adaptive iterative reweighted penalized least squares method to obtain Raman spectral data with removed fluorescence background.

[0012] In one exemplary embodiment, the Raman spectral data with removed fluorescence background is smoothed and denoised to obtain smoothed and denoised Raman spectral data, including: using the Savitzky-Golay smoothing algorithm to smooth and denoise the Raman spectral data with removed fluorescence background to obtain smoothed and denoised Raman spectral data.

[0013] In one exemplary embodiment, normalizing the smoothed and denoised Raman spectral data to obtain normalized Raman spectral data includes: normalizing the smoothed and denoised Raman spectral data using a max-min normalization algorithm to obtain normalized Raman spectral data.

[0014] Secondly, this application provides a glioma 1p / 19q chromosome co-deletion detection device, employing the aforementioned glioma 1p / 19q chromosome co-deletion detection method, comprising: a laser for emitting laser light onto a glioma tissue sample to be tested; a spectrometer for collecting Raman light scattered by the glioma tissue sample to obtain Raman spectral data, preprocessing the Raman spectral data to obtain normalized Raman spectral data, extracting intensity values ​​at characteristic shifts from the normalized Raman spectral data, and inputting the intensity values ​​at characteristic shifts into a classification model to calculate a classification prediction value; wherein if the classification prediction value is greater than or equal to a predetermined threshold, the 1p / 19q chromosome co-deletion status is determined to be positive; and if the classification prediction value is less than the predetermined threshold, the 1p / 19q chromosome co-deletion status is determined to be negative.

[0015] In an exemplary embodiment, 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 for adjusting the position and height of the glioma tissue sample to be tested.

[0016] In an exemplary embodiment, the glioma 1p / 19q chromosome co-deletion detection device further includes: a display connected to the spectral analyzer, used to display the classification prediction value and auxiliary determination result; the auxiliary determination result is determined based on the classification prediction value.

[0017] In an exemplary embodiment, the glioma 1p / 19q chromosome co-deletion detection device further includes: an optical fiber probe, connected to the laser and the spectrometer respectively, for transmitting the laser emitted by the laser to the surface of the glioma tissue sample to be tested, and transmitting the Raman light scattered from the surface of the glioma tissue sample to the spectrometer.

[0018] In one exemplary embodiment, the laser has an excitation wavelength of 532 nm and an integration time of 1 to 3 seconds.

[0019] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a method and apparatus for detecting 1p / 19q chromosome co-deletion in gliomas. First, Raman spectroscopy is performed on the glioma tissue sample to be tested to obtain Raman spectral data. Then, the Raman spectral data is preprocessed and features are extracted to obtain the intensity values ​​at feature shifts. Finally, the intensity values ​​at feature shifts are input into a pre-trained classification model to calculate a classification prediction value, which is used to assist in determining the 1p / 19q chromosome co-deletion status of the glioma tissue sample to be tested. Compared with the prior art, this application utilizes Raman spectroscopy technology to perform Raman spectral analysis on the glioma tissue sample to be tested, combined with a trained classification model, to achieve low-cost and rapid detection of the 1p / 19q chromosome co-deletion status of gliomas, which can partially replace the high-cost tumor gene detection and analysis function. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 is a flowchart of the glioma 1p / 19q chromosome co-deletion detection method provided in this application.

[0022] Figure 2 is a shift feature weighting diagram of the Raman spectroscopy provided in this application for predicting the co-deletion state of the 1p / 19q chromosome in gliomas.

[0023] Figure 3 is a curve showing the predictive efficacy of the classification model provided in this application for the co-deletion status of chromosome 1p / 19q.

[0024] Figure 4 is a structural diagram of the glioma 1p / 19q chromosome co-deletion detection device provided in this application.

[0025] Figure reference numerals: Laser-1, Spectrometer-2, Display-3, Optical Microscope Platform-4. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] This application provides a simple, efficient, and accurate method and device for detecting 1p / 19q chromosome co-deletion in gliomas, offering a new technical means for the auxiliary diagnosis and treatment of gliomas. This method utilizes Raman spectroscopy to identify the 1p / 19q chromosome co-deletion status by performing Raman spectral analysis on the glioma tissue sample, thereby achieving rapid detection of gliomas with 1p / 19q chromosome co-deletion and guiding the formulation of treatment plans.

[0028] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0029] In one exemplary embodiment, this application provides a method for detecting 1p / 19q chromosome co-deletion in gliomas. This method is executed by a computer device, specifically a terminal or server, or both. As shown in FIG1, in this embodiment, the method for detecting 1p / 19q chromosome co-deletion in gliomas provided by this application includes the following steps S1 to S4.

[0030] Step S1: Perform Raman spectroscopy scanning on the glioma tissue sample to be tested to obtain Raman spectral data.

[0031] The glioma tissue sample to be tested can be collected directly during the operation without any sectioning. Simply take a tissue fragment with a long diameter of about 2 to 20 mm and place it on a glass slide.

[0032] For example, a Raman spectroscopy excitation device (such as a laser with an excitation wavelength of 532 nm) was used to perform Raman spectroscopy scanning on the glioma tissue sample to be tested, and the Raman spectral data were acquired using a spectrometer. The integration time of the Raman spectroscopy scan was controlled within 1 to 3 seconds.

[0033] Step S2: Preprocess the Raman spectral data to obtain normalized Raman spectral data.

[0034] For example, firstly, the Raman spectral data is processed to remove the fluorescence background to obtain Raman spectral data with the fluorescence background removed; secondly, the Raman spectral data with the fluorescence background removed is processed to smooth and reduce noise to obtain smooth and denoised Raman spectral data; finally, the smooth and denoised Raman spectral data is processed to normalize to obtain normalized Raman spectral data.

[0035] Preferably, the fluorescence background removal process employs the Adaptive Iterative Re-weighted Penalized Least Squares (airPLS) method.

[0036] Preferably, the smoothing and noise reduction process uses the Savitzky-Golay smoothing algorithm, and the Python function name is savgol_filter.

[0037] Preferably, the normalization process employs a maximum-minimum normalization algorithm. The formula is: x' = (x - min(x)) / (max(x) - min(x)); where x' is the normalized Raman spectral data, x is the smoothed and denoised Raman spectral data, min(x) is the minimum value of the smoothed and denoised Raman spectral data, and max(x) is the maximum value of the smoothed and denoised Raman spectral data.

[0038] Step S3: Extract the intensity values ​​at characteristic shifts from the normalized Raman spectral data. Characteristic shifts include the Raman shift of 502 cm⁻¹. -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 .

[0039] Step S4: Input the intensity value at the feature displacement into the classification model to calculate the classification prediction value. The classification model is a multivariate linear equation relating the classification prediction value and the intensity value at the feature displacement. The classification prediction value is used to assist in determining the 1p / 19q chromosome co-deletion status of the glioma tissue sample to be tested. The 1p / 19q chromosome co-deletion status includes 1p / 19q chromosome co-deletion positive and 1p / 19q chromosome co-deletion negative. If the classification prediction value is greater than or equal to a predetermined threshold, the 1p / 19q chromosome co-deletion status is determined to be positive; if the classification prediction value is less than the predetermined threshold, the 1p / 19q chromosome co-deletion status is determined to be negative. The classification model is determined using machine learning or pattern recognition algorithms.

[0040] For example, the classification model is based on the least absolute shrinkage and selection operator. The LASSO (Laser-Operator) regression algorithm is used to determine the co-deletion status of chromosome 1p / 19q. The determination process includes: acquiring several Raman spectral samples labeled with co-deletion status of chromosome 1p / 19q, preprocessing them, and extracting feature spectral information to construct a sample dataset; the sample dataset includes feature spectral information corresponding to several normalized Raman spectral samples and the co-deletion status of chromosome 1p / 19q; the feature spectral information includes intensity values ​​at several Raman shifts; the co-deletion status of chromosome 1p / 19q includes 1 and 0, where 1 represents a positive co-deletion and 0 represents a negative co-deletion; using the co-deletion status of chromosome 1p / 19q as the target variable and the feature spectral information as the feature variable, a linear regression model is constructed; based on the sample dataset, 5-fold cross-validation is used to determine the optimal regularization parameter value, and based on the optimal regularization parameter value, the LASSO regression algorithm is used to train the linear regression model, gradually reducing the coefficients of irrelevant Raman shifts in the linear regression model to zero, and selecting the feature shifts and classification model.

[0041] In this embodiment, training was performed based on spectral data from 155 retrospectively included patients, totaling 681 cases (including 273 positive cases of 1p / 19q chromosome co-deletion and 408 negative cases of 1p / 19q chromosome co-deletion). The LASSO regression algorithm was used for 5-fold cross-validation, and the optimal regularization parameter λ (0.0035) was selected to gradually reduce the coefficients of irrelevant Raman shifts to zero. Finally, 20 feature shifts were selected, as shown in Figure 2.

[0042] When using the LASSO regression algorithm, its cost function expression is first defined as follows: Where n is the number of samples, p is the number of features, and y i Let x be the observation value of the i-th sample. ij Let β be the j-th feature of the i-th sample, and β be the regression coefficient.j Let be the regression coefficient of the j-th feature, β0 be the initial value of the regression coefficient, and λ be the regularization parameter used to control the strength of regularization. This process minimizes the cost function while obtaining a set of regression coefficients corresponding to each feature, making the predicted value as close as possible to the actual observed value.

[0043] Optimizing machine learning model parameters to predict the co-deletion status of glioma 1p / 19q chromosome, the area under the curve (AUC) of the trained classification model can reach up to 85.5%, and the sensitivity can reach 80.0%, as shown in Figure 3.

[0044] The main possible characteristic peaks involved in the spectral feature screening process using the LASSO regression algorithm are as follows.

[0045] 502cm -1 The position of this peak is affected by the stretching of the SS disulfide bonds of proteins or cysteine.

[0046] 683cm -1 This peak position may be affected by the cyclic respiration of tryptophan, or it may involve the effects of lipids such as cholesterol and phospholipids.

[0047] 1161~1166cm -1 Many substances may form peaks here, such as carotenoids, aromatic compounds (CH bending vibration or C-C stretching vibration of aromatic rings), etc.

[0048] 1566~1571cm -1 The peak position in this region may correspond to the characteristic vibration of tryptophan, which is a precursor for the synthesis of many bioactive molecules.

[0049] 2874~3004cm -1 The peak position in this region corresponds to the stretching vibration of the CH bond in the methyl group of the protein.

[0050] 3140~3192cm -1 The peak position in this region is related to the Amide B group, which involves the stretching of free NH bonds.

[0051] 3268~3494cm -1 The peak position in this region is very likely due to the action of hydroxyl (OH) groups in water molecules.

[0052] Specifically, the expression for 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 .

[0053] Where y represents the classification prediction value; when y ≥ 0.5, it is classified as a glioma positive for 1p / 19q chromosome co-deletion; when y < 0.5, it is classified as a glioma negative for 1p / 19q chromosome co-deletion. I represents the normalized intensity value at this Raman shift, hereinafter referred to as the intensity value. 502 This indicates a Raman displacement of 502 cm. -1 Intensity value at; I 683 This indicates a Raman displacement of 683 cm. -1 Intensity value at; I 1161 This indicates a Raman displacement of 1161 cm. -1 Intensity value at; I 1166 This indicates a Raman displacement of 1166 cm. -1 Intensity value at; I 1566 This indicates a Raman displacement of 1566 cm. -1 Intensity value at; I 1571 This indicates a Raman displacement of 1571 cm. -1 Intensity value at; I 2874 This indicates a Raman displacement of 2874 cm. -1 Intensity value at; I 2899 This indicates a Raman displacement of 2899 cm. -1 Intensity value at; I 2903 This indicates a Raman displacement of 2903 cm. -1 Intensity value at; I 3004This indicates a Raman displacement of 3004 cm. -1 Intensity value at; I 3140 This indicates a Raman displacement of 3140 cm. -1 Intensity value at; I 3144 This indicates a Raman displacement of 3144 cm. -1 Intensity value at; I 3172 This indicates a Raman displacement of 3172 cm. -1 Intensity value at; I 3192 This indicates a Raman displacement of 3192 cm. -1 Intensity value at; I 3268 This indicates a Raman displacement of 3268 cm. -1 Intensity value at; I 3308 This indicates a Raman displacement of 3308 cm. -1 Intensity value at; I 3367 This indicates a Raman displacement of 3367 cm. -1 Intensity value at; I 3382 This indicates a Raman displacement of 3382 cm. -1 Intensity value at; I 3486 This indicates a Raman displacement of 3486 cm. -1 Intensity value at; I 3494 This indicates a Raman displacement of 3494 cm. -1 The intensity value at that location.

[0054] In an exemplary embodiment, this application provides a device for detecting 1p / 19q chromosome co-deletion in gliomas. As shown in FIG4, the 1p / 19q chromosome co-deletion detection device for gliomas provided in this application includes a laser 1 and a spectrometer 2. The laser 1 emits a laser beam towards the glioma tissue sample to be tested; the spectrometer 2 collects the Raman light scattered by the glioma tissue sample to obtain Raman spectral data, preprocesses the Raman spectral data to obtain normalized Raman spectral data, extracts the intensity values ​​at characteristic shifts from the normalized Raman spectral data, and inputs the intensity values ​​at the characteristic shifts into a classification model to calculate a classification prediction value. If the classification prediction value is greater than or equal to a predetermined threshold, the 1p / 19q chromosome co-deletion status is determined to be positive; if the classification prediction value is less than the predetermined threshold, the 1p / 19q chromosome co-deletion status is determined to be negative.

[0055] Preferably, the excitation wavelength of laser 1 is 532 nm, and the integration time is 1 to 3 seconds.

[0056] Furthermore, the aforementioned glioma 1p / 19q chromosome co-deletion detection device also includes: an optical microscopy platform 4. The optical microscopy 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.

[0057] Furthermore, the aforementioned glioma 1p / 19q chromosome co-deletion detection device also includes a display 3. The display 3 is connected to the spectral 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.

[0058] Furthermore, the aforementioned 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 spectrometer 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 to transmit the Raman light scattered from the surface of the glioma tissue sample to the spectrometer 2.

[0059] The method and apparatus for detecting glioma 1p / 19q chromosome co-deletion provided in this application have the following advantages.

[0060] 1. Fast: Utilizing Raman spectroscopy, the detection time is short and the results are rapid.

[0061] 2. Accuracy: Utilizing characteristic spectral information for analysis, it accurately identifies the co-deletion status of the 1p / 19q chromosome.

[0062] 3. Non-destructive: No additional processing or staining of tissue samples is required, maintaining the integrity of the samples.

[0063] 4. Simple: It is easy to operate and does not require complicated experimental conditions or professional skills.

[0064] In summary, this application provides a method and device for detecting 1p / 19q chromosomal co-deletion in gliomas, which has the advantages of being rapid, accurate, and non-destructive. It can be used as a supplementary means of gene testing and is applicable to clinical medical and scientific research fields.

[0065] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0066] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for detecting 1p / 19q chromosomal co-deletion in gliomas, characterized in that, include: Raman spectroscopy was performed on the glioma tissue sample to be tested to obtain Raman spectral data; The Raman spectral data are preprocessed to obtain normalized Raman spectral data; Intensity values ​​at characteristic shifts are extracted from the normalized Raman spectral data; the characteristic shifts include a Raman shift of 502 cm⁻¹. -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 status of the glioma tissue sample to be tested; the 1p / 19q chromosome co-deletion status includes 1p / 19q chromosome co-deletion positive and 1p / 19q chromosome co-deletion negative. If the classification prediction value is greater than or equal to a predetermined threshold, the co-deletion status of chromosome 1p / 19q is determined to be positive; and if the classification prediction value is less than the predetermined threshold, the co-deletion status of chromosome 1p / 19q is determined to be negative.

2. The method for detecting glioma 1p / 19q chromosome co-deletion according to claim 1, characterized in that, The Raman spectral data is preprocessed to obtain normalized Raman spectral data, including: The Raman spectral data are subjected to fluorescence background removal processing to obtain Raman spectral data with fluorescence background removed; The Raman spectral data with removed fluorescence background is smoothed and denoised to obtain smoothed and denoised Raman spectral data. The smoothed and denoised Raman spectral data are normalized to obtain normalized Raman spectral 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 process of determining the classification model includes: A number of Raman spectral samples labeled with 1p / 19q chromosome co-deletion states were obtained, preprocessed, and feature spectral information was extracted to construct a sample dataset. The sample dataset includes feature spectral information corresponding to several normalized Raman spectral samples and 1p / 19q chromosome co-deletion states. The feature spectral information includes intensity values ​​at several Raman shifts. The 1p / 19q chromosome co-deletion states include 1 and 0, where 1 represents a positive 1p / 19q chromosome co-deletion and 0 represents a negative 1p / 19q chromosome co-deletion. A linear regression model was constructed using the 1p / 19q chromosome co-deletion status as the target variable and the characteristic spectral information as the characteristic variable. Based on the sample dataset, the optimal regularization parameter value is determined using 5-fold cross-validation. Based on the optimal regularization parameter value, the linear regression model is trained using the LASSO regression algorithm. The coefficients of irrelevant Raman shifts in the linear regression model are gradually reduced to zero, and feature shifts and classification models are obtained through screening.

4. The method for detecting glioma 1p / 19q chromosome co-deletion according to claim 1, characterized in that, The expression for 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 ; Where y represents the classification prediction value; when y ≥ 0.5, it is classified as a glioma positive for 1p / 19q chromosome co-deletion; when y < 0.5, it is classified as a glioma negative for 1p / 19q chromosome co-deletion. 502 This indicates a Raman displacement of 502 cm. -1 Intensity value at; I 683 This indicates a Raman displacement of 683 cm. -1 Intensity value at; I 1161 This indicates a Raman displacement of 1161 cm. -1 Intensity value at; I 1166 This indicates a Raman displacement of 1166 cm. -1 Intensity value at; I 1566 This indicates a Raman displacement of 1566 cm. -1 Intensity value at; I 1571 This indicates a Raman displacement of 1571 cm. -1 Intensity value at; I 2874 This indicates a Raman displacement of 2874 cm. -1 Intensity value at; I 2899 This indicates a Raman displacement of 2899 cm. -1 Intensity value at; I 2903 This indicates a Raman displacement of 2903 cm. -1 Intensity value at; I 3004 This indicates a Raman displacement of 3004 cm. -1 Intensity value at; I 3140 This indicates a Raman displacement of 3140 cm. -1 Intensity value at; I 3144 This indicates a Raman displacement of 3144 cm. -1 Intensity value at; I 3172 This indicates a Raman displacement of 3172 cm. -1 Intensity value at; I 3192 This indicates a Raman displacement of 3192 cm. -1 Intensity value at; I 3268 This indicates a Raman displacement of 3268 cm. -1 Intensity value at; I 3308 This indicates a Raman displacement of 3308 cm. -1 Intensity value at; I 3367 This indicates a Raman displacement of 3367 cm. -1 Intensity value at; I 3382 This indicates a Raman displacement of 3382 cm. -1 Intensity value at; I 3486 This indicates a Raman displacement of 3486 cm. -1 Intensity value at; I 3494 This indicates a Raman displacement of 3494 cm. -1 The intensity value at that location.

5. The method for detecting glioma 1p / 19q chromosome co-deletion according to claim 2, characterized in that, The Raman spectral data were processed to remove fluorescence background using an adaptive iterative reweighted penalized least squares method. The Savitzky-Golay smoothing algorithm was used to smooth and denoise the Raman spectral data after removing the fluorescence background; the max-min normalization algorithm was used to normalize the smoothed and denoised Raman spectral data.

6. A device for detecting glioma 1p / 19q chromosome co-deletion, employing the glioma 1p / 19q chromosome co-deletion detection method as described in claim 1, characterized in that, include: A laser used to emit laser light onto a glioma tissue sample to be tested; A spectrometer is used to collect Raman light scattered by the glioma tissue sample to be tested, obtain Raman spectral data, preprocess the Raman spectral data to obtain normalized Raman spectral data, extract the intensity value at the characteristic shift from the normalized Raman spectral data, and input the intensity value at the characteristic shift into the classification model to calculate the classification prediction value. If the classification prediction value is greater than or equal to a predetermined threshold, the co-deletion status of chromosome 1p / 19q is determined to be positive; and if the classification prediction value is less than the predetermined threshold, the co-deletion status of chromosome 1p / 19q is determined to be negative.

7. The glioma 1p / 19q chromosome co-deletion detection device according to claim 6, characterized in that, Also includes: An 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 spectral analyzer, is used to display the classification prediction values ​​and auxiliary judgment results; 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: An optical fiber probe is connected to the laser and the spectrometer, respectively, for transmitting the laser emitted by the laser to the surface of the glioma tissue sample to be tested, and for transmitting the Raman light scattered from the surface of the glioma tissue sample to the spectrometer.

10. The glioma 1p / 19q chromosome co-deletion detection device according to claim 6, characterized in that, The laser has an excitation wavelength of 532 nm and an integration time of 1 to 3 seconds.

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