CN113350704B - Cervical cancer radiotherapy curative effect evaluation method based on near-infrared scattering spectrum - Google Patents
Cervical cancer radiotherapy curative effect evaluation method based on near-infrared scattering spectrum Download PDFInfo
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Abstract
The invention discloses a cervical cancer radiotherapy curative effect evaluation method based on near-infrared scattering spectrum, which comprises the steps of acquiring a spectrum of a patient with confirmed cervical cancer diagnosis but no treatment, a spectrum of a patient in cervical cancer radiotherapy and a spectrum of a patient after cervical cancer radiotherapy is finished and cured by using a spectrum acquisition system, carrying out principal component analysis after pretreatment, establishing a classification model and training the model by using an SVM algorithm in combination with a C # version LibSVM software package, and realizing classification of cervical cancer patients in different periods in the treatment process and assisting in judging whether the treatment stage is finished or not. The collection of the spectral data is completed by using a double-fiber probe of the spectral collection system, and the near-infrared scattering spectral data of the whole cervical moving band is collected. The method can be used as an auxiliary method for evaluating the curative effect of the cervical cancer radiotherapy, so that the spectrum technology is used for effectively evaluating the curative effect of the radiotherapy, the treatment plan adjustment of the whole treatment process is facilitated, the cost of the cervical cancer treatment can be reduced, and the convenience of the treatment process is improved.
Description
Technical Field
The invention relates to a cervical cancer radiotherapy curative effect evaluation method based on near-infrared scattering spectrum, and belongs to the field of biomedical engineering.
Background
Cervical cancer is the most common gynecological malignant tumor, the morbidity and mortality of women are the fourth in the world, and the number of new cases of cervical cancer in China accounts for about 30 percent of the total morbidity of the world, so that the life health of women is seriously harmed. Human Papillomaviruses (HPV) are a major risk factor for the development of cervical cancer.
The clinical existing curative effect evaluation methods mainly comprise gynecological examination, imaging detection, tumor markers and pathological examination, wherein the gynecological examination is the most common method. The above methods for evaluating the therapeutic effect are mostly based on large-scale instruments or require doctors to perform a diagnosis.
Radiotherapy belongs to a comprehensive treatment means and is also an important means for treating middle and late-stage cervical cancer. Mainly by external irradiation, intracavity irradiation and the like of a cervical cancer patient. Most of cervical cancer is squamous carcinoma, and can be treated by radiotherapy because of being sensitive to radiotherapy, and the effect of early radiotherapy treatment is similar to that of operation. The sensitivity and prognosis of tumors to radiotherapy are closely related, and some radiotherapy-resistant cases can lead to treatment failure and tumor progression. The early accurate prediction of the radiotherapy effect is the premise of adjusting the clinical treatment scheme and is also the basis of the individual treatment of the tumor. Therefore, the radiotherapy curative effect evaluation technology has important guiding significance for dose adjustment in the radiotherapy process, and early evaluation of the treatment response of the tumor is important for improving the survival rate of the cervical cancer patient.
The support vector machine is a two-class model whose main purpose is to solve the separate hyperplane that can correctly partition the training data set and has the largest geometrical spacing. In the case of linear separable, the instance of a sample point in the training dataset with the sample point closest in separation hyperplane distance is referred to as a support vector. For the nonlinear classification problem, the original space is firstly transformed into a new high-dimensional feature space by using a kernel function during model training, so that the samples can be linearly separable in the new high-dimensional space. When the form of feature mapping cannot be determined, a proper kernel function cannot be selected, the selection of the kernel function influences the selection of the feature space, and the quality of the feature space directly influences the performance of the support vector machine, so that the selection of the kernel function is the largest influencing factor of the support vector machine. During model testing, the same kernel function is utilized to transform the test set into a high-dimensional space, and the category of the test set is judged according to the position of the transformed point in the optimal hyperplane, so that a prediction result is given. The LibSVM is a very mature software package for SVM pattern recognition and regression, provides a compiled execution file and source codes, and can be modified and improved on the basis to be suitable for own programs.
Disclosure of Invention
The invention provides a cervical cancer radiotherapy curative effect evaluation method based on near-infrared scattering spectrum, aiming at solving the problem.
The invention adopts the following technical scheme for solving the technical problems:
a cervical cancer radiotherapy curative effect evaluation method based on near-infrared scattering spectrum comprises the following steps:
(1) Using a spectral data acquisition system to perform in-vivo acquisition of lesion spectral data before cervical cancer radiotherapy, spectral data in the cervical cancer radiotherapy process and spectral data after the cervical cancer radiotherapy is finished and healed;
(2) Respectively carrying out smoothing and normalization processing on the spectral data acquired in the step (1);
(3) Dividing the spectral data processed in the step (2) into a training set, a verification set and a test set, and respectively carrying out principal component analysis;
(4) Selecting the first four components after principal component analysis in the step (3) as input, establishing a spectrum classification model by using a LibSVM software package, and training, verifying and testing the established spectrum classification model by using a training set, a verifying set and a testing set after principal component analysis;
(5) And (5) evaluating the curative effect of the cervical cancer radiotherapy based on the model obtained in the step (4).
Further, the spectrum data acquisition system in the step (1) comprises a halogen light source, a fiber optic spectrometer and a double-fiber probe, wherein the double-fiber probe is respectively connected with the halogen light source and the fiber optic spectrometer.
Further, the in-vivo acquisition of the spectral data in step (1) comprises the following steps:
(1) Disinfecting the spectral data acquisition system and reserving a background spectrum of the current detection environment;
(2) The front end detection area of the double optical fiber probe is close to the outer edge of the cervix transition zone, the double optical fiber probe is moved clockwise to slide across the whole cervix transition zone, after the collection is finished, the probe is moved away to obtain a group of near infrared spectrum data, the data is stored, and the spectrum data collection system is disinfected.
Further, the dual-fiber probe in the step (1) comprises a spectrum fiber and a light guide fiber, the spectrum fiber and the light guide fiber are independently wrapped and integrated in the same probe, wherein light generated by the halogen light source is transmitted to the cervical tissue through the light guide fiber of the dual-fiber probe, and is transmitted to the fiber spectrometer through the spectrum fiber after being scattered by the cervical tissue.
Further, the collection wavelength of the spectral data collection system in the step (1) is 200-1100nm.
Further, the step (1) further comprises screening the collected spectrum data by setting the slope and the spectrum peak of the wave band.
Further, in the step (2), the spectral data is averaged every 20 points and smoothed.
A cervical cancer radiotherapy curative effect evaluation device based on near-infrared scattering spectrum comprises a spectrum data acquisition system, a data processing module, a principal component analysis module and a spectrum classification module, wherein the spectrum data acquisition system transmits spectrum data acquired in vivo to the data processing module, and the data processing module smoothes and normalizes the received spectrum data and transmits the spectrum data to the principal component analysis module; and the principal component analysis module is used for carrying out principal component analysis on the normalized spectral data and transmitting the first four components to the spectral classification module, and the classification result output by the spectral classification module is an evaluation result.
Further, the spectrum classification module utilizes a LibSVM software package to establish a spectrum classification model, and training data of the spectrum classification model are data which are acquired by a spectrum data acquisition system and are obtained by sequentially processing the spectral data of the lesion before cervical cancer radiotherapy, the spectral data in the cervical cancer radiotherapy process and the spectral data after cervical cancer radiotherapy is finished by a data processing module and a principal component analysis module.
Compared with the prior art, the invention adopting the technical scheme has the following technical effects:
the method for evaluating the curative effect of the cervical cancer radiotherapy based on the near-infrared scattering spectrum can be used as an auxiliary means for evaluating the curative effect of the cervical cancer radiotherapy, and has important guiding significance for dose adjustment in the radiotherapy process. The technology is a convenient, simple and low-cost cervical cancer curative effect evaluation auxiliary means, is convenient to adjust a treatment plan in the whole treatment process, and hopefully can reduce the cost of cervical cancer treatment and improve the convenience of the treatment process. The curative effect evaluation process of the method does not need complex operation of a clinician, does not need to adopt a large medical instrument, does not need to use a contrast medium and the like, and does not cause damage to a body. The technology can be used as an auxiliary evaluation mode for the whole treatment process of the cervical cancer so as to observe the development condition of the focus of a patient in real time. The cervical tissue classification model established based on clinical trial near infrared spectrum data in different radiotherapy periods has feasibility as an evaluation means of the cervical cancer radiotherapy curative effect.
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FIG. 1 is a schematic diagram of a spectral data acquisition system;
FIG. 2 is a schematic flow chart of the overall algorithm of the present invention;
FIG. 3 is a flow chart of the present invention for processing data.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings.
The invention relates to a cervical cancer radiotherapy curative effect evaluation method based on near-infrared scattering spectrum, which establishes a spectrum classification model by using spectral data subjected to principal component analysis, realizes classification of different periods in the treatment process of cervical cancer patients, and can be used as an auxiliary evaluation mode for cervical cancer curative effect evaluation.
The data used in the method are three types, namely a focus spectrum before cervical cancer radiotherapy, a spectrum in the cervical cancer radiotherapy process and spectrum data after the cervical cancer radiotherapy is finished and healed.
FIG. 1 is a schematic diagram of a spectral data acquisition system of the present invention; 1 is PC,2 is a fiber spectrometer, 3 is a halogen light source, 4 is a double-fiber probe, and 5 is cervical tissue. The double-optical-fiber probe comprises a spectrum optical fiber and a light guide optical fiber, wherein the two optical fibers are independently wrapped and integrated in the same probe.
The spectrum data acquisition is that the halogen light source generates light, the light is transmitted to the cervix uteri tissue through the light guide incidence optical fiber of the double-optical-fiber probe, the light is transmitted to the optical fiber spectrometer through the spectrum optical fiber of the double-optical-fiber probe through the scattering of the tissue, and then is transmitted to the PC for storage through the optical fiber spectrometer.
FIG. 2 is a schematic diagram of the overall algorithm flow of the invention, which mainly comprises the steps of spectral data acquisition, spectral screening and data preprocessing, principal component analysis, modeling, and predictive evaluation.
The spectral data acquisition mainly comprises the following steps:
(1) Before the spectrum acquisition system is used, equipment is disinfected, and a current detection environment background spectrum is reserved;
(2) Slightly pressing the detection area at the front end of the double-optical-fiber probe to the outer edge of the cervical moving belt, slowly sliding to enable the front end of the probe to slightly contact the moving belt, moving the probe clockwise to enable the probe to slide through the whole moving belt, removing the probe after collection is finished to obtain a group of near infrared spectrum data, storing the data and sterilizing equipment;
(3) Collecting time of focus region is prolonged properly, the probe slides on the moving belt for one circle in the same way, after collecting, the probe is removed to obtain a group of near infrared spectrum data, the data is stored and the device is disinfected.
And (II) spectrum screening mainly considers the influence of manual operation and environment, and mainly screens out unqualified spectra caused by probe shaking, over-long probe distance, environmental light pollution, too low amplitude and the like. And (4) screening out unqualified spectra in the three types of spectral data through the slopes and spectral peaks of a plurality of specific wave bands.
For environmental effects, mainly the sharp peaks of the light spectrum at 545nm and above 612nm appear in the environment, the spectrum intensity at these two positions is usually much greater than the normal spectrum intensity at the periphery, and whether to screen out the spectrum is determined by comparing the spectrum intensities at 612nm and 700 nm. An abnormal rising peak exists in the wave band of 1000nm-1200nm of the spectrum, so the peak value of the wave band can be used as the screening condition of the spectrum of the cervical cancer patient.
(III) data preprocessing
Averaging the spectrum of the focus before the cervical cancer radiotherapy, the spectrum in the cervical cancer radiotherapy process and the spectrum data of every 20 points after the cervical cancer radiotherapy is finished, smoothing, and then normalizing.
And (IV) after preprocessing the spectral data, performing principal component analysis, selecting the first four principal components of the spectral data after the principal component analysis as spectral features to be input as a model, establishing a spectral classification model by using a LibSVM software package, training the model, and improving the recognition rate of the model by changing SVM parameters. When new data needs to be predicted, the new data is input into the trained model to obtain a prediction result, and the radiotherapy curative effect is evaluated according to the prediction result.
Fig. 3 is a flowchart of processing data according to the present invention, specifically:
in order to ensure the accuracy of the prediction result, the collected original spectrum needs to be screened, unqualified spectra caused by human factors, environmental light influence and other factors are screened out, then the qualified spectra are preprocessed, smoothing and normalization processing are respectively carried out, principal component analysis is carried out on the processed data, the first four principal components are extracted, and the processed spectral data are exported.
The exported data format is not the data format required by the LibSVM software package, data conversion is needed, the exported data is converted into the data format required by the LibSVM software package by adopting a FormatDataLibsvm.
The invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the above-mentioned method. The computer-readable storage medium may include: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It should be noted that the above description of the embodiments is only for the purpose of assisting understanding of the method of the present application and the core idea thereof, and that those skilled in the art can make several improvements and modifications to the present application without departing from the principle of the present application, and these improvements and modifications are also within the protection scope of the claims of the present application.
Claims (9)
1. A cervical cancer radiotherapy curative effect evaluation method based on near-infrared scattering spectrum is characterized by comprising the following steps:
(1) Using a spectral data acquisition system to carry out in-vivo acquisition on lesion spectral data before cervical cancer radiotherapy, spectral data in the cervical cancer radiotherapy process and spectral data after the cervical cancer radiotherapy is finished and healed;
(2) Respectively carrying out smoothing and normalization processing on the spectral data acquired in the step (1);
(3) Dividing the spectral data processed in the step (2) into a training set, a verification set and a test set, and respectively carrying out principal component analysis;
(4) Selecting the first four components after principal component analysis in the step (3) as input, establishing a spectrum classification model by using a LibSVM software package, and training, verifying and testing the established spectrum classification model by using a training set, a verifying set and a testing set after principal component analysis;
(5) And (5) evaluating the curative effect of the cervical cancer radiotherapy based on the model obtained in the step (4).
2. The method for evaluating the curative effect of cervical cancer radiotherapy based on near-infrared scattering spectrum as claimed in claim 1, wherein the spectral data acquisition system in step (1) comprises a halogen light source, a fiber spectrometer and a dual-fiber probe, wherein the dual-fiber probe is respectively connected to the halogen light source and the fiber spectrometer.
3. The method for evaluating the curative effect of radiotherapy for cervical cancer based on near-infrared scattering spectrum as claimed in claim 2, wherein the in-vivo collection of the spectral data in step (1) comprises the following steps:
(1) Disinfecting the spectral data acquisition system and reserving a background spectrum of the current detection environment;
(2) And (3) enabling the front end detection region of the double-optical-fiber probe to be close to the outer edge of the cervical transition zone, moving the double-optical-fiber probe clockwise to enable the double-optical-fiber probe to slide across the whole cervical transition zone, after the collection is finished, removing the probe to obtain a group of near infrared spectrum data, storing the data and disinfecting the spectrum data collection system.
4. The method for evaluating the curative effect of cervical cancer radiotherapy based on near-infrared scattering spectrum as claimed in claim 2, wherein the dual-fiber probe in step (1) comprises a spectrum fiber and a light guide fiber, the spectrum fiber and the light guide fiber are independently wrapped and integrated in the same probe, wherein the light generated by the halogen light source is transmitted to the cervical tissue through the light guide fiber of the dual-fiber probe, and is transmitted to the fiber spectrometer through the spectrum fiber after being scattered by the cervical tissue.
5. The method for evaluating the curative effect of cervical cancer radiotherapy based on near-infrared scattering spectroscopy as claimed in claim 1, wherein the collection wavelength of the spectral data collection system in step (1) is 200-1100nm.
6. The method for evaluating the curative effect of cervical cancer radiotherapy based on near-infrared scattering spectrum as claimed in claim 1, wherein the step (1) further comprises screening the collected spectrum data by setting the slope and the peak of the spectrum of the band.
7. The method for evaluating the curative effect of cervical cancer radiotherapy based on near-infrared scattering spectroscopy as claimed in claim 1, wherein the spectral data is averaged every 20 points and smoothed in the step (2).
8. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
9. The cervical cancer radiotherapy curative effect evaluation device based on the near-infrared scattering spectrum is characterized by comprising a spectrum data acquisition system, a data processing module, a principal component analysis module and a spectrum classification module, wherein the spectrum data acquisition system transmits spectrum data acquired in vivo to the data processing module, and the data processing module smoothes and normalizes the received spectrum data and transmits the spectrum data to the principal component analysis module; the principal component analysis module is used for carrying out principal component analysis on the normalized spectrum data and transmitting the first four components to the spectrum classification module, and the classification result output by the spectrum classification module is an evaluation result; the spectrum classification module utilizes a LibSVM software package to establish a spectrum classification model, and training data of the spectrum classification model are data which are acquired by a spectrum data acquisition system in vivo and are obtained by processing spectral data of a focus before cervical cancer radiotherapy, spectral data in the cervical cancer radiotherapy process and spectral data after cervical cancer radiotherapy is finished and healed by a data processing module and a principal component analysis module in sequence.
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