Study of cervical precancerous lesions detection by spectroscopy and support vector machine

Abstract

Background and objective

Diffuse reflectance spectroscopy (DRS) offers a fast, non-invasive, and low-cost alternative for cervical cancer diagnosis. We aim to develop a method for screening precancerous lesions based on DRS.

Material and methods

Characteristic parameters of cervical tissue were extracted from spectra, including optical characteristic parameters such as absorption and scattering coefficients, and some slope and area parameters of the spectrum. Data were randomly divided into training (60%) and test (40%) sets. Of the 210 included patients, 166 were healthy, 22 had erosion of the cervix, and 31 had cervical intraepithelial neoplasia (CIN). The support vector machine (SVM) algorithm was used to classify normal and abnormal cervical tissue based on 11 characteristic parameters.

Results

The SVM with linear kernel function, applied on the training data, could distinguish tissue with lesions from healthy tissue with an accuracy of 1.00. When the classifiers were applied to the test set, erosion of cervix and CIN could be discriminated from healthy tissue with an accuracy of 0.95 ($\pm$0.03).

Conclusions

This research shows that the diagnostic algorithm can be valuable for non-invasive diagnosis of cervical cancer. This is a significant step toward the development of a tool for tissue assessment of cervical cancer.

Keywords:

• Cervical cancer
• Support vector machine (SVM)
• Diffuse reflectance spectroscopy (DRS)

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This study was supported by National Natural Science Foundation of China [61875085] and the Postgraduate Research and Practice Innovation Program of Jiangsu Province [KYCX19_0173]. Meanwhile, the authors are very grateful to the Department of Gynecology of Nanjing BenQ Hospital for supporting the experiment.