Support Vector Machine Model Predicts Dose for Organs at Risk in High-Dose Rate Brachytherapy of Cervical Cancer.

Ping Zhou,Yu Zhang,Hao Zhou,Xiao Fu,Haowen Pang,Sheng Lin,Bo Liu,Xiaojie Li

doi:10.3389/fonc.2021.619384

Abstract

IntroductionThis study aimed to establish a support vector machine (SVM) model to predict the dose for organs at risk (OARs) in intracavitary brachytherapy planning for cervical cancer with tandem and ovoid treatments.MethodsFifty patients with loco-regionally advanced cervical cancer treated with 200 CT-based tandem and ovoid brachytherapy plans were included. The brachytherapy plans were randomly divided into the training (N = 160) and verification groups (N = 40). The bladder, rectum, sigmoid colon, and small intestine were divided into sub-OARs. The SVM model was established using MATLAB software based on the sub-OAR volume to predict the bladder, rectum, sigmoid colon, and small intestine . Model performance was quantified by mean squared error (MSE) and δ . The goodness of fit of the model was quantified by the coefficient of determination (R2). The accuracy and validity of the SVM model were verified using the validation group.ResultsThe value of the bladder, rectum, sigmoid colon, and small intestine correlated with the volume of the corresponding sub-OARs in the training group. The mean squared error (MSE) in the SVM model training group was <0.05; the R2 of each OAR was >0.9. There was no significant difference between the -predicted and actual values in the validation group (all P > 0.05): bladder δ = 0.024 ± 0.022, rectum δ = 0.026 ± 0.014, sigmoid colon δ = 0.035 ± 0.023, and small intestine δ = 0.032 ± 0.025.ConclusionThe SVM model established in this study can effectively predict the for the bladder, rectum, sigmoid colon, and small intestine in cervical cancer brachytherapy.

Highlights

This study aimed to establish a support vector machine (SVM) model to predict the dose for organs at risk (OARs) in intracavitary brachytherapy planning for cervical cancer with tandem and ovoid treatments
The D2cm3 value of the bladder, rectum, sigmoid colon, and small intestine correlated with the volume of the corresponding sub-OARs in the training group
There was no significant difference between the D2cm3 -predicted and actual values in the validation group: bladder d = 0.024 ± 0.022, rectum d = 0.026 ± 0.014, sigmoid colon d = 0.035 ± 0.023, and small intestine d = 0.032 ± 0.025

Summary

Introduction

This study aimed to establish a support vector machine (SVM) model to predict the dose for organs at risk (OARs) in intracavitary brachytherapy planning for cervical cancer with tandem and ovoid treatments. Methods for predicting the dose to the OARs have been widely introduced in external irradiation intensity-modulated radiotherapy [6,7,8,9,10] These approaches typically use libraries of existing patient plans to create models that predict the extent of OAR sparing that can be achieved in a new patient based on, for example, the planning target volume (PTV)-OAR distance and overlap [11]. The bladder, rectum, sigmoid colon, and small intestine were divided into subOARs. We analyzed the correlation between the sub-organ volume and D2cm of each OAR, and the SVM prediction model based on the correlation was established to predict the dose of each OAR before brachytherapy; the model can be used as an evaluation standard for brachytherapy plans to minimize the effects of confounding factors on the quality of the plans. This approach has been granted a Chinese invention patent (patent no.: 201610529290.8)

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