{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T07:23:55Z","timestamp":1770621835440,"version":"3.49.0"},"reference-count":22,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,7,15]],"date-time":"2021-07-15T00:00:00Z","timestamp":1626307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Oncol."],"abstract":"Introduction<\/jats:title>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.<\/jats:p><\/jats:sec>Methods<\/jats:title>Fifty 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 D<\/mml:mtext>2<\/mml:mn>c<\/mml:mtext>m<\/mml:mtext>3<\/mml:mn><\/mml:msup><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math><\/jats:inline-formula>. Model performance was quantified by mean squared error (MSE) and \u03b4 (<\/mml:mo>\u03b4<\/mml:mi>=<\/mml:mo>|<\/mml:mo>D<\/mml:mtext>2<\/mml:mn>c<\/mml:mtext>m<\/mml:mtext>3<\/mml:mn><\/mml:msup><\/mml:mrow><\/mml:msub>\/<\/mml:mo>D<\/mml:mtext>prescription<\/mml:mtext><\/mml:mrow><\/mml:msub>(<\/mml:mo>actual<\/mml:mtext><\/mml:mrow>)<\/mml:mo><\/mml:mrow>\u2212<\/mml:mo>D<\/mml:mtext>2<\/mml:mn>c<\/mml:mtext>m<\/mml:mtext>3<\/mml:mn><\/mml:msup><\/mml:mrow><\/mml:msub>\/<\/mml:mo>D<\/mml:mtext>prescription<\/mml:mtext><\/mml:mrow><\/mml:msub>(<\/mml:mo>predicted<\/mml:mtext><\/mml:mrow>)<\/mml:mo><\/mml:mrow><\/mml:mrow>|<\/mml:mo><\/mml:mrow><\/mml:mrow>)<\/mml:mo><\/mml:mrow><\/mml:mrow><\/mml:math><\/jats:inline-formula>. The goodness of fit of the model was quantified by the coefficient of determination (R2<\/jats:sup>). The accuracy and validity of the SVM model were verified using the validation group.<\/jats:p><\/jats:sec>Results<\/jats:title>The D<\/mml:mtext>2<\/mml:mn>c<\/mml:mtext>m<\/mml:mtext>3<\/mml:mn><\/mml:msup><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math><\/jats:inline-formula> 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 &lt;0.05; the R2<\/jats:sup> of each OAR was &gt;0.9. There was no significant difference between the D<\/mml:mtext>2<\/mml:mn>c<\/mml:mtext>m<\/mml:mtext>3<\/mml:mn><\/mml:msup><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math><\/jats:inline-formula> -predicted and actual values in the validation group (all P<\/jats:italic> &gt; 0.05): bladder \u03b4 = 0.024 \u00b1 0.022, rectum \u03b4 = 0.026 \u00b1 0.014, sigmoid colon \u03b4 = 0.035 \u00b1 0.023, and small intestine \u03b4 = 0.032 \u00b1 0.025.<\/jats:p><\/jats:sec>Conclusion<\/jats:title>The SVM model established in this study can effectively predict the D<\/mml:mtext>2<\/mml:mn>c<\/mml:mtext>m<\/mml:mtext>3<\/mml:mn><\/mml:msup><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math><\/jats:inline-formula> for the bladder, rectum, sigmoid colon, and small intestine in cervical cancer brachytherapy.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fonc.2021.619384","type":"journal-article","created":{"date-parts":[[2021,7,15]],"date-time":"2021-07-15T12:20:03Z","timestamp":1626351603000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Support Vector Machine Model Predicts Dose for Organs at Risk in High-Dose Rate Brachytherapy of Cervical Cancer"],"prefix":"10.3389","volume":"11","author":[{"given":"Ping","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojie","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sheng","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haowen","family":"Pang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2021,7,15]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1002\/cncr.30667","article-title":"Cervical Cancer: A Global Health Crisis","volume":"123","author":"Small","year":"2017","journal-title":"Cancer"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1097\/IGC.0000000000001216","article-title":"The European Society of Gynaecological Oncology\/European Society for Radiotherapy and Oncology\/European Society of Pathology Guidelines for the Management of Patients With Cervical Cancer","volume":"28","author":"Cibula","year":"2018","journal-title":"Int J Gynecol Cancer"},{"key":"B3","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/j.brachy.2016.03.008","article-title":"American Brachytherapy Task Group Report. 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