A knowledge-based organ dose prediction tool for brachytherapy treatment planning of patients with cervical cancer.

Brachytherapy
Tahir I YusufalySandra M Meyers

Abstract

The purpose of this study is to explore knowledge-based organ-at-risk dose estimation for intracavitary brachytherapy planning for cervical cancer. Using established external-beam knowledge-based dose-volume histogram (DVH) estimation methods, we sought to predict bladder, rectum, and sigmoid D2cc for tandem and ovoid treatments. A total of 136 patients with loco-regionally advanced cervical cancer treated with 456 (356:100 training:validation ratio) CT-based tandem and ovoid brachytherapy fractions were analyzed. Single fraction prescription doses were 5.5-8 Gy with dose criteria for the high-risk clinical target volume, bladder, rectum, and sigmoid. DVH estimations were obtained by subdividing training set organs-at-risk into high-risk clinical target volume boundary distance subvolumes and computing cohort-averaged differential DVHs. Full DVH estimation was then performed on the training and validation sets. Model performance was quantified by ΔD2cc = D2cc(actual)-D2cc(predicted) (mean and standard deviation). ΔD2cc between training and validation sets were compared with a Student's t test (p < 0.01 significant). Categorical variables (physician, fraction-number, total fractions, and case complexity) that might explain model...Continue Reading

Citations

Jan 30, 2021·JCO Clinical Cancer Informatics·Brent M CoveleKevin L Moore
Feb 16, 2021·Medical Physics·Christian V GuthierRobert A Cormack
May 18, 2021·BioMed Research International·Venkatesan ChandranS Manoharan

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