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Updated: May 26, 2026
Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
A volume-controlled, anatomy-driven autoplanning strategy for whole-pelvic volumetric modulated arc therapy
Chih-Yuan Lin1,2, An-Cheng Shiau1,3,4, Ti-Hao Wang4,5
1Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Background And Purpose:
Whole pelvic radiotherapy (WPRT) involves volumetric modulated arc therapy (VMAT) planning that requires careful consideration of target coverage and organ-at-risk (OAR) sparing. Manual planning is labor-intensive and subject to inter-planner variability. To address these challenges, we developed and evaluated a Volume-Controlled Autoplan (VCAP), an anatomy-driven automated planning strategy that incorporates volumetric overlap information into the optimization framework.
Materials And Methods:
This study retrospectively analyzed a cohort of patients with pelvic malignancies who underwent WPRT. VCAP was compared against clinical planning (CP), Autoplan (AP), and RapidPlan (RP). Dosimetric endpoints included PTV coverage (V95, conformity index, homogeneity index) and OAR sparing (rectum, bladder, bowel bag, and femoral heads). Regression models based on OAR-PTV overlap were used to derive predefined thresholds for guiding the optimization process. Dose-volume histograms (DVHs) and dose distributions were evaluated, and statistical comparisons were performed.
Results:
VCAP achieved comparable PTV coverage relative to CP, AP, and RP, with V95 consistently above 95%. Rectal doses were reduced, with V30 decreased by an average of 24.6% relative to CP and 12-13% relative to AP and RP. Bladder sparing was also improved in the 15-40 Gy range. The bowel bag showed lower intermediate-dose exposure, with V30 reduced by more than 20.5% compared with CP. Planning efficiency was markedly enhanced, with mean planning time reduced from approximately 120 minutes with CP to 21 minutes with automatic strategies, while VCAP demonstrated consistent plan quality across the cohort.
Conclusion:
VCAP provides an efficient and anatomy-driven approach to VMAT planning for WPRT. By incorporating volumetric overlap constraints into the optimization process, VCAP enhances OAR sparing while preserving robust PTV coverage. These findings suggest that VCAP may improve planning efficiency and consistency in clinical practice. Further validation is warranted to assess its generalizability and potential role in broader clinical applications.
