Purpose: The purpose of this work was to investigate the impact of a predictive DVH (pDVH) model developed at one institution on IMRT plan quality control (QC) at an unrelated radiotherapy facility. Methods: DICOM‐RT datasets for twenty randomly selected intact prostate cancer patients treated at a small clinic were analyzed with knowledge based pDVH models developed at a larger institution. Previously validated rectum and bladder pDVH models used in this study were derived based on the correlation of expected dose to the distance from a voxel to the PTV surface. A sum of residuals (SR) metric quantifying the integrated difference between clinical DVHs and the pDVHs was used to rank the 20 evaluated plans. The 5 plans with greatest deviation from the prediction were replanned by the small clinic to evaluate the ability to achieve rectum and bladder DVH predictions while maintaining PTV quality metrics per institutional standard. Metrics used to evaluate plan quality (V65 and V40) quantified the clinical gains in the rectum and bladder DVHs. The pDVHs were compared to the replan DVHs using dV65=V65(replan)‐V65(pred), dV40=V40(replan) ‐ V40(pred), and mean SR to measure DVH prediction accuracy. Results: The significance of IMRT QC using pDVHs was demonstrated by an average reduction in V65 and V40 in the 5 replanned patients of 4.8% ± 2.3% and 17.9% ± 10.3% for the rectum and 3.4% ± 2.1% and 6.0% ± 2.8% for the bladder, respectively. The pDVH models demonstrated excellent prediction accuracy with an average dV65 and dV40 of 0.9% ± 1.1% and 0.7% ± 1.4% for the rectum and 0.4% ± 0.5% and 0.6% ± 0.9% for the bladder, respectively. Conclusion: DICOM‐based pDVH modeling methods based on patient geometry accurately predict achievable rectum and bladder DVH parameters that are clinically relevant and may facilitate improved IMRT plan quality across multiple institutions. L.Appenzoller, S. Mutic, K. Moore: Patent Application # 13, 486,809 : Developing Predictive Dose‐Volume Relationships for a Radiotherapy Treatment.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging