title: An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm.
abstract: Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be satisfied when the TPS-QC tool generated re-optimized plans without sacrificing other dosimetric endpoints. In addition to its feasibility and accuracy, the proposed TPS-QC tool is also user-friendly and easy to operate, both of which are necessary characteristics for clinical use.
authors.affiliation: Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China.|Radiation Oncology Department, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.
authors.forename: Ting
authors.initials: T
authors.lastname: Song
authors.affiliation: Center for Advanced Radiotherapy Technologies and Department of Radiation Oncology, University of California San Diego, La Jolla, United States of America.
authors.forename: Nan
authors.initials: N
authors.lastname: Li
authors.affiliation: Center for Advanced Radiotherapy Technologies and Department of Radiation Oncology, University of California San Diego, La Jolla, United States of America.
authors.forename: Masoud
authors.initials: M
authors.lastname: Zarepisheh
authors.affiliation: Radiation Oncology Department, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.
authors.forename: Yongbao
authors.initials: Y
authors.lastname: Li
authors.affiliation: Center for Advanced Radiotherapy Technologies and Department of Radiation Oncology, University of California San Diego, La Jolla, United States of America.
authors.forename: Quentin
authors.initials: Q
authors.lastname: Gautier
authors.affiliation: Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China.
authors.forename: Linghong
authors.initials: L
authors.lastname: Zhou
authors.affiliation: Center for Advanced Radiotherapy Technologies and Department of Radiation Oncology, University of California San Diego, La Jolla, United States of America.
authors.forename: Loren
authors.initials: L
authors.lastname: Mell
authors.affiliation: Radiation Oncology Department, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.
authors.forename: Steve
authors.initials: S
authors.lastname: Jiang
authors.affiliation: Center for Advanced Radiotherapy Technologies and Department of Radiation Oncology, University of California San Diego, La Jolla, United States of America.
authors.forename: Laura
authors.initials: L
authors.lastname: Cerviño
mesh_terms: D000465:Algorithms; D002584:Cervix Uteri / Q000528:radiation effects; D005260:Female; D006801:Humans; D058958:Organs at Risk / Q000528:radiation effects; D011786:Quality Control; D011880:Radiotherapy Planning, Computer-Assisted / Q000191:economics / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000191:economics / Q000379:methods*; D002583:Uterine Cervical Neoplasms / Q000532:radiotherapy; D057188:Workflow