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Published on: March 11, 2021
Clinical iterative model development improves knowledge-based plan quality for high-risk prostate cancer with four
Johanna Austrheim Hundvin1, Kristine Fjellanger1, Helge Egil Seime Pettersen1
1Department of Oncology and Medical Physics, Haukeland University Hospital, Bergen, Norway.
Knowledge-based planning (KBP) using RapidPlan improved radiotherapy treatment plans for prostate cancer patients. Model tuning further enhanced plan quality and consistency, reducing organ-at-risk doses.
Area of Science:
- Radiation Oncology
- Medical Physics
- Prostate Cancer Treatment
Background:
- Manual Volumetric Modulated Arc Therapy (VMAT) for high-risk prostate cancer with whole pelvic radiotherapy (WPRT) is complex and time-consuming.
- Investigated the use of a tuned Knowledge-Based Planning (KBP) model via a commercial system to improve radiotherapy planning.
- Focus on optimizing treatment for high-risk prostate cancer patients requiring multiple integrated dose levels.
Purpose of the Study:
- To evaluate if a well-tuned KBP model can enhance the radiotherapy planning process and improve plan quality for high-risk prostate cancer.
- To assess the impact of KBP on achieving prescribed dose levels for pelvic lymph nodes, prostate, and seminal vesicles.
- To compare the efficiency and quality of KBP-generated plans against manually created VMAT plans.
Main Methods:
- Developed an initial KBP model (RapidPlan, RP) using 69 manually planned VMAT treatments for high-risk prostate cancer.
- Used clinical plans from an RP model (July 2019-Feb 2020) to develop a second, tuned RP model.
- Validated both models on an independent cohort of 40 patients, comparing target coverage, conformity indices, and organ-at-risk doses (bladder, bowel bag, rectum).
Main Results:
- Target coverage and conformity were comparable between manual and RP-generated plans.
- The final RP model significantly reduced mean dose and generalized equivalent uniform dose (gEUD) for bladder, bowel bag, and rectum compared to manual plans (p < .05).
- Rectal dose-volume histogram (DVH) interpatient variation was reduced by 23% with the final RP model.
Conclusions:
- Knowledge-Based Planning (KBP) demonstrably improves the quality and consistency of radiotherapy treatment plans for high-risk prostate cancer.
- Tuning the KBP model using clinically delivered plans further refines outcomes, leading to superior plan quality.
- KBP offers a promising approach to streamline complex radiotherapy planning while enhancing therapeutic efficacy and patient safety.
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