Benchmarking daily adaptation using fully automated radiotherapy treatment plan optimization for rectal cancer. (October 2022)

• Record Type: Journal Article
• Authors: Jagt, Thyrza Z.; Janssen, Tomas M.; Betgen, Anja; Wiersema, Lisa; Verhage, Rick; Garritsen, Sanne; Vijlbrief-Bosman, Tineke; de Ruiter, Peter; Remeijer, Peter; Marijnen, Corrie A.M.; Peters, Femke P.; Sonke, Jan-Jakob
• Is Part Of: Physics and imaging in radiation oncology. Volume 24(2022)
• Page Start: 7
• Page End: 13
• Publication Date: 2022-10
• Subjects: Online plan adaptation -- MRI guided radiotherapy -- Automated treatment planning; Radiotherapy -- Periodicals; Radiation dosimetry -- Periodicals; Cancer -- Imaging -- Periodicals; Oncology -- Periodicals; 615.842
• DOI: 10.1016/j.phro.2022.08.006
• Languages: English
• ISSNs: 2405-6316

Abstract

Highlights: Daily adaptation efficiency can improve by using the reference plan objectives. Automated treatment planning can be used to benchmark daily adaptation methods. Daily adaptation yielded plan quality comparable to automated treatment planning. Abstract: Background/purpose: In daily plan adaptation the radiotherapy treatment plan is adjusted just prior to delivery. A simple approach is taking the planning objectives of the reference plan and directly applying these in re-optimization. Here we present a tested method to verify whether daily adaptation without tweaking of the objectives can maintain the plan quality throughout treatment. Materials/methods: For fifteen rectal cancer patients, automated treatment planning was used to generate plans mimicking manual reference plans on the planning scans. For 74 fraction scans (4–5 per patient) an automated plan and a daily adapted plan were generated, where the latter re-optimizes the reference plan objectives without any tweaking. To evaluate the robustness of the daily adaptation, the adapted plans were compared to the autoplanning plans. Results: Median differences between the autoplanning plans on the planning scans and the reference plans were between −1 and 0.2 Gy. The largest interquartile range (1 Gy) was seen for the Lumbar Skin D2%. For the daily scans the PTV D2% and D98% differences between autoplanning and adapted plans were within ± 0.7 Gy, with mean differences within ± 0.3 Gy. Positive differences indicate higher values were obtained using autoplanning. For the Bowelarea + Bladder and the Lumbar Skin the D2% and Dmean differences were all within ± 2.6 Gy, with mean differences between −0.9 and 0.1 Gy. Conclusion: Automated treatment planning can be used to benchmark daily adaptation techniques. The investigated adaptation workflow can robustly perform high quality adaptations without daily adjusting of the patient-specific planning objectives for rectal cancer radiotherapy.