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Geometric and Dosimetric Validation of Deformable Image Registration for Prostate MR-guided Adaptive Radiotherapy

Geometric and Dosimetric Validation of Deformable Image Registration for Prostate MR-guided Adaptive Radiotherapy

来源:Arxiv_logoArxiv
英文摘要

Objective: Quantify geometric and dosimetric accuracy of a novel prostate MR-to-MR deformable image registration (DIR) approach to support MR-guided adaptive radiation therapy dose accumulation. Approach: We evaluated DIR accuracy in 25 patients treated with 30 Gy in 5 fractions on a 1.5 T MR-linac using an adaptive workflow. A reference MR was used for planning, with three images collected at each fraction: adapt MR for adaptive planning, verify MR for pretreatment position verification and beam-on for capturing anatomy during radiation delivery. We assessed three DIR approaches: intensity-based, intensity-based with controlling structures (CS) and novel intensity based with controlling structures and points of interest (CS+P). DIRs were performed between the reference and fraction images and within fractions. We propagated CTV, bladder, and rectum contours using the DIRs and compared to manual contours using Dice similarity coefficient, mean distance to agreement (DTAmean), and dose-volume metrics. Results: CS and CS+P improved geometric agreement between contours over intensity-only DIR. DTAmean for reference-to-beam-on intensity-only DIR was 0.131+/-0.009cm (CTV), 0.46+/-0.08cm (bladder), and 0.154+/-0.013cm (rectum). For the CS, the values were 0.018+/-0.002cm, 0.388+/-0.14cm, and 0.036+/-0.013cm. For CS+P these values were 0.015+/-0.001cm, 0.025+/-0.004cm, and 0.021+/-0.002cm. Dosimetrically, comparing CS and CS+P for reference to beam-on DIRs resulted in a change of CTV D98% from [-29cGy, 19cGy] to [-18cGy, 26cGy], rectum D1cc from [-106cGy, 72cGy] to [-52cGy, 74cGy], and bladder D5cc from [-51cGy, 544cGy] to [-79cGy, 36cGy]. Significance: CS improved geometric and dosimetric accuracy over intensity-only DIR, with CS+P providing the most consistent performance. However, session image segmentation remains a challenge, which may be addressed with automated contouring.

Victor N. Malkov、Iymad R. Mansour、Vickie Kong、Winnie Li、Jennifer Dang、Parisa Sadeghi、Inmaculada Navarro、Jerusha Padayachee、Peter Chung、Jeff D. Winter、Tony Tadic

Mayo Clinic, Department of Radiation Oncology, Rochester, MN, USARadiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, CanadaRadiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, CanadaRadiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, CanadaRadiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, CanadaRadiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, CanadaRadiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, CanadaRadiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, CanadaRadiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, CanadaRadiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, CanadaRadiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, Canada

医学研究方法临床医学

Victor N. Malkov,Iymad R. Mansour,Vickie Kong,Winnie Li,Jennifer Dang,Parisa Sadeghi,Inmaculada Navarro,Jerusha Padayachee,Peter Chung,Jeff D. Winter,Tony Tadic.Geometric and Dosimetric Validation of Deformable Image Registration for Prostate MR-guided Adaptive Radiotherapy[EB/OL].(2025-04-10)[2025-05-14].https://arxiv.org/abs/2504.07933.点此复制

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