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Evaluation of an Open Source Registration Package for Automatic Contour Propagation in Online Adaptive Intensity-Modulated Proton Therapy of Prostate Cancer.
- Source :
- Frontiers in Oncology; 11/27/2019, Vol. 9, p1-13, 13p
- Publication Year :
- 2019
-
Abstract
- Objective: Our goal was to investigate the performance of an open source deformable image registration package, elastix , for fast and robust contour propagation in the context of online-adaptive intensity-modulated proton therapy (IMPT) for prostate cancer. Methods: A planning and 7–10 repeat CT scans were available of 18 prostate cancer patients. Automatic contour propagation of repeat CT scans was performed using elastix and compared with manual delineations in terms of geometric accuracy and runtime. Dosimetric accuracy was quantified by generating IMPT plans using the propagated contours expanded with a 2 mm (prostate) and 3.5 mm margin (seminal vesicles and lymph nodes) and calculating dosimetric coverage based on the manual delineation. A coverage of V <subscript>95%</subscript> ≥ 98% (at least 98% of the target volumes receive at least 95% of the prescribed dose) was considered clinically acceptable. Results: Contour propagation runtime varied between 3 and 30 s for different registration settings. For the fastest setting, 83 in 93 (89.2%), 73 in 93 (78.5%), and 91 in 93 (97.9%) registrations yielded clinically acceptable dosimetric coverage of the prostate, seminal vesicles, and lymph nodes, respectively. For the prostate, seminal vesicles, and lymph nodes the Dice Similarity Coefficient (DSC) was 0.87 ± 0.05, 0.63 ± 0.18, and 0.89 ± 0.03 and the mean surface distance (MSD) was 1.4 ± 0.5 mm, 2.0 ± 1.2 mm, and 1.5 ± 0.4 mm, respectively. Conclusion: With a dosimetric success rate of 78.5–97.9%, this software may facilitate online adaptive IMPT of prostate cancer using a fast, free and open implementation. [ABSTRACT FROM AUTHOR]
- Subjects :
- PROTON therapy
PROSTATE cancer
SEMINAL vesicles
CANCER treatment
IMAGE registration
Subjects
Details
- Language :
- English
- ISSN :
- 2234943X
- Volume :
- 9
- Database :
- Complementary Index
- Journal :
- Frontiers in Oncology
- Publication Type :
- Academic Journal
- Accession number :
- 139905864
- Full Text :
- https://doi.org/10.3389/fonc.2019.01297