Literature DB >> 29873296

An automated planning strategy for near real-time adaptive proton therapy in prostate cancer.

Thyrza Jagt1, Sebastiaan Breedveld, Rens van Haveren, Ben Heijmen, Mischa Hoogeman.   

Abstract

Proton therapy plans are very sensitive to anatomical changes such as density changes along the pencil-beam paths and changes in organ shape and location. Previously, we developed a restoration method which compensates for density changes along the pencil-beam paths but which is unable to adapt for anatomical changes. This study's purpose is to develop and evaluate an automated method for adaptation of IMPT plans in near real-time to the anatomy of the day. We developed an automated treatment plan adaptation method using (1) a restoration of spot positions (Bragg peaks) by adapting the energies to the new water equivalent path lengths; and (2) a spot addition to fully cover the target of the day, followed by a fast reference point method optimization of the spot weights resulting in a Pareto optimal plan for the daily anatomy. The method was developed and evaluated using 8-10 repeat CT scans of 11 prostate cancer patients, prescribing 55 Gy(RBE) (seminal vesicles and lymph nodes) with a boost to 74 Gy(RBE) (prostate). Applying the automated adaptation method resulted in a clinically acceptable target coverage (V 95% [Formula: see text] 98% and V 107% [Formula: see text] 2%) for 96% of the scans after a single iteration of adding 2500 spots. The other scans obtained target coverages with V 95% [Formula: see text] 98% and 2  <  V 107% [Formula: see text] 5%. When using two spot-addition iterations, all scans obtained clinically acceptable results. Compared to the restoration method the adaptation lowered the mean dose to rectum and bladder with median values of 6.2 Gy(RBE) and 4.7 Gy(RBE) respectively. The largest improvements were obtained for V 45Gy(RBE) for both rectum and bladder, with median differences of 10.3%-point and 10.8%-point respectively, and maximum differences up to 22%-point. The two adaptation steps took on average 7.3 s and 1.7 min respectively. No user interaction was needed, making this fast and fully automated method a first step towards online adaptive proton therapy.

Entities:  

Mesh:

Year:  2018        PMID: 29873296     DOI: 10.1088/1361-6560/aacaa7

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  7 in total

1.  Automatic configuration of the reference point method for fully automated multi-objective treatment planning applied to oropharyngeal cancer.

Authors:  Rens van Haveren; Ben J M Heijmen; Sebastiaan Breedveld
Journal:  Med Phys       Date:  2020-03-05       Impact factor: 4.071

Review 2.  Online daily adaptive proton therapy.

Authors:  Francesca Albertini; Michael Matter; Lena Nenoff; Ye Zhang; Antony Lomax
Journal:  Br J Radiol       Date:  2019-11-11       Impact factor: 3.039

Review 3.  Adaptive proton therapy.

Authors:  Harald Paganetti; Pablo Botas; Gregory C Sharp; Brian Winey
Journal:  Phys Med Biol       Date:  2021-11-15       Impact factor: 3.609

4.  Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer.

Authors:  Mohamed S Elmahdy; Thyrza Jagt; Roel Th Zinkstok; Yuchuan Qiao; Rahil Shahzad; Hessam Sokooti; Sahar Yousefi; Luca Incrocci; C A M Marijnen; Mischa Hoogeman; Marius Staring
Journal:  Med Phys       Date:  2019-07-12       Impact factor: 4.071

5.  Stability of daily rectal movement and effectiveness of replanning protocols for sparing rectal doses based on the daily CT images during proton treatment for prostate cancer.

Authors:  Yoshikazu Maeda; Yoshitaka Sato; Kazutaka Yamamoto; Hiroyasu Tamamura; Makoto Sasaki; Nobukazu Fuwa; Shigeyuki Takamatsu; Kyo Kume
Journal:  J Appl Clin Med Phys       Date:  2020-09-05       Impact factor: 2.102

6.  Dosimetric Uncertainties in Dominant Intraprostatic Lesion Simultaneous Boost Using Intensity Modulated Proton Therapy.

Authors:  Jun Zhou; Xiaofeng Yang; Chih-Wei Chang; Sibo Tian; Tonghe Wang; Liyong Lin; Yinan Wang; James Robert Janopaul-Naylor; Pretesh Patel; John D Demoor; Duncan Bohannon; Alex Stanforth; Bree Eaton; Mark W McDonald; Tian Liu; Sagar Anil Patel
Journal:  Adv Radiat Oncol       Date:  2021-10-04

7.  Integrating Structure Propagation Uncertainties in the Optimization of Online Adaptive Proton Therapy Plans.

Authors:  Lena Nenoff; Gregory Buti; Mislav Bobić; Arthur Lalonde; Konrad P Nesteruk; Brian Winey; Gregory Charles Sharp; Atchar Sudhyadhom; Harald Paganetti
Journal:  Cancers (Basel)       Date:  2022-08-14       Impact factor: 6.575

  7 in total

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