Literature DB >> 27782706

Investigating deformable image registration and scatter correction for CBCT-based dose calculation in adaptive IMPT.

Christopher Kurz1, Florian Kamp2, Yang-Kyun Park3, Christoph Zöllner4, Simon Rit5, David Hansen6, Mark Podesta7, Gregory C Sharp3, Minglun Li2, Michael Reiner2, Jan Hofmaier2, Sebastian Neppl2, Christian Thieke2, Reinoud Nijhuis2, Ute Ganswindt2, Claus Belka2, Brian A Winey3, Katia Parodi4, Guillaume Landry4.   

Abstract

PURPOSE: This work aims at investigating intensity corrected cone-beam x-ray computed tomography (CBCT) images for accurate dose calculation in adaptive intensity modulated proton therapy (IMPT) for prostate and head and neck (H&N) cancer. A deformable image registration (DIR)-based method and a scatter correction approach using the image data obtained from DIR as prior are characterized and compared on the basis of the same clinical patient cohort for the first time.
METHODS: Planning CT (pCT) and daily CBCT data (reconstructed images and measured projections) of four H&N and four prostate cancer patients have been considered in this study. A previously validated Morphons algorithm was used for DIR of the planning CT to the current CBCT image, yielding a so-called virtual CT (vCT). For the first time, this approach was translated from H&N to prostate cancer cases in the scope of proton therapy. The warped pCT images were also used as prior for scatter correction of the CBCT projections for both tumor sites. Single field uniform dose and IMPT (only for H&N cases) treatment plans have been generated with a research version of a commercial planning system. Dose calculations on vCT and scatter corrected CBCT (CBCTcor) were compared by means of the proton range and a gamma-index analysis. For the H&N cases, an additional diagnostic replanning CT (rpCT) acquired within three days of the CBCT served as additional reference. For the prostate patients, a comprehensive contour comparison of CBCT and vCT, using a trained physician's delineation, was performed.
RESULTS: A high agreement of vCT and CBCTcor was found in terms of the proton range and gamma-index analysis. For all patients and indications between 95% and 100% of the proton dose profiles in beam's eye view showed a range agreement of better than 3 mm. The pass rate in a (2%,2 mm) gamma-comparison was between 96% and 100%. For H&N patients, an equivalent agreement of vCT and CBCTcor to the reference rpCT was observed. However, for the prostate cases, an insufficient accuracy of the vCT contours retrieved from DIR was found, while the CBCTcor contours showed very high agreement to the contours delineated on the raw CBCT.
CONCLUSIONS: For H&N patients, no considerable differences of vCT and CBCTcor were found. For prostate cases, despite the high dosimetric agreement, the DIR yields incorrect contours, probably due to the more pronounced anatomical changes in the abdomen and the reduced soft-tissue contrast in the CBCT. Using the vCT as prior, these inaccuracies can be overcome and images suitable for accurate delineation and dose calculation in CBCT-based adaptive IMPT can be retrieved from scatter correction of the CBCT projections.

Entities:  

Mesh:

Year:  2016        PMID: 27782706     DOI: 10.1118/1.4962933

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  26 in total

1.  Water equivalent path length calculations using scatter-corrected head and neck CBCT images to evaluate patients for adaptive proton therapy.

Authors:  Jihun Kim; Yang-Kyun Park; Gregory Sharp; Paul Busse; Brian Winey
Journal:  Phys Med Biol       Date:  2016-12-14       Impact factor: 3.609

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

3.  Beam angle optimization using angular dependency of range variation assessed via water equivalent path length (WEPL) calculation for head and neck proton therapy.

Authors:  Jihun Kim; Yang-Kyun Park; Gregory Sharp; Paul Busse; Brian Winey
Journal:  Phys Med       Date:  2019-12-05       Impact factor: 2.685

Review 4.  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

5.  A Comparison Study Between CNN-Based Deformed Planning CT and CycleGAN-Based Synthetic CT Methods for Improving iCBCT Image Quality.

Authors:  Bo Yang; Yankui Chang; Yongguang Liang; Zhiqun Wang; Xi Pei; Xie George Xu; Jie Qiu
Journal:  Front Oncol       Date:  2022-05-30       Impact factor: 5.738

6.  Evaluation of CBCT scatter correction using deep convolutional neural networks for head and neck adaptive proton therapy.

Authors:  Arthur Lalonde; Brian Winey; Joost Verburg; Harald Paganetti; Gregory C Sharp
Journal:  Phys Med Biol       Date:  2020-12-04       Impact factor: 3.609

7.  Comparison of weekly and daily online adaptation for head and neck intensity-modulated proton therapy.

Authors:  Mislav Bobić; Arthur Lalonde; Gregory C Sharp; Clemens Grassberger; Joost M Verburg; Brian A Winey; Antony J Lomax; Harald Paganetti
Journal:  Phys Med Biol       Date:  2021-02-25       Impact factor: 3.609

8.  Onboard cone-beam CT-based replan evaluation for head and neck proton therapy.

Authors:  Alexander Stanforth; Liyong Lin; Jonathan J Beitler; James R Janopaul-Naylor; Chih-Wei Chang; Robert H Press; Sagar A Patel; Jennifer Zhao; Bree Eaton; Eduard E Schreibmann; James Jung; Duncan Bohannon; Tian Liu; Xiaofeng Yang; Mark W McDonald; Jun Zhou
Journal:  J Appl Clin Med Phys       Date:  2022-02-07       Impact factor: 2.243

9.  Image-based shading correction for narrow-FOV truncated pelvic CBCT with deep convolutional neural networks and transfer learning.

Authors:  Matteo Rossi; Gabriele Belotti; Chiara Paganelli; Andrea Pella; Amelia Barcellini; Pietro Cerveri; Guido Baroni
Journal:  Med Phys       Date:  2021-10-26       Impact factor: 4.506

10.  Dosimetric assessment of patient dose calculation on a deep learning-based synthesized computed tomography image for adaptive radiotherapy.

Authors:  Olga M Dona Lemus; Yi-Fang Wang; Fiona Li; Sachin Jambawalikar; David P Horowitz; Yuanguang Xu; Cheng-Shie Wuu
Journal:  J Appl Clin Med Phys       Date:  2022-03-25       Impact factor: 2.243

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.