SU-E-T-574: Novel Chance-Constrained Optimization in Intensity-Modulated Proton Therapy Planning to Account for Range and Patient Setup Uncertainties

2015 ◽  
Vol 42 (6Part21) ◽  
pp. 3467-3468
Author(s):  
Y An ◽  
J Liang ◽  
W Liu
Keyword(s):  
Constrained Optimization ◽  
Proton Therapy ◽  
Therapy Planning ◽  
Intensity Modulated Proton Therapy ◽  
Intensity Modulated ◽  
Patient Setup

scholarly journals A fast optimization algorithm for multicriteria intensity modulated proton therapy planning

2010 ◽  
Vol 37 (9) ◽  
pp. 4938-4945 ◽  
Author(s):  
Wei Chen ◽  
David Craft ◽  
Thomas M. Madden ◽  
Kewu Zhang ◽  
Hanne M. Kooy ◽  
...  
Keyword(s):  
Proton Therapy ◽  
Optimization Algorithm ◽  
Therapy Planning ◽  
Intensity Modulated Proton Therapy ◽  
Intensity Modulated ◽  
Fast Optimization

scholarly journals Effectiveness of robust optimization in intensity-modulated proton therapy planning for head and neck cancers

2013 ◽  
Vol 40 (5) ◽  
pp. 051711 ◽  
Author(s):  
Wei Liu ◽  
Steven J. Frank ◽  
Xiaoqiang Li ◽  
Yupeng Li ◽  
Peter C. Park ◽  
...  
Keyword(s):  
Robust Optimization ◽  
Head And Neck ◽  
Proton Therapy ◽  
Head And Neck Cancers ◽  
Therapy Planning ◽  
Intensity Modulated Proton Therapy ◽  
Intensity Modulated

scholarly journals Intensity modulated proton therapy planning study for organ at risk sparing in rectal cancer re-irradiation

2021 ◽  
pp. 1-4
Author(s):  
H. S. Rønde ◽  
J. F. Kallehauge ◽  
C. J. S. Kronborg ◽  
L. Nyvang ◽  
B. L. Rekstad ◽  
...  
Keyword(s):  
At Risk ◽  
Rectal Cancer ◽  
Proton Therapy ◽  
Therapy Planning ◽  
Planning Study ◽  
Intensity Modulated Proton Therapy ◽  
Intensity Modulated ◽  
Organ At Risk

scholarly journals CBCT-Based Adaptive Assessment Workflow for Intensity Modulated Proton Therapy for Head and Neck Cancer

2021 ◽  
Author(s):  
Mariluz De Ornelas ◽  
Yihang Xu ◽  
Kyle Padgett ◽  
Ryder M. Schmidt ◽  
Michael Butkus ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Head And Neck ◽  
Proton Therapy ◽  
Case Scenario ◽  
Worst Case ◽  
Intensity Modulated Proton Therapy ◽  
Intensity Modulated ◽  
Worst Case Scenario ◽  
Patient Setup ◽  
Delivered Dose

Abstract Purpose Anatomical changes and patient setup uncertainties during intensity modulated proton therapy (IMPT) of head and neck (HN) cancers demand frequent evaluation of delivered dose. This work investigated a cone-beam computed tomography (CBCT) and deformable image registration based therapy workflow to demonstrate the feasibility of proton dose calculation on synthetic computed tomography (sCT) for adaptive IMPT treatment of HN cancer. Materials and Methods Twenty-one patients with HN cancer were enrolled in this study, a retrospective institutional review board protocol. They had previously been treated with volumetric modulated arc therapy and had daily iterative CBCT. For each patient, robust optimization (RO) IMPT plans were generated using ±3 mm patient setup and ±3% proton range uncertainties. The sCTs were created and the weekly delivered dose was recalculated using an adaptive dose accumulation workflow in which the planning computed tomography (CT) was deformably registered to CBCTs and Hounsfield units transferred from the planning CT. Accumulated doses from ±3 mm/±3% RO-IMPT plans were evaluated using clinical dose-volume constraints for targets (clinical target volume, or CTV) and organs at risk. Results Evaluation of weekly recalculated dose on sCTs showed that most of the patient plans maintained target dose coverage. The primary CTV remained covered by the V95 > 95% (95% of the volume receiving more than 95% of the prescription dose) worst-case scenario for 84.5% of the weekly fractions. The oral cavity accumulated mean dose remained lower than the worst-case scenario for all patients. Parotid accumulated mean dose remained within the uncertainty bands for 18 of the 21 patients, and all were kept lower than RO-IMPT worst-case scenario for 88.7% and 84.5% for left and right parotids, respectively. Conclusion This study demonstrated that RO-IMPT plans account for most setup and anatomical uncertainties, except for large weight-loss changes that need to be tracked throughout the treatment course. We showed that sCTs could be a powerful decision tool for adaptation of these cases in order to reduce workload when using repeat CTs.

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