Adam D Yock1, Radhe Mohan2, Stella Flampouri3, Walter Bosch4, Paige A Taylor2, David Gladstone5, Siyong Kim6, Jason Sohn7, Robert Wallace8, Ying Xiao9, Jeff Buchsbaum10. 1. Vanderbilt University Medical Center, Nashville, Tennessee. 2. University of Texas, MD Anderson Cancer Center, Houston, Texas. 3. University of Florida, Health Proton Therapy Institute, Jacksonville, Florida. 4. Washington University, St. Louis, Missouri. 5. Geisel School of Medicine at Dartmouth, Hannover, New Hampshire. 6. Virginia Commonwealth University, Richmond, Virginia. 7. Allegheny Health Network, Pittsburgh, Pennsylvania. 8. Cedars-Sinai Medical Center, Los Angeles, California. 9. University of Pennsylvania, Philadelphia, Pennsylvania. 10. National Cancer Institute, National Institutes of Health, Bethesda, Maryland. Electronic address: jeff.buchsbaum@nih.gov.
Abstract
PURPOSE: With external beam radiation therapy, uncertainties in treatment planning and delivery can result in an undesirable dose distribution delivered to the patient that can compromise the benefit of treatment. Techniques including geometric margins and probabilistic optimization have been used effectively to mitigate the effects of uncertainties. However, their broad application is inconsistent and can compromise the conclusions derived from cross-technique and cross-modality comparisons. METHODS AND MATERIALS: Conventional methods to deal with treatment planning and delivery uncertainties are described, and robustness analysis is presented as a framework that is applicable across treatment techniques and modalities. RESULTS: This report identifies elements that are imperative to include when conducting a robustness analysis and describing uncertainties and their dosimetric effects. CONCLUSION: The robustness analysis approach described here is presented to promote reliable plan evaluation and dose reporting, particularly during clinical trials conducted across institutions and treatment modalities. Published by Elsevier Inc.
PURPOSE: With external beam radiation therapy, uncertainties in treatment planning and delivery can result in an undesirable dose distribution delivered to the patient that can compromise the benefit of treatment. Techniques including geometric margins and probabilistic optimization have been used effectively to mitigate the effects of uncertainties. However, their broad application is inconsistent and can compromise the conclusions derived from cross-technique and cross-modality comparisons. METHODS AND MATERIALS: Conventional methods to deal with treatment planning and delivery uncertainties are described, and robustness analysis is presented as a framework that is applicable across treatment techniques and modalities. RESULTS: This report identifies elements that are imperative to include when conducting a robustness analysis and describing uncertainties and their dosimetric effects. CONCLUSION: The robustness analysis approach described here is presented to promote reliable plan evaluation and dose reporting, particularly during clinical trials conducted across institutions and treatment modalities. Published by Elsevier Inc.
Authors: Steve B Jiang; Cynthia Pope; Khaled M Al Jarrah; Jong H Kung; Thomas Bortfeld; George T Y Chen Journal: Phys Med Biol Date: 2003-06-21 Impact factor: 3.609
Authors: Harald Paganetti; Andrzej Niemierko; Marek Ancukiewicz; Leo E Gerweck; Michael Goitein; Jay S Loeffler; Herman D Suit Journal: Int J Radiat Oncol Biol Phys Date: 2002-06-01 Impact factor: 7.038
Authors: A Gutierrez; V Rompokos; K Li; C Gillies; D D'Souza; F Solda; N Fersht; Y-C Chang; G Royle; R A Amos; T Underwood Journal: Acta Oncol Date: 2019-08-20 Impact factor: 4.089
Authors: Liyong Lin; Paige A Taylor; Jiajian Shen; Jatinder Saini; Minglei Kang; Charles B Simone; Jeffrey D Bradley; Zuofeng Li; Ying Xiao Journal: Int J Part Ther Date: 2021-05-25