Simultaneous dose and dose rate optimization (SDDRO) for FLASH proton therapy

被引:66
作者
Gao, Hao [1 ]
Lin, Bowen [1 ,2 ]
Lin, Yuting [1 ]
Fu, Shujun [2 ]
Langen, Katja [1 ]
Liu, Tian [1 ]
Bradley, Jeffery [1 ]
机构
[1] Emory Univ, Winship Canc Inst, Dept Radiat Oncol, Atlanta, GA 30322 USA
[2] Shandong Univ, Sch Math, Jinan, Shandong, Peoples R China
关键词
dose rate optimization; FLASH; IMPT; proton therapy; MONITOR UNIT CONSTRAINTS;
D O I
10.1002/mp.14531
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: FLASH radiotherapy (RT) can potentially reduce normal tissue toxicity while preserving tumoricidal effectiveness to improve the therapeutic ratio. The key of FLASH for sparing normal tissues is to irradiate tissues with an ultra-high dose rate (i.e., >= 40 Gy/s), for which proton RT can be used. However, currently available treatment plan optimization method only optimizes the dose distribution and does not directly optimize the dose rate. The contribution of this work to FLASH proton RT is the development of a novel treatment optimization method, that is, simultaneous dose and dose rate optimization (SDDRO), to optimize tissue-receiving dose rate distribution as well as dose distribution. Methods: Distinguished from existing methods, SDDRO accounts for dose rate constraint and optimizes dose rate distribution. In terms of mathematical formulation, SDDRO is a constrained optimization problem with dose-volume constraint on dose distribution, minimum dose rate constraint on dose-averaged tissue-receiving dose rates, minimum monitor unit constraint on spot weight, and maximum intensity constraint on beam intensity. In terms of optimization algorithm, SDDRO is solved by iterative convex relaxation and alternating direction method of multipliers. SDDRO algorithms are presented for both scenarios with either constant or variable beam intensity. Results: SDDRO was compared with intensity modulated proton therapy (IMPT) (dose optimization alone, and no dose rate optimization) using three lung cases. SDDRO substantially improved the dose rate distribution compared to IMPT, for example, increasing of the region-of-interest (ROI) volume (ROI = CTV_10mm: the ring sandwiched by 10 mm outer and inner expansion of CTV boundary) receiving at least 40 Gy/s from similar to 30-50% to at least 98%, and the lung volume receiving at least 40 Gy/s from similar to 30-40% to similar to 70-90%. Moreover, both dose and dose rate distributions from SDDRO were further considerably improved via the combined use of hypofractionation and multiple beams. Conclusions: We have developed a joint dose and dose rate optimization method for FLASH proton RT, namely SDDRO, which is first-of-its-kind to the best of our knowledge. The results suggest that (a) SDDRO can substantially improve the FLASH-dose rate coverage (e.g., in terms of dose rate volume histogram) compared to IMPT for the purpose of normal tissue sparing while preserving the dose distribution and (b) the combination of hypofractionation and multiple beams can further considerably improve the SDDRO plan quality in terms of both dose and dose rate distribution. (c) 2020 American Association of Physicists in Medicine [https://doi.org/10.1002/mp.14531]
引用
收藏
页码:6388 / 6395
页数:8
相关论文
共 23 条
[1]   Distributed optimization and statistical learning via the alternating direction method of multipliers [J].
Boyd S. ;
Parikh N. ;
Chu E. ;
Peleato B. ;
Eckstein J. .
Foundations and Trends in Machine Learning, 2010, 3 (01) :1-122
[2]   Incorporating deliverable monitor unit constraints into spot intensity optimization in intensity-modulated proton therapy treatment planning [J].
Cao, Wenhua ;
Lim, Gino ;
Li, Xiaoqiang ;
Li, Yupeng ;
Zhu, X. Ronald ;
Zhang, Xiaodong .
PHYSICS IN MEDICINE AND BIOLOGY, 2013, 58 (15) :5113-5125
[3]   Ultrahigh dose-rate FLASH irradiation increases the differential response between normal and tumor tissue in mice [J].
Favaudon, Vincent ;
Caplier, Laura ;
Monceau, Virginie ;
Pouzoulet, Frederic ;
Sayarath, Mano ;
Fouillade, Charles ;
Poupon, Marie-France ;
Brito, Isabel ;
Hupe, Philippe ;
Bourhis, Jean ;
Hall, Janet ;
Fontaine, Jean-Jacques ;
Vozenin, Marie-Catherine .
SCIENCE TRANSLATIONAL MEDICINE, 2014, 6 (245)
[4]   Technical Note: Plan-delivery-time constrained inverse optimization method with minimum-MU-per-energy-layer (MMPEL) for efficient pencil beam scanning proton therapy [J].
Gao, Hao ;
Clasie, Benjamin ;
McDonald, Mark ;
Langen, Katja M. ;
Liu, Tian ;
Lin, Yuting .
MEDICAL PHYSICS, 2020, 47 (09) :3892-3897
[5]   Hybrid proton-photon inverse optimization with uniformity-regularized proton and photon target dose [J].
Gao, Hao .
PHYSICS IN MEDICINE AND BIOLOGY, 2019, 64 (10)
[6]   Robust fluence map optimization via alternating direction method of multipliers with empirical parameter optimization [J].
Gao, Hao .
PHYSICS IN MEDICINE AND BIOLOGY, 2016, 61 (07) :2838-2850
[7]   The Split Bregman Method for L1-Regularized Problems [J].
Goldstein, Tom ;
Osher, Stanley .
SIAM JOURNAL ON IMAGING SCIENCES, 2009, 2 (02) :323-343
[8]  
HOWARD M, 2014, MED PHYS, V41
[9]   Minimum-MU and sparse-energy-layer (MMSEL) constrained inverse optimization method for efficiently deliverable PBS plans [J].
Lin, Yuting ;
Clasie, Benjamin ;
Liu, Tian ;
McDonald, Mark ;
Langen, Katja M. ;
Gao, Hao .
PHYSICS IN MEDICINE AND BIOLOGY, 2019, 64 (20)
[10]   A Greedy reassignment algorithm for the PBS minimum monitor unit constraint [J].
Lin, Yuting ;
Kooy, Hanne ;
Craft, David ;
Depauw, Nicolas ;
Flanz, Jacob ;
Clasie, Benjamin .
PHYSICS IN MEDICINE AND BIOLOGY, 2016, 61 (12) :4665-4678