PTV-based IMPT optimization incorporating planning risk volumes vs robust optimization

被引:72
|
作者
Liu, Wei [1 ]
Frank, Steven J. [2 ]
Li, Xiaoqiang [1 ]
Li, Yupeng [3 ]
Zhu, Ron. X. [1 ]
Mohan, Radhe [1 ]
机构
[1] Univ Texas MD Anderson Canc Ctr, Dept Radiat Phys, Houston, TX 77030 USA
[2] Univ Texas MD Anderson Canc Ctr, Dept Radiat Oncol, Houston, TX 77030 USA
[3] Varian Med Syst Inc, Palo Alto, CA 94304 USA
基金
美国国家卫生研究院;
关键词
robust optimization; IMPT; planning risk volume; robustness evaluation; MODULATED PROTON THERAPY; TREATMENT UNCERTAINTIES; RANGE UNCERTAINTIES; SENSITIVITY; CANCER; TUMORS; PLANS; RADIOTHERAPY; DELIVERY; PHOTON;
D O I
10.1118/1.4774363
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: Robust optimization leads to intensity-modulated proton therapy (IMPT) plans that are less sensitive to uncertainties and superior in terms of organs-at-risk (OARs) sparing, target dose coverage, and homogeneity compared to planning target volume (PTV)-based optimized plans. Robust optimization incorporates setup and range uncertainties, which implicitly adds margins to both targets and OARs and is also able to compensate for perturbations in dose distributions within targets and OARs caused by uncertainties. In contrast, the traditional PTV-based optimization considers only setup uncertainties and adds a margin only to targets but no margins to the OARs. It also ignores range uncertainty. The purpose of this work is to determine if robustly optimized plans are superior to PTV-based plans simply because the latter do not assign margins to OARs during optimization. Methods: The authors retrospectively selected from their institutional database five patients with head and neck (H&N) cancer and one with prostate cancer for this analysis. Using their original images and prescriptions, the authors created new IMPT plans using three methods: PTV-based optimization, optimization based on the PTV and planning risk volumes (PRVs) (i.e., "PTV+PRV-based optimization"), and robust optimization using the "worst-case" dose distribution. The PRVs were generated by uniformly expanding OARs by 3 mm for the H&N cases and 5 mm for the prostate case. The dose-volume histograms (DVHs) from the worst-case dose distributions were used to assess and compare plan quality. Families of DVHs for each uncertainty for all structures of interest were plotted along with the nominal DVHs. The width of the "bands" of DVHs was used to quantify the plan sensitivity to uncertainty. Results: Compared with conventional PTV-based and PTV+PRV-based planning, robust optimization led to a smaller bandwidth for the targets in the face of uncertainties {clinical target volume [CTV] bandwidth: 0.59 [robust], 3.53 [PTV+PRV], and 3.53 [PTV] Gy (RBE)}. It also resulted in higher doses to 95% of the CTV {D-95%:60.8 [robust] vs 59.3 [PTV+PRV] vs 59.6 [PTV] Gy (RBE)}, smaller D-5% (doses to 5% of the CTV) minus D-95% {D-5% - D-95%: 13.2 [robust] vs 17.5 [PTV+PRV] vs 17.2 [PTV] Gy (RBE)}. At the same time, the robust optimization method irradiated OARs less {maximum dose to 1 cm(3) of the brainstem: 48.3 [robust] vs 48.8 [PTV+PRV] vs 51.2 [PTV] Gy (RBE); mean dose to the oral cavity: 22.3 [robust] vs 22.9 [PTV+PRV] vs 26.1 [PTV] Gy (RBE); maximum dose to 1% of the normal brain: 66.0 [robust] vs 68.0 [PTV+PRV] vs 69.3 [PTV] Gy (RBE)}. Conclusions: For H&N cases studied, OAR sparing in PTV+PRV-based optimization was inferior compared to robust optimization but was superior compared to PTV-based optimization; however, target dose robustness and homogeneity were comparable in the PTV+PRV-based and PTV-based optimizations. The same pattern held for the prostate case. The authors' data suggest that the superiority of robust optimization is not due simply to its inclusion of margins for OARs, but that this is due mainly to the ability of robust optimization to compensate for perturbations in dose distributions within target volumes and normal tissues caused by uncertainties. (C) 2013 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4774363]
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Difference in LET-based biological doses between IMPT optimization techniques: Robust and PTV-based optimizations
    Hirayama, Shusuke
    Matsuura, Taeko
    Yasuda, Koichi
    Takao, Seishin
    Fujii, Takaaki
    Miyamoto, Naoki
    Umegaki, Kikuo
    Shimizu, Shinichi
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2020, 21 (04): : 42 - 50
  • [2] Robust optimization incorporating weekly predicted anatomical CTs in IMPT of nasopharyngeal cancer
    Chan, Mark Ka Heng
    Zhang, Ying
    PHYSICS IN MEDICINE AND BIOLOGY, 2024, 69 (21)
  • [3] PTV-based VMAT vs. robust IMPT for head-and-neck cancer: A probabilistic uncertainty analysis of clinical plan evaluation with the Dutch model-based selection
    Rojo-Santiago, Jesus
    Korevaar, Erik
    Perko, Zoltan
    Both, Stefan
    Habraken, Steven J. M.
    Hoogeman, Mischa S.
    RADIOTHERAPY AND ONCOLOGY, 2023, 186
  • [4] Uncertainty incorporated beam angle optimization for IMPT treatment planning
    Cao, Wenhua
    Lim, Gino J.
    Lee, Andrew
    Li, Yupeng
    Liu, Wei
    Zhu, X. Ronald
    Zhang, Xiaodong
    MEDICAL PHYSICS, 2012, 39 (08) : 5248 - 5256
  • [5] Incorporating variable RBE in IMPT optimization for ependymoma
    Goudarzi, Hadis Moazami
    Lim, Gino
    Grosshans, David
    Mohan, Radhe
    Cao, Wenhua
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2024, 25 (01):
  • [6] Time of PTV is ending, robust optimization comes next
    Biston, M-C
    Chiavassa, S.
    Gregoire, V
    Thariat, J.
    Lacornerie, T.
    CANCER RADIOTHERAPIE, 2020, 24 (6-7): : 676 - 686
  • [7] Robust Optimization for IMPT: Introducing and Comparing Different Automated Approaches
    Neves, Joana
    Rocha, Humberto
    Ferreira, Brigida
    Dias, Joana
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS-ICCSA 2024 WORKSHOPS, PT II, 2024, 14816 : 324 - 340
  • [8] On the PTV homogeneity objective in the era of photon advanced dose calculation algorithms: Bridging robust and PTV-based planning
    Jurado-Bruggeman, Diego
    Angerud, Agnes
    Fredriksson, Albin
    Munoz-Montplet, Carles
    RADIOTHERAPY AND ONCOLOGY, 2025, 207
  • [9] An Evaluation of Three Robust Optimization Approaches in IMPT Treatment Planning
    Cao, W.
    Zaqhian, M.
    Liu, W.
    Kardar, L.
    Randeniya, S.
    Urn, G.
    Mohan, R.
    MEDICAL PHYSICS, 2014, 41 (06) : 552 - 552
  • [10] Effectiveness of robust optimization in intensity-modulated proton therapy planning for head and neck cancers
    Liu, Wei
    Frank, Steven J.
    Li, Xiaoqiang
    Li, Yupeng
    Park, Peter C.
    Dong, Lei
    Zhu, X. Ronald
    Mohan, Radhe
    MEDICAL PHYSICS, 2013, 40 (05)