Evidence map›Paper›PMID 35181892›Full record

ArticleMedical physics2022

Reformulated McNamara RBE-weighted beam orientation optimization for intensity modulated proton therapy.

Pavitra Ramesh, Qihui Lyu, Wenbo Gu, Dan Ruan, Ke Sheng

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Article in Medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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3 · Its place in the literature

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5 citing papers in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Pavitra RameshDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Qihui LyuDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Wenbo GuDepartment of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Dan RuanDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Ke ShengDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.

Funding

Robust IMPT with automated beam orientation and scanning spot optimizationR01CA230278 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SHENG, KE · 2019 to 2023
$1.9M
NCI NIH HHS R01 CA230278NIH HHS R01CA230278
6 · The paper itself

Abstract

purposeEmpirical relative biological effectiveness (RBE) models have been used to estimate the biological dose in proton therapy but do not adequately capture the factors influencing RBE values for treatment planning. We reformulate the McNamara RBE model such that it can be added as a linear biological dose fidelity term within our previously developed sensitivity-regularized and heterogeneity-weighted beam orientation optimization (SHBOO) framework.

methodsBased on our SHBOO framework, we formulated the biological optimization problem to minimize total McNamara RBE dose to OARs. We solve this problem using two optimization algorithms: FISTA (McNam-FISTA) and Chambolle-Pock (McNam-CP). We compare their performances with a physical dose optimizer assuming RBE = 1.1 in all structures (PHYS-FISTA) and an LET-weighted dose model (LET-FISTA). Three head and neck patients were planned with the four techniques and compared on dosimetry and robustness.

resultsCompared to Phys-FISTA, McNam-CP was able to match CTV [HI, Dmax, D95%, D98%] by [0.00, 0.05%, 1.4%, 0.8%]. McNam-FISTA and McNam-CP were able to significantly improve overall OAR [Dmean, Dmax] by an average of [36.1%,26.4%] and [29.6%, 20.3%], respectively. Regarding CTV robustness, worst [Dmax, V95%, D95%, D98%] improvement of [-6.6%, 6.2%, 6.0%, 4.8%] was reported for McNam-FISTA and [2.7%, 2.7%, 5.3%, -4.3%] for McNam-CP under combinations of range and setup uncertainties. For OARs, worst [Dmax, Dmean] were improved by McNam-FISTA and McNam-CP by an average of [25.0%, 19.2%] and [29.5%, 36.5%], respectively. McNam-FISTA considerably improved dosimetry and CTV robustness compared to LET-FISTA, which achieved better worst-case OAR doses.

conclusionThe four optimization techniques deliver comparable biological doses for the head and neck cases. Besides modest CTV coverage and robustness improvement, OAR biological dose and robustness were substantially improved with both McNam-FISTA and McNam-CP, showing potential benefit for directly incorporating McNamara RBE in proton treatment planning.

Indexed as

Proton TherapyRadiotherapy, Intensity-ModulatedHumansOrgans at RiskRadiotherapy DosageRadiotherapy Planning, Computer-AssistedRelative Biological Effectivenessproton therapy-dose optimizationRBERBio-particle therapy-protons

Identifiers

PMID35181892
PMCPMC9894336

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