Hypoxia‐informed RBE‐weighted beam orientation optimization for intensity modulated proton therapy

Author:

Ramesh Pavitra1,Ruan Dan1,Liu S. John2,Seo Youngho3,Braunstein Steve2,Sheng Ke2

Affiliation:

1. Department of Radiation Oncology University of California Los Angeles Los Angeles California USA

2. Department of Radiation Oncology University of California San Francisco San Francisco California USA

3. Department of Radiology and Biomedical Imaging University of California San Francisco San Francisco California USA

Abstract

AbstractBackgroundVariable relative biological effectiveness (RBE) models in treatment planning have been proposed to optimize the therapeutic ratio of proton therapy. It has been reported that proton RBE decreases with increasing tumor oxygen level, offering an opportunity to address hypoxia‐related radioresistance with RBE‐weighted optimization.PurposeHere, we obtain a voxel‐level estimation of partial oxygen pressure to weigh RBE values in a single biologically informed beam orientation optimization (BOO) algorithm.MethodsThree glioblastoma patients with [18F]‐fluoromisonidazole (FMISO)‐PET/CT images were selected from the institutional database. Oxygen values were derived from tracer uptake using a nonlinear least squares curve fitting. McNamara RBE, calculated from proton dose, was then weighed using oxygen enhancement ratios (OER) for each voxel and incorporated into the dose fidelity term of the BOO algorithm. The nonlinear optimization problem was solved using a split‐Bregman approach, with FISTA as the solver. The proposed hypoxia informed RBE‐weighted method (HypRBE) was compared to dose fidelity terms using the constant RBE of 1.1 (cRBE) and the normoxic McNamara RBE model (RegRBE). Tumor homogeneity index (HI), maximum biological dose (Dmax), and D95%, as well as OAR therapeutic index (TI = gEUDCTV/gEUDOAR) were evaluated along with worst‐case statistics after normalization to normal tissue isotoxicity.ResultsCompared to [cRBE, RegRBE], HypRBE increased tumor HI, Dmax, and D95% across all plans by on average [31.3%, 31.8%], [48.6%, 27.1%], and [50.4%, 23.8%], respectively. In the worst‐case scenario, the parameters increase on average by [12.5%, 14.7%], [7.3%,−8.9%], and [22.3%, 2.1%]. Despite increased OAR Dmean and Dmax by [8.0%, 3.0%] and [13.1%, −0.1%], HypRBE increased average TI by [22.0%, 21.1%]. Worst‐case OAR Dmean, Dmax, and TI worsened by [17.9%, 4.3%], [24.5%, −1.2%], and [9.6%, 10.5%], but in the best cases, HypRBE escalates tumor coverage significantly without compromising OAR dose, increasing the therapeutic ratio.ConclusionsWe have developed an optimization algorithm whose dose fidelity term accounts for hypoxia‐informed RBE values. We have shown that HypRBE selects bE:\Alok\aaeams better suited to deliver high physical dose to low RBE, hypoxic tumor regions while sparing the radiosensitive normal tissue.

Funder

National Institutes of Health

Publisher

Wiley

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