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It has been reported that proton RBE decreases with increasing tumor oxygen level, offering an opportunity to address hypoxia\u2010related radioresistance with RBE\u2010weighted optimization.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>Here, we obtain a voxel\u2010level estimation of partial oxygen pressure to weigh RBE values in a single biologically informed beam orientation optimization (BOO) algorithm.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Three glioblastoma patients with [<jats:sup>18<\/jats:sup>F]\u2010fluoromisonidazole (FMISO)\u2010PET\/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\u2010Bregman approach, with FISTA as the solver. The proposed hypoxia informed RBE\u2010weighted 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\u00a0=\u00a0gEUD<jats:sub>CTV<\/jats:sub>\/gEUD<jats:sub>OAR<\/jats:sub>) were evaluated along with worst\u2010case statistics after normalization to normal tissue isotoxicity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Compared 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\u2010case scenario, the parameters increase on average by [12.5%, 14.7%], [7.3%,\u22128.9%], and [22.3%, 2.1%]. Despite increased OAR Dmean and Dmax by [8.0%, 3.0%] and [13.1%, \u22120.1%], HypRBE increased average TI by [22.0%, 21.1%]. Worst\u2010case OAR Dmean, Dmax, and TI worsened by [17.9%, 4.3%], [24.5%, \u22121.2%], and [9.6%, 10.5%], but in the best cases, HypRBE escalates tumor coverage significantly without compromising OAR dose, increasing the therapeutic ratio.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>We have developed an optimization algorithm whose dose fidelity term accounts for hypoxia\u2010informed 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.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.16978","type":"journal-article","created":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T07:50:48Z","timestamp":1707724248000},"page":"2320-2333","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Hypoxia\u2010informed RBE\u2010weighted beam orientation optimization for intensity modulated proton therapy"],"prefix":"10.1002","volume":"51","author":[{"given":"Pavitra","family":"Ramesh","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology University of California Los Angeles  Los Angeles California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Ruan","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology University of California Los Angeles  Los Angeles California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S. 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