Citations

PurposeProvide an adaptive multicriteria optimization (MCO) method for intensity‐modulated proton therapy (IMPT) utilizing GPU technology. Previously described limitations of MCO such as Pareto approximation and limitation on the number of objectives were addressed.MethodsThe treatment planning process for IMPT must account for multiple objectives, which requires extensive treatment planning resources. Often a large number of objectives (>10) are required. Hence the need for an MCO algorithm that can handle large number of objectives. The novelty of the MCO method presented here lies on the introduction of the adaptive weighting scheme that can generate a well‐distributed and dense representation of the Pareto surface for a large number of objectives in an efficient manner. In our approach the generated Pareto surface is constructed for a set of DVH objectives. The MCO algorithm is based on the augmented weighted Chebychev metric (AWCM) method with an adaptive weighting scheme. This scheme uses the differential evolution (DE) method to generate a set of well‐distributed Pareto points. The quality of the Pareto points’ distribution in the objective space was assessed quantitatively using the Pareto sampling metric. The MCO algorithm was developed to perform multiple parallel searches to achieve a rapid mapping of the Pareto surface, produce clinically deliverable plans, and was implemented on a GPU cluster. The MCO algorithm was tested on two clinical cases with 10 and 18 objectives. For each case one of the MCO‐generated plans was selected for comparison with the clinically generated plan. The MCO plan was randomly selected out of the set of MCO plans that had target coverage similar to the clinically generated plan and the same or better sparing of the organs at risk (OAR). Additionally, a validation study of the AWCM method vs the weighted sum method was performed.ResultsThe adaptive MCO algorithm generated Pareto points on the Pareto hypersurface in a fast (2–3 hr) and efficient manner for 2 cases with 10 and 18 objectives. The MCO algorithm generated a dense and well‐distributed set of Pareto points on the objective space, and was able to achieve minimization of the Pareto sampling metric. The selected MCO plan showed an improvement of the DVH objectives in comparison to the clinically optimized plan in both cases. For case one, the MCO plan showed a 48% reduction of the 50% dose to OARs and a 16% reduction of the 1% dose to OARs. For case 2, the MCO plan showed a 72% reduction of the 50% dose to OARs and a 42% reduction of the 1% dose to OARs. The comparison of AWCM to WS showed that the AWCM method has a dosimetric advantage over WS for both patient cases.ConclusionWe introduced an adaptive MCO algorithm for IMPT accelerated using GPUs. The algorithm is based on an adaptive method for generating Pareto plans in the objective space. We have shown that the algorithm can provide rapid and efficient mapping of the multicriteria Pareto surface with clinically deliverable plans.

PurposeThe presence of respiratory motion during radiation treatment leads to degradation of the expected dose distribution, both for target coverage and healthy tissue sparing, particularly for techniques like pencil beam scanning proton therapy which have dynamic delivery systems. While tools exist to estimate this degraded four‐dimensional (4D) dose, they typically have one or more deficiencies such as not including the particular effects from a dynamic delivery, using analytical dose calculations, and/or using nonphysical dose‐accumulation methods. This work presents a clinically useful 4D‐dose calculator that addresses each of these shortcomings.MethodsTo quickly compute the 4D dose, the three main tasks of the calculator were run on graphics processing units (GPUs). These tasks were (a) simulating the delivery of the plan using measured delivery parameters to distribute the plan amongst 4DCT phases characterizing the patient breathing, (b) using an in‐house Monte Carlo simulation (MC) dose calculator to determine the dose delivered to each breathing phase, and (c) accumulating the doses from the various breathing phases onto a single phase for evaluation. The accumulation was performed by individually transferring the energy and mass of dose‐grid subvoxels, a technique that models the transfer of dose in a more physically realistic manner. The calculator was run on three test cases, with lung, esophagus, and liver targets, respectively, to assess the various uncertainties in the beam delivery simulation as well as to characterize the dose‐accumulation technique.ResultsFour‐dimensional doses were successfully computed for the three test cases with computation times ranging from 4–6 min on a server with eight NVIDIA Titan X graphics cards; the most time‐consuming component was the MC dose engine. The subvoxel‐based dose‐accumulation technique produced stable 4D‐dose distributions at subvoxel scales of 0.5–1.0 mm without impairing the total computation time. The uncertainties in the beam delivery simulation led to moderate variations of the dose–volume histograms for these cases; the variations were reduced by implementing repainting or phase‐gating motion mitigation techniques in the calculator.ConclusionsA MC‐based and GPU‐accelerated 4D‐dose calculator was developed to estimate the effects of respiratory motion on pencil beam scanning proton therapy treatments. After future validation, the calculator could be used to assess treatment plans and its quick runtime would make it easily usable in a future 4D‐robust optimization system.

11534 Background: To date, there are no validated blood-based biomarkers of predicting response to PD-1 blockade. We previously reported that Bim is a downstream signaling molecule of the PD-1 pathway, and that measurement of Bim levels in circulating T-cells may predict and monitor responses to anti–PD-1 therapy in melanoma. We have identified the existence of sPD-L1 in cancer patients and showed that the sPD-L1 is biologically active and capable of triggering apoptosis in activated T-cells. Here we evaluated T cell Bim and sPD-L1 in the peripheral blood (PB) as biomarkers of response in a cohort of patients with metastatic melanoma and lung cancer undergoing anti-PD1 therapy. Methods: 60 pts treated with anti-PD-1 had PB collected at baseline and at radiographic tumor evaluation. Frequencies of Bim+ T cells and Bim median fluorescence intensity (MFI) were measured by flow cytometry in gated tumor-reactive CD11ahighPD1+ CD8+ T cells. We also measured levels of sPD-L1 at baseline and serially during treatment with sPD-L1 ELISA. Baseline Bim and sPD-L1 levels and percent change in Bim levels in patients (pts) who had a radiographic response (CR/PR) were compared to those who had progressive disease (PD) at 12 wks. Results: Similarly to previously reported preliminary data, pts with objective response (CR/PR, 15/60) after 4 cycles of anti-PD1 therapy had higher frequency of Bim T cells at baseline compared to pts with PD (16/60) (mean 43% vs. 30%, P = 0.0484). The frequencies of Bim+ T cells decreased significantly after the first 3 months of treatment in responders compared with progressors (mean -16% vs. + 40% P = 0.0111). High baseline sPD-L1 were associated with progression on anti-PD1 therapy (mean 2.8 ng/mL vs. 0.7 ng/mL, p = 0.07, n = 13) and the levels increased by the first tumor assessment in patients resistant to anti-PD-1. Conclusions: Measurements of Bim and sPD-L1 levels may help to select patients who are likely to benefit from anti-PD1 monotherapy versus combinatorial strategies, and provide a new non-invasive way to monitor response to anti-PD-1 blockade. A larger validation study is underway.

e20502 Background: The CNS is often a site of first disease progression in CRZ-treated ALK+ NSCLC. The ALTA trial is assessing BRG, an investigational next-generation ALK inhibitor, in pts with CRZ-refractory advanced ALK+ NSCLC, including pts with baseline brain metastases. Methods: In ALTA (NCT02094573), pts were stratified by presence of baseline brain metastases and best response to prior CRZ and randomized 1:1 to receive BRG at 90 mg qd (arm A) or 180 mg qd with a 7-d lead-in at 90 mg (arm B). Here, we show data for pts with baseline brain metastases. An independent review committee (IRC) assessed intracranial efficacy. Results: Of 222 pts (112 in arm A; 110 in arm B), 80 (71%)/74 (67%) in A/B had baseline brain metastases per investigators, with median age 49/55 y; 74%/76% had received chemotherapy. As of May 31, 2016, 51%/59% of these pts continued to receive BRG in A/B; median follow-up was 9.6/11.4 mo. Intracranial efficacy is shown in the table. Among these pts, most common treatment-emergent adverse events were: nausea 35%/46% (A/B), headache 30%/31%, vomiting 29%/31%, diarrhea 21%/38%, cough 25%/32%; grade ≥3: increased blood CPK 1%/12%, hypertension 4%/7%, increased lipase 4%/3%. Conclusions: BRG yielded substantial intracranial responses with robust iPFS and acceptable safety in ALK+ NSCLC pts with baseline brain metastases in ALTA. 180 mg (with lead-in) showed consistently improved intracranial efficacy compared with 90 mg. Clinical trial information: NCT02094573. [Table: see text]

9090 Background: We identified factors associated with better OS for previously treated, PD-L1–expressing advanced NSCLC using data from KEYNOTE-010 (NCT01905657; Herbst et al. Lancet. 2016;387:1540-50), in which pembrolizumab had superior OS over docetaxel. Methods: 1033 patients were randomly assigned 1:1:1 to pembrolizumab 2 or 10 mg/kg every 3 weeks (Q3W) or docetaxel 75 mg/m2 Q3W. Response was assessed per RECIST v1.1 by independent central review. Multivariate analyses were performed using a Cox proportional hazards regression model on OS in the pembrolizumab arms. A set of variable selection methods was applied to 19 baseline demographic and disease characteristics, including smoking status, and identified 7 factors that contributed to OS. Data cut was September 30, 2016. Results: Adjusted hazard ratios (HRs) for the factors in the pembrolizumab arm from the model are shown in the Table. Updated OS with an additional 6 months of follow-up from this data lock for KEYNOTE-010 will be presented. Conclusions: While the overall result of KEYNOTE-010 revealed improved OS with pembrolizumab compared with docetaxel in previously treated patients with PD-L1–positive advanced NSCLC, exploratory, post hoc multivariate analyses showed that some laboratory and tumor characteristics such as nonsquamous histology, normal baseline lactate dehydrogenase (LDH), PD-L1 TPS ≥50%, and wild-type EGFR mutation status were associated with better OS among patients treated with pembrolizumab. Clinical trial information: NCT01905657. [Table: see text]