PurposeLimits on mean lung dose (MLD) allow for individualization of radiation doses at safe levels for patients with lung tumors. However, MLD does not account for individual differences in the extent or spatial distribution of pulmonary dysfunction among patients, which leads to toxicity variability at the same MLD. We investigated dose rearrangement to minimize the radiation dose to the functional lung as assessed by perfusion single photon emission computed tomography (SPECT) and maximize the target coverage to maintain conventional normal tissue limits.Methods and materialsRetrospective plans were optimized for 15 patients with locally advanced non-small cell lung cancer who were enrolled in a prospective imaging trial. A staged, priority-based optimization system was used. The baseline priorities were to meet physical MLD and other dose constraints for organs at risk, and to maximize the target generalized equivalent uniform dose (gEUD). To determine the benefit of dose rearrangement with perfusion SPECT, plans were reoptimized to minimize the generalized equivalent uniform functional dose (gEUfD) to the lung as the subsequent priority.ResultsWhen only physical MLD is minimized, lung gEUfD was 12.6 ± 4.9 Gy (6.3-21.7 Gy). When the dose is rearranged to minimize gEUfD directly in the optimization objective function, 10 of 15 cases showed a decrease in lung gEUfD of >20% (lung gEUfD mean 9.9 ± 4.3 Gy, range 2.1-16.2 Gy) while maintaining equivalent planning target volume coverage. Although all dose-limiting constraints remained unviolated, the dose rearrangement resulted in slight gEUD increases to the cord (5.4 ± 3.9 Gy), esophagus (3.0 ± 3.7 Gy), and heart (2.3 ± 2.6 Gy).ConclusionsPriority-driven optimization in conjunction with perfusion SPECT permits image guided spatial dose redistribution within the lung and allows for a reduced dose to the functional lung without compromising target coverage or exceeding conventional limits for organs at risk.

Purpose Current radiation therapy (RT) treatment planning relies mainly on pre‐defined dose‐based objectives and constraints to develop plans that aim to control disease while limiting damage to normal tissues during treatment. These objectives and constraints are generally population‐based, in that they are developed from the aggregate response of a broad patient population to radiation. However, correlations of new biologic markers and patient‐specific factors to treatment efficacy and toxicity provide the opportunity to further stratify patient populations and develop a more individualized approach to RT planning. We introduce a novel intensity‐modulated radiation therapy (IMRT) optimization strategy that directly incorporates patient‐specific dose response models into the planning process. In this strategy, we integrate the concept of utility‐based planning where the optimization objective is to maximize the predicted value of overall treatment utility, defined by the probability of efficacy (e.g., local control) minus the weighted sum of toxicity probabilities. To demonstrate the feasibility of the approach, we apply the strategy to treatment planning for non‐small cell lung cancer (NSCLC) patients. Methods and materials We developed a prioritized approach to patient‐specific IMRT planning. Using a commercial treatment planning system (TPS), we calculate dose based on an influence matrix of beamlet‐dose contributions to regions‐of‐interest. Then, outside of the TPS, we hierarchically solve two optimization problems to generate optimal beamlet weights that can then be imported back to the TPS. The first optimization problem maximizes a patient's overall plan utility subject to typical clinical dose constraints. In this process, we facilitate direct optimization of efficacy and toxicity trade‐off based on individualized dose‐response models. After optimal utility is determined, we solve a secondary optimization problem that minimizes a conventional dose‐based objective subject to the same clinical dose constraints as the first stage but with the addition of a constraint to maintain the optimal utility from the first optimization solution. We tested this method by retrospectively generating plans for five previously treated NSCLC patients and comparing the prioritized utility plans to conventional plans optimized with only dose metric objectives. To define a plan utility function for each patient, we utilized previously published correlations of dose to local control and grade 3–5 toxicities that include patient age, stage, microRNA levels, and cytokine levels, among other clinical factors. Results The proposed optimization approach successfully generated RT plans for five NSCLC patients that improve overall plan utility based on personalized efficacy and toxicity models while accounting for clinical dose constraints. Prioritized utility plans demonstrated the largest average improvement in local control (16.6%) when compared to plans generated with conventional planning objectives. However, for some p...

Purpose: The use of mean lung dose (MLD) limits allows individualization of lung patient tumor doses at safe levels. However, MLD does not account for local lung function differences between patients, leading to toxicity variability at the same MLD. We investigated dose rearrangement to minimize dose to functional lung, as measured by perfusion SPECT, while maintaining target coverage and conventional MLD limits. Methods: Retrospective plans were optimized for 15 locally advanced NSCLC patients enrolled in a prospective imaging trial. A priority‐based optimization system was used. The baseline priorities were (1) meet OAR dose constraints, (2) maximize target gEUD, and (3) minimize physical MLD. As a final step, normal tissue doses were minimized. To determine the benefit of rearranging dose using perfusion SPECT, plans were reoptimized to minimize functional lung gEUD as the 4th priority. Results: When only minimizing physical MLD, the functional lung gEUD was 10.8+/−5.0 Gy (4.3–19.8 Gy). Only 3/15 cases showed a decrease in functional lung gEUD of ≥4% when rearranging dose to minimize functional gEUD in the cost function (10.5+/−5.0 Gy range 4.3−19.7). Although OAR constraints were respected, the dose rearrangement resulted in ≥10% increases in gEUD to an OAR in 4/15 cases. Only slight reductions in functional lung gEUD were noted when omitting the minimization of physical MLD, suggesting that constraining the target gEUD minimizes the potential to redistribute dose. Conclusion: Prioritydriven optimization permits the generation of plans that respect traditional OAR limits and target coverage, but with the ability to rearrange dose based on functional imaging. The latter appears to be limited due to the decreased solution space when constraining target coverage. Since dose rearrangement may increase dose to other OARs, it is also worthwhile to investigate global biomarkers of lung toxicity to further individualize treatment in this population. Partially supported by R01‐CA142840 and P01‐CA59827

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