Individualized estimates of overall survival in radiation therapy plan optimization — A concept study

Modiri, Arezoo; Stick, Line Bjerregaard; Rice, Stephanie R.; Rechner, Laura Ann; Vogelius, I.R.; Bentzen, Søren M.; Sawant, Amit

doi:10.1002/mp.13211

Cited by 8 publications

(8 citation statements)

References 42 publications

(109 reference statements)

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“…Dose-volume constraints are an integral component of conventional treatment-planning methods. Recent studies attempted to directly optimize the clinical goals of treatment by using dose-response models (Wilkens and Oelfke 2005, Allen et al 2012, Rechner et al 2015, Modiri et al 2018. Both of these methods, however, rely on scaling proton doses by a delivery methodinvariant factor of 1.1.…”

Section: Discussionmentioning

confidence: 99%

Proton therapy delivery method affects dose-averaged linear energy transfer in patients

et al. 2021

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The dosimetric advantages of proton therapy have led to its rapid proliferation in recent decades. This has been accompanied by a shift in technology from older units that deliver protons by passive scattering (PS) to newer units that increasingly use pencil-beam scanning (PBS). The biologic effectiveness of proton physical dose purportedly rises with increasing dose-weighted average linear energy transfer (LETD). The objective of this study was to determine the extent to which proton delivery methods affect LETD. We calculated LETD from simple, dosimetrically matched, and clinical treatment plans with TOPAS Monte-Carlo transport code. Simple treatment plans comprised single fields of PS and PBS protons in a water phantom. We performed simulations of matched and clinical treatment plans by using the treatment and anatomic data obtained from a cohort of children with craniopharyngioma who previously received PS or PBS proton therapy. We compared the distributions of LETD from PS and PBS delivery methods in clinically relevant ROIs. Wilcoxon signed-rank tests comparing single fields in water revealed that the LETD values from PBS were significantly greater than those from PS inside and outside the targeted volume (p < 0.01). Statistical tests comparing LETD-volume histograms from matched and clinical treatment plans showed that LETD was generally greater for PBS treatment plans than for PS treatment plans (p < 0.05). In conclusion, the proton delivery method affects LETD both inside and outside of the target volume. These findings suggest that PBS is more biologically effective than PS. Given the rapid expansion of PBS proton therapy, future studies are needed to confirm the applicability of treatment evaluation methods developed for PS proton therapy to those for modern PBS treatments to ensure their safety and effectiveness for the growing population of patients receiving proton therapy. This study uses data from two clinical trials: NCT01419067 and NCT02792582.

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Section: Discussionmentioning

confidence: 99%

Proton therapy delivery method affects dose-averaged linear energy transfer in patients

et al. 2021

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“…Inverse planning was performed by our in-house particle swarm optimization (PSO) engine, implemented in MATLAB (R2016a; MathWorks, Matick, MA, USA) [33]. PSO algorithm's highly-parallelizable, metaheuristic and global nature has been thoroughly introduced in the literature [34,35] and applied to various RT inverse planning studies [36][37][38].…”

Section: Inverse Plan Optimizationmentioning

confidence: 99%

Biological optimization for mediastinal lymphoma radiotherapy – a preliminary study

et al. 2020

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Purpose: In current radiotherapy (RT) planning and delivery, population-based dose-volume constraints are used to limit the risk of toxicity from incidental irradiation of organs at risks (OARs). However, weighing tradeoffs between target coverage and doses to OARs (or prioritizing different OARs) in a quantitative way for each patient is challenging. We introduce a novel RT planning approach for patients with mediastinal Hodgkin lymphoma (HL) that aims to maximize overall outcome for each patient by optimizing on tumor control and mortality from late effects simultaneously. Material and Methods: We retrospectively analyzed 34 HL patients treated with conformal RT (3DCRT). We used published data to model recurrence and radiation-induced mortality from coronary heart disease and secondary lung and breast cancers. Patient-specific doses to the heart, lung, breast, and target were incorporated in the models as well as age, sex, and cardiac risk factors (CRFs). A preliminary plan of candidate beams was created for each patient in a commercial treatment planning system. From these candidate beams, outcome-optimized (O-OPT) plans for each patient were created with an in-house optimization code that minimized the individual risk of recurrence and mortality from late effects. O-OPT plans were compared to VMAT plans and clinical 3DCRT plans. Results: O-OPT plans generally had the lowest risk, followed by the clinical 3DCRT plans, then the VMAT plans with the highest risk with median (maximum) total risk values of 4.9 (11.1), 5.1 (17.7), and 7.6 (20.3)%, respectively (no CRFs). Compared to clinical 3DCRT plans, O-OPT planning reduced the total risk by at least 1% for 9/34 cases assuming no CRFs and 11/34 cases assuming presence of CRFs. Conclusions: We developed an individualized, outcome-optimized planning technique for HL. Some of the resulting plans were substantially different from clinical plans. The results varied depending on how risk models were defined or prioritized.

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“…Recent studies have focused on addressing this through the inclusion of personalized models in the planning process. 20 , 21 , 22 , 23 While these studies have demonstrated the ability to optimize treatments based on patient‐specific outcome predictions, they remain limited to three‐dimensional conformal radiotherapy (3DCRT) optimizing the beam angles and monitoring units 20 , 21 , 22 or prescription. 23 Additionally, these methods do not explicitly incorporate currently accepted clinical dose constraints which may impede clinical acceptance or diminish the realized benefit of the planning strategies.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, these systems continue to rely on aggregated response models and do not account for patient‐to‐patient variability in tissue radiosensitivity. Recent studies have focused on addressing this through the inclusion of personalized models in the planning process 20–23 . While these studies have demonstrated the ability to optimize treatments based on patient‐specific outcome predictions, they remain limited to three‐dimensional conformal radiotherapy (3DCRT) optimizing the beam angles and monitoring units 20–22 or prescription 23 .…”

Section: Introductionmentioning

confidence: 99%

Direct incorporation of patient‐specific efficacy and toxicity estimates in radiation therapy plan optimization

Polan

Epelman

et al. 2022

Medical Physics

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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...

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Individualized estimates of overall survival in radiation therapy plan optimization — A concept study

Cited by 8 publications

References 42 publications

Proton therapy delivery method affects dose-averaged linear energy transfer in patients

Proton therapy delivery method affects dose-averaged linear energy transfer in patients

Biological optimization for mediastinal lymphoma radiotherapy – a preliminary study

Direct incorporation of patient‐specific efficacy and toxicity estimates in radiation therapy plan optimization

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