Fluence Map Optimization in Intensity‐modulated Radiation Therapy Treatment Planning

Aleman, Dionne M.

doi:10.1002/9781118960158.ch13

Cited by 3 publications

(2 citation statements)

References 65 publications

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“…where f i (d) denote the objectives, g j (d) denote the constraints, D denotes the dose influence matrix, d denotes the dose distribution, and x denotes the solution. For IMRT, the solution, x, can be a fluence map (Romeijn et al 2004, Jinet al 2010, Aleman 2018 or a set of MLC apertures weights (Shepard et al 2002, Broderick et al 2009, Salari and Unkelbach 2013. For IMPT, the solution is a set of spot weights for the designated proton beamlets (Lomax 2008, Jagt et al 2017, van de Water et al 2020.…”

Section: Treatment Planning As An Optimization Problemmentioning

confidence: 99%

Online adaptive planning methods for intensity-modulated radiotherapy

et al. 2023

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Online adaptive radiation therapy aims at adapting a patient’s treatment plan to their current anatomy to account for inter-fraction variations before daily treatment delivery. As this process needs to be accomplished while the patient is immobilized on the treatment couch, it requires time-efficient adaptive planning methods to generate a quality daily treatment plan rapidly. The conventional planning methods do not meet the time requirement of online adaptive radiation therapy because they often involve excessive human intervention, significantly prolonging the planning phase. This article reviews the planning strategies employed by current commercial online adaptive radiation therapy systems, research on online adaptive planning, and artificial intelligence’s potential application to online adaptive planning.

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Section: Treatment Planning As An Optimization Problemmentioning

confidence: 99%

Online adaptive planning methods for intensity-modulated radiotherapy

et al. 2023

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“…More specifically, we compare three different mathematical models for SDO in LGK Icon TM : the linear programming model (LP), piecewise quadratic penalty model (QP), and unconstrained convex moment based model (UCMP). We select these modeling approaches in correspondence to the diverse methods that are commonly used for FMO in IMRT (Aleman 2018). In our analysis, we explore the challenges using these methods in SDO as well.…”

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confidence: 99%

Modeling and comparison of alternative approaches for sector duration optimization in a dedicated radiosurgery system

et al. 2018

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Stereotactic radiosurgery (SRS) is an effective technique to treat brain metastasis for which several inverse planning methods may be appropriate. We compare three different optimization models for segment duration optimization in SRS using Leksell Gamma Knife Icon (Elekta, Stockholm, Sweden). We investigate (1) a linear programming approach, (2) a piecewise quadratic penalty approach, and (3) an unconstrained convex moment-based penalty approach. We examine the performances of these approaches using anonymized data from 14 previously treated cases. In addition, we investigate the important modeling question of selecting weights for the objective functions where we use a simulated annealing algorithm to determine these weights for each model. The inverse plans obtained via optimization models are compared against each other and against the clinical plans. The three inverse planning models can all yield optimal treatment plans in a reasonable amount of time and the treatment plans obtained by these models meet or exceed clinical guidelines while displaying high conformity.

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Conic formulation of fluence map optimization problems

et al. 2021

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The convexity of objectives and constraints in fluence map optimization (FMO) for radiation therapy has been extensively studied. Next to convexity, there is another important characteristic of optimization functions and problems, which has thus far not been considered in FMO literature: conic representation. Optimization problems that are conically representable using quadratic, exponential and power cones are solvable with advanced primal-dual interior-point algorithms. These algorithms guarantee an optimal solution in polynomial time and have good performance in practice. In this paper, we construct conic representations for most FMO objectives and constraints. This paper is the first that shows that FMO problems containing multiple biological evaluation criteria can be solved in polynomial time. For fractionation-corrected functions for which no exact conic reformulation is found, we provide an accurate approximation that is conically representable. We present numerical results on the TROTS data set, which demonstrate very stable numerical performance for solving FMO problems in conic form. With ongoing research in the optimization community, improvements in speed can be expected, which makes conic optimization a promising alternative for solving FMO problems.

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Fluence Map Optimization in Intensity‐modulated Radiation Therapy Treatment Planning

Cited by 3 publications

References 65 publications

Online adaptive planning methods for intensity-modulated radiotherapy

Online adaptive planning methods for intensity-modulated radiotherapy

Modeling and comparison of alternative approaches for sector duration optimization in a dedicated radiosurgery system

Conic formulation of fluence map optimization problems

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