Abstract
PurposeAdaptive stereotactic body radiation therapy (SBRT) for prostate cancer (PC) by the 1.5 T MR-linac currently requires online planning by an expert user. A fully automated and user-independent solution to adaptive planning (mCycle) of PC-SBRT was compared with user's plans for the 1.5 T MR-linac. Methods and MaterialsFifty adapted plans on daily magnetic resonance imaging scans for 10 patients with PC treated by 35 Gy (prescription dose [Dp]) in 5 fractions were reoptimized offline from scratch, both by an expert planner (manual) and by mCycle. Manual plans consisted of multicriterial optimization (MCO) of the fluence map plus manual tweaking in segmentation, whereas in mCycle plans, the objectives were sequentially optimized by MCO according to an a-priori assigned priority list. The main criteria for planning approval were a dose ≥95% of the Dp to at least 95% of the planning target volume (PTV), V33.2 (PTV) ≥ 95%, a dose less than the Dp to the hottest cubic centimeter (V35 ≤ 1 cm3) of rectum, bladder, penile bulb, and urethral planning risk volume (ie, urethra plus 3 mm isotropically), and V32 ≤ 5%, V28 ≤ 10%, and V18 ≤ 35% to the rectum. Such dose-volume metrics, plus some efficiency and deliverability metrics, were used for the comparison of mCycle versus manual plans. ResultsmCycle plans improved target dose coverage, with V33.2 (PTV) passing on average (±1 SD) from 95.7% (±1.0%) for manual plans to 97.5% (±1.3%) for mCycle plans (P < .001), and rectal dose sparing, with significantly reduced V32, V28, and V18 (P ≤ .004). Although at an equivalent number of segments, mCycle plans consumed moderately more monitor units (+17%) and delivery time (+9%) (P < .001), whereas they were generally faster (–19%) in terms of optimization times (P < .019). No significant differences were found for the passing rates of locally normalized γ (3 mm, 3%) (P = .059) and γ (2 mm, 2%) (P = .432) deliverability metrics. ConclusionsIn the offline setting, mCycle proved to be a trustable solution for automated planning of PC-SBRT on the 1.5 T MR-linac. mCycle integration in the online workflow will free the user from the challenging online-optimization task.
Highlights
Automated planning for radiation therapy (RT), that is, plan generation by the treatment planning system (TPS) without any user intervention during optimization, is a longstanding aim of RT, both to speed the planning process and to reduce interplanner variability.[2]
As a further step toward automatization, a priori multicriterial optimization (MCO) can be combined with lexicographic optimization,[5] where optimization criteria are distinguished between constraints, which cannot be violated, and objectives, with an assigned relative importance
Ten patients with low- to medium-risk localized prostate cancer (PC) treated on Unity by a 7 MV-FFF photon beam from October 2019 to January 2020, with a prescription dose (Dp) of 35 get ≥y (Gy) given in 5 fractions within 2 weeks, were selected for this institutional review board−approved retrospective dosimetry study, which included informed consent from each patient and whose inclusion and exclusion criteria had been previously described.[16]
Summary
Automated planning for radiation therapy (RT), that is, plan generation by the treatment planning system (TPS) without any user intervention during optimization (autoplanning), is a longstanding aim of RT (eg, since 19981), both to speed the planning process and to reduce interplanner variability.[2]. In the a priori approach to MCO (eg, Monaco TPS, Elekta AB, Stockholm, Sweden) a single pareto-optimal plan, as the clinically desired tradeoff among all treatment goals, is directly generated.[3,4]. As a further step toward automatization, a priori MCO can be combined with lexicographic optimization (eg, Erasmus-iCycle optimizer, Erasmus University, Rotterdam, Netherlands),[5] where optimization criteria are distinguished between constraints, which cannot be violated, and objectives, with an assigned relative importance (or priority). The set of constraints and prioritized objectives for a specific treatment site and protocol defines a “wish list.”. Applications of Erasmus-iCycle were reported for various anatomic sites such as head and neck,[6,7] cervix,[8] prostate,[9] and lungs.[10]. Erasmus-iCycle was implemented into the Monaco TPS11-13 as “mCycle,” the main novelty being the adoption of the physical and radiobiological cost functions of Monaco into the lexicographic logic
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