Advances in radiation oncology · 2022
Automated Planning for Prostate Stereotactic Body Radiation Therapy on the 1.5 T MR-Linac.
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Naccarato Stefania, Rigo Michele, Pellegrini Roberto, Voet Peter, Akhiat Hafid, Gurrera Davide, De Simone Antonio, Sicignano Gianluisa, Mazzola Rosario, Figlia Vanessa, Ricchetti Francesco, Nicosia Luca, Giaj-Levra Niccolò, Cuccia Francesco, Stavreva Nadejda, Pressyanov Dobromir S, Stavrev Pavel, Alongi Filippo, Ruggieri Ruggero
Аннотация
PURPOSE: Adaptive 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 MATERIALS: Fifty 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.
RESULTS: mCycle 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.
CONCLUSIONS: In 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.
METHODS AND MATERIALS: Fifty 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.
RESULTS: mCycle 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.
CONCLUSIONS: In 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.