Novel inverse planning optimization algorithm for robotic radiosurgery: First clinical implementation and dosimetric evaluation. (August 2019)

• Record Type: Journal Article
• Authors: Zeverino, Michele; Marguet, Maud; Zulliger, Cedric; Durham, André; Jumeau, Raphael; Herrera, Fernanda; Schiappacasse, Luis; Bourhis, Jean; Bochud, Francois O.; Moeckli, Raphael
• Is Part Of: Physica medica. Volume 64(2019)
• Page Start: 230
• Page End: 237
• Publication Date: 2019-08
• Subjects: Cyberknife -- Inverse planning -- SRS -- SBRT -- Plan comparison; Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2019.07.020
• Languages: English
• ISSNs: 1120-1797

Abstract

Highlights: The new optimization algorithm VOLO for the CyberKnife TPS was compared with the older for IRIS and MLC collimators. VOLO was significantly superior for target coverage for prostate and spine, and for brain and urethra dose sparing. For IRIS-based plans VOLO significantly reduced the nodes (36%), beams (14%), MU (31%) and delivery time (20%). For MLC plans VOLO significantly increased the nodes and beams with same MU. The increase in delivery time was 4 min. Abstract: Purpose: A novel optimization algorithm (VOLO™) for robotic radiosurgery in the Precision™ treatment planning system was evaluated for different SRS/SBRT treatments and compared with the previous Sequential Optimization (SO) algorithm. Materials and methods: Fifty cases of brain, spine, prostate and lung tumors previously optimized with SO, were re-planned with VOLO™ algorithm keeping the same prescription, collimator type and size, optimization shells, and blocking structures. The dosimetric comparison involved target coverage, conformity (CI), gradient (GI) and homogeneity indexes, specific indicators of dose to OARs and number of nodes, beams, MU and delivery time. For brain only, plans were IRIS- and MLC-based (10 each). The remaining 30 plans were all IRIS-based. Results: VOLO™ optimization was significantly superior for target coverage for prostate and spine, CI for brain, and for brain and urethra dose sparing. SO gave significantly better results for GI for prostate. VOLO™ showed a significantly steeper dose fall-off for brain MLC-based, while for prostate and spine SO was superior. For IRIS-based plans, VOLO™ significantly reduced the nodes (36%), beams (14%), and MU (31%). This led to an average reduction of delivery time of 20% (from 8% for brain to 30% for prostate). For MLC-based plans, VOLO™ significantly increased the nodes and beams (42%) keeping the same number of MU. The averaged delivery time increased by 18%. Conclusions: With respect to SO, VOLO™ optimization algorithm provided better results in terms of delivery time for IRIS-based and of quality of dose distribution for MLC-based plans, respectively.