Author: Avery Antes, Bulent Aydogan, Rama Chicfeh, Erik Pearson, Neslihan Sarigul 👨🔬
Affiliation: The University Of Chicago, The University of Chicago 🌍
Purpose: This study evaluates the performance of the Ethos Treatment Planning System (TPS) in managing oligometastatic cancer patients previously treated using multiple isocenter plans.
Methods: This study included 99 patients with thoracic oligometastatic cancers previously treated using c-arm LINACs. Prescriptions ranged from 30 to 50 Gy over 3 to 5 fractions, covered by 1-3 isocenter IMRT plans with varying numbers of fields. Patients with tumors in lung and mediastinal region were categorized by isocenters (1-3) and targets (1-4). Automated contouring, along with tumor-specific planning templates and criteria, was implemented. The primary goal was achieving V95%≥95% for the planning target volume (PTV), with V70%≥99.5% as a secondary goal. Ethos plans employed a 12-field IMRT technique, and plan creation times and dose coverage were compared with clinical results.
Results: Ethos planning initially required an average of 135 minutes for the first 10 patients. Incorporation of auto-contouring, planning templates, and organ-specific planning criteria significantly reduced planning time to 32.4 ± 6.9 minutes. Results showed that planning time was primarily influenced by tumor location rather than the number of targets or isocenters. Ethos produced comparable or superior plans in approximately 50% of cases when benchmarked against clinical plans. Mediastinal tumors overlapping with critical organs or located within 7 cm laterally of critical structures, as well as basal lower lobe lung tumors, necessitate advanced planning expertise. In contrast, tumors in regions such as the subcarinal vein, peritracheal space, or those confined to specific lung lobes can be planned with relative ease, even by less experienced planners.
Conclusion: Ethos significantly reduced planning time and enhanced PTV dose coverage in complex thoracic cases. These results encourage same day sim and treat even for the most complex clinical cases.