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Enhancing Radiotherapy for Locally Advanced Non-Small Cell Lung Cancer Patients with iCE, a Novel System for Automated Multi-Criterial Treatment Planning Including Beam Angle Optimization.
- Source :
-
Cancers [Cancers (Basel)] 2021 Nov 13; Vol. 13 (22). Date of Electronic Publication: 2021 Nov 13. - Publication Year :
- 2021
-
Abstract
- In this study, the novel iCE radiotherapy treatment planning system (TPS) for automated multi-criterial planning with integrated beam angle optimization (BAO) was developed, and applied to optimize organ at risk (OAR) sparing and systematically investigate the impact of beam angles on radiotherapy dose in locally advanced non-small cell lung cancer (LA-NSCLC). iCE consists of an in-house, sophisticated multi-criterial optimizer with integrated BAO, coupled to a broadly used commercial TPS. The in-house optimizer performs fluence map optimization to automatically generate an intensity-modulated radiotherapy (IMRT) plan with optimal beam angles for each patient. The obtained angles and dose-volume histograms are then used to automatically generate the final deliverable plan with the commercial TPS. For the majority of 26 LA-NSCLC patients, iCE achieved improved heart and esophagus sparing compared to the manually created clinical plans, with significant reductions in the median heart D <subscript>mean</subscript> (8.1 vs. 9.0 Gy, p = 0.02) and esophagus D <subscript>mean</subscript> (18.5 vs. 20.3 Gy, p = 0.02), and reductions of up to 6.7 Gy and 5.8 Gy for individual patients. iCE was superior to automated planning using manually selected beam angles. Differences in the OAR doses of iCE plans with 6 beams compared to 4 and 8 beams were statistically significant overall, but highly patient-specific. In conclusion, automated planning with integrated BAO can further enhance and individualize radiotherapy for LA-NSCLC.
Details
- Language :
- English
- ISSN :
- 2072-6694
- Volume :
- 13
- Issue :
- 22
- Database :
- MEDLINE
- Journal :
- Cancers
- Publication Type :
- Academic Journal
- Accession number :
- 34830838
- Full Text :
- https://doi.org/10.3390/cancers13225683