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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.

Authors :
Fjellanger K
Hysing LB
Heijmen BJM
Pettersen HES
Sandvik IM
Sulen TH
Breedveld S
Rossi L
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