Evaluating the Quality of Patient-Specific Deformable Image Registration in Adaptive Radiotherapy Using a Digitally Enhanced Head and Neck Phantom

Autor: Elisabetta Cagni, Andrea Botti, Matteo Orlandi, Marco Galaverni, Cinzia Iotti, Mauro Iori, Geraint Lewis, Emiliano Spezi
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Applied Sciences, Vol 12, Iss 19, p 9493 (2022)
Druh dokumentu: article
ISSN: 2076-3417
DOI: 10.3390/app12199493
Popis: Despite the availability of national and international guidelines, an accurate and efficient, patient-specific, deformable image registration (DIR) validation methodology is not yet established, and several groups have found an incompatibility of the various digital phantoms with the commercial systems. To evaluate the quality of the computed tomography (CT) and on-board cone-beam CT (CBCT) DIRs, a novel methodology was developed and tested on 10 head and neck (HN) patients, using CT and CBCT anthropomorphic HN phantom images, digitally reprocessed to include the common organs at risk. Reference DVFs (refDVFs) were generated from the clinical patient CT-CBCT fused images using an independent registration software. The phantom CT images were artificially deformed, using the refDVFs, and registered with the phantom CBCT images, using the clinical registration software, generating a test DVF (testDVF) dataset. The clinical plans were recalculated on the daily patient ‘deformed’ CTs, and the dose maps transferred to the patient-planning CT, using both the refDVF and testDVF. The spatial and dosimetric errors were quantified and the DIR performance evaluated using an established operative tolerance level. The method showed the ability to quantify the DIR spatial errors and assess their dose impact at the voxel level and could be applied to patient-specific DIR evaluation during adaptive HN radiotherapy in routine practice.
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