Need for standardization in the use of structures in the intensity-modulated radiation therapy planning of head and neck cancers, a GORTEC study.

Radiother Oncol

Université de Caen Normandie, ENSICAEN, CNRS/IN2P3, LPC Caen UMR6534, F-14000 Caen, France; Department of Radiotherapy, Centre François-Baclesse, Caen, France. Electronic address:

Published: November 2023

Background: Most radiotherapy structures contoured on CT scans during IMRT planning are defined by the ICRU, forming part of standard practice. Associated dose-volume constraints serve as parameters for dose computation algorithms to produce optimized dose maps. On the ground, however, physicists/dosimetrists routinely delineate auxiliary "non-standard" radiotherapy structures (nsRS).

Materials/methods: From 287 patients' data, five categories of nsRS were identified. Inter-center, inter-patient variability, and temporal trends in nsRS use were investigated. Relation of nsRS with topological complexity, plan quality, calculated quality assurance (QA) and expert QA, was investigated using machine learning classification.

Results: nsRS accounted for 19.2% of all structures. Average number of nsRS per patient was 8.92 ± 6.70. Variation coefficient across centers was > 70% for nsRS frequency. There was no effect of patient volume per center on averaged nsRS number between low, intermediate, and high-volume centers. No temporal trends in nsRS use were detected at the high-volume centers, except for an increase in 'forced-dose' nsRS (p = 3.08 × (10)^(-5)) at one center. Machine learning prediction accuracy including nsRS features were 0.70 ± 0.06 for topological complexity, 0.58 ± 0.05 for calculated QA and 0.72 ± 0.05 for expert QA.

Conclusion: Use of nsRS is frequent but heterogeneous and should be standardized further in line with ICRU initiatives in IMRT planning. Use of nsRS should be documented with respect to the need for nsRS from dose computation algorithms of treatment planning systems and IMRT machines in terms of modulation capacity and plan robustness.

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Source
http://dx.doi.org/10.1016/j.radonc.2023.109895DOI Listing

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