Synthetic computed tomography data allows for accurate absorbed dose calculations in a magnetic resonance imaging only workflow for head and neck radiotherapy
•The geometry of the synthetic CT is comparable to the CT in the H&N region.•Synthetic CT in the H&N region provides similar absorbed dose calculation as the CT.•Absorbed dose calculations in the dental region could benefit from using synthetic CT. Few studies on magnetic resonance imaging (...
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Veröffentlicht in: | Physics and imaging in radiation oncology 2021-01, Vol.17, p.36-42 |
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Sprache: | eng |
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Zusammenfassung: | •The geometry of the synthetic CT is comparable to the CT in the H&N region.•Synthetic CT in the H&N region provides similar absorbed dose calculation as the CT.•Absorbed dose calculations in the dental region could benefit from using synthetic CT.
Few studies on magnetic resonance imaging (MRI) only head and neck radiation treatment planning exist, and none using a generally available software. The aim of this study was to evaluate the accuracy of absorbed dose for head and neck synthetic computed tomography data (sCT) generated by a commercial convolutional neural network-based algorithm.
For 44 head and neck cancer patients, sCT were generated and the geometry was validated against computed tomography data (CT). The clinical CT based treatment plan was transferred to the sCT and recalculated without re-optimization, and differences in relative absorbed dose were determined for dose-volume-histogram (DVH) parameters and the 3D volume.
For overall body, the results of the geometric validation were (Mean ± 1sd): Mean error −5 ± 10HU, mean absolute error 67 ± 14HU, Dice similarity coefficient 0.98 ± 0.05, and Hausdorff distance difference 4.2 ± 1.7 mm. Water equivalent depth difference for region Th1-C7, mid mandible and mid nose were −0.3 ± 3.4, 1.1 ± 2.0 and 0.7 ± 3.8 mm respectively. The maximum mean deviation in absorbed dose for all DVH parameters was 0.30% (0.12 Gy). The absorbed doses were considered equivalent (p-value |
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ISSN: | 2405-6316 2405-6316 |
DOI: | 10.1016/j.phro.2020.12.007 |