Fully-automated, CT-only GTV contouring for palliative head and neck radiotherapy

• Published in: Scientific reports Vol. 13; no. 1; p. 21797
• Main Authors: Gay, Skylar S., Cardenas, Carlos E., Nguyen, Callistus, Netherton, Tucker J., Yu, Cenji, Zhao, Yao, Skett, Stephen, Patel, Tina, Adjogatse, Delali, Guerrero Urbano, Teresa, Naidoo, Komeela, Beadle, Beth M., Yang, Jinzhong, Aggarwal, Ajay, Court, Laurence E.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 09.12.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705/1046; 639/766/747; 692/4028/67/1536; Computed tomography; Head & neck cancer; Head and Neck Neoplasms - diagnostic imaging; Head and Neck Neoplasms - radiotherapy; Humanities and Social Sciences; Humans; Image processing; Multicenter Studies as Topic; multidisciplinary; Palliation; Palliative Care; Positron-Emission Tomography - methods; Radiation therapy; Radiotherapy Planning, Computer-Assisted - methods; Retrospective Studies; Science; Science (multidisciplinary); Statistical analysis; Tomography, X-Ray Computed - methods
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-48944-2

Planning for palliative radiotherapy is performed without the advantage of MR or PET imaging in many clinics. Here, we investigated CT-only GTV delineation for palliative treatment of head and neck cancer. Two multi-institutional datasets of palliative-intent treatment plans were retrospectively acquired: a set of 102 non-contrast-enhanced CTs and a set of 96 contrast-enhanced CTs. The nnU-Net auto-segmentation network was chosen for its strength in medical image segmentation, and five approaches separately trained: (1) heuristic-cropped, non-contrast images with a single GTV channel, (2) cropping around a manually-placed point in the tumor center for non-contrast images with a single GTV channel, (3) contrast-enhanced images with a single GTV channel, (4) contrast-enhanced images with separate primary and nodal GTV channels, and (5) contrast-enhanced images along with synthetic MR images with separate primary and nodal GTV channels. Median Dice similarity coefficient ranged from 0.6 to 0.7, surface Dice from 0.30 to 0.56, and 95th Hausdorff distance from 14.7 to 19.7 mm across the five approaches. Only surface Dice exhibited statistically-significant difference across these five approaches using a two-tailed Wilcoxon Rank-Sum test ( p  ≤ 0.05). Our CT-only results met or exceeded published values for head and neck GTV autocontouring using multi-modality images. However, significant edits would be necessary before clinical use in palliative radiotherapy.