| Autor: |
J. John Lucido, Todd A. DeWees, Todd R. Leavitt, Aman Anand, Chris J. Beltran, Mark D. Brooke, Justine R. Buroker, Robert L. Foote, Olivia R. Foss, Angela M. Gleason, Teresa L. Hodge, Cían O. Hughes, Ashley E. Hunzeker, Nadia N. Laack, Tamra K. Lenz, Michelle Livne, Megumi Morigami, Douglas J. Moseley, Lisa M. Undahl, Yojan Patel, Erik J. Tryggestad, Megan Z. Walker, Alexei Zverovitch, Samir H. Patel |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Frontiers in Oncology, Vol 13 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2234-943X |
| DOI: |
10.3389/fonc.2023.1137803 |
| Popis: |
IntroductionOrgan-at-risk segmentation for head and neck cancer radiation therapy is a complex and time-consuming process (requiring up to 42 individual structure, and may delay start of treatment or even limit access to function-preserving care. Feasibility of using a deep learning (DL) based autosegmentation model to reduce contouring time without compromising contour accuracy is assessed through a blinded randomized trial of radiation oncologists (ROs) using retrospective, de-identified patient data.MethodsTwo head and neck expert ROs used dedicated time to create gold standard (GS) contours on computed tomography (CT) images. 445 CTs were used to train a custom 3D U-Net DL model covering 42 organs-at-risk, with an additional 20 CTs were held out for the randomized trial. For each held-out patient dataset, one of the eight participant ROs was randomly allocated to review and revise the contours produced by the DL model, while another reviewed contours produced by a medical dosimetry assistant (MDA), both blinded to their origin. Time required for MDAs and ROs to contour was recorded, and the unrevised DL contours, as well as the RO-revised contours by the MDAs and DL model were compared to the GS for that patient.ResultsMean time for initial MDA contouring was 2.3 hours (range 1.6-3.8 hours) and RO-revision took 1.1 hours (range, 0.4-4.4 hours), compared to 0.7 hours (range 0.1-2.0 hours) for the RO-revisions to DL contours. Total time reduced by 76% (95%-Confidence Interval: 65%-88%) and RO-revision time reduced by 35% (95%-CI,-39%-91%). All geometric and dosimetric metrics computed, agreement with GS was equivalent or significantly greater (p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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