ArticleClinical and translational radiation oncology2018
A prospective in silico analysis of interdisciplinary and interobserver spatial variability in post-operative target delineation of high-risk oral cavity cancers: Does physician specialty matter?
Article in Clinical and translational radiation oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 19 citations in OpenAlex.
- Article
- Investigation on performance of multiple AI-based auto-contouring systems in organs at risks (OARs) delineation.Physical and engineering sciences in medicine · 2024Article
- Article
- Applying a novel two-step deep learning network to improve the automatic delineation of esophagus in non-small cell lung cancer radiotherapy.Frontiers in oncology · 2023Article
- Clinical evaluation of deep learning-based clinical target volume three-channel auto-segmentation algorithm for adaptive radiotherapy in cervical cancer.BMC medical imaging · 2022Article
- Comprehensive Quantitative Evaluation of Variability in Magnetic Resonance-Guided Delineation of Oropharyngeal Gross Tumor Volumes and High-Risk Clinical Target Volumes: An R-IDEAL Stage 0 Prospective Study.International journal of radiation oncology, biology, physics · 2022Article
- Deep learning-based GTV contouring modeling inter- and intra- observer variability in sarcomas.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2022Article
- Effects of interobserver and interdisciplinary segmentation variabilities on CT-based radiomics for pancreatic cancer.Scientific reports · 2021Article
- Comparison of tumor delineation using dual energy computed tomography versus magnetic resonance imaging in head and neck cancer re-irradiation cases.Physics and imaging in radiation oncology · 2020Article
Corrections and comments
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Authors and funding
22 authors at 8 institutions in 1 country.
Funding
Abstract
backgroundThe aim of this study was to determine the interdisciplinary agreement in identifying the post-operative tumor bed.
methodsThree radiation oncologists (ROs), four surgeons, and three radiologists segmented post-operative tumor and nodal beds for three patients with oral cavity cancer. Specialty cohort composite contours were created by STAPLE algorithm implementation results for interspecialty comparison. Dice similarity coefficient and Hausdorff distance were utilized to compare spatial differentials between specialties.
resultsThere were significant differences between disciplines in target delineation. There was unacceptable variation in Dice similarity coefficient for each observer and discipline when compared to the STAPLE contours. Within surgery and radiology disciplines, there was good consistency in volumes. ROs and radiologists have similar Dice similarity coefficient scores compared to surgeons.
conclusionThere were significant interdisciplinary differences in perceptions of tissue-at-risk. Better communication and explicit description of at-risk areas between disciplines is required to ensure high-risk areas are adequately targeted.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.