ReviewDiagnostics (Basel, Switzerland)2023
Automated Contouring and Planning in Radiation Therapy: What Is 'Clinically Acceptable'?
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In one paragraph
Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.
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74citing papers in PubMed
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Who cites it
74 citing papers in PubMed.
- Clinical evaluation of three deep learning contouring models for head and neck organs at risk and lymph node levels.Technical innovations & patient support in radiation oncology · 2026Article
- Clinical evaluation and regression test of a commercial deep-learning auto-segmentation model.Journal of applied clinical medical physics · 2026Article
- Multi-modal direct LINAC parameter prediction for pancreatic VMAT: An optimization-free approach.Medical physics · 2026Article
- Cross-fraction prior learning for scalable organ-at-risk segmentation in abdominal MR-guided radiotherapy.Medical physics · 2026Article
- Comparison of DVH-based machine learning and 3D convolutional neural network approaches for automated VMAT planning in head and neck cancer.Radiological physics and technology · 2026Article
- AI-assisted automation will reduce the need for medical physics trainees and entry-level workforce.Journal of applied clinical medical physics · 2026Article
- Development and Clinical Validation of a Protocol-Agnostic Machine Learning Platform for Automated Treatment Planning in External Beam Radiation Therapy.Advances in radiation oncology · 2026Article
- A prospective development and evaluation of a 2D convolutional neural network-based auto-segmentation model for cervical cancer radiotherapy.Journal of the Egyptian National Cancer Institute · 2026Article
- A Real-World Evaluation of Failure Detection for Liver CT Segmentation.medRxiv : the preprint server for health sciences · 2026Article
- AI-Based Dose Compliance of Secondary Organs at Risk in Head and Neck Cancer Radiotherapy.Diagnostics (Basel, Switzerland) · 2026Article
- Automated vs. manual segmentation for small renal mass imaging.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2026Article
- The illusory correlation between geometrical similarity and physician satisfaction in heart auto-segmentation revealed by a physician-blind test.Journal of applied clinical medical physics · 2026Article
- Nanomaterials reshaping cancer radiotherapy: Radiosensitization mechanisms, delivery and theranostic platforms, multimodal synergy, and clinical translation strategies.Materials today. Bio · 2026Review
- Artificial intelligence in radiation treatment planning: a narrative review from automation to clinical decision support.Translational cancer research · 2026Review
- Review
- Explicit modeling of beam geometry improves three-dimensional dose prediction for esophageal cancer radiotherapy under heterogeneous beam configurations.Radiation oncology (London, England) · 2026Article
- Development and clinical deployment of an automated planning tool for prostate only and male whole pelvis plans based on multi-criteria optimization.Journal of applied clinical medical physics · 2026Article
- Evaluation of a quasi-automatic treatment planning workflow for head-and-neck cancer in radiotherapy.Physics and imaging in radiation oncology · 2026Article
- Comparison of Auto-Contouring Tools for Delineation of Normal Organs at Risk in Paediatric Patients Undergoing Radiotherapy.Journal of medical radiation sciences · 2026Article
- Clinical validation of AI-assisted contouring in prostate radiation therapy treatment planning: Highlighting automation bias and the need for standardized quality assurance.Journal of applied clinical medical physics · 2026Article
14 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
28 authors.
Hana BaroudiDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Kristy K BrockDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0001-9364-5040
Wenhua CaoDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Xinru ChenDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0002-9989-8943
Caroline ChungDepartment of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Laurence E CourtDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0002-3241-6145
Mohammad D El BashaDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Maguy FarhatDepartment of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Skylar GayDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0003-4659-0766
Mary P GronbergDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0002-0121-9579
Aashish Chandra GuptaDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Soleil HernandezDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0003-1934-8157
Kai HuangDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0002-7683-5093
David A JaffrayDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0001-7378-7543
Rebecca LimDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Barbara MarquezDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Kelly NealonDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Tucker J NethertonDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Callistus M NguyenDepartment of Imaging Physics, Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Brandon ReberThe University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, TX 77030, USA.
Dong Joo RheeDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Ramon M SalazarDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Mihir D ShankerThe University of Queensland, Saint Lucia 4072, Australia.
Carlos SjogreenDepartment of Physics, University of Houston, Houston, TX 77004, USA.
McKell WoodlandDepartment of Imaging Physics, Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0003-0995-3695
Jinzhong YangDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Cenji YuDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Yao ZhaoDepartment of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0001-8863-841X
Funding
Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DIANE BODURKA · 1985 to 2026
$290.8MProject 3: Enhanced Sensitivity of Tumors to Proton Beam Therapy: Mechanisms and Biomarkers.P01CA261669 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI TITT, UWE · 2021 to 2025
$14.0MOptimization and Evaluation of Anatomical Models of Liver Radiation ResponseR01CA221971 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BROCK, KRISTY · 2018 to 2022
$1.8MAnatomical Modeling to Improve the Precision of Image Guided Liver AblationR01CA235564 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BROCK, KRISTY, ODISIO, BRUNO C · 2019 to 2023
$1.7MNCI NIH HHS P01 CA261669NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA221971NCI NIH HHS R01 CA235564
Abstract
Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is 'clinical acceptability'? Quantitative and qualitative approaches have been used to assess this ill-defined concept, all of which have advantages and disadvantages or limitations. The approach chosen may depend on the goal of the study as well as on available resources. In this paper, we discuss various aspects of 'clinical acceptability' and how they can move us toward a standard for defining clinical acceptability of new autocontouring and planning tools.
Indexed as
artificial intelligencequality assuranceradiotherapy treatment planning
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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.