In one paragraphArticle in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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0citing papers in PubMed
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What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
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3 · Its place in the literatureWho cites it
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4 · The recordCorrections and comments
5 · Who and what moneyAuthors and funding
31 authors.
Laia Humbert-VidanDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0002-8005-6770 Austin H CasteloDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0009-0009-3015-3570 Renjie HeDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0001-9166-6286 Lisanne V van DijkDepartment of Radiation Oncology, University Medical Center Groningen, Groningen, Netherlands.ORCID 0000-0002-9515-5616 Dong Joo RheeDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0003-0486-1556 Congjun WangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
He C WangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0002-4904-531X Kareem A WahidDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0002-0503-0175 Natalie WestDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0009-0007-0211-8845 Zaphanlene KaffeyDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0009-0008-7999-5245 Sarah MirbahaeddinDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0009-0006-5864-4468 Jaqueline CurielDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0009-0009-9378-218X Samrina AcharyaDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Amal ShekhaDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Praise OderindeDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0009-0001-2334-5381 Alaa M S AliDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Ruth Wesson-AponteDepartment of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Steven J FrankDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0001-6517-7884 Carly E A BarbonDepartment of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0001-8971-6870 Kristy K BrockDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0001-9364-5040 Mark S ChambersDepartment of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Muhammad WaljiDepartment of Clinical and Health Informatics, Texas Center of Oral Health Care Quality & Safety, Houston, Texas, USA.
Katherine A HutchesonDepartment of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0003-3710-5706 Stephen Y LaiDepartment of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0001-8301-7286 Clifton D FullerDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0002-5264-3994 Mohamed A NaserDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0003-1020-4966 Amy C MorenoDivision of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0001-6762-6807 Funding
Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DIANE BODURKA · 1985 to 2026
$290.8MPaul Calabresi Clinical Oncology AwardK12CA088084 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI David S. Hong, Scott Kopetz · 2000 to 2026
$14.0MProject 3: OPC-RADP01CA285249 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Clifton David Fuller, Katherine Arnold Hutcheson · 2024 to 2026
$9.4MDevelopment of functional magnetic resonance imaging-guided adaptive radiotherapy for head and neck cancer patients using novel MR-Linac deviceR01DE028290 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI CHRISTODOULEAS, JOHN PAUL, FULLER, CLIFTON DAVID · 2019 to 2023
$4.3MUsing Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to Establish Objective Clinical Outcome Measures for Mandibular OsteoradionecrosisR01DE025248 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LAI, STEPHEN Y · 2016 to 2020
$2.9MQuantitative Imaging Biomarker Prospective Validation of Dynamic Contrast-Enhanced MRI as a Metric of Orodental Injury After Radiotherapy (QI-ProVE-MRI)U01DE032168 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Clifton David Fuller, STEPHEN Y LAI · 2023 to 2026
$2.8MMedical Students Summer in Oncology at Anderson Research (Med Students SOAR) programR25CA265800 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Jillian Rebecca Gunther, Marites Pasuelo Melancon · 2023 to 2026
$1.3MImage Guided Cancer Therapy Training ProgramT32CA261856 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Kristy Brock, Clifton David Fuller · 2022 to 2026
$1.2MCTSA Predoctoral T32 at the University of Texas Health Science Center at HoustonT32TR004905 · NCATS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Joya Chandra, Jeffrey A. Frost · 2024 to 2026
$811kProbabilistic Deep Learning Cervical Lymph-Node Auto-Segmentation For Imaging-enhanced Evaluation of Extracapsular Extension Risk (PDL-CLASIFIER)R03DE033550 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI FULLER, CLIFTON DAVID, NASER, MOHAMED · 2024 to 2025
$499kProvider and Patient-generated Remote Oro-Dental Health Electronic Data Capture for Algorithmic Longitudinal Evaluation and Risk-Assessment (PROHEALER)K01DE030524 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI MORENO, AMY CATHERINE · 2022 to 2024
$479kRadiation-specific Automated Dental Dose Distributions via Machine-learning based Mapping for Accurate Predictions of (Peri)odontal Problems (RADMAP)R21DE031082 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI MORENO, AMY CATHERINE · 2021 to 2022
$452kNCATS NIH HHS T32 TR004905NCI NIH HHS K12 CA088084NCI NIH HHS P01 CA285249NCI NIH HHS P30 CA016672NCI NIH HHS R25 CA265800NCI NIH HHS T32 CA261856NIDCR NIH HHS K01 DE030524NIDCR NIH HHS R01 DE025248NIDCR NIH HHS R01 DE028290NIDCR NIH HHS R03 DE033550NIDCR NIH HHS R21 DE031082NIDCR NIH HHS U01 DE032168
6 · The paper itselfAbstract
Background: Accurate delineation of orodental structures on radiotherapy CT images is essential for dosimetric assessments and dental decisions. We propose a deep-learning auto-segmentation framework for individual teeth and mandible/maxilla sub-volumes aligned with the ClinRad ORN staging system. Methods: Mandible and maxilla sub-volumes were manually defined, differentiating between alveolar and basal regions, and teeth were labelled individually. For each task, a DL segmentation model was independently trained. A Swin UNETR-based model was used for the mandible sub-volumes. For the smaller structures (e.g., teeth and maxilla sub-volumes) a two-stage segmentation model first used the ResUNet to segment the entire teeth and maxilla regions as a single ROI that was then used to crop the image input of the Swin UNETR. In addition to segmentation accuracy and geometric precision, a dosimetric comparison was made between manual and model-predicted segmentations. Results: Segmentation performance varied across sub-volumes - mean Dice values of 0.85 (mandible basal), 0.82 (mandible alveolar), 0.78 (maxilla alveolar), 0.80 (upper central teeth), 0.69 (upper premolars), 0.76 (upper molars), 0.76 (lower central teeth), 0.70 (lower premolars), 0.71 (lower molars) - and exhibited limited applicability in segmenting teeth and sub-volumes often absent in the data. Only the maxilla alveolar central sub-volume showed a statistically significant dosimetric difference (Bonferroni-adjusted p-value = 0.02). Conclusion: We present a novel DL-based auto-segmentation framework of orodental structures, enabling spatial localization of dose-related differences in the jaw. This tool enhances image-based bone injury detection, including ORN, and improves clinical decision-making in radiation oncology and dental care for head and neck cancer patients.
Identifiers
PMID40166584
PMCPMC11957087
What OpenQuestion holds
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LicenceCC BY
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