Spatially aware radiomics integrating anatomical knowledge to improve lymph node malignancy prediction in head and neck cancer

This study demonstrates that incorporating lymphatic anatomy and clinical context into radiomics models significantly improves predictive performance. The proposed approach enhances interpretability, aligns with clinical workflows, and holds promises for personalized radiation therapy planning.

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Publication Details

Journal
Journal of Applied Clinical Medical Physics
Published
2026-01-27
DOI
https://doi.org/10.1002/acm2.70483
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00

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article

Spatially aware radiomics integrating anatomical knowledge to improve lymph node malignancy prediction in head and neck cancer

Sepeadeh Radpour, Michael Dohopolski, David Sher, Jing Wang et al.
Journal of Applied Clinical Medical Physics
Radiomics and Machine Learning in Medical Imaging
article

Spatially aware radiomics integrating anatomical knowledge to improve lymph node malignancy prediction in head and neck cancer

Sepeadeh Radpour, Michael Dohopolski, David Sher, Jing Wang, Liyuan Chen
article en

Abstract

This study demonstrates that incorporating lymphatic anatomy and clinical context into radiomics models significantly improves predictive performance. The proposed approach enhances interpretability, aligns with clinical workflows, and holds promises for personalized radiation therapy planning.

Journal of Applied Clinical Medical PhysicsVol. 27(2)
Southwestern Medical Center (US), Southwestern Medical Center (US), The University of Texas Southwestern Medical Center (US)
University of Texas Southwestern Medical Center, National Institutes of Health
Openalex Percentile: Top 79%
Radiomics and Machine Learning in Medical Imaging
DOIOpen Access PDFOpenAlex
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