Early Experience Utilizing 4D-CT Radiomic Features for Differentiation of Parathyroid Adenomas From Lymph Nodes and Thyroid Nodules

Parathyroid adenomas and lymph nodes have statistically distinct radiomic textural signatures on arterial phase 4D-CT, with the most significant differences found in first-order textural features. These findings may facilitate the development of future machine learning models for automated differentiation of parathyroid adenomas, further enhancing uptake of MIP and improving clinical outcomes.

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Publication Details

Journal
Journal of Computer Assisted Tomography
Published
2025-11-21
DOI
https://doi.org/10.1097/rct.0000000000001825
Citations
1
Primary Topic
Parathyroid Disorders and Treatments
Type
article
Field-Weighted Citation Impact
1.43
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article

Early Experience Utilizing 4D-CT Radiomic Features for Differentiation of Parathyroid Adenomas From Lymph Nodes and Thyroid Nodules

Michael H. Zhang, Anup Dhungana, Irfan Hussain, Daniel Thomas Ginat et al.
1 citations
Journal of Computer Assisted Tomography
Parathyroid Disorders and Treatments
1.43
article

Early Experience Utilizing 4D-CT Radiomic Features for Differentiation of Parathyroid Adenomas From Lymph Nodes and Thyroid Nodules

Michael H. Zhang, Anup Dhungana, Irfan Hussain, Daniel Thomas Ginat, Chime Ezenekwe
article en
1 citations

Abstract

Parathyroid adenomas and lymph nodes have statistically distinct radiomic textural signatures on arterial phase 4D-CT, with the most significant differences found in first-order textural features. These findings may facilitate the development of future machine learning models for automated differentiation of parathyroid adenomas, further enhancing uptake of MIP and improving clinical outcomes.

Journal of Computer Assisted Tomography
University of Chicago (US)
Openalex Percentile: Top 14%
Parathyroid Disorders and Treatments
1.43
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