Radiomics of Voxel-Wise DCE-MRI Wash-In and Wash-Out Maps Enable Quantitative Assessment of Hemodynamic Heterogeneity within Breast Lesions

Motivation: Tumor hemodynamic heterogeneity offers potential for characterizing, diagnosing, and prognosticating breast lesions. Current methods primarily address either spatial morphological heterogeneity or temporal aspects. Goal(s): This study aims to develop a method that visualizes and quantifies both temporal and spatial hemodynamic heterogeneity simultaneously to enhance breast lesion management. Approach: We propose generating voxel-wise time-intensity curve (TIC) corresponding wash-in and wash-out parameter maps to visualize the spatial distribution of temporal information. Radiomics is then used to extract features that quantify hemodynamic heterogeneity. Results: The study successfully demonstrated the clinical utility (AUC = 0.9846) of these quantitative features in differentiating benign from malignant lesions. Impact: This novel approach provides an intuitive and self-explainable visualization and quantification of spatial and temporal hemodynamic heterogeneity, with potential applications across a broader range of clinical settings.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/4129
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Radiomics of Voxel-Wise DCE-MRI Wash-In and Wash-Out Maps Enable Quantitative Assessment of Hemodynamic Heterogeneity within Breast Lesions

Binze Han, Kexin Chen, Jie Wen, Qian Wan et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Radiomics and Machine Learning in Medical Imaging
article

Radiomics of Voxel-Wise DCE-MRI Wash-In and Wash-Out Maps Enable Quantitative Assessment of Hemodynamic Heterogeneity within Breast Lesions

Binze Han, Kexin Chen, Jie Wen, Qian Wan, Wei Cui, Dehong Luo, Na Zhang, Ya Ren, Zhou Liu, Meng Wang
article en

Abstract

Motivation: Tumor hemodynamic heterogeneity offers potential for characterizing, diagnosing, and prognosticating breast lesions. Current methods primarily address either spatial morphological heterogeneity or temporal aspects. Goal(s): This study aims to develop a method that visualizes and quantifies both temporal and spatial hemodynamic heterogeneity simultaneously to enhance breast lesion management. Approach: We propose generating voxel-wise time-intensity curve (TIC) corresponding wash-in and wash-out parameter maps to visualize the spatial distribution of temporal information. Radiomics is then used to extract features that quantify hemodynamic heterogeneity. Results: The study successfully demonstrated the clinical utility (AUC = 0.9846) of these quantitative features in differentiating benign from malignant lesions. Impact: This novel approach provides an intuitive and self-explainable visualization and quantification of spatial and temporal hemodynamic heterogeneity, with potential applications across a broader range of clinical settings.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 63%
Radiomics and Machine Learning in Medical Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.