Radiomics Analysis of Gadoxetic Acid-Enhanced MRI for Predicting Proliferative Hepatocellular Carcinoma

Motivation: Proliferative HCC exhibits more aggressive biological behavior and has a poorer prognosis. Goal(s): This study aimed to preoperatively diagnose proliferative HCC using diverse radiomics models and a nomogram, while also assessing their prognostic value. Approach: This study is a retrospective research. Results: BCLC stage and combined radscore are independent prognostic factors for proliferative HCC. The nomograms based on these factors had AUCs of 0.838 and 0.801 in the training and validation cohorts, respectively. The delta radiomics model (DR)-predicted proliferative HCC showed the best performance in risk stratification. Impact: The nomogram combining independent clinical predictive factors and the combined radscore demonstrates the best diagnostic efficacy for proliferative HCC, while different radiomic models and the nomogram can provide varying prognostic stratification values.

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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/10.58530/2025/2677
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Radiomics Analysis of Gadoxetic Acid-Enhanced MRI for Predicting Proliferative Hepatocellular Carcinoma

Xiance Zhao, Xueqin Zhang, Zixin Liu, Zuyi Yan
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 Analysis of Gadoxetic Acid-Enhanced MRI for Predicting Proliferative Hepatocellular Carcinoma

Xiance Zhao, Xueqin Zhang, Zixin Liu, Zuyi Yan
article en

Abstract

Motivation: Proliferative HCC exhibits more aggressive biological behavior and has a poorer prognosis. Goal(s): This study aimed to preoperatively diagnose proliferative HCC using diverse radiomics models and a nomogram, while also assessing their prognostic value. Approach: This study is a retrospective research. Results: BCLC stage and combined radscore are independent prognostic factors for proliferative HCC. The nomograms based on these factors had AUCs of 0.838 and 0.801 in the training and validation cohorts, respectively. The delta radiomics model (DR)-predicted proliferative HCC showed the best performance in risk stratification. Impact: The nomogram combining independent clinical predictive factors and the combined radscore demonstrates the best diagnostic efficacy for proliferative HCC, while different radiomic models and the nomogram can provide varying prognostic stratification values.

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
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Radiomics Analysis of Gadoxetic Acid-Enhanced MRI for Predicting Proliferative Hepatocellular Carcinoma — Xiance Zhao, Xueqin Zhang, 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 (2025) | TGRS Research Map | TGRS