The Clinical Utility of Radiomics Models Based on Non-Contrast T1 Mapping in CMR for Discriminating Acute and Chronic Myocardial Infarction

Motivation: The complexity of differentiation between acute and chronic myocardial infarctions(MI) not only complicates the choice of treatment plans but also poses challenges for post-treatment follow-up. Goal(s): This study aimed to determine whether radiomics model based on T1 mapping can be applied in differential diagnosis of acute and chronic MI. Approach: Images of 61 patients were included for feature extraction, and the statistically significant features were selected to establish the radiomics model. Results: This radiomics model demonstrates significant efficacy in distinguishing between acute and chronic myocardial infarction lesions in patients, providing valuable support for clinical diagnosis and follow-up treatment. Impact: The development of radiomics model to differentiate acute from chronic myocardial infarction lesions holds promise for facilitating prompt clinical decision-making. This advancement enables early medical intervention for MI patients, reducing the risk of adverse cardiovascular events and enhancing patient prognosis.

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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
2024-11-26
DOI
https://doi.org/10.58530/2024/3794
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

The Clinical Utility of Radiomics Models Based on Non-Contrast T1 Mapping in CMR for Discriminating Acute and Chronic Myocardial Infarction

Yunzhu Wu, Ruqian Hao, Yueluan Jiang, Zhiyuan Liu 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

The Clinical Utility of Radiomics Models Based on Non-Contrast T1 Mapping in CMR for Discriminating Acute and Chronic Myocardial Infarction

Yunzhu Wu, Ruqian Hao, Yueluan Jiang, Zhiyuan Liu, Yang Song, Shinuo Li
article en

Abstract

Motivation: The complexity of differentiation between acute and chronic myocardial infarctions(MI) not only complicates the choice of treatment plans but also poses challenges for post-treatment follow-up. Goal(s): This study aimed to determine whether radiomics model based on T1 mapping can be applied in differential diagnosis of acute and chronic MI. Approach: Images of 61 patients were included for feature extraction, and the statistically significant features were selected to establish the radiomics model. Results: This radiomics model demonstrates significant efficacy in distinguishing between acute and chronic myocardial infarction lesions in patients, providing valuable support for clinical diagnosis and follow-up treatment. Impact: The development of radiomics model to differentiate acute from chronic myocardial infarction lesions holds promise for facilitating prompt clinical decision-making. This advancement enables early medical intervention for MI patients, reducing the risk of adverse cardiovascular events and enhancing patient prognosis.

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
Reduced inequalities
Openalex Percentile: Top 63%
Radiomics and Machine Learning in Medical Imaging
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