ArticleKorean journal of radiology2021
Radiomics of Non-Contrast-Enhanced T1 Mapping: Diagnostic and Predictive Performance for Myocardial Injury in Acute ST-Segment-Elevation Myocardial Infarction.
Article in Korean journal of radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04682756 (A Multicenter Study on Early Diagnosis of NSTE-ACS Patients Based on Machine Learning Model), which is not on this map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Multicenter Study on Early Diagnosis of NSTE-ACS Patients Based on Machine Learning Model
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Quality of science and reporting for radiomics in cardiac magnetic resonance imaging studies: a systematic review.European radiology · 2022Pooled it
- Non-Contrast Cine Cardiac Magnetic Resonance Derived-Radiomics for the Prediction of Left Ventricular Adverse Remodeling in Patients With ST-Segment Elevation Myocardial Infarction.Korean journal of radiology · 2023Trial
- Incremental prognostic value of CCTA-based myocardial radiomics over clinical factors, anatomic and hemodynamic CTA findings in patients with stable angina.The international journal of cardiovascular imaging · 2026Review
- An interpretable radiomics-based machine learning model for predicting reverse left ventricular remodeling in STEMI patients using late gadolinium enhancement of myocardial scar.European radiology · 2025Article
- AI Applied to Cardiac Magnetic Resonance for Precision Medicine in Coronary Artery Disease: A Systematic Review.Journal of cardiovascular development and disease · 2025Review
- Association Between Extracellular Volume Assessed by Cardiac MRI and New-Onset Atrial Fibrillation in Patients With ST-Segment Elevation Myocardial Infarction.Korean journal of radiology · 2025Article
- Repeatability of radiomic features in myocardial T1 and T2 mapping.European radiology · 2025Article
- Machine Learning Applications in Acute Coronary Syndrome: Diagnosis, Outcomes and Management.Advances in therapy · 2025Review
- Radiomics of pericardial fat: a new frontier in heart failure discrimination and prediction.European radiology · 2024Article
- Late gadolinium enhanced cardiac MR derived radiomics approach for predicting all-cause mortality in cardiac amyloidosis: a multicenter study.European radiology · 2024Article
- Artificial Intelligence in Cardiology and Atherosclerosis in the Context of Precision Medicine: A Scoping Review.Applied bionics and biomechanics · 2024Article
- From multi-omics approaches to personalized medicine in myocardial infarction.Frontiers in cardiovascular medicine · 2023Review
- Development and evaluation of a radiomics model of restingAnnals of translational medicine · 2022Article
- Native T1 Mapping-Based Radiomics for Noninvasive Prediction of the Therapeutic Effect of Pulmonary Arterial Hypertension.Diagnostics (Basel, Switzerland) · 2022Article
- The Road Toward Reproducibility of Parametric Mapping of the Heart: A Technical Review.Frontiers in cardiovascular medicine · 2022Review
- Artificial Intelligence Based Multimodality Imaging: A New Frontier in Coronary Artery Disease Management.Frontiers in cardiovascular medicine · 2021Review
- Artificial Intelligence-A Good Assistant to Multi-Modality Imaging in Managing Acute Coronary Syndrome.Frontiers in cardiovascular medicine · 2021Review
- Magnetic Resonance Texture Analysis in Myocardial Infarction.Frontiers in cardiovascular medicine · 2021Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveTo evaluate the feasibility of texture analysis on non-contrast-enhanced T1 maps of cardiac magnetic resonance (CMR) imaging for the diagnosis of myocardial injury in acute myocardial infarction (MI). MATERIALS AND
methodsThis study included 68 patients (57 males and 11 females; mean age, 55.7 ± 10.5 years) with acute ST-segment-elevation MI who had undergone 3T CMR after a percutaneous coronary intervention. Forty patients of them also underwent a 6-month follow-up CMR. The CMR protocol included T2-weighted imaging, T1 mapping, rest first-pass perfusion, and late gadolinium enhancement. Radiomics features were extracted from the T1 maps using open-source software. Radiomics signatures were constructed with the selected strongest features to evaluate the myocardial injury severity and predict the recovery of left ventricular (LV) longitudinal systolic myocardial contractility.
resultsA total of 1088 segments of the acute CMR images were analyzed; 103 (9.5%) segments showed microvascular obstruction (MVO), and 557 (51.2%) segments showed MI. A total of 640 segments were included in the 6-month follow-up analysis, of which 160 (25.0%) segments showed favorable recovery of LV longitudinal systolic myocardial contractility. Combined radiomics signature and T1 values resulted in a higher diagnostic performance for MVO compared to T1 values alone (area under the curve [AUC] in the training set; 0.88, 0.72,
conclusionThe combination of radiomics of non-contrast-enhanced T1 mapping and T1 values could provide higher diagnostic accuracy for MVO. Radiomics also provides incremental value in the prediction of LV longitudinal systolic myocardial contractility at six months.
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