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Objectives <p>To develop and validate a nomogram based on T1 and extracellular volume fraction (ECV) mapping derived from cardiovascular magnetic resonance (CMR) for differentiating ischemic from nonischemic cardiomyopathies during the acute phase.</p> Methods <p>This retrospective study included patients who underwent CMR at the Fifth Affiliated Hospital of Wenzhou Medical University (internal dataset) and the Fifth Affiliated Hospital of Sun Yat-sen University (external dataset). Patients were assigned to a training set (<i>n</i> = 73), a test set (<i>n</i> = 30), an internal validation set (<i>n</i> = 28), and an external validation set (<i>n</i> = 16). Six multivariable logistic regression models were constructed to predict acute nonischemic myocardial injury (NMI), and the best-performing model was selected to create an interactive online nomogram accessible via a dedicated webpage.</p> Result <p>The optimal model incorporated coronary stenosis, hypertension, ejection fraction (EF), myocardial salvage index (MSI), T1 native non-edema, and ECV edema. It demonstrated strong predictive performance in the training set (AUC 0.970, 95% CI 0.938–0.989), test set (AUC 0.902, 95% CI 0.789–0.954), internal validation set (AUC 0.839, 95% CI 0.668–0.907), and external validation set (AUC 0.767, 95% CI 0.520–0.936). The model also showed excellent calibration and potential clinical utility.</p> Conclusions <p>In acute myocardial injury, increased T1 native non-edema values and reduced ECV edema values are indicative of NMI. The proposed nomogram demonstrated good generalizability and robustness, particularly in complex clinical scenarios, and offers promising potential for clinical application.</p>

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Establishing T1 and ECV mapping based nomogram differentiate acute ischemic and nonischemic myocardial injury: a proof-of-concept study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月29日

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  • Yanping Su,
  • Cunxue Pan,
  • Hongfei Hu,
  • Di Shen,
  • Ruolei Ye,
  • Chenhui Zhou,
  • Mingzhen Chen,
  • Minjiang Chen,
  • Jian Chen,
  • Kan Liu,
  • Jiayi Shen,
  • Shuiwei Xia,
  • Min Xu,
  • Lingchun Lv,
  • Chenying Lu,
  • Jiansong Ji

摘要

Objectives

To develop and validate a nomogram based on T1 and extracellular volume fraction (ECV) mapping derived from cardiovascular magnetic resonance (CMR) for differentiating ischemic from nonischemic cardiomyopathies during the acute phase.

Methods

This retrospective study included patients who underwent CMR at the Fifth Affiliated Hospital of Wenzhou Medical University (internal dataset) and the Fifth Affiliated Hospital of Sun Yat-sen University (external dataset). Patients were assigned to a training set (n = 73), a test set (n = 30), an internal validation set (n = 28), and an external validation set (n = 16). Six multivariable logistic regression models were constructed to predict acute nonischemic myocardial injury (NMI), and the best-performing model was selected to create an interactive online nomogram accessible via a dedicated webpage.

Result

The optimal model incorporated coronary stenosis, hypertension, ejection fraction (EF), myocardial salvage index (MSI), T1 native non-edema, and ECV edema. It demonstrated strong predictive performance in the training set (AUC 0.970, 95% CI 0.938–0.989), test set (AUC 0.902, 95% CI 0.789–0.954), internal validation set (AUC 0.839, 95% CI 0.668–0.907), and external validation set (AUC 0.767, 95% CI 0.520–0.936). The model also showed excellent calibration and potential clinical utility.

Conclusions

In acute myocardial injury, increased T1 native non-edema values and reduced ECV edema values are indicative of NMI. The proposed nomogram demonstrated good generalizability and robustness, particularly in complex clinical scenarios, and offers promising potential for clinical application.