Exercise CMR-derived myocardial dynamic index was lower in cardiac versus non-cardiac dyspnea (25.9 vs 45.1 mL·W/g/m², p<0.0001) and improved diagnostic AUC from 0.86 to 0.93 (p=0.012).
Observational (n=93)
Yes
Does the Ex-CMR derived myocardial dynamic index (MDI) improve the diagnostic differentiation of cardiac from non-cardiac dyspnea in patients with dyspnea?
The Ex-CMR derived myocardial dynamic index is a novel non-invasive imaging marker that significantly improves the differentiation of cardiac from non-cardiac dyspnea beyond conventional clinical and resting imaging parameters.
Absolute Event Rate: 25.9% vs 45.1%
p-value: p=<0.0001
Identifying the cause of dyspnea (i.e., cardiac vs. non-cardiac) can be challenging in the absence of significant resting cardiac abnormalities. Exercise cardiovascular magnetic resonance (Ex-CMR) enables quantification of cardiac volumetric indices under physiological stress. Using Ex-CMR, we sought to develop a non-invasive imaging marker, referred to as the myocardial dynamic index (MDI), and to demonstrate its potential for evaluating cardiac dyspnea. MDI is a metric derived from Ex-CMR work–volume loop model that integrates rest and stress left ventricular (LV) end-diastolic and end-systolic volumes with workload measured during supine exercise, while accounting for body size and LV mass. To evaluate MDI as a marker of cardiac dyspnea, we retrospectively analyzed data from a prospective multicenter study measuring MDI in patients with cardiac or non-cardiac dyspnea. All had invasive exercise testing before Ex-CMR. Cardiac dyspnea was defined by established invasive and non-invasive criteria, including HFpEF (early to advanced) and HFmrEF. Non-cardiac dyspnea patients had normal invasive hemodynamics and cardiac function. Univariable and multivariable logistic regression identified clinical and imaging predictors of cardiac dyspnea. A base model incorporating clinical and rest CMR variables was compared to a model that included the base model plus MDI. Diagnostic performance was assessed using receiver operating characteristic analysis and compared using the DeLong test. MDI scan/re-scan reproducibility over one year, inter- and intra-observer reproducibility, and correlation with VO₂ max were evaluated. Among 93 patients (66 with cardiac dyspnea, 27 with non-cardiac dyspnea), MDI was lower in patients with cardiac dyspnea (25.9±9.5 vs. 45.1±10.7 mL·W/g/m², p<0.0001). The base model included age, body mass index, NYHA class, and left atrial strain. In multivariable analysis, MDI emerged as the only independent predictor of cardiac dyspnea when added to the base model. Inclusion of MDI improved the AUC from 0.86 to 0.93 (p=0.012), while MDI alone yielded an AUC of 0.91. A strong correlation was observed between MDI and the VO₂ max index (r=0.84, p<0.0001). Reproducibility was excellent. Ex-CMR MDI is independently associated with cardiac dyspnea and strongly correlates with the VO₂ max index. It aids in differentiating cardiac from non-cardiac dyspnea and provides incremental diagnostic value beyond conventional clinical and resting imaging parameters. The MDI is derived from the Ex-CMR work–volume loop area equation, adjusted for myocardial mass and body surface area. MDI was evaluated in 93 patients with cardiac or non-cardiac dyspnea and demonstrated added value beyond conventional clinical and resting CMR variables, along with a strong correlation with the VO₂ max index. Ex-CMR = exercise cardiovascular magnetic resonance; iCEPT= invasive cardiopulmonary exercise testing; max.W = maximum workload achieved within 10 minutes of supine Ex-CMR; RHC= right heart catheterization; SVi = stroke volume index.
Ghanbari et al. (Wed,) conducted a observational in Cardiac dyspnea (n=93). Exercise cardiovascular magnetic resonance myocardial dynamic index (MDI) vs. Non-cardiac dyspnea / Base clinical model was evaluated on Myocardial dynamic index (MDI) in cardiac vs. non-cardiac dyspnea (p=<0.0001). Exercise CMR-derived myocardial dynamic index was lower in cardiac versus non-cardiac dyspnea (25.9 vs 45.1 mL·W/g/m², p<0.0001) and improved diagnostic AUC from 0.86 to 0.93 (p=0.012).
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