Abstract
BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.