Felicia Seemann^{1,2}, Per Arvidsson^{1}, David Nordlund^{1}, Sascha Kopic^{1}, Marcus Carlsson^{1}, Håkan Arheden^{1}, and Einar Heiberg^{1,2}

Cardiac pressure-volume loop analysis provides important information on cardiac function, but is currently not widely utilized clinically since invasive measurements are required. This study aimed to develop and validate a non-invasive method of estimating pressure-volume loops, via a model-based framework using cardiovascular magnetic resonance. The method yields individualized pressure-volume loops computed using time-varying elastance, with left ventricular volume and brachial pressure as input. Experimental validation showed strong agreement to in-vivo measurements, and application to healthy controls and heart failure patients yielded expected results. Hence, the model is a promising method for obtaining pressure-volume loops from magnetic resonance imaging.

**Introduction**

The proposed model is the first validated, non-invasive method to derive individualized left ventricular pressure-volume loops and associated quantitative measures, for potential use in the clinic or in clinical trials. The experimental validation showed a strong agreement between model output and in-vivo derived measurements. Application in healthy controls and heart failure patients yielded expected cohort differences.

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Figure 1. Schematic
illustration of a pressure-volume loop and derived quantitative measures. The
pressure-volume (PV) loop in black, with corresponding end-systolic and
end-diastolic PV relation (ESPVR, EDPVR) in blue. The gray area within the PV-loop
is the stroke work (SW), and the area within the red triangle represents the
approximation of mechanical potential energy (PE) used in this study.
Ventricular efficiency is defined as SW/(SW + PE).

Figure 2. Example of model output result. Example of left ventricular
(LV) pressure-volume loop measured in-vivo
(blue line) and by modeling (black dashed line).

Figure 3. Validation results. Comparison of model
against in-vivo calculated
hemodynamic parameters, disclosing a strong agreement.

Figure 4. Cohort comparison of PV-loop
derived quantitative measures. Model application in healthy controls (n=13) and
patients (n=28). Dots represent the quantitative measure of each subject. Black
horizontal lines represent the mean for each cohort. ns, non-significant, ****
p<0.0001