Monte Carlo method applied to the evaluation of the relationship between ejection fraction and its constituent components

Ventricular function is routinely assessed by applying the clinically accepted metric ejection fraction (EF). The numerical value of EF depends on the interplay between end-systolic volume (ESV) and end-diastolic volume (EDV). The relative impact of the two constitutive components has received little attention. Pediatric cardiologists are interested in EF vs ESV when evaluating various congenital abnormalities. Following successful surgical intervention of Fallot tetralogy, many of these patients receive follow-up, not only during childhood, but also when being adults. Cardiologists diagnosing and treating elderly patients often analyze EF vs EDV, notably for phenotyping heart failure patients. Therefore, we study EF vs ESV as well as EF vs EDV in more detail. We explore the fundamentals of EF while analyzing a Fallot patient group. Three routes were followed, namely nonlinear regression, by implementing a Monte Carlo approach to generate EDV on the basis of known ESV values, and by using a theoretical graphical derivation. Our MRI-based post Fallot repair study includes left (LV) and right ventricular (RV) data (N=124). Using a robust approach we employed nonlinear regression with ESV as an independent variable. EDV was also assessed by Monte Carlo generated values for stroke volume within a physiological range. In all cases ESV emerges as the dominant component of EF, with less (P<;0.0001) impact of EDV. Using three independent routes we demonstrate that values for EF primarily depend on the corresponding ESV. This relationship is nonlinear, and correlation is always better with ESV compared to EDV in these patients, and confirmed in random number modeling studies.restrictio