Impact of Inferior Venae Cava Assessment In Tetralogy of Fallot

Abstract Background Inferior vena cava (IVC) size and collapsibility provides a noninvasive estimate of right heart filling pressures, an important determinant of right heart hemodynamic performance that is not measured by cardiac magnetic resonance imaging (CMRI). We hypothesized that compared to CMRI risk model alone, a combined CMRI-IVC risk model will have better correlation with disease severity and peak oxygen consumption (VO2) in patients with tetralogy of Fallot (TOF). Methods Retrospective review of TOF patients with moderate/severe pulmonary regurgitation that underwent CMRI and echocardiography. CMRI risk model was constructed using right ventricular (RV) end-diastolic volume index, RV end-systolic volume index, RV ejection fraction, and left ventricular ejection fraction. We added IVC hemodynamic classification to the CMRI indices to create CMRI-IVC risk model, and IVC hemodynamics was modeled as a categorical variable: normal vs mild/moderately abnormal (dilated IVC or reduced collapsibility) vs severely abnormal IVC hemodynamics (dilated IVC and reduced collapsibility). We defined disease severity as atrial arrhythmias, ventricular arrhythmias, and heart failure hospitalization. Results Of 207 patients, 131(63%), 72 (35%), and 4 (2%) had normal, mild/moderately abnormal, and had severely abnormal IVC hemodynamics respectively. Compared to CMRI risk model, CMRI-IVC risk model had a better correlation with disease severity (AUC 0.62, 95% CI 0.51-0.74 vs AUC 0.84, 95% CI 0.78-0.91, p=0.006) and peak VO2 (r=0.35, p=0.042 vs r=0.43, p=0.031, Meng test p=0.026). Conclusions The combined CMRI-IVC risk model had better correlation with disease severity as compared to CMRI indices alone, and can potentially improve risk stratification in the TOF population.