Abstract
BACKGROUND: Inferior vena cava (IVC) size and collapsibility provide 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 with CMRI risk model alone, a combined CMRI-IVC risk model will have better correlation with disease severity and peak oxygen consumption in patients with tetralogy of Fallot (TOF). METHODS: We performed a retrospective review of patients with TOF with moderate/severe pulmonary regurgitation who underwent CMRI and echocardiography. A 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 were 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 severely abnormal IVC hemodynamics, respectively. Compared with the CMRI risk model, the CMRI-IVC risk model had a better correlation with disease severity (area under the curve, 0.62; 95% confidence interval, 0.51-0.74 vs area under the curve 0.84, 95% confidence interval, 0.78-0.91, P = 0.006) and peak oxygen consumption (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 a better correlation with disease severity compared with CMRI indices alone and can potentially improve risk stratification in the population with TOF.