Background: The aim of our study was to render age- and sex-specific normal values for aortic blood flow profiles using 4D flow cardiovascular magnetic resonance (CMR) derived data in a population based study cohort.

Methods: An age- and sex-stratified sample of the population of the city of Freiburg, Germany (n=126, age 20-80 years, female 51%) underwent 4D flow CMR of the thoracic aorta at 3 Tesla. Five parameters were analyzed in 12 analysis planes along the entire thoracic aorta: BSA-adjusted aortic area (A’), normalized flow displacement (NFD), angle between average flow direction and centerline (α), degree of wall parallelity (WPD) and the minimal relative cross-sectional area through which 80% of the volume flow rate passes (A₈₀). Age- and sex-specific percentiles (PCTL) were computed and age- and sex- specific differences studied. Additionally, blood flow profiles in the ascending aorta of a patient with severe aortic valve stenosis were quantified and compared to age- and sex-matched percentiles.

Results: Age- and sex-specific normal values for aortic blood flow profiles using 4D flow CMR derived data were collected. In this data collection, significant age-related differences in blood flow profiles were found in the ascending aorta with increase in NFD and α (p<0.001 and p=0.003, respectively) and decrease in WPD and A₈₀ (both: p<0.001). In the ascending aorta, all blood flow profiles correlated with the cross-sectional area (NFD: r=0.40; α: r=0.39, WPD: r=-0.80; A80: r=-0.66) suggesting possible influence between blood flow profiles and area. Comparison of blood flow profiles in the ascending aorta from a patient with severe aortic valve stenosis against age- and sex-matched reference values showed values lower than 3^rd or higher than 90^th percentile (α > 97. PCTL, WPD < 3. PCTL, A80 < 3. PCTL, NFD >90. PCTL). 

Conclusions: This study provides age- and sex-specific reference values for parameters that describe blood flow profiles along the thoracic aorta to discriminate physiological from pathological flow profiles, which might allow clinical applicability of aortic blood flow pattern quantification.