Fully Automated Valve Segmentation for Blood Flow Assessment From 4D Flow MRI Including Automated Cardiac Valve Tracking and Transvalvular Velocity Mapping

Abstract

BackgroundAutomated 4D flow MRI valvular flow quantification without time‐consuming manual segmentation might improve workflow.PurposeCompare automated valve segmentation (AS) to manual (MS), and manually corrected automated segmentation (AMS), in corrected atrioventricular septum defect (c‐AVSD) patients and healthy volunteers, for assessing net forward volume (NFV) and regurgitation fraction (RF).Study TypeRetrospective.Population27 c‐AVSD patients (median, 23 years; interquartile range, 16–31 years) and 24 healthy volunteers (25 years; 12.5–36.5 years).Field strength/SequenceWhole‐heart 4D flow MRI and cine steady‐state free precession at 3T.AssessmentAfter automatic valve tracking, valve annuli were segmented on time‐resolved reformatted trans‐valvular velocity images by AS, MS, and AMS. NFV was calculated for all valves, and RF for right and left atrioventricular valves (RAVV and LAVV). NFV variation (standard deviation divided by mean NFV) and NFV differences (NFV difference of a valve vs. mean NFV of other valves) expressed internal NFV consistency.Statistical TestsComparisons between methods were assessed by Wilcoxon signed‐rank tests, and intra/interobserver variability by intraclass correlation coefficients (ICCs). P < 0.05 was considered statistically significant, with multiple testing correction.ResultsAMS mean analysis time was significantly shorter compared with MS (5.3 ± 1.6 minutes vs. 9.1 ± 2.5 minutes). MS NFV variation (6.0%) was significantly smaller compared with AMS (6.3%), and AS (8.2%). Median NFV difference of RAVV, LAVV, PV, and AoV between segmentation methods ranged from −0.7–1.0 mL, −0.5–2.8 mL, −1.1–3.6 mL, and − 3.1–‐2.1 mL, respectively. Median RAVV and LAVV RF, between 7.1%–7.5% and 3.8%–4.3%, respectively, were not significantly different between methods. Intraobserver/interobserver agreement for AMS and MS was strong‐to‐excellent for NFV and RF (ICC ≥0.88).Data ConclusionMS demonstrates strongest internal consistency, followed closely by AMS, and AS. Automated segmentation, with or without manual correction, can be considered for 4D flow MRI valvular flow quantification.Level of Evidence3Technical EfficacyStage 3