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In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging
Published on: February 25, 2022
Multicenter Consistency Assessment of Valvular Flow Quantification With Automated Valve Tracking in 4D Flow CMR
Joe F Juffermans1, Savine C S Minderhoud2, Johan Wittgren3
1Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
Insights
Automated valve tracking in 4D flow cardiac magnetic resonance (CMR) provides consistent valvular flow quantification across multiple sites. This method is reliable regardless of scanner type or local protocols, ensuring dependable clinical assessments.
Area of Science:
- Cardiovascular imaging
- Medical physics
- Biomedical engineering
Background:
- Automated retrospective valve tracking in 4D flow cardiac magnetic resonance (CMR) enables consistent assessment of valvular flow.
- Variability in CMR scanners and protocols across clinical centers raises questions about the reproducibility of these assessments.
- This study addresses the uncertainty regarding the consistency of 4D flow CMR valvular flow quantification in diverse clinical settings.
Purpose of the Study:
- To determine interobserver agreement in valvular flow quantification using 4D flow CMR with automated valve tracking.
- To assess valvular flow variation across different intracardiac valves.
- To identify variables, including CMR scanner and protocol specifics, that predict variations in valvular flow quantification.
Main Methods:
- Multi-site study involving 7 centers with 64 patients and 76 healthy volunteers.
- Acquisition of whole-heart 4D flow CMR using various vendors and field strengths (1.5-T and 3-T).
- Local and central performance of automated retrospective valve tracking for valvular flow quantification; interobserver agreement assessed via ICCs; intervalvular variation evaluated; regression analysis for predictor identification.
Main Results:
- Strong-to-excellent interobserver agreement for Net Forward Volume (NFV) (ICC: 0.85–0.96) and moderate-to-excellent for regurgitation fraction (ICC: 0.53–0.97).
- Low intervalvular variation (≤10.5%) consistently observed across all observers and valves.
- Availability of 2 cine images per valve for tracking, compared to 1, predicted a significant decrease in NFV variation (beta = -1.3; p = 0.01).
Conclusions:
- Automated retrospective valve tracking in 4D flow CMR enables consistent valvular flow quantification.
- The reliability of this technique is independent of the specific CMR scanners and protocols used at local clinical sites.
- This finding supports the widespread clinical adoption of automated valve tracking for accurate valvular flow assessment.
Objectives:
This study determined: 1) the interobserver agreement; 2) valvular flow variation; and 3) which variables independently predicted the variation of valvular flow quantification from 4-dimensional (4D) flow cardiac magnetic resonance (CMR) with automated retrospective valve tracking at multiple sites.
Background:
Automated retrospective valve tracking in 4D flow CMR allows consistent assessment of valvular flow through all intracardiac valves. However, due to the variance of CMR scanners and protocols, it remains uncertain if the published consistency holds for other clinical centers.
Methods:
Seven sites each retrospectively or prospectively selected 20 subjects who underwent whole heart 4D flow CMR (64 patients and 76 healthy volunteers; aged 32 years [range 24 to 48 years], 47% men, from 2014 to 2020), which was acquired with locally used CMR scanners (scanners from 3 vendors; 2 1.5-T and 5 3-T scanners) and protocols. Automated retrospective valve tracking was locally performed at each site to quantify the valvular flow and repeated by 1 central site. Interobserver agreement was evaluated with intraclass correlation coefficients (ICCs). Net forward volume (NFV) consistency among the valves was evaluated by calculating the intervalvular variation. Multiple regression analysis was performed to assess the predicting effect of local CMR scanners and protocols on the intervalvular inconsistency.
Results:
The interobserver analysis demonstrated strong-to-excellent agreement for NFV (ICC: 0.85 to 0.96) and moderate-to-excellent agreement for regurgitation fraction (ICC: 0.53 to 0.97) for all sites and valves. In addition, all observers established a low intervalvular variation (≤10.5%) in their analysis. The availability of 2 cine images per valve for valve tracking compared with 1 cine image predicted a decreasing variation in NFV among the 4 valves (beta = -1.3; p = 0.01).
Conclusions:
Independently of locally used CMR scanners and protocols, valvular flow quantification can be performed consistently with automated retrospective valve tracking in 4D flow CMR.
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