Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1354-1366 |
| Number of pages | 13 |
| Journal | JACC: Cardiovascular Imaging |
| Volume | 14 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Jul 2021 |
Bibliographical note
Funding Information:Drs. Zhang and Zhong were supported by the National Medical Research Council (NMRC/OFIRG/0018/2016; NMRC/BnB/0017/2015; MOH-000358; MOH-000351) and SingHealth Duke-NUS Academic Medicine Research Grants (AM/TP015/2018 (SRDUKAMR1814); AM/TP032/2020 (SRDUKAMR2032). All other authors have reported that they have no relationships relevant to the content of this paper to disclose.
Publisher Copyright:
© 2021 American College of Cardiology Foundation
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