Table 1.
Clinical information summary of the included studies in this systematic review assessing 4D-flow in MVR
| First author | Year | Aim of the study | Study type | Population cohort | Mean age (years) | Gender (Male%) | Reproducibility data | MVR evaluation method | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Echo | 2D-PCStandard | Volumetric | 4D-flowAIM | 4D-flowjet | ||||||||
| Fidock et al. [20] | 2021 | Assess the consistency and reproducibility of various MVR quantification methods using CMR across different etiologies | Prospective | 35 patients (unclassified cardiac disease) | 66 ± 11 | 66 | ✓ | ✗ | ✓ | ✓ | ✓ | ✓ |
| Mills et al. [17] | 2021 | Assess the possibility of obtaining 4D-flow CMR in AF patients and investigate the consistency and reliability of RVT in the assessment of aortic and mitral valvular flow in AF patients versus healthy controls | Prospective | 8 AF/10 healthy | 62 ± 13/41 ± 20 | 88/70 | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| Gupta et al. [18] | 2021 | Evaluate LA KE in HCM patients using 4D-flow CMR and examine coupling correlations with MVR and LVOT obstruction | Retrospective | 29 HCM | 55.25 ± 9.95 | 55 | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| Juffermans et al. [25] | 2021 | Assess interobserver agreement, valvular flow variation, and which variables independently predicted the variance of valvular flow quantification at multiple sites using 4D-flow CMR with automated RVT | Retrospective/ Prospective | 64 patients with cardiac disease/76 healthy (20 subjects per site, 7 sites) | 32 (24–48) | 47 | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| Spampinato et al. [16] | 2021 | Investigate the clinical efficacy of cine guided valve segmentation of 4D-flow CMR in MVR evaluation in mitral valve prolapse compared to normal routine CMR and TTE | Retrospective | 54 mitral valve prolapse/6 healthy | 58 ± 14/31 ± 5 | 78/ 83 | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ |
| Blanken et al. [22] | 2020 | Assess the accuracy of semiautomated flow tracking against semiautomated RVT in quantifying MVR using 4D-flow CMR data in patients with mild, moderate, or severe MVR | Retrospective | 30 MVR | 61 ± 10 | 70 | ✓ | ✓ | ✓ | ✗ | ✓ | ✓ |
| Jacobs K. et al.[19] | 2020 | Direct evaluation of MVR jets using 4D-flow CMR versus volumetric techniques and as an internal validation approach against annular inflow method | Retrospective | 18 CHD with MVR | 12.6 ± 7.8 | 56 | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| Morichi et al. [12] | 2020 | Determine the effect of annuloplasty in mitral valve repair on LV vortex flow and aortic outflow patterns, and flow energy loss | Prospective | 14 MVR/ 20 healthy | 64 ± 12/NS | 71/ NS | ✗ | ✓ | ✗ | ✗ | ✓ | ✗ |
| Pruijssen et al. [8] | 2020 | Evaluate relationships between hemodynamic parameters in HCM patients using 4D-flow CMR | Prospective | 13 HCM/11 healthy | 51 ± 16/54 ± 15 | 77/ 73 | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| Kamphuis et al. [26] | 2019 | Compare 4D-flow CMR with automated RVT to manual RVT in acquired or CHD | Retrospective | 114 patients (81 CHD)/46 healthy | 17 (13–49)/28 (22–36) | 55/ 59 | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ |
| Arvidsson et al. [32] | 2018 | Investigate hemodynamic forces change in HF patients with LV dyssynchrony using 4D-flow CMR | Retrospective | 31 HF and LV dyssynchrony/39 healthy | 67 (50–87)/27 (18–63) | 77/ 46 | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| Feneis et al. [23] | 2018 | Determine the consistency and reproducibility of 4D-flow CMR in quantifying MVR in comparison with 2D flow CMR | Retrospective | 21 patients | 54.1 (21–83) | 48 | ✓ | ✗ | ✓ | ✗ | ✓ | ✓ |
| Al-Wakeel et al. [41] | 2015 | Evaluate LV blood flow dynamics as measured by KE in MVR patients before and after mitral valve repair surgery | Prospective | 6 mitral valve repair/4 biological valve replacement/7 healthy | 56 ± 9/27 ± 7 | 70/ NS | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| Calkoen et al. [21] | 2015 | Investigate flow patterns in patients with repaired AVSD and healthy controls | Prospective | 32 AVSD/30 healthy | 25 ± 14/26 ± 12 | 28/46 | ✗ | ✗ | ✗ | ✗ | ✓ | ✗ |
| Calkoen et al. [11] | 2015 | Determine the effect of LAVV anomaly on vortex ring generation in AVSD patients | Prospective | 32 AVSD/30 healthy | 25 ± 14/26 ± 12 | 28/46 | ✓ | ✗ | ✓ | ✗ | ✓ | ✗ |
| Calkoen et al. [9] | 2015 | Assess LAVV blood flow and optimize LV inflow quantification in repaired AVSD patients and healthy controls | Prospective | 25 AVSD/25 healthy | 22 (16–31)/17 [12–28] | 28/40 | ✗ | ✓ | ✓ | ✗ | ✓ | ✗ |
| Calkoen et al. [10] | 2015 | Quantifying LAVV regurgitant jets in corrected AVSD patients using 4D-flow CMR | Prospective | 32 AVSD | 26 ± 12 | 28 | ✗ | ✓ | ✓ | ✗ | ✓ | ✗ |
| Hsiao et al. [24] | 2015 | Evaluate the possibility of measuring net and regurgitant flow volume using 4D-flow CMR across heart valves | Retrospective | 34 pediatric CHD | 6.9 (0.8–15) | 56 | ✗ | ✗ | ✓ | ✓ | ✓ | ✗ |
The mitral valve regurgitation (MVR) evaluation methods are: (1) echocardiography (Echo), (2) 2D-PC CMR gold standard (2D-PCStandrad), (3) volumetric method, (4) 4D-flowAIM, and (5) 4D-flowjet. CMR, cardiovascular magnetic resonance imaging; AF, atrial fibrillation; RVT, retrospective valve tracking; LA, left atrium; KE, kinetic energy; HCM, hypertrophic cardiomyopathy; LVOT, left ventricular outflow track; TTE, transthoracic echocardiography; CHD, congenital heart disease; HF, heart failure; LV, left ventricle; AVSD, Atrioventricular Septal Defect; LAVV, Left Atrial Ventricular Valve.