Aug 2026· Journal of Cardiovascular Magnetic Resonance· pp.
102789
· 0 citations· 63 references
Medicine
TL;DR
This document addresses the needs for an "ideal" post-processing software for 4D flow in patients with CHD and provides information on general requirements, velocity encoding, offset and aliasing correction, visualization, segmentation and reconstruction as well as output data.
Abstract
The large majority of patients with congenital heart disease (CHD) survive into adulthood in the modern era of surgical advancements. However, patients require life-long follow-up and non-invasive imaging is crucial for diagnostic and therapeutic purposes. Cardiovascular magnetic resonance (CMR) plays a major role in patients with CHD as it is a non-invasive and ionizing radiation free imaging tool which overcomes the technical limitations of echocardiography. 4D flow is an evolving technique for flow quantification allowing improved CMR exam quality and reduced scan time. However, comprehensive postprocessing of hemodynamics in CHD may be demanding. This document addresses the needs for an "ideal" post-processing software for 4D flow in patients with CHD. It provides information on general requirements, velocity encoding, offset and aliasing correction, visualization, segmentation and reconstruction as well as output data. This document aims to support stakeholders in the field to develop solutions for improved 4D flow post-processing and visualization in CHD patients and thus improve the accuracy and efficiency of patient care.
AIMS
Cardiac MRI is central to evaluating ventricular function and hemodynamics in pediatric congenital heart disease (CHD). Conventional two-dimensional phase-contrast (2D-PC) imaging is challenged by fixed planes, operator dependence, and multiple breath-holds, where four-dimensional flow (4DF) MRI overcomes these challenges. This study compares accelerated whole heart 4D Flow (WH-4DF) MRI with 2D-PC and volumetric measurements in routine clinical follow up of pediatric CHD and highlights its applicability.
METHODS AND RESULTS
For this prospective study seventy-one consecutive pediatric patients (median age 14 ± 2.4 years; 49 male) with surgically corrected CHD underwent both 2D-PC and accelerated WH-4DF MRI. Planning and acquisition times and overall success rate were recorded. Flow, velocity and volumetric measurements were compared using Bland-Altman analysis, orthogonal regression, and intraclass correlation coefficients. WH-4DF showed excellent agreement with 2D-PC and short-axis volumetry for aortic, pulmonary, and ventricular stroke volumes (mean differences <5%). Mean planning and acquisition time for WH-4DF was 10.3minutes (SD 1.1), where planning and acquisition time of 2D-PC was 11.2minutes (SD 6.25). Aliasing was observed in 11% of the WH-4DF acquisitions but did not compromise interpretability.
CONCLUSIONS
Accelerated WH-4DF MRI is clinically robust and broadly applicable across CHD, including complex postoperative anatomies. It provides comparable numbers to 2D-PC, reproducible, and time-efficient flow quantification with superior coverage and reduced operator dependence. A single WH-4DF scan can replace multiple 2D-PC acquisitions with comparable results and may enhance assessment of regurgitant flow. These features underscore its potential role in routine clinical practice and in advancing our understanding of disease processes.
J. van Schuppen, A. E. van der Hulst, R. A. P. Takx et al.· Journal of Cardiovascular Ma...· 0 citations
Volumetric real-time MRI is feasible for the guidance of invasive procedures such as right-heart catheterization at 0.55T and offers flexible real-time re-slicing, volumetric 3D visualization, and the potential for improved device monitoring.
Prakash Kumar, R. Ramasawmy, A. Javed et al.· Journal of Cardiovascular Ma...· 0 citations
Abstract Aims 4D flow cardiovascular magnetic resonance (CMR) offers a comprehensive haemodynamic assessment but is often limited by long acquisition times and complex post-processing. The magnitude images derived from 4D flow sequences contain time-resolved 3D anatomical information. We aimed to validate the anatomical accuracy of these images against standard cine imaging and develop an artificial intelligence (AI) model for automated segmentation to facilitate analysis. Methods and results Forty patients prospectively identified from the PREFER-CMR registry underwent CMR, including standard cine stacks and 4D flow. The study consisted of two stages. In Stage 1, manual segmentation of the cardiac chambers and great vessels was performed on 4D flow magnitude images. These were validated against standard cine volumetrics (LV/RV) and normative reference values (LA/RA). In Stage 2, a fully automated deep learning algorithm was trained and validated. Advanced haemodynamic metrics were derived using both manual and AI segmentations to assess agreement. The study cohort (n = 40) had a mean age of 69.0 ± 17.2 years, and 60.0% were male. In Stage 1, 4D flow magnitude analysis demonstrated excellent correlations with cine measurements for LV end-diastolic volume (ρ = 0.98, ICC = 0.99) and RV end-diastolic volume (ρ = 0.97, ICC = 0.98). In Stage 2, the AI model achieved excellent segmentation performance (mean Dice similarity coefficient 0.88). Comparisons of haemodynamic metrics derived from AI vs. manual contours showed strong agreement (r ≥ 0.88 for all peak metrics). Conclusion 4D flow magnitude imaging provides accurate volumetrics. Deep learning automation of this process is feasible, allowing for rapid, comprehensive assessment of cardiac structure, function, and advanced energetics.
Alexander Gall, C. Grafton-Clarke, Rui Li et al.· European heart journal. Imag...· 0 citations
Aortic stenosis (AS) is the most common degenerative valvular disease in elderly patients and is linked to high morbidity and mortality. Accurate diagnosis and risk stratification are critical for effective management. Transthoracic echocardiography is the standard diagnostic tool, but its reliance on flow-dependent parameters can lead to inconsistent grading, especially in low-flow, low-gradient, or normal-flow, low-gradient AS. Advanced echocardiographic methods, such as 3D imaging, stress echocardiography, and Doppler indices, such as the mean gradient-to-effective orifice area ratio, improve the evaluation of AS severity and assist in clinical decision-making. Computed tomography provides a flow-independent evaluation of AS. It uses noncontrast calcium scoring with sex-specific thresholds, along with contrast-enhanced angiography, for detailed anatomical assessment. These modalities are essential for procedural planning, particularly for transcatheter aortic valve replacement. Cardiac magnetic resonance (CMR) provides additional prognostic information. It quantifies myocardial remodeling and fibrosis, which are associated with outcomes and recovery potential. Emerging technologies are expanding diagnostic capabilities in AS. Examples include 18F-sodium fluoride positron emission tomography for detecting microcalcification, artificial intelligence-based ECG and echocardiography for early diagnosis, and 4D flow CMR. Integration of echocardiography, computed tomography, CMR, and emerging positron emission tomography and artificial intelligence-based approaches can help address diagnostic uncertainty. This integration helps refine AS subtype classification and inform individualized intervention strategies.
H. Itani, M. Moumneh, A. Zayed et al.· Cardiology in Review· 0 citations
BACKGROUND
Ferumoxytol is used off-label as a contrast agent for cardiovascular magnetic resonance (CMR). However, the dose-response relationship between ferumoxytol, longitudinal relaxation, and image quality in pediatric and young patients remains unclear.
OBJECTIVE
To evaluate the effects of sequential ferumoxytol dose escalation on three-dimensional (3D) whole-heart (WH) image quality and blood-pool nulling inversion time (TI), a physiologic surrogate of post-contrast T1 shortening.
MATERIALS AND METHODS
In this prospective study, 45 patients with congenital heart disease underwent ferumoxytol-enhanced 3D WH CMR at 1.5 T using sequential dose regimens (1 mg/kg→2 mg/kg or 2 mg/kg→3 mg/kg). Right coronary artery (RCA) image quality and visible length, contrast-to-noise ratio (CNR), and image quality of the cardiac chambers and great vessels, as well as diagnostic completeness, were assessed. Blood-pool and myocardial nulling TI were measured using Look-Locker sequences. Baseline-adjusted change-score regression was the primary analysis, with mixed-effects ANCOVA performed to model TI behavior while accounting for repeated within-patient measurements.
RESULTS
No significant differences were observed in CNR, RCA length, image quality, or diagnostic completeness between all doses (all P>0.05). Myocardial and blood-pool nulling TI shortened significantly with dose escalation (P≤0.02). Change in blood-pool TI after the second dose was strongly predicted by TI after the first dose (β=-0.63, P<0.001), whereas starting dose (1 mg/kg or 2 mg/kg) was not associated with TI change (P=0.70). At 1 mg/kg, prolonged myocardial nulling TI may encroach upon the systolic rest period.
CONCLUSIONS
Ferumoxytol-enhanced 3D WH imaging provides diagnostic-quality assessment across 1-3 mg/kg dosing. Dose-dependent TI shortening follows a nonlinear, saturating pattern, supporting optimized low-dose protocols.
Sukran Erdem, Tarique Hussain, Aya El Jerbi et al.· Pediatric Radiology· 1 citation
Fetal cardiac MRI (fCMR) provides valuable diagnostic information complementary to echocardiography, particularly for complex congenital heart disease (CHD). Dynamic cine imaging captures cardiac motion essential for assessment of cardiac function; however, the reconstruction of 3D+time cine volumes from 2D+time acquired slices remains challenging due to unpredictable fetal motion and the absence of automated and robust processing tools suitable for clinical deployment. We present the SPARC pipeline (Slice-to-volume Pipeline for Automated Reconstruction of gated 3D+time fetal Cardiac MRI) which combines physics-informed slice-to-volume reconstruction (SVR) of Doppler ultrasound (DUS) gated stacks of slices, assisted by deep learning (DL) models for thoracic segmentation and anatomical reorientation. The proposed SVR algorithm achieves a tenfold reduction in reconstruction time relative to existing frame-wise approaches ($4.8 \pm 1.0$ vs $49.0 \pm 14.1$ min, $p<0.0001$) while improving the reconstruction quality. Thoracic segmentation performance using ensemble aggregation exceeded inter-rater agreement (Dice $84.7 \pm 3.9\%$ vs $81.4 \pm 7.7\%$, $p<0.05$), while anatomical reorientation achieved a success rate of $90.1\%$. End-to-end evaluation on a large held-out clinical cohort ($n = 121$) demonstrated fully automatic processing in $82.6\%$ of cases with a mean runtime of $7.1 \pm 1.3$ min, compatible with clinical deployment. The complete SPARC pipeline is publicly available as a Docker container https://hub.docker.com/r/aboutill/sparc and is currently deployed at our institution as a clinical research tool.
Arnaud Boutillon, Naomi Clarke, Tomás Woodgate et al.· 0 citations