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A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 6076

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Special Issue Editors

Dr. Qing Zou

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Guest Editor

Division of Cardiology, Department of Pediatrics, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
Interests: advanced cardiac imaging for congenital heart diseases; coronary imaging; translational cardiology based on advanced cardiac imaging

Prof. Dr. Gerald Greil

E-Mail Website
Guest Editor

Special Issue Information

Dear Colleagues,

Advanced cardiac MRI is crucial for managing both congenital and acquired heart diseases, prized for its lack of radiation and superior soft-tissue imaging capabilities. However, it faces challenges such as prolonged scan durations and image artifacts in clinical settings. This Special Issue is dedicated to showcasing cutting-edge methods in cardiac MRI acquisition and processing, bridging the gap between fundamental research and clinical application. Topics to be explored include, but are not limited to, the following:

Innovative cardiac MRI reconstruction techniques, focusing on the development and clinical integration of AI-driven algorithms.
Innovative cardiac MRI post-processing applications, including denoising, segmentation, and super-resolution.
Techniques and applications of novel fast imaging acquisition methods.
Advanced techniques and applications for first-pass perfusion cardiac MRI.
Techniques and applications in non-contrast parametric mapping.
Development of new imaging biomarkers.
Development and applications of novel cardiac MRI sequences, such as 4D flow sequences.
Novel clinical practices of cardiac MRI.
Development and applications of non-breath-hold and non-ECG-gated cardiac MR techniques.
Novel contrast agents for cardiac MRI.

This Special Issue aims to highlight significant advancements and applications that improve diagnostic accuracy and patient outcomes in cardiac MRI.

Dr. Qing Zou
Prof. Dr. Gerald Greil
Guest Editors

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Keywords

cardiac MRI
post-processing
deep learning
fast imaging
novel sequences

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Published Papers (4 papers)

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Research

17 pages, 17994 KB

Open AccessArticle

Efficient Interleaved Multi-Band Outer Volume Suppression for Highly Accelerated Simultaneous Multi-Slice Imaging of the Heart

by Ayda Arami, Omer Burak Demirel, Toygan Kilic, Steen Moeller, Yidong Zhao, Yi Zhang, Qian Tao, Hildo J. Lamb, Mehmet Akçakaya and Sebastian Weingärtner

Bioengineering 2026, 13(3), 286; https://doi.org/10.3390/bioengineering13030286 - 28 Feb 2026

Viewed by 684

Abstract

In this work, we aimed to develop and evaluate multi-band outer volume suppression pulses for increased acceleration rates in simultaneous multi-slice accelerated cardiac MRI. MB-OVS pulses were constructed from a multi-band combination of two slab-selective saturation pulses and tested for various pulse shapes using Bloch simulation and phantom experiment. The MB-OVS pulses were interleaved between imaging pulses to ensure homogeneous suppression throughout the cardiac cycle/imaging window in vivo. Simultaneous multi-slice (SMS) CINE and first-pass myocardial perfusion scans with and without the proposed MB-OVS pulses were compared in terms of residual artifacts at high acceleration rates. Among the tested pulses, both Bloch simulation and phantom experiments showed that amplitude-optimized sinc pulses provided the best trade-off in suppression efficiency, the required

B_{1}^{+}

, SAR, and slab profile. CINE imaging with 5-fold SMS-OVS acceleration significantly outperformed imaging without MB-OVS, maintaining leakage-free image quality, even when adding 2-fold in-plane acceleration. SMS-OVS also enabled perfusion imaging in 9 slices with 1.7 × 1.7 mm² resolution, achieving a 16-fold spatial-only acceleration while ensuring accurate contrast dynamics without leakage artifacts. Interleaved MB-OVS modules enabled thorough leakage artifact suppression in cardiac SMS-accelerated CINE and perfusion imaging, particularly at high acceleration rates. The proposed approach may be promising for unlocking further acceleration potential of SMS in cardiac imaging. Full article

(This article belongs to the Special Issue Recent Advances in Cardiac MRI)

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16 pages, 4337 KB

Open AccessArticle

4D Flow MRI at 0.6 T—Self-Gating Versus Camera-Based Respiratory Binning

by Sébastien Emery, Luuk Jacobs, Jacob Malich, Gloria Wolkerstorfer, Yiming Dong, Ece Ercan, Jouke Smink, Martijn Nagtegaal and Sebastian Kozerke

Bioengineering 2026, 13(3), 282; https://doi.org/10.3390/bioengineering13030282 - 27 Feb 2026

Viewed by 702

Abstract

Four-dimensional (4D) flow MRI enables the comprehensive assessment of cardiovascular hemodynamics. To compensate for respiratory motion, self-gating strategies are typically used and perform reliably at clinical field strengths. With the recent push towards field strengths below 1 Tesla, these strategies need to be re-evaluated given the reduced signal-to-noise ratio (SNR). Camera-based, contactless respiratory monitoring offers an attractive alternative to self-gating, as it is unaffected by imaging. This study compared respiratory self-gating (SG) and camera-based (VE) binning for phase-contrast gradient-echo (PC-GRE) 4D flow MRI at 0.6 T. Data were acquired from twenty healthy subjects (age: 32.8 ± 12.6 years) using a pseudo-spiral undersampled Cartesian four-point velocity encoding scheme. Reconstructions were performed with FlowMRI-Net for the end-expiratory state using either SG or VE binning. SG and VE showed strong agreement, with cross-correlation coefficients of ~0.87, accuracies of ~0.87, and F1-scores of ~0.9. Velocity analysis revealed high concordance (R² = 0.99; RMSE = 3.9 cm/s), with mean differences in peak velocity of 1.25 ± 2.36 cm/s. In this feasibility study, respiratory self-gating and camera-based binning yielded similar hemodynamic parameters from PC-GRE 4D flow MRI at 0.6 T, with the camera-based approach being independent of MR image SNR. Full article

(This article belongs to the Special Issue Recent Advances in Cardiac MRI)

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18 pages, 2843 KB

Open AccessArticle

Feasibility of Golden Angle Spiral Real-Time Phase Contrast MRI at 0.55T: A Single-Center Prospective Study

by Salman Pervaiz, Chong Chen, Yingmin Liu, Katherine Binzel, Kelvin Chow, Rizwan Ahmad, Yuchi Han, Orlando P. Simonetti, Ning Jin and Juliet Varghese

Bioengineering 2026, 13(2), 166; https://doi.org/10.3390/bioengineering13020166 - 29 Jan 2026

Viewed by 838

Abstract

Background: Real-time phase-contrast magnetic resonance (RT-PCMR) imaging allows free-breathing assessment of blood flow across cardiac valves and vessels. However, the feasibility of free-breathing RT-PCMR on a mid-field (0.55T) MRI system has yet to be established. Aim: The primary objective of this study was to implement a RT-PCMR sequence using a dual-density golden-angle spiral readout with SENSE-based compressed sensing (CS) reconstruction on a 0.55T MRI system. The secondary objective was to evaluate the feasibility of this approach in an adult cohort comprising healthy volunteers and patients with cardiovascular disease. Materials and Methods: Data from 33 participants were included in the flow quantification analysis (healthy volunteers: n = 17, 9 females, mean age 30.4 ± 14.6 years; patients: n = 16, 11 females, mean age 45.9 ± 17.4 years), with breath-held (BH) segmented Cartesian PCMR used as the reference standard. Results: In volunteers, RT-PCMR showed good agreement for net flow, peak flow rate, and pulmonary–systemic flow ratio (Qp/Qs), without significant bias (p > 0.05) and slightly underestimated peak velocity [7.9% in the aorta and 8.6% in the main pulmonary artery (MPA)]. In patients, RT-PCMR slightly underestimated peak flow rate (aorta, 6.2%; MPA; 4.6%) and peak velocity (aorta,12.7%; MPA, 10.4%). A sub-analysis of six patients scanned at both 0.55T and 3T showed close agreement between field strengths. Conclusions: These results demonstrate the feasibility of our RT-PCMR sequence on a commercial 0.55T system. Full article

(This article belongs to the Special Issue Recent Advances in Cardiac MRI)

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17 pages, 8549 KB

Open AccessArticle

A Fully Automated Analysis Pipeline for 4D Flow MRI in the Aorta

by Ethan M. I. Johnson, Haben Berhane, Elizabeth Weiss, Kelly Jarvis, Aparna Sodhi, Kai Yang, Joshua D. Robinson, Cynthia K. Rigsby, Bradley D. Allen and Michael Markl

Bioengineering 2025, 12(8), 807; https://doi.org/10.3390/bioengineering12080807 - 27 Jul 2025

Cited by 1 | Viewed by 3004

Abstract

Four-dimensional (4D) flow MRI has shown promise for the assessment of aortic hemodynamics. However, data analysis traditionally requires manual and time-consuming human input at several stages. This limits reproducibility and affects analysis workflows, such that large-cohort 4D flow studies are lacking. Here, a fully automated artificial intelligence (AI) 4D flow analysis pipeline was developed and evaluated in a cohort of over 350 subjects. The 4D flow MRI analysis pipeline integrated a series of previously developed and validated deep learning networks, which replaced traditionally manual processing tasks (background-phase correction, noise masking, velocity anti-aliasing, aorta 3D segmentation). Hemodynamic parameters (global aortic pulse wave velocity (PWV), peak velocity, flow energetics) were automatically quantified. The pipeline was evaluated in a heterogeneous single-center cohort of 379 subjects (age = 43.5 ± 18.6 years, 118 female) who underwent 4D flow MRI of the thoracic aorta (n = 147 healthy controls, n = 147 patients with a bicuspid aortic valve [BAV], n = 10 with mechanical valve prostheses, n = 75 pediatric patients with hereditary aortic disease). Pipeline performance with BAV and control data was evaluated by comparing to manual analysis performed by two human observers. A fully automated 4D flow pipeline analysis was successfully performed in 365 of 379 patients (96%). Pipeline-based quantification of aortic hemodynamics was closely correlated with manual analysis results (peak velocity: r = 1.00, p < 0.001; PWV: r = 0.99, p < 0.001; flow energetics: r = 0.99, p < 0.001; overall r ≥ 0.99, p < 0.001). Bland–Altman analysis showed close agreement for all hemodynamic parameters (bias 1–3%, limits of agreement 6–22%). Notably, limits of agreement between different human observers’ quantifications were moderate (4–20%). In addition, the pipeline 4D flow analysis closely reproduced hemodynamic differences between age-matched adult BAV patients and controls (median peak velocity: 1.74 m/s [automated] or 1.76 m/s [manual] BAV vs. 1.31 [auto.] vs. 1.29 [manu.] controls, p < 0.005; PWV: 6.4–6.6 m/s all groups, any processing [no significant differences]; kinetic energy: 4.9 μJ [auto.] or 5.0 μJ [manu.] BAV vs. 3.1 μJ [both] control, p < 0.005). This study presents a framework for the complete automation of quantitative 4D flow MRI data processing with a failure rate of less than 5%, offering improved measurement reliability in quantitative 4D flow MRI. Future studies are warranted to reduced failure rates and evaluate pipeline performance across multiple centers. Full article

(This article belongs to the Special Issue Recent Advances in Cardiac MRI)

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