Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition - Novel Developments and Applications in Flow MRI

Novel Developments and Applications in Flow MRI

Digital Poster

Contrast Mechanisms

Tuesday, 12 May 2026

Digital Posters Row F

09:15 - 10:10

Session Number: 465-02

No CME/CE Credit

Similar Sessions

This session focuses on advances in flow MRI techniques and novel clinical applications.

		465-02-001. Uncertainty quantification and active learning for efficient super-resolution 4D Flow MRI Nathan Blanchard, David Marlevi, Oliver Welin Odeback, Måns Magnusson, Hannes Waldetoft Karolinska Institutet, Solna, Sweden Impact: Through an uncertainty-aware network, this study highlights the potential of active learning strategies for super-resolution 4D Flow MRI, enabling efficient data sampling and training convergence with minimal training data.
		465-02-002. Robustness of 4D flow turbulence mapping across field strengths and scan parameters Twan Bakker, Tamara Bianchessi, Chiara Trenti, Sohaib Qazi, Federica Viola, Petter Dyverfeldt, Tino Ebbers Linköping University, Linköping, Sweden Impact: Scanner field strength does not appear to influence turbulent kinetic energy (TKE) in 4D Flow MRI measurements, enabling consistent analysis across multiple systems. A suboptimal VENC can affect maximum TKE measurements and should therefore be carefully chosen.
		465-02-003. Towards Artifact-Free Fast EPI-based Flow Imaging: Modified interleaved Flyback with VD-CAIPI Sampling Simon Blömer, Rüdiger Stirnberg, Philipp Ehses, Marten Veldmann, Tony Stoecker German Center for Neurodegenerative Diseases (DZNE e.V.), Bonn, Germany Impact: Modified interleaved Flyback with Variable Density (VD)-CAIPI sampling and temporal random walk reduces flow artifacts, enabling velocity quantification through readout gradients at EPI-equivalent acquisition times. This addresses major limitations of EPI-based 4D-flow MRI for hemodynamic imaging.
		465-02-004. Accurate Quantification of TKE using Deep Learning-Reconstructed Highly Undersampled 4D Flow MRI using FlowVN Sohaib Qazi, Tamara Bianchessi, Federica Viola, Chiara Trenti, Erik Ylipää, Tino Ebbers, Petter Dyverfeldt Linköping University, Linköping, Sweden Impact: Accurate reconstruction of turbulence kinetic energy (TKE) from highly accelerated 4D Flow MRI using a deep learning model (FlowVN) can substantially reduce scan and reconstruction times, facilitating the clinical use of 4D Flow MRI for cardiovascular assessment.
		465-02-005. Deep learning reconstruction of 4D Flow MRI using FlowVN: Generalization for Spatial and Spatio-Temporal Undersampling Sohaib Qazi, Tamara Bianchessi, Federica Viola, Chiara Trenti, Erik Ylipää, Tino Ebbers, Petter Dyverfeldt Linköping University, Linköping, Sweden Impact: Deep learning reconstruction with variational network FlowVN yields high-quality 4D Flow velocity and TKE images for multiple undersampling patterns and a wide range of undersampling factors, highlighting the potential of FlowVN for diverse utility in 4D Flow MRI.
		465-02-006. Advance Parcellation Toolbox for 4D FLOW (APT 4D FLOW): Software development and validation Yu-Chien Li, Mei-Yu Yeh, JOU-HSUAN Huang, Chia-Wei Lee, Yi-Ping Chao, Shyh-Jye Chen Chang Gung University, Taoyuan, Taiwan Impact: Our developed APT 4D FLOW toolbox provides a user-friendly and high-speed workflow for 4D FLOW analysis, producing wall stress and peak velocity measurements that are comparable to those obtained using the widely adopted cvi42 software.
		465-02-007. Bias-free nonlinear background phase correction for accurate and robust Phase Contrast Cine MRI Ana Beatriz Solana, Junjie Ma, Carolin Pirkl, Xinzeng Wang, Tim Sprenger GE Healthcare, Munich, Germany Impact: The proposed bias-free non linear background phase correction method enhances flow quantification accuracy in PC Cine MRI and it performs robustly across diverse acquisition and reconstruction conditions including low-SNR and denoised datasets.
		465-02-008. Is Aortic Shape Indicative of Bicuspid Aortic Valve Disease Status? Ethan Johnson, Anahita Najafi, Minyoung Kim, Jonathan Andrae, Andreas Harloff, Michael Markl, Bradley Allen, Kelly Jarvis Northwestern University, Chicago, United States of America Impact: This study will provide reference for how aortic shape relates to BAV disease status, including quantitative associations with primary clinical parameters. It may reveal new markers of disease state; alternatively, it would show which parameters do not indicate disease progression.
		465-02-009. Evaluating wall shear stress in rheumatic heart disease using 4D Flow MRI and computational fluid dynamics Thandiwe Zhanje, Stephen Jermy, Jordan Bougardt, Ernesta Meintjes, Ntobeko Ntusi Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa Impact: We extend the use of 4D Flow MRI to rheumatic heart disease (RHD), establishing baseline wall shear stress (WSS) values that may serve as prognostic markers and validate them through the use of computational fluid dynamics (CFD).
		465-02-010. Feasibility of Rapid 4D Flow MRI for LVOT Flow Assessment in HOCM Using Fast3D and PIQE Deep-Learning Reconstruction Kanae Miyake, Takeru Makiyama, Yuichiro Sano, Rimika Imai, Hajime Sagawa, Koji Itagaki, Hiroki Shiomi, Sachi Okuchi, Koji Fujimoto, Yuji Nakamoto Advanced Medical Imaging Research, Kyoto University Graduate School of Medicine, Kyoto, Japan Impact: Fast3D–accelerated 4D flow MRI with PIQE enables rapid and reliable quantification of LVOT hemodynamics in HOCM. This approach may facilitate broader clinical adoption of 4D flow imaging for comprehensive cardiac outflow assessment in routine MRI practice.
		465-02-011. Prospective Evaluation of Single Beat Cardiac Phase-Contrast MRI using Model-Based Deep Learning with Channel-Shift Chenwei Tang, Simon Thalén, Chi Zhang, Ana Beatriz Solana, Julio Oscanoa, Matthew Middione, Ali Syed, Shreyas Vasanawala, Daniel Ennis Stanford University, Stanford, United States of America Impact: We demonstrated feasibility of performing cardiac 2D PC-MRI in a single heartbeat and provided evaluations in prospectively acquired data. Single-beat PC-MRI could benefit clinical care of patients unable to perform breath-holds and patients with arrhythmia.
		465-02-012. Deep learning based gold-standard background offset correction of cardiovascular 4D flow MRI: Evaluation on a clinical cohort Federica Viola, Chiara Trenti, Mattias Ekstedt, Farkas Vanky, Peter Lundberg, Nils Dahlström, Patrik Nasr, Carl-Johan Carlhäll, Petter Dyverfeldt, Tino Ebbers Linköping University, Linköping, Sweden Impact: Our deep learning-based background phase offset correction method may facilitate broader implementation of 4D flow MRI in the clinical settings, due to its speed and superior performance compared to conventional approaches.
		465-02-013. Compressed Sensing 4D Flow MRI for Rapid and Reliable Evaluation of Ventricular Hemodynamics in Heart Failure Subtypes longjiang fang, Wenjing Zhao, Wenjuan Wang, Gaorui Zhang, Jiaxiang xin Weifang People's Hospital, Shandong Second Medical University, Weifang, China Impact: CS 4D Flow markedly shortens scan time while preserving consistency with conventional 4D Flow in evaluating left ventricular blood flow. It enhances feasibility in heart failure and delineates distinct hemodynamic patterns across subtypes, indicating potential value for diagnosis and prognosis.
		465-02-014. Simultaneous Quantitative Evaluation of Iliac Vasculature and Vascular Aging from a 4D Flow perspective Qiming Liu, Xinyu Wang, Chen Zhang, Qi Yang Beijing Chaoyang Hospital, Capital Medical University, beijing, China Impact: This pilot study validates an accelerated MRI technique for rapid, simultaneous iliac artery and vein assessment. It also reveals altered patterns of vascular aging in DVT patients, offering a new tool for pathophysiological insight.
		465-02-015. Evaluation of Dual-VENC 4D Flow MRI in the Portal Venous System: Comparison with Single-VENC Acquisition Ryota Hyodo, Ryota Horiguchi, Takashi Mizuno, Shunsuke Tajima, Mami Iima, Daniel Giese, Michaela Schmidt, Akihiro Manabe, Shinji Naganawa Nagoya University Graduate School of Medicine, Nagoya, Japan Impact: Dual-VENC 4D Flow MRI improves sensitivity to slow flow while preserving flow quantification consistency with single-VENC. This approach may enhance accuracy of biomarkers such as wall shear stress and facilitate comprehensive hemodynamic evaluation in portal venous imaging and interventional planning.
		465-02-016. Clinical Feasibility and Diagnostic Performance of PASL for Wrist Synovitis in Rheumatoid Arthritis: A Comparative Study with Satoshi Nakayama, Mitsue MIYAZAKI, Shimpei Yano, Naoko Mita, Seiko Shimizu, Vadim Malis, Won Bae, Hajime Kono, Asako Yamamoto Teikyo University School of Medicine, Tokyo, Japan Impact: PASL enables contrast-free, reproducible assessment of synovitis in RA. Its integration into standard MRI workflows enhances early treatment and monitoring, at the same time complementing non-contrast static evaluation of dynamic blood flow.