Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition

Cardiac Tissue Characterization

Digital Poster

Cardiovascular

Tuesday, 12 May 2026

Digital Posters Row B

08:20 - 09:15

Session Number: 461-01

No CME/CE Credit

Similar Sessions

Session on novel tissue characterization techniques showing initial feasibility and promise as well as cases with clinical utility

		461-01-001. Retrospective cardiac motion correction using interleaved 1H/23Na MRI Simon Konstandin, Laurent Ruck, Ilseok Lee, Snawar Hussain, Armin NAGEL Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany Impact: The presented technique improves sodium MRI for myocardial viability assessment by providing enhanced image quality and tissue differentiation. Binning strategies and deformable registration address limitations posed by low sodium concentrations and electrocardiogram gating, enabling more accurate myocardial tissue sodium quantification.
		461-01-002. Dark Blood LGE Imaging in Patients with Implanted Cardiac Devices using Inversion Recovery Unbalanced SSFP at 3T Tess Wallace, Manuel Morales, Bora Bozdag, Patrick Pierce, Nicole C.Y. Deng, Kelvin Chow, Xiaoming Bi, Warren Manning, Robert Edelman, Reza Nezafat MR R&D Collaborations, Siemens Medical Solutions USA, Inc., Chicago, United States of America Impact: Inversion recovery unbalanced steady-state free precession (IR-uSSFP) with high spectral bandwidth enables robust dark blood late gadolinium enhancement imaging in patients with implanted cardiac devices.
		461-01-003. Towards Imaging Microbubble Contrast Agents with MRI: Simulation, Phantom, and Pre-clinical Results Milo Commandeur, Ayda Arami, Elias Ylä-Herttuala, Yi Zhang, Qian Tao, Alexandru Cernicanu, Iida Räty, Maarit Pulkkinen, Hildo Lamb, Sebastian Weingärtner TU Delft, Delft, Netherlands Impact: Simulation and phantom demonstrate that susceptibility fields by microbubble contrast agents was detected in the transverse signal decay: $R_2$, $R_2^*$, $R_{1\rho}$. However, pre-clinical in vivo showed insufficient effect size compared to the physiological noise in cardiac imaging.
		461-01-004. Variability in T2 Measurements in Cardiac MR Mauricio Garrido, Brian Taylor The University of Texas MD Anderson Cancer Center, Houston, United States of America Impact: Quantitative T2 values were statistically different between vendors limiting the use of this measurement for clinical diagnosis of cardiac diseases. Careful standardization and harmonization of these measurements are critical as part of a clinical quality assurance program for cardiac MR.
		461-01-005. Automated Cardiac Inversion Time Prediction with Confidence Feedback for LGE Imaging Sai Gannavarapu, SUDHANYA Chatterjee, Subhashis Banerjee, Gaspar Delso, Sajith Rajamani, Justin Leonard, Uday Patil, Martin Janich, Dattesh Dayanand Shanbhag GE HealthCare, Bengaluru, India Impact: The study demonstrates an inbuilt mechanism to not only determine the inversion time for remote myocardium and blood pool nulling but provide feedback as well to user about algorithm confidence and any manual review or annotation needed in clinical practice.
		461-01-006. Sub-millimeter cardiac MR quantification using a novel single-shot Cartesian sampling Hongzhang Huang, Qinfang Miao, Zhenfeng Lyu, Peng Hu, Haikun Qi School of Biomedical Engineering, ShanghaiTech University, Shanghai, China Impact: The proposed high-resolution quantitative MR technique may achieve improved myocardial tissue characterization by detecting subtle pathological changes in the myocardium or papillary muscles.
		461-01-007. Simultaneous charactering myocardium tissue and wall motion at 5T magnetic field Junpu Hu, Rui Guo, Ne Yang, Qi Liu, Yichen Hu, Vlad Zaha, Tarique Hussain, Qing Zou University of Texas Southwestern Medical Center, Dallas, United States of America Impact: This optimized MyoFold sequence at 5T MRI overcomes SAR and B0 inhomogeneity challenges, enabling single-breath-hold simultaneous T1/T2/B1 mapping and cine imaging. Validated in humans, it delivers accurate ejection fractions and tissue characterization, streamlining high-field cardiac assessments.
		461-01-008. Towards Consistent Myocardial T1 and T2 Mapping: A Phantom-Based Harmonization Method Utsav Shrestha, Julius Heidenreich, Jeff Kammerman, David Rutkowski, David Harris, Diego Hernando, Jean Brittain, Scott Reeder University of Wisconsin - Madison, Madison, United States of America Impact: Improved cardiac T1/T2 mapping inter-method reproducibility enables enhanced quantitative comparison across techniques, protocols, and platforms. Harmonization increases confidence in myocardial tissue characterization, supports multi-center studies, and facilitates broader clinical adoption of quantitative relaxometry as a robust biomarker of cardiac disease.
		461-01-009. Accelerated motion-corrected 3D whole-heart T2 mapping at 0.55 T Dabne Barrera, Rafael De La Sotta, Carlos Castillo-Passi, Karl Kunze, Rene Botnar, Claudia Prieto Millennium Institute for Intelligent Healthcare Engineering - iHEALTH, Santiago, Chile Impact: The proposed technique demonstrates potential of low-field MRI by enabling rapid, isotropic high-resolution characterization of myocardial tissue in 3D at 0.55 T, making cardiac-imaging solutions more accessible. This approach could reduce scan times and improve diagnostic capabilities in clinical practice.
		461-01-010. Cardiac Phase-Resolved Simultaneous T1 and T2* Mapping in Rodent Hearts Shahriar Shalikar, Jose Raul Velasquez Vides, Mostafa Berangi, Alexis Jouenne, Yuheng Huang, Thomas Gladytz, Jason Millward, Hsin-Jung Yang, Thoralf Niendorf, Frank Kober, Min-Chi Ku Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Ultrahigh Field Facility (B.U.F.F.), Berlin, Germany Impact: Simultaneous myocardial T₁-T₂* mapping enables time-efficient and motion-robust multi-parametric assessment in preclinical models. It provides a technical foundation for research into myocardial changes in disease, facilitating better understanding of cardiac pathophysiology and improved evaluation of therapeutic interventions.
		461-01-011. Quantitative Evaluation of Myocardial T1ρ Using Non-Contrast Multitasking MRI in Acute and Chronic Porcine Infarction Models Haoran Li, Xinheng Zhang, Hsu-Lei Lee, João Pedro Torres Neiva Rodrigues, Leon Riehakainen, Yibin Xie, Ivan Cokic, Hsin-Jung Yang, Suvai Gunasekaran Cedars-Sinai Medical Center, Los Angeles, United States of America Impact: This non-contrast MT T1/T1ρ technique enables simultaneous quantification of T1 and T1ρ relaxation, facilitating detection fibrosis without gadolinium. It may improve cardiac tissue characterization and benefit patients with renal dysfunction or contraindications to contrast-enhanced MRI.
		461-01-012. Enhanced phase-sensitive reconstruction for cardiac late gadolinium enhancement imaging using deep learning-based algorithm Junjie Ma, Xinzeng Wang, Michael Vinsky, Daming Shen, Melany Atkins, Martin Janich GE HealthCare., NY, United States of America Impact: Replacing conventional low-pass filter with a deep learning-based phase correction algorithm (DLPC) in single-shot PS LGE imaging enhances edge sharpness and noise suppression, particularly at challenging tissue interfaces, without compromising scar visualization—offering a promising enhancement for cardiac LGE imaging.
		461-01-013. A mixed single-echo and multi-echo MyoFold* for simultaneous quantification of myocardial T1, T2, T2, and wall motion Rui Guo, Bowei Liu, Yifei Jiang, Peng Wu, Guozhao Dong, Yingwei Fan, JingJing Xiao, Haiying Ding, Xiaoying Tang Beijing Institute of Technology, Beijing, China Impact:* The proposed MyoFold* sequence offers a comprehensive cardiac examination with co-registered T₁/T₂/T₂^* tissue properties and wall-motion quantification, achieving performance comparable to conventional single-task techniques while delivering a four-fold reduction in imaging time.
		461-01-014. Deep Learning–Accelerated MOLLI T1 Mapping with Variable-Density Undersampling Junjie Ma, Gaspar Delso, Haonan Wang, Sagar Mandava, Xucheng Zhu, Fara Nikbeh, Dan Rettmann, Michael Carl, Martin Janich GE HealthCare, San Ramon, United States of America Impact: The deep learning-based acceleration technique (Sonic DL, GE HealthCare) enables improved spatial resolution for MOLLI T1 mapping while preserving temporal resolution and quantification accuracy. This advancement would facilitate more precise myocardial tissue characterization and enhance the reliability of ECV quantification.
		461-01-015. Multiparametric CMR Characterization of Exercise-Induced Cardiac Remodeling in Amateur Marathon Runners Xinqiao Lian, Wei Huai, Xinyu Wang, Chengduo Zhang, Xiaoli Mo, Dong Wang, Jing An, Kelvin Chow, Minjie Lu Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China Impact: This study enhances insight into exercise-induced cardiac remodeling, identifying imaging markers that help clinicians distinguish physiologic adaptation from early pathology, guide individualized monitoring of amateur athletes, and promote safe endurance training strategies for cardiovascular health.
		461-01-016. Supervised DE-MRI Infarct Segmentation with Novel Synthetic Data Generation via Simulation and Conditional GAN Omar Abdelbar, Hana Hesham, Omar Othman, Khaled Badr, Mishkat Habib, Tamer Basha, Ahmed Gharib, Ahmed Abdelfadeel, Khaled Abd-Elmoniem Systems and Biomedical Engineering Department, Faculty of Engineering, Cairo University, Giza, Egypt Impact: GAN-based DE-MRI infarct segmentation framework combining nnU-Net ROI localization, a lesion-aware mathematical simulator, modified Pix2Pix and mask-guided CycleGAN synthesis, and an Attention-Residual U-Net overcomes annotation scarcity and class imbalance, boosting infarct and no-reflow Dice and enabling robust, reproducible clinical benchmarking.