Purpose: To develop a free-breathing cardiac self-gated technique that provides cine images and slice profile-corrected T maps from a single acquisition.
Methods: Without breath-holding or electrocardiogram gating, data were acquired continuously on a 3T scanner using a golden-angle gradient-echo spiral pulse sequence, with an inversion RF pulse applied every 4 seconds. Flip angles of 3° and 15° were used for readouts after the first four and second four inversions. Self-gating cardiac triggers were extracted from heart image navigators, and respiratory motion was corrected by rigid registration on each heartbeat. Cine images were reconstructed from the steady-state portion of 15° readouts using a low-rank plus sparse reconstruction. The T maps were fit using a projection onto convex sets approach from images reconstructed using slice profile-corrected dictionary learning. This strategy was evaluated in a phantom and 14 human subjects.
Results: The self-gated signal demonstrated close agreement with the acquired electrocardiogram signal. The image quality for the proposed cine images and standard clinical balanced SSFP images were 4.31 (±0.50) and 4.65 (±0.30), respectively. The slice profile-corrected T values were similar to those of the inversion-recovery spin-echo technique in phantom, and had a higher global T value than that of MOLLI in human subjects.
Conclusions: Cine and T mapping using spiral acquisition with respiratory and cardiac self-gating successfully acquired T maps and cine images in a single acquisition without the need for electrocardiogram gating or breath-holding. This dual-excitation flip-angle approach provides a novel approach for measuring T while accounting for and slice profile effect on the apparent .
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http://dx.doi.org/10.1002/mrm.28675 | DOI Listing |
Int J Numer Method Biomed Eng
January 2025
Dipartimento di Scienze Chirurgiche Odontostomatologiche e Materno-Infantili, Università di Verona, Verona, Italy.
Accurate reconstruction of the right heart geometry and motion from time-resolved medical images is crucial for diagnostic enhancement and computational analysis of cardiac blood dynamics. Commonly used segmentation and/or reconstruction techniques, exclusively relying on short-axis cine-MRI, lack precision in critical regions of the right heart, such as the ventricular base and the outflow tract, due to its unique morphology and motion. Furthermore, the reconstruction procedure is time-consuming and necessitates significant manual intervention for generating computational domains.
View Article and Find Full Text PDFJACC Adv
December 2024
Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Background: Risk stratification for sudden cardiac death (SCD) in patients with nonischemic cardiomyopathy (NICM) remains challenging.
Objectives: This study aimed to investigate the impact of epicardial adipose tissue (EAT) on SCD in NICM patients.
Methods: Our study cohort included 173 consecutive patients (age 53 ± 14 years, 73% men) scheduled for primary prevention implantable cardioverter-defibrillators (ICDs) implantation who underwent preimplant cardiovascular magnetic resonance.
Comput Med Imaging Graph
December 2024
Medical Image and Data Analysis (MIDAS.lab), Department of Diagnostic and Interventional Radiology, University of Tuebingen, Tuebingen, Germany.
Cardiac Cine Magnetic Resonance Imaging (MRI) provides an accurate assessment of heart morphology and function in clinical practice. However, MRI requires long acquisition times, with recent deep learning-based methods showing great promise to accelerate imaging and enhance reconstruction quality. Existing networks exhibit some common limitations that constrain further acceleration possibilities, including single-domain learning, reliance on a single regularization term, and equal feature contribution.
View Article and Find Full Text PDFJACC Asia
December 2024
National Heart Research Institute Singapore, National Heart Centre Singapore, Singapore.
Background: Right ventricular restrictive physiology (RVRP) is a common occurrence in repaired tetralogy of Fallot (rTOF). The relationship of RVRP with biventricular blood flow components and kinetic energy (KE) from 4-dimensional (4D) flow cardiovascular magnetic resonance (CMR) is unclear.
Objectives: The purpose of this study was to investigate the association of 4D flow CMR parameters with RVRP in rTOF patients.
Eur Heart J Cardiovasc Imaging
January 2025
Vall d'Hebron Research Institute (VHIR), Barcelona, Spain.
Background: Cardiac magnetic resonance (CMR) is essential for diagnosing cardiomyopathy, serving as the gold standard for assessing heart chamber volumes and tissue characterization. Hemodynamic forces (HDF) analysis, a novel approach using standard cine CMR images, estimates energy exchange between the left ventricular (LV) wall and blood. While prior research has focused on peak or mean longitudinal HDF values, this study aims to investigate whether unsupervised clustering of HDF curves can identify clinically significant patterns and stratify cardiovascular risk in non-ischemic LV cardiomyopathy (NILVC).
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