Objective: To explore the feasibility of single-breath-hold compressed sensing real-time cine imaging (CS-cine) in the assessment of ventricular function and left ventricular (LV) strain.
Methods: A total of 70 subjects were enrolled prospectively, and all subjects underwent cardiac magnetic resonance imaging (cardiac MRI) using both the standard steady-state free procession cine (sta-cine) acquisition and a prototype CS-cine sequence. For both CS-cine and sta-cine imaging, continuous short-axis cine images were acquired from the base to the apex to cover the entire left ventricle, and long-axis cine images including two-, three-, and four-chamber views were also acquired. The scanning range, number of slices, slice thickness and intervals were kept identical for the two cine images of the same participant. Subjective evaluation of the image quality was performed on all cine images. For both sequences, the conventional function parameters of the left and the right ventricles and LV strain values were assessed with post-processing software analysis. The cine image quality, conventional ventricular function parameters, and LV strain values were compared between the two cine groups and the differences were examined. Inter- and intraobserver agreements for CS-cine images were measured using intraclass correlation coefficient ( ). Bland-Altman analysis was performed to assess reproducibility between the two cine methods.
Results: The median scanning time of CS-cine was 21 s versus 272 s for sta-cine ( <0.001). The median image quality scores of two groups were significantly different, 4 points for sta-cine and 2 points for CS-cine ( <0.001). Bi-ventricular end-diastolic volumes (EDV), stroke volume (SV) and ejection fraction (EF) were significantly smaller in CS-cine ( <0.001). Nevertheless, no significant differences between the two groups in bi-ventricular ESV or LV mass were observed ( >0.05). LV strain parameters, including the peak radial strain, peak circumferential strain and peak longitudinal strain derived from LV mid-ventricular slice, were significantly different in the two sequences ( <0.001). Moreover, CS-cine-derived functional parameters and strain measurements have a good correlation with those of sta-cine (for RV function parameters, and left ventricular PLS, PCS values, more than 95% points fell within the limits of agreement [ ]; meanwhile, more than 91% points fell within the for other parameters) and inter- and intraobserver agreements were strong ( =0.88 to 0.99) for CS-cine.
Conclusion: CS-cine can well realize the rapid acquisition of cine images for quantitative analysis of cardiac function, and the conventional ventricular function parameters and LV globalized strain values obtained from CS-cine imaging have good reproducibility.
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http://dx.doi.org/10.12182/20220560506 | DOI Listing |
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).
View Article and Find Full Text PDFInt J Cardiovasc Imaging
January 2025
Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
The initial evaluation of stenosis during coronary angiography is typically performed by visual assessment. Visual assessment has limited accuracy compared to fractional flow reserve and quantitative coronary angiography, which are more time-consuming and costly. Applying deep learning might yield a faster and more accurate stenosis assessment.
View Article and Find Full Text PDFCir Cir
January 2025
Department of Neurosurgery, Spinal Health Center, Memorial Hospital, Istanbul, Turkey.
Objective: We aimed to elucidate the histopathological pre-diagnosis of cranial gliomas with magnetic resonance imaging (MRI) techniques in gliomas.
Method: A total of 82 glioma patients were enrolled to our study. Pre-operative conventional MRI images (non-contrast T1/T2/flair/contrast-enhanced T1) and advanced MRI images (DAG and ADC mapping, MRI spectroscopy and perfusion MRI [PMRI]) were analyzed.
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