Objectives: Feature tracking for assessing myocardial strain from cardiac magnetic resonance (CMR) cine images detects myocardial deformation abnormalities with prognostic implication, e.g., in myocardial infarction and cardiomyopathy. Standards for image acquisition and processing are not yet available. Study aim was analyzing the influence of spatial resolution and contrast agent on myocardial strain results.
Methods: Seventy-five patients underwent CMR for analyzing peak systolic circumferential, longitudinal, and radial strain. Group A included n = 50 with normal left ventricular ejection fraction, no wall motion abnormality, and no fibrosis on late enhancement imaging. Group B included n = 25 with chronic myocardial infarct. For feature tracking, steady-state free precession cine images were acquired repeatedly. (1) Native standard cine (spatial resolution 1.4 × 1.4 × 8 mm). (2) Native cine with lower spatial resolution (2.0 × 2.0 × 8 mm). (3) Cine equal to variant 1 acquired after administration of gadoteracid.
Results: Lower spatial resolution was associated with elevated longitudinal strain (- 21.7% vs. - 19.8%; p < 0.001) in viable myocardium in group A, and with elevated longitudinal (- 17.0% vs. - 14.3%; p = 0.001), circumferential (- 18.6% vs. - 14.6%; p = 0.002), and radial strain (36.8% vs. 31.0%; p = 0.013) in infarcted myocardium in group B. Gadolinium administration was associated with reduced circumferential (- 21.4% vs. - 22.3%; p = 0.001) and radial strain (44.4% vs. 46.9%; p = 0.016) in group A, whereas strain results of the infarcted tissue in group B did not change after contrast agent administration.
Conclusions: Variations in spatial resolution and the administration of contrast agent may influence myocardial strain results in viable and partly in infarcted myocardium. Standardized image acquisition seems important for CMR feature tracking.
Key Points: • Feature tracking is used for calculating myocardial strain from cardiac magnetic resonance (CMR) cine images. • This prospective study demonstrated that CMR strain results may be influenced by spatial resolution and by the administration of gadolinium-based contrast agent. • The results underline the need for standardized image acquisition for CMR strain analysis, with constant imaging parameters and without contrast agent.
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Brief Bioinform
November 2024
Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, No. 15 Shangxiadian Road, Cangshan District, Fuzhou 350002, China.
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View Article and Find Full Text PDFMass Spectrom (Tokyo)
December 2024
Department of Pharmaceutical Engineering, Faculty of Engineering, Toyama Prefectural University, 5180 Kurokawa, Imizu-City, Toyama 939-0398, Japan.
Matrix-assisted laser desorption/ionization (MALDI), surface-assisted laser desorption/ionization (SALDI), and time-of-flight mass spectrometry (TOFMS) imaging are used for visualizing the spatial distribution of analytes. Mass spectrometry (MS) imaging of a sample with a rough surface with a uniform distribution of an analyte does not provide uniform ion intensities in the image. A shift in the value of the analyte ions is also observed.
View Article and Find Full Text PDFSpatially variable genes (SVGs) reveal the molecular and functional heterogeneity of cells across different spatial regions of a tissue. We found that sample-wide SVGs, identified by previous methods across the whole sample, largely overlap with cell-type marker genes derived from single-cell gene expression, leaving the spatial location information largely underutilized. We developed ctSVG, a computational method specifically tailored for Visium HD spatial transcriptomics at single-cell resolution.
View Article and Find Full Text PDFThe advent of spatial transcriptomics and spatial proteomics have enabled profound insights into tissue organization to provide systems-level understanding of diseases. Both technologies currently remain largely independent, and emerging same slide spatial multi-omics approaches are generally limited in plex, spatial resolution, and analytical approaches. We introduce IN-situ DEtailed Phenotyping To High-resolution transcriptomics (IN-DEPTH), a streamlined and resource-effective approach compatible with various spatial platforms.
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