Multi-centre Investigation of Cardiac Diffusion Tensor Imaging in Healthy Volunteers by SCMR Cardiac Diffusion Special Interest Group NETwork (SIGNET).

Background: Cardiac diffusion tensor imaging (cDTI) is an emerging technique for microstructural characterization of the heart and has shown clinical potential in a range of cardiomyopathies. However, there is substantial variation reported for in vivo cDTI results across the literature, and sensitivity of cDTI to differences in imaging sites, scanners, acquisition protocols and post-processing methods remains incompletely understood.

Methods: SIGNET is a prospective multi-centre, observational study in travelling and non-travelling healthy volunteers.

Enhanced DTCMR With Cascaded Alignment and Adaptive Diffusion.

Diffusion tensor cardiovascular magnetic resonance (DTCMR) is the only non-invasive method for visualizing myocardial microstructure, but it is challenged by inconsistent breath-holds and imperfect cardiac triggering, causing in-plane shifts and through-plane warping with an inadequate tensor fitting. While rigid registration corrects in-plane shifts, deformable registration risks distorting the diffusion distribution, and selecting a reference frame among low SNR frames is challenging. Existing pairwise deep learning and iterative methods are unsuitable for DTCMR due to their inability to handle the drastic in-plane motion and disentangle the diffusion contrast distortion with through-plane motions on low SNR frames, which compromises the accuracy of clinical biomarker tensor estimation.

DENSE-SIM: A modular pipeline for the evaluation of cine displacement encoding with stimulated echoes images with sub-voxel ground-truth strain.

Background: Myocardial strain is a valuable biomarker for diagnosing and predicting cardiac conditions, offering additional prognostic information to traditional metrics such as ejection fraction. While cardiovascular magnetic resonance (CMR) methods, particularly cine displacement encoding with stimulated echoes (DENSE), are the gold standard for strain estimation, evaluation of regional strain estimation requires precise ground truth. This study introduces DENSE-SIM, an open-source simulation pipeline for generating realistic cine DENSE images with high-resolution known ground-truth strain, enabling evaluation of accuracy and precision in strain analysis pipelines.

Cardiac diffusion-weighted and tensor imaging: A consensus statement from the special interest group of the Society for Cardiovascular Magnetic Resonance.

Thanks to recent developments in cardiovascular magnetic resonance (CMR), cardiac diffusion-weighted magnetic resonance is fast emerging in a range of clinical applications. Cardiac diffusion-weighted imaging (cDWI) and diffusion tensor imaging (cDTI) now enable investigators and clinicians to assess and quantify the tridimensional microstructure of the heart. Free-contrast DWI is uniquely sensitized to the presence and displacement of water molecules within the myocardial tissue, including the intracellular, extracellular, and intravascular spaces.

Characterization of dynamic changes in cardiac microstructure after reperfused ST-elevation myocardial infarction by biphasic diffusion tensor cardiovascular magnetic resonance.

Background And Aims: Microstructural disturbances underlie dysfunctional contraction and adverse left ventricular (LV) remodelling after ST-elevation myocardial infarction (STEMI). Biphasic diffusion tensor cardiovascular magnetic resonance (DT-CMR) quantifies dynamic reorientation of sheetlets (E2A) from diastole to systole during myocardial thickening, and markers of tissue integrity [mean diffusivity (MD) and fractional anisotropy (FA)]. This study investigated whether microstructural alterations identified by biphasic DT-CMR: (i) enable contrast-free detection of acute myocardial infarction (MI); (ii) associate with severity of myocardial injury and contractile dysfunction; and (iii) predict adverse LV remodelling.

Deep learning method with integrated invertible wavelet scattering for improving the quality ofcardiac DTI.

Respiratory motion, cardiac motion and inherently low signal-to-noise ratio (SNR) are major limitations ofcardiac diffusion tensor imaging (DTI). We propose a novel enhancement method that uses unsupervised learning based invertible wavelet scattering (IWS) to improve the quality ofcardiac DTI.Our method starts by extracting nearly transformation-invariant features from multiple cardiac diffusion-weighted (DW) image acquisitions using multi-scale wavelet scattering (WS).

The effects of field strength on stimulated echo and motion-compensated spin-echo diffusion tensor cardiovascular magnetic resonance sequences.

Background: In-vivo diffusion tensor cardiovascular magnetic resonance (DT-CMR) is an emerging technique for microstructural tissue characterization in the myocardium. Most studies are performed at 3T, where higher signal-to-noise ratio (SNR) should benefit this signal-starved method. However, a few studies have suggested that DT-CMR is possible at 1.

Nonperturbative Fluorogenic Labeling of Immunophilins Enables the Wash-free Detection of Immunosuppressants.

Immunosuppressants are clinically approved drugs to treat the potential rejection of transplanted organs and require frequent monitoring due to their narrow therapeutic window. Immunophilins are small proteins that bind immunosuppressants with high affinity, yet there are no examples of fluorogenic immunophilins and their potential application as optical biosensors for immunosuppressive drugs in clinical biosamples. In the present work, we designed novel diazonium BODIPY salts for the site-specific labeling of tyrosine residues in peptides via solid-phase synthesis as well as for late-stage functionalization of whole recombinant proteins.

Referenceless Nyquist ghost correction outperforms standard navigator-based method and improves efficiency of in vivo diffusion tensor cardiovascular magnetic resonance.

Purpose: The study aims to assess the potential of referenceless methods of EPI ghost correction to accelerate the acquisition of in vivo diffusion tensor cardiovascular magnetic resonance (DT-CMR) data using both computational simulations and data from in vivo experiments.

Methods: Three referenceless EPI ghost correction methods were evaluated on mid-ventricular short axis DT-CMR spin echo and STEAM datasets from 20 healthy subjects at 3T. The reduced field of view excitation technique was used to automatically quantify the Nyquist ghosts, and DT-CMR images were fit to a linear ghost model for correction.

STEAM-SASHA: a novel approach for blood- and fat-suppressed native T1 measurement in the right ventricular myocardium.

Objective: The excellent blood and fat suppression of stimulated echo acquisition mode (STEAM) can be combined with saturation recovery single-shot acquisition (SASHA) in a novel STEAM-SASHA sequence for right ventricular (RV) native T1 mapping.

Materials And Methods: STEAM-SASHA splits magnetization preparation over two cardiac cycles, nulling blood signal and allowing fat signal to decay. Breath-hold T1 mapping was performed in a T1 phantom and twice in 10 volunteers using STEAM-SASHA and a modified Look-Locker sequence at peak systole at 3T.

Biophysical screening and characterisation in medicinal chemistry.

In the last two decades the use of biophysical assays and methods in medicinal chemistry has increased significantly, to meet the demands of the novel targets and modalities that drug discoverers are looking to tackle. The desire to obtain accurate affinities, kinetics, thermodynamics and structural data as early as possible in the drug discovery process has fuelled this innovation. This review introduces the principles underlying the techniques in common use and provides a perspective on the weaknesses and strengths of different methods.

Realistic numerical simulations of diffusion tensor cardiovascular magnetic resonance: The effects of perfusion and membrane permeability.

Purpose: To study the sensitivity of diffusion tensor cardiovascular magnetic resonance (DT-CMR) to microvascular perfusion and changes in cell permeability.

Methods: Monte Carlo (MC) random walk simulations in the myocardium have been performed to simulate self-diffusion of water molecules in histology-based media with varying extracellular volume fraction (ECV) and permeable membranes. The effect of microvascular perfusion on simulations of the DT-CMR signal has been incorporated by adding the contribution of particles traveling through an anisotropic capillary network to the diffusion signal.

Effects of myocardial sheetlet sliding on left ventricular function.

Left ventricle myocardium has a complex micro-architecture, which was revealed to consist of myocyte bundles arranged in a series of laminar sheetlets. Recent imaging studies demonstrated that these sheetlets re-orientated and likely slided over each other during the deformations between systole and diastole, and that sheetlet dynamics were altered during cardiomyopathy. However, the biomechanical effect of sheetlet sliding is not well-understood, which is the focus here.

Automated segmentation of long and short axis DENSE cardiovascular magnetic resonance for myocardial strain analysis using spatio-temporal convolutional neural networks.

Background: Cine Displacement Encoding with Stimulated Echoes (DENSE) facilitates the quantification of myocardial deformation, by encoding tissue displacements in the cardiovascular magnetic resonance (CMR) image phase, from which myocardial strain can be estimated with high accuracy and reproducibility. Current methods for analyzing DENSE images still heavily rely on user input, making this process time-consuming and subject to inter-observer variability. The present study sought to develop a spatio-temporal deep learning model for segmentation of the left-ventricular (LV) myocardium, as spatial networks often fail due to contrast-related properties of DENSE images.

Random walk diffusion simulations in semi-permeable layered media with varying diffusivity.

In this paper we present random walk based solutions to diffusion in semi-permeable layered media with varying diffusivity. We propose a novel transit model for solving the interaction of random walkers with a membrane. This hybrid model is based on treating the membrane permeability and the step change in diffusion coefficient as two interactions separated by an infinitesimally small layer.

Accelerating Cardiac Diffusion Tensor Imaging With a U-Net Based Model: Toward Single Breath-Hold.

Background: In vivo cardiac diffusion tensor imaging (cDTI) characterizes myocardial microstructure. Despite its potential clinical impact, considerable technical challenges exist due to the inherent low signal-to-noise ratio.

Purpose: To reduce scan time toward one breath-hold by reconstructing diffusion tensors for in vivo cDTI with a fitting-free deep learning approach.

Reproducibility of global and segmental myocardial strain using cine DENSE at 3 T: a multicenter cardiovascular magnetic resonance study in healthy subjects and patients with heart disease.

Background: While multiple cardiovascular magnetic resonance (CMR) methods provide excellent reproducibility of global circumferential and global longitudinal strain, achieving highly reproducible segmental strain is more challenging. Previous single-center studies have demonstrated excellent reproducibility of displacement encoding with stimulated echoes (DENSE) segmental circumferential strain. The present study evaluated the reproducibility of DENSE for measurement of whole-slice or global circumferential (E), longitudinal (E) and radial (E) strain, torsion, and segmental E at multiple centers.

Development of a cardiovascular magnetic resonance-compatible large animal isolated heart model for direct comparison of beating and arrested hearts.

Cardiac motion results in image artefacts and quantification errors in many cardiovascular magnetic resonance (CMR) techniques, including microstructural assessment using diffusion tensor cardiovascular magnetic resonance (DT-CMR). Here, we develop a CMR-compatible isolated perfused porcine heart model that allows comparison of data obtained in beating and arrested states. Ten porcine hearts (8/10 for protocol optimisation) were harvested using a donor heart retrieval protocol and transported to the remote CMR facility.

Validation of cardiac diffusion tensor imaging sequences: A multicentre test-retest phantom study.

Cardiac diffusion tensor imaging (DTI) is an emerging technique for the in vivo characterisation of myocardial microstructure, and there is a growing need for its validation and standardisation. We sought to establish the accuracy, precision, repeatability and reproducibility of state-of-the-art pulse sequences for cardiac DTI among 10 centres internationally. Phantoms comprising 0%-20% polyvinylpyrrolidone (PVP) were scanned with DTI using a product pulsed gradient spin echo (PGSE; N = 10 sites) sequence, and a custom motion-compensated spin echo (SE; N = 5) or stimulated echo acquisition mode (STEAM; N = 5) sequence suitable for cardiac DTI in vivo.