RÉSUMÉ
Cardiac magnetic resonance (CMR) imaging allows precise non-invasive quantification of cardiac function. It requires reliable image segmentation for myocardial tissue. Clinically used software usually offers automatic approaches for this step. These are, however, designed for segmentation of human images obtained at clinical field strengths. They reach their limits when applied to preclinical data and ultrahigh field strength (such as CMR of pigs at 7 T). In our study, eleven animals (seven with myocardial infarction) underwent four CMR scans each. Short-axis cine stacks were acquired and used for functional cardiac analysis. End-systolic and end-diastolic images were labelled manually by two observers and inter- and intra-observer variability were assessed. Aiming to make the functional analysis faster and more reproducible, an established deep learning (DL) model for myocardial segmentation in humans was re-trained using our preclinical 7 T data (n = 772 images and labels). We then tested the model on n = 288 images. Excellent agreement in parameters of cardiac function was found between manual and DL segmentation: For ejection fraction (EF) we achieved a Pearson's r of 0.95, an Intraclass correlation coefficient (ICC) of 0.97, and a Coefficient of variability (CoV) of 6.6%. Dice scores were 0.88 for the left ventricle and 0.84 for the myocardium.
Sujet(s)
Apprentissage profond , Modèles animaux de maladie humaine , Infarctus du myocarde , Animaux , Infarctus du myocarde/imagerie diagnostique , Infarctus du myocarde/physiopathologie , Suidae , Reproductibilité des résultats , Traitement d'image par ordinateur/méthodes , IRM dynamique/méthodes , Humains , Coeur/imagerie diagnostique , Coeur/physiopathologie , Débit systolique , Imagerie par résonance magnétique/méthodesRÉSUMÉ
CMR at 3.0T in the presence of active cardiac implants remains a challenge due to susceptibility artifacts. Beyond a signal void that cancels image information, magnetic field inhomogeneities may cause distorted appearances of anatomical structures. Understanding influencing factors and the extent of distortion are a first step towards optimizing the image quality of CMR with active implants at 3.0T. All measurements were obtained at a clinical 3.0T scanner. An in-house designed phantom with a 3D cartesian grid of water filled spheres was used to analyze the distortion caused by four representative active cardiac devices (cardiac loop recorder, pacemaker, 2 ICDs). For imaging a gradient echo (3D-TFE) sequence and a turbo spin echo (2D-TSE) sequence were used. The work defines metrics to quantify the different features of distortion such as changes in size, location and signal intensity. It introduces a specialized segmentation technique based on a reaction-diffusion-equation. The distortion features are dependent on the amount of magnetic material in the active implants and showed a significant increase when measured with the 3D TFE compared to the 2D TSE. This work presents a quantitative approach for the evaluation of image distortion at 3.0T caused by active cardiac implants and serves as foundation for both further optimization of sequences and devices but also for planning of imaging procedures.
Sujet(s)
Imagerie tridimensionnelle , Imagerie par résonance magnétique , Fantômes en imagerie , Humains , Imagerie tridimensionnelle/méthodes , Imagerie par résonance magnétique/méthodes , Artéfacts , PacemakerRÉSUMÉ
Cardiac myocyte sodium (Na+) homoeostasis is pivotal in cardiac diseases and heart failure. Intracellular Na+ ([Na+]i) is an important regulator of excitation-contraction coupling and mitochondrial energetics. In addition, extracellular Na+ ([Na+]e) and its water-free storage trigger collagen cross-linking, myocardial stiffening and impaired cardiac function. Therefore, understanding the allocation of tissue Na+ to intra- and extracellular compartments is crucial in comprehending the pathophysiological processes in cardiac diseases. We extrapolated [Na+]e using a three-compartment model, with tissue Na+ concentration (TSC) measured by in vivo 23Na-MRI, extracellular volume (ECV) data calculated from T1 maps, and [Na+]i measured by in vitro fluorescence microscopy using Na+ binding benzofuran isophthalate (SBFI). To investigate dynamic changes in Na+ compartments, we induced pressure overload (TAC) or myocardial infarction (MI) via LAD ligation in mice. Compared to SHAM mice, TSC was similar after TAC but increased after MI. Both TAC and MI showed significantly higher [Na+]i compared to SHAM (around 130% compared to SHAM). Calculated [Na+]e increased after MI, but not after TAC. Increased TSC after TAC was primarily driven by increased [Na+]i, but the increase after MI by elevations in both [Na+]i and [Na+]e.