Coronary Angiography Breathhold Three-Dimensional Coronary Magnetic Resonance Angiography Using Real-Time Navigator Technology

The acquisition duration of most three-dimensional (30) coronary magnetic resonance angiography (MRA) techniques is considerably prolonged, thereby precluding breathholding as a mechanism to suppress respiratory motion artifacts. Splitting the acquired 30 volume into multiple subvolumes or slabs serves to shorten individual breathhold duration. Still, problems associated with misregistration due to inconsistent depths of expiration and diaphragmatic drift during sustained respiration remain to be resolved. Me propose the combination of an ultrafast 30 coronary MRA imaging sequence with prospective real-time navigator technology, which allows correction of the measured volume position. 30 volume splitting using prospective real-time navigator technology, was successfillly applied for3D coronary MRA in five healthy individuals. An ultrafast 30 interleaved hybrid gradient-echoplanar imaging sequence, including T2Prep for contrast enhancement, was used with the navigator localized at the basal anterior wall of the left ventricle. A 9-cm-thick volume, with in-plane spatial resolution of 1.1 X 2.2 mm, was acquired during five breathholds of 15-sec duration each. Consistently, no evidence of misregistration was observed in the images. Extensive contiguous segments of the left anterior descending coronary artery (48 2 18 mm) and the right coronary artery (75

Coronary artery size and origin imaging in children: a comparative study of MRI and trans-thoracic echocardiography

BACKGROUND: The purpose of this study was to see how coronary magnetic resonance angiography (CMRA) compared to echocardiography for the detection of coronary artery origins and to compare CMRA measurements for coronary dimensions in children with published echocardiographic reference values.METHODS: Enrolled patients underwent dual cardiac phase CMRA and echocardiography under the same anesthetic. Echocardiographic measurements of the right coronary artery (RCA), left anterior descending (LAD) and left main (LM) were made. CMRA dimensions were assessed manually at the same points as the echocardiographic measurements. The number of proximal LAD branches imaged was also recorded in order to give an estimate of distal coronary tree visualization.RESULTS: Fifty patients (24 boys, mean age 4.0 years (range 18 days to 18 years)) underwent dual-phase CMRA. Coronary origins were identified in 47/50 cases for CMRA (remaining 3 were infants aged 3, 9 and 11 months). In comparison, origins were identified in 41/50 cases for echo (remaining were all older children). CMRA performed better than echocardiography in terms of distal visualization of the coronary tree (median 1 LAD branch vs. median 0; p = 0.001). Bland-Altman plots show poor agreement between echocardiography and CMRA for coronary measurements. CMRA measurements did vary according to cardiac phase (systolic mean 1.90, s.d. 0.05 mm vs. diastolic mean 1.84, s.d. 0.05 mm; p = 0.002).CONCLUSIONS: Dual-phase CMRA has an excellent (94 %) success rate for the detection of coronary origins in children. Newborn infants remain challenging and echocardiography remains the accepted imaging modality for this age group. Echocardiographic reference ranges are not applicable to CMRA measurements as agreement was poor between modalities. Future coronary reference values, using any imaging modality, should quote the phase in which it was measured.</p

Contrast-Enhanced Magnetic Resonance Angiography Using a Novel Elastin-Specific Molecular Probe in an Experimental Animal Model

Objectives. The aim of this study was to test the potential of a new elastin-specific molecular agent for the performance of contrast-enhanced first-pass and 3D magnetic resonance angiography (MRA), compared to a clinically used extravascular contrast agent (gadobutrol) and based on clinical MR sequences. Materials and Methods. Eight C57BL/6J mice (BL6, male, aged 10 weeks) underwent a contrast-enhanced first-pass and 3D MR angiography (MRA) of the aorta and its main branches. All examinations were on a clinical 3 Tesla MR system (Siemens Healthcare, Erlangen, Germany). The clinical dose of 0.1 mmol/kg was administered in both probes. First, a time-resolved MRA (TWIST) was acquired during the first-pass to assess the arrival and washout of the contrast agent bolus. Subsequently, a high-resolution 3D MRA sequence (3D T1 FLASH) was acquired. Signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) were calculated for all sequences. Results. The elastin-specific MR probe and the extravascular imaging agent (gadobutrol) enable high-quality MR angiograms in all animals. During the first-pass, the probes demonstrated a comparable peak enhancement (300.6 +/- 32.9 vs. 288.5 +/- 33.1, p > 0.05). Following the bolus phase, both agents showed a comparable intravascular enhancement (SNR: 106.7 +/- 11 vs. 102.3 +/- 5.3; CNR 64.5 +/- 7.4 vs. 61.1 +/- 7.2, p > 0.05). Both agents resulted in a high image quality with no statistical difference (p > 0.05). Conclusion. The novel elastin-specific molecular probe enables the performance of first-pass and late 3D MR angiography with an intravascular contrast enhancement and image quality comparable to a clinically used extravascular contrast agent

Dual-probe molecular MRI for the in vivo characterization of atherosclerosis in a mouse model: Simultaneous assessment of plaque inflammation and extracellularmatrix remodeling

Molecular MRI is a promising in-vivo modality to detect and quantify morphological and molecular vessel-wall changes in atherosclerosis. The combination of different molecular biomarkers may improve the risk stratification of patients. This study aimed to investigate the feasibility of simultaneous visualization and quantification of plaque-burden and inflammatory activity by dual-probe molecular MRI in a mouse-model of progressive atherosclerosis and in response-to-therapy. Homozygous apolipoprotein E knockout mice (ApoE-/-) were fed a high-fat-diet (HFD) for up to four-months prior to MRI of the brachiocephalic-artery. To assess response-to-therapy, a statin was administered for the same duration. MR imaging was performed before and after administration of an elastin-specific gadolinium-based and a macrophage-specific iron-oxide-based probe. Following in-vivo MRI, samples were analyzed using histology, immunohistochemistry, inductively-coupled-mass-spectrometry and laser-inductively-coupled-mass-spectrometry. In atherosclerotic-plaques, intraplaque expression of elastic-fibers and inflammatory activity were not directly linked. While the elastin-specific probe demonstrated the highest accumulation in advanced atherosclerotic-plaques after four-months of HFD, the iron-oxide-based probe showed highest accumulation in early atherosclerotic-plaques after two-months of HFD. In-vivo measurements for the elastin and iron-oxide-probe were in good agreement with ex-vivo histopathology (Elastica-van-Giesson stain: y = 298.2 + 5.8, R2 = 0.83, p < 0.05; Perls' Prussian-blue-stain: y = 834.1 + 0.67, R2 = 0.88, p < 0.05). Contrast-to-noise-ratio (CNR) measurements of the elastin probe were in good agreement with ICP-MS (y = 0.11x-11.3, R² = 0.73, p < 0.05). Late stage atherosclerotic-plaques displayed the strongest increase in both CNR and gadolinium concentration (p < 0.05). The gadolinium probe did not affect the visualization of the iron-oxide-probe and vice versa. This study demonstrates the feasibility of simultaneous assessment of plaque-burden and inflammatory activity by dual-probe molecular MRI of progressive atherosclerosis. The in-vivo detection and quantification of different MR biomarkers in a single scan could be useful to improve characterization of atherosclerotic-lesions

Quantitative MRI in cardiometabolic disease:From conventional cardiac and liver tissue mapping techniques to multi-parametric approaches

Cardiometabolic disease refers to the spectrum of chronic conditions that include diabetes, hypertension, atheromatosis, non-alcoholic fatty liver disease, and their long-term impact on cardiovascular health. Histological studies have confirmed several modifications at the tissue level in cardiometabolic disease. Recently, quantitative MR methods have enabled non-invasive myocardial and liver tissue characterization. MR relaxation mapping techniques such as T 1, T 1ρ, T 2 and T 2* provide a pixel-by-pixel representation of the corresponding tissue specific relaxation times, which have been shown to correlate with fibrosis, altered tissue perfusion, oedema and iron levels. Proton density fat fraction mapping approaches allow measurement of lipid tissue in the organ of interest. Several studies have demonstrated their utility as early diagnostic biomarkers and their potential to bear prognostic implications. Conventionally, the quantification of these parameters by MRI relies on the acquisition of sequential scans, encoding and mapping only one parameter per scan. However, this methodology is time inefficient and suffers from the confounding effects of the relaxation parameters in each single map, limiting wider clinical and research applications. To address these limitations, several novel approaches have been proposed that encode multiple tissue parameters simultaneously, providing co-registered multiparametric information of the tissues of interest. This review aims to describe the multi-faceted myocardial and hepatic tissue alterations in cardiometabolic disease and to motivate the application of relaxometry and proton-density cardiac and liver tissue mapping techniques. Current approaches in myocardial and liver tissue characterization as well as latest technical developments in multiparametric quantitative MRI are included. Limitations and challenges of these novel approaches, and recommendations to facilitate clinical validation are also discussed.</p

From Compressed-Sensing to Artificial Intelligence-based Cardiac MRI Reconstruction

Cardiac magnetic resonance (CMR) imaging is an important tool for the non-invasive assessment of cardiovascular disease. However, CMR suffers from long acquisition times due to the need of obtaining images with high temporal and spatial resolution, different contrasts, and/or whole-heart coverage. In addition, both cardiac and respiratory-induced motion of the heart during the acquisition need to be accounted for, further increasing the scan time. Several undersampling reconstruction techniques have been proposed during the last decades to speed up CMR acquisition. These techniques rely on acquiring less data than needed and estimating the non-acquired data exploiting some sort of prior information. Parallel imaging and compressed sensing undersampling reconstruction techniques have revolutionized the field, enabling 2- to 3-fold scan time accelerations to become standard in clinical practice. Recent scientific advances in CMR reconstruction hinge on the thriving field of artificial intelligence. Machine learning reconstruction approaches have been recently proposed to learn the non-linear optimization process employed in CMR reconstruction. Unlike analytical methods for which the reconstruction problem is explicitly defined into the optimization process, machine learning techniques make use of large data sets to learn the key reconstruction parameters and priors. In particular, deep learning techniques promise to use deep neural networks (DNN) to learn the reconstruction process from existing datasets in advance, providing a fast and efficient reconstruction that can be applied to all newly acquired data. However, before machine learning and DNN can realize their full potentials and enter widespread clinical routine for CMR image reconstruction, there are several technical hurdles that need to be addressed. In this article, we provide an overview of the recent developments in the area of artificial intelligence for CMR image reconstruction. The underlying assumptions of established techniques such as compressed sensing and low-rank reconstruction are briefly summarized, while a greater focus is given to recent advances in dictionary learning and deep learning based CMR reconstruction. In particular, approaches that exploit neural networks as implicit or explicit priors are discussed for 2D dynamic cardiac imaging and 3D whole-heart CMR imaging. Current limitations, challenges, and potential future directions of these techniques are also discussed