Highlights of the Society for Magnetic Resonance Angiography 2024 Conference.

The 36th Annual International Meeting of the Society for Magnetic Resonance Angiography (SMRA), held from November 12-15, 2024, in Santiago de Chile, marked a milestone as the first SMRA conference in Latin America. Themed "The Ever-Changing Landscape of MRA", the event highlighted the rapid advancements in magnetic resonance angiography (MRA), including cutting-edge developments in contrast-enhanced MRA, contrast-free techniques, dynamic, multi-parametric, and multi-contrast MRA, 4D flow, low-field solutions and AI-driven technologies, among others. The program featured 174 attendees from 15 countries, including 43 early-career scientists and 30 industry representatives.

Repeatability-encouraging self-supervised learning reconstruction for quantitative MRI.

Purpose: The clinical value of quantitative MRI hinges on its measurement repeatability. Deep learning methods to reconstruct undersampled quantitative MRI can accelerate reconstruction but do not aim to promote quantitative repeatability. This study proposes a repeatability-encouraging self-supervised learning (SSL) reconstruction method for quantitative MRI.

Generalizable, sequence-invariant deep learning image reconstruction for subspace-constrained quantitative MRI.

Purpose: To develop a deep subspace learning network that can function across different pulse sequences.

Methods: A contrast-invariant component-by-component (CBC) network structure was developed and compared against previously reported spatiotemporal multicomponent (MC) structure for reconstructing MR Multitasking images. A total of 130, 167, and 16 subjects were imaged using T, T-T, and T-T- -fat fraction (FF) mapping sequences, respectively.

Accurate Intramyocardial Hemorrhage Assessment with Fast, Free-running, Cardiac Quantitative Susceptibility Mapping.

Purpose To evaluate the performance of a high-dynamic-range quantitative susceptibility mapping (HDR-QSM) cardiac MRI technique to detect intramyocardial hemorrhage (IMH) and quantify iron content using phantom and canine models. Materials and Methods A free-running whole-heart HDR-QSM technique for IMH assessment was developed and evaluated in calibrated iron phantoms and 14 IMH female canine models. IMH detection and iron content quantification performance of this technique was compared with the conventional iron imaging approaches, R2*(1/T2*) maps, using measurements from ex vivo imaging as the reference standard.

Coronary Plaque Characterization with T1-weighted MRI and Near-Infrared Spectroscopy to Predict Periprocedural Myocardial Injury.

Purpose To clarify the predominant causative plaque constituent for periprocedural myocardial injury (PMI) following percutaneous coronary intervention: erythrocyte-derived materials, indicated by a high plaque-to-myocardium signal intensity ratio (PMR) at coronary atherosclerosis T1-weighted characterization (CATCH) MRI, or lipids, represented by a high maximum 4-mm lipid core burden index (maxLCBI) at near-infrared spectroscopy intravascular US (NIRS-IVUS). Materials and Methods This retrospective study included consecutive patients who underwent CATCH MRI before elective NIRS-IVUS-guided percutaneous coronary intervention at two facilities. PMI was defined as post-percutaneous coronary intervention troponin T values greater than five times the upper reference limit.

Ferumoxytol-Enhanced 5D Multiphase Steady-State Imaging Using Rotating Cartesian K-Space With Low-Rank Reconstruction for Pediatric Congenital Heart Disease.

Background: The rotating Cartesian k-space multiphase steady-state imaging with contrast (ROCK-MUSIC) pulse sequence enables acquisition of whole-heart, cardiac phase-resolved images in pediatric congenital heart disease (CHD) without reliance on the ventilator gating signal. Multidimensional reconstruction with low rank tensor (LRT) has shown promise for resolving complex cardiorespiratory motion.

Purpose: To enhance ROCK-MUSIC by resolving cardiorespiratory phases using LRT reconstruction and to enable semi-automatic hyperparameter tuning by developing an image quality scoring model.

Mitigation of Fetal Radiation Injury from Mid-Gestation Total-body Irradiation by Maternal Administration of Mitochondrial-Targeted GS-Nitroxide JP4-039.

Victims of a radiation terrorist event will include pregnant women and unborn fetuses. Mitochondrial dysfunction and oxidative stress are key pathogenic factors of fetal radiation injury. The goal of this preclinical study is to investigate the efficacy of mitigating fetal radiation injury by maternal administration of the mitochondrial-targeted gramicidin S (GS)-nitroxide radiation mitigator JP4-039.

Physics-guided self-supervised learning for retrospective T and T mapping from conventional weighted brain MRI: Technical developments and initial validation in glioblastoma.

Purpose: To develop a self-supervised learning method to retrospectively estimate T and T values from clinical weighted MRI.

Methods: A self-supervised learning approach was constructed to estimate T, T, and proton density maps from conventional T- and T-weighted images. MR physics models were employed to regenerate the weighted images from the network outputs, and the network was optimized based on loss calculated between the synthesized and input weighted images, alongside additional constraints based on prior information.

Modeling normal mouse uterine contraction and placental perfusion with non-invasive longitudinal dynamic contrast enhancement MRI.

Background: The placenta is a transient organ critical for fetal development. Disruptions of normal placental functions can impact health throughout an individual's entire life. Although being recognized by the NIH Human Placenta Project as an important organ, the placenta remains understudied, partly because of a lack of non-invasive tools for longitudinally evaluation for key aspects of placental functionalities.

Alternating low-rank tensor reconstruction for improved multiparametric mapping with cardiovascular MR Multitasking.

Purpose: To develop a novel low-rank tensor reconstruction approach leveraging the complete acquired data set to improve precision and repeatability of multiparametric mapping within the cardiovascular MR Multitasking framework.

Methods: A novel approach that alternated between estimation of temporal components and spatial components using the entire data set acquired (i.e.

Dynamic Regularized Adaptive Cluster Optimization (DRACO) for Quantitative Cardiac Cine MRI in Complex Arrhythmias.

Background: Irregular cardiac motion can render conventional segmented cine MRI nondiagnostic. Clustering has been proposed for cardiac motion binning and may be optimized for complex arrhythmias.

Purpose: To develop an adaptive cluster optimization method for irregular cardiac motion, and to generate the corresponding time-resolved cine images.

Mitigation of Fetal Irradiation Injury from Mid-Gestation Total Body Radiation with Mitochondrial-Targeted GS-Nitroxide JP4-039.

Unlabelled: Victims of a radiation terrorist event will include pregnant women and unborn fetuses. Mitochondrial dysfunction and oxidative stress are key pathogenic factors of fetal irradiation injury. The goal of this preclinical study is to investigate the efficacy of mitigating fetal irradiation injury by maternal administration of the mitochondrial-targeted gramicidin S (GS)- nitroxide radiation mitigator, JP4-039.

The future of cardiovascular magnetic resonance: All-in-one vs. real-time (Part 1).

Cardiovascular magnetic resonance (CMR) protocols can be lengthy and complex, which has driven the research community to develop new technologies to make these protocols more efficient and patient-friendly. Two different approaches to improving CMR have been proposed, specifically "all-in-one" CMR, where several contrasts and/or motion states are acquired simultaneously, and "real-time" CMR, in which the examination is accelerated to avoid the need for breathholding and/or cardiac gating. The goal of this two-part manuscript is to describe these two different types of emerging rapid CMR.

ECG-free cine MRI with data-driven clustering of cardiac motion for quantification of ventricular function.

Background: Despite the widespread use of cine MRI for evaluation of cardiac function, existing real-time methods do not easily enable quantification of ventricular function. Moreover, segmented cine MRI assumes periodicity of cardiac motion. We aim to develop a self-gated, cine MRI acquisition scheme with data-driven cluster-based binning of cardiac motion.

Non-electrocardiogram-gated, free-breathing, off-resonance reduced, high-resolution, whole-heart myocardial T * mapping at 3 T within 5 min.

Purpose: Widely used conventional 2D T * approaches that are based on breath-held, electrocardiogram (ECG)-gated, multi-gradient-echo sequences are prone to motion artifacts in the presence of incomplete breath holding or arrhythmias, which is common in cardiac patients. To address these limitations, a 3D, non-ECG-gated, free-breathing T * technique that enables rapid whole-heart coverage was developed and validated.

Methods: A continuous random Gaussian 3D k-space sampling was implemented using a low-rank tensor framework for motion-resolved 3D T * imaging.

Retrospective T2 quantification from conventional weighted MRI of the prostate based on deep learning.

Purpose: To develop a deep learning-based method to retrospectively quantify T2 from conventional T1- and T2-weighted images.

Methods: Twenty-five subjects were imaged using a multi-echo spin-echo sequence to estimate reference prostate T2 maps. Conventional T1- and T2-weighted images were acquired as the input images.

Motion-compensated T mapping in cardiovascular magnetic resonance imaging: a technical review.

mapping is becoming a staple magnetic resonance imaging method for diagnosing myocardial diseases such as ischemic cardiomyopathy, hypertrophic cardiomyopathy, myocarditis, and more. Clinically, most mapping sequences acquire a single slice at a single cardiac phase across a 10 to 15-heartbeat breath-hold, with one to three slices acquired in total. This leaves opportunities for improving patient comfort and information density by acquiring data across multiple cardiac phases in free-running acquisitions and across multiple respiratory phases in free-breathing acquisitions.

Retrospective quantification of clinical abdominal DCE-MRI using pharmacokinetics-informed deep learning: a proof-of-concept study.

Introduction: Dynamic contrast-enhanced (DCE) MRI has important clinical value for early detection, accurate staging, and therapeutic monitoring of cancers. However, conventional multi-phasic abdominal DCE-MRI has limited temporal resolution and provides qualitative or semi-quantitative assessments of tissue vascularity. In this study, the feasibility of retrospectively quantifying multi-phasic abdominal DCE-MRI by using pharmacokinetics-informed deep learning to improve temporal resolution was investigated.

Physics-informed deep learning for T2-deblurred superresolution turbo spin echo MRI.

Purpose: Deep learning superresolution (SR) is a promising approach to reduce MRI scan time without requiring custom sequences or iterative reconstruction. Previous deep learning SR approaches have generated low-resolution training images by simple k-space truncation, but this does not properly model in-plane turbo spin echo (TSE) MRI resolution degradation, which has variable T relaxation effects in different k-space regions. To fill this gap, we developed a T -deblurred deep learning SR method for the SR of 3D-TSE images.

Direct synthesis of multi-contrast brain MR images from MR multitasking spatial factors using deep learning.

Purpose: To develop a deep learning method to synthesize conventional contrast-weighted images in the brain from MR multitasking spatial factors.

Methods: Eighteen subjects were imaged using a whole-brain quantitative T -T -T MR multitasking sequence. Conventional contrast-weighted images consisting of T MPRAGE, T gradient echo, and T fluid-attenuated inversion recovery were acquired as target images.

Multitasking dynamic contrast enhanced magnetic resonance imaging can accurately differentiate chronic pancreatitis from pancreatic ductal adenocarcinoma.

Background And Aims: Accurate differentiation of chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC) is an area of unmet clinical need. In this study, a novel Multitasking dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) technique was used to quantitatively evaluate the microcirculation properties of pancreas in CP and PDAC and differentiate between them.

Methods: The Multitasking DCE technique was able to acquire one 3D image per second during the passage of MRI contrast agent, allowing the quantitative estimation of microcirculation properties of tissue, including blood flow F, plasma volume fraction v, transfer constant K, and extravascular extracellular volume fraction v.