CoRRECT: A Deep Unfolding Framework for Motion-Corrected Quantitative R2* Mapping.

Quantitative MRI (qMRI) refers to a class of MRI methods for quantifying the spatial distribution of biological tissue parameters. Traditional qMRI methods usually deal separately with artifacts arising from accelerated data acquisition, involuntary physical motion, and magnetic field inhomogeneities, leading to sub-optimal end-to-end performance. This paper presents CoRRECT, a unified deep unfolding (DU) framework for qMRI consisting of a model-based end-to-end neural network, a method for motion artifact reduction, and a self-supervised learning scheme.

Quantum magnetization exchange through transient hydrogen bond matrix defines magnetic resonance signal relaxation and anisotropy in central nervous system.

The integrity of cellular membranes (lipid bilayers) and myelin sheaths covering axons is a crucial feature controlling normal brain structural and functional networks. Yet, in vivo evaluation of this integrity at the nanoscale level of the cellular membranes organization is challenging. Herein we explore the dual property of biological water in Central Nervous System (CNS), as one of the major stabilizing factors of cellular membranes, and the major source of MRI signal.

Unraveling the major role of vascular (R2') contributions to R2* signal relaxation at ultra-high-field MRI: A comprehensive analysis with quantitative gradient recalled echo in mouse brain.

Purpose: Ultra-high-field (UHF) R2* relaxometry is often used for in vivo analysis of biological tissue microstructure without accounting for vascular contributions to R2* signal, that is, the BOLD signal component, and magnetic field inhomogeneities. These effects are especially important at UHF as their contribution to R2* scales linearly with magnetic field. Our study aims to report on the results of separate contributions of R2t* (tissue-specific sub-component) and R2' (vascular BOLD sub-component), corrected for the adverse effects of magnetic field inhomogeneities, to the total R2* signal at in vivo UHF MRI of mouse brain.

Claustrum Volume Is Reduced in Multiple Sclerosis and Predicts Disability.

Objective: The claustrum is a small, thin structure of predominantly gray matter with broad connectivity and enigmatic function. Little is known regarding the impact of claustrum pathology in multiple sclerosis (MS).

Methods: This study assessed whether claustrum volume was reduced in MS and whether reductions were associated with specific disability domains.

Quantum dipole interactions and transient hydrogen bond orientation order in cells, cellular membranes and myelin sheath: Implications for MRI signal relaxation, anisotropy, and T magnetic field dependence.

Purpose: Despite significant impact on the study of human brain, MRI lacks a theory of signal formation that integrates quantum interactions involving proton dipoles (a primary MRI signal source) with brain intricate cellular environment. The purpose of the present study is developing such a theory.

Methods: We introduce the Transient Hydrogen Bond (THB) model, where THB-mediated quantum dipole interactions between water and protons of hydrophilic heads of amphipathic biomolecules forming cells, cellular membranes and myelin sheath serve as a major source of MR signal relaxation.

Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient-Recalled Echo (qGRE) magnetic resonance imaging metrics associated with human brain neuronal structure and hemodynamic properties.

The purpose of the current study was to introduce a Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) method for reconstructing quantitative maps of biological tissue cellular-specific, R2t*, and hemodynamic-specific, R2', metrics of quantitative gradient-recalled echo (qGRE) MRI. The DANSE method adapts a supervised learning paradigm to train a convolutional neural network for robust estimation of R2t* and R2' maps with significantly reduced sensitivity to noise and the adverse effects of macroscopic (B ) magnetic field inhomogeneities directly from the gradient-recalled echo (GRE) magnitude images. The R2t* and R2' maps for training were generated by means of a voxel-by-voxel fitting of a previously developed biophysical quantitative qGRE model accounting for tissue, hemodynamic, and B -inhomogeneities contributions to multigradient-echo GRE signal using a nonlinear least squares (NLLS) algorithm.

Evaluating brain damage in multiple sclerosis with simultaneous multi-angular-relaxometry of tissue.

Objective: Multiple sclerosis (MS) is a common demyelinating central nervous system disease. MRI methods that can quantify myelin loss are needed for trials of putative remyelinating agents. Quantitative magnetization transfer MRI introduced the macromolecule proton fraction (MPF), which correlates with myelin concentration.

Microscopic theory of spin-spin and spin-lattice relaxation of bound protons in cellular and myelin membranes-A lateral diffusion model (LDM).

Purpose: Deciphering salient features of biological tissue cellular microstructure in health and diseases is an ultimate goal of MRI. While most MRI approaches are based on studying MR properties of tissue "free" water indirectly affected by tissue microstructure, other approaches, such as magnetization transfer (MT), directly target signals from tissue-forming macromolecules. However, despite three-decades of successful applications, relationships between MT measurements and tissue microstructure remain elusive, hampering interpretation of experimental results.

Stronger Microstructural Damage Revealed in Multiple Sclerosis Lesions With Central Vein Sign by Quantitative Gradient Echo MRI.

Background: Multiple sclerosis (MS) lesions typically form around a central vein that can be visualized with FLAIR* MRI, creating the central vein sign (CVS) which may reflect lesion pathophysiology. Herein we used gradient echo plural contrast imaging (GEPCI) MRI to simultaneously visualize CVS and measure tissue damage in MS lesions. We examined CVS in relation to tissue integrity in white matter (WM) lesions and among MS subtypes.

Learning-based motion artifact removal networks for quantitative mapping.

Purpose: To introduce two novel learning-based motion artifact removal networks (LEARN) for the estimation of quantitative motion- and -inhomogeneity-corrected maps from motion-corrupted multi-Gradient-Recalled Echo (mGRE) MRI data.

Methods: We train two convolutional neural networks (CNNs) to correct motion artifacts for high-quality estimation of quantitative -inhomogeneity-corrected maps from mGRE sequences. The first CNN, LEARN-IMG, performs motion correction on complex mGRE images, to enable the subsequent computation of high-quality motion-free quantitative (and any other mGRE-enabled) maps using the standard voxel-wise analysis or machine learning-based analysis.

The Role of the Human Brain Neuron-Glia-Synapse Composition in Forming Resting-State Functional Connectivity Networks.

While significant progress has been achieved in studying resting-state functional networks in a healthy human brain and in a wide range of clinical conditions, many questions related to their relationship to the brain's cellular constituents remain. Here, we use quantitative Gradient-Recalled Echo (qGRE) MRI for mapping the human brain cellular composition and BOLD (blood-oxygen level-dependent) MRI to explore how the brain cellular constituents relate to resting-state functional networks. Results show that the BOLD signal-defined synchrony of connections between cellular circuits in network-defined individual functional units is mainly associated with the regional neuronal density, while the between-functional units' connectivity strength is also influenced by the glia and synaptic components of brain tissue cellular constituents.

Quantitative Gradient Echo MRI Identifies Dark Matter as a New Imaging Biomarker of Neurodegeneration that Precedes Tisssue Atrophy in Early Alzheimer's Disease.

Background: Currently, brain tissue atrophy serves as an in vivo MRI biomarker of neurodegeneration in Alzheimer's disease (AD). However, postmortem histopathological studies show that neuronal loss in AD exceeds volumetric loss of tissue and that loss of memory in AD begins when neurons and synapses are lost. Therefore, in vivo detection of neuronal loss prior to detectable atrophy in MRI is essential for early AD diagnosis.

In vivo evaluation of heme and non-heme iron content and neuronal density in human basal ganglia.

Non-heme iron is an important element supporting the structure and functioning of biological tissues. Imbalance in non-heme iron can lead to different neurological disorders. Several MRI approaches have been developed for iron quantification relying either on the relaxation properties of MRI signal or measuring tissue magnetic susceptibility.

Deep learning using a biophysical model for robust and accelerated reconstruction of quantitative, artifact-free and denoised images.

Purpose: To introduce a novel deep learning method for Robust and Accelerated Reconstruction (RoAR) of quantitative and B0-inhomogeneity-corrected maps from multi-gradient recalled echo (mGRE) MRI data.

Methods: RoAR trains a convolutional neural network (CNN) to generate quantitative maps free from field inhomogeneity artifacts by adopting a self-supervised learning strategy given (a) mGRE magnitude images, (b) the biophysical model describing mGRE signal decay, and (c) preliminary-evaluated F-function accounting for contribution of macroscopic B0 field inhomogeneities. Importantly, no ground-truth images are required and F-function is only needed during RoAR training but not application.

In vivo evolution of biopsy-proven inflammatory demyelination quantified by R2t* mapping.

A 35-year-old man with an enhancing tumefactive brain lesion underwent biopsy, revealing inflammatory demyelination. We used quantitative Gradient-Recalled-Echo (qGRE) MRI to visualize and measure tissue damage in the lesion. Two weeks after biopsy, qGRE showed significant R2t* reduction in the left optic radiation and surrounding tissue, consistent with the histopathological and clinical findings.

A Novel Gradient Echo Plural Contrast Imaging Method Detects Brain Tissue Abnormalities in Patients With TBI Without Evident Anatomical Changes on Clinical MRI: A Pilot Study.

Research Objectives: It is widely accepted that mild traumatic brain injury (mTBI) causes injury to the white matter, but the extent of gray matter (GM) damage in mTBI is less clear.

Methods: We tested 26 civilian healthy controls and 14 civilian adult subacute-chronic mTBI patients using quantitative features of MRI-based Gradient Echo Plural Contrast Imaging (GEPCI) technique. GEPCI data were reconstructed using previously developed algorithms allowing the separation of R2t*, a cellular-specific part of gradient echo MRI relaxation rate constant, from global R2* affected by BOLD effect and background gradients.

Genetically defined cellular correlates of the baseline brain MRI signal.

fMRI revolutionized neuroscience by allowing in vivo real-time detection of human brain activity. While the nature of the fMRI signal is understood as resulting from variations in the MRI signal due to brain-activity-induced changes in the blood oxygenation level (BOLD effect), these variations constitute a very minor part of a baseline MRI signal. Hence, the fundamental (and not addressed) questions are how underlying brain cellular composition defines this baseline MRI signal and how a baseline MRI signal relates to fMRI.

Single scan quantitative gradient recalled echo MRI for evaluation of tissue damage in lesions and normal appearing gray and white matter in multiple sclerosis.

Background: Multiple sclerosis (MS) is a chronic disease affecting the human central nervous system (CNS) and leading to neurologic disability. Although conventional MRI techniques can readily detect focal white matter (WM) lesions, it remains challenging to quantify tissue damage in normal-appearing gray matter (GM) and WM.

Purpose: To demonstrate that a new MRI biomarker, R2t*, can provide quantitative analysis of tissue damage across the brain in MS patients in a single scan.

Lorentzian effects in magnetic susceptibility mapping of anisotropic biological tissues.

The ultimate goal of MRI is to provide information on biological tissue microstructure and function. Quantitative Susceptibility Mapping (QSM) is one of the newer approaches for studying tissue microstructure by means of measuring phase of Gradient Recalled Echo (GRE) MRI signal. The fundamental question in the heart of this approach is: what is the relationship between the net phase/frequency of the GRE signal from an imaging voxel and the underlying tissue microstructure at the cellular and sub-cellular levels? In the presence of external magnetic field, biological media (e.

Phase-sensitive B mapping: Effects of relaxation and RF spoiling.

Purpose: To develop a phase-based B mapping technique accounting for the effects of imperfect RF spoiling and magnetization relaxation.

Theory And Methods: The technique is based on a multi-gradient-echo sequence with 2 successive orthogonal radiofrequency (RF) excitation pulses followed by the train of gradient echoes measurements. We have derived a theoretical expression relating the MR signal phase produced by the 2 successive RF pulses to the B field and B -related frequency shift.

Limbic system damage in MS: MRI assessment and correlations with clinical testing.

Volume loss in some limbic region structures has been observed in multiple sclerosis (MS) patients. However, in vivo evaluation of existing tissue cellular microstructure integrity has received less attention. The goal of studies reported here was to quantitatively assess loss of limbic system volumes and tissue integrity, and to evaluate associations of these measures with cognitive and physical dysfunction in MS patients.

What makes a good pediatric transplant lung: Insights from in vivo lung morphometry with hyperpolarized He magnetic resonance imaging.

Obtaining information on transplanted lung microstructure is an important part of the current care for monitoring transplant recipients. However, until now this information was only available from invasive lung biopsy. The objective of this study was to evaluate the use of an innovative non-invasive technique, in vivo lung morphometry with hyperpolarized ³He MRI-to characterize lung microstructure in the pediatric lung transplant population.