Publications by authors named "Yablonskiy D"

Article Synopsis
  • The study investigates how thalamic tissue damage occurs in multiple sclerosis (MS) patients, following a specific gradient from the ventricular surface, using quantitative gradient-recalled echo (qGRE) MRI.
  • Results showed that MS patients had a steeper gradient of tissue integrity compared to healthy controls, and this gradient was linked to longer disease duration and higher disability levels.
  • These findings support the idea that the damage in MS follows a 'surface-in' pattern and may involve a process influenced by cerebrospinal fluid (CSF), affecting both sides of the thalamus symmetrically.
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Article Synopsis
  • Robust methods are crucial for evaluating new Alzheimer Disease therapies to speed up drug discovery.
  • A novel quantitative Gradient Recalled Echo (qGRE) MRI technique can non-invasively track neuronal loss in the hippocampus of a mouse model (Tg4510) of Alzheimer’s, showing a significant decrease in neuronal density over time.
  • The findings suggest that qGRE can be used effectively in preclinical research to monitor neurodegeneration and assess drug effects, demonstrated by clear correlations between decreases in neuronal markers and changes in myelin content.
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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.

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Article Synopsis
  • MOGAD is a CNS disorder that resembles multiple sclerosis (MS) and can be mistakenly diagnosed as such, with both conditions showing similar patterns of recurring symptoms and inflammatory lesions.
  • The study utilized quantitative gradient-recalled echo (qGRE) MRI to compare tissue damage in the brains of MOGAD patients with those of MS patients and healthy controls, focusing on changes in various brain regions.
  • Results indicated that MOGAD patients had less severe tissue damage than MS patients in non-lesional areas, suggesting detectable abnormalities that standard MRI may miss, highlighting the differences in these disorders.
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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.

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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.

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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.

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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.

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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.

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Article Synopsis
  • - The study focuses on finding effective imaging biomarkers to assess progression in multiple sclerosis (MS) using quantitative gradient recalled echo (qGRE) MRI to evaluate microstructural damage.
  • - Researchers compared qGRE-derived R2t* with traditional metrics like atrophy and lesion burden in various MS patient groups and healthy controls over 45 months.
  • - Results showed that R2t* reductions were strongly linked to clinical progression in patients, indicating it may serve as a more reliable biomarker of MS progression than just measuring lesions or brain atrophy.
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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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Background: Alzheimer disease (AD) affects at least 5 million individuals in the USA alone stimulating an intense search for disease prevention and treatment therapies as well as for diagnostic techniques allowing early identification of AD during a long pre-symptomatic period that can be used for the initiation of prevention trials of disease-modifying therapies in asymptomatic individuals.

Methods: Our approach to developing such techniques is based on the Gradient Echo Plural Contrast Imaging (GEPCI) technique that provides quantitative in vivo measurements of several brain-tissue-specific characteristics of the gradient echo MRI signal (GEPCI metrics) that depend on the integrity of brain tissue cellular structure. Preliminary data were obtained from 34 participants selected from the studies of aging and dementia at the Knight Alzheimer's Disease Research Center at Washington University in St.

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Quantitative susceptibility mapping is a potentially powerful technique for mapping tissue magnetic susceptibility from gradient recalled echo (GRE) MRI signal phase. In this review, we present up-to-date theoretical developments in analyzing the relationships between GRE signal phase and the underlying tissue microstructure and magnetic susceptibility at the cellular level. Two important phenomena contributing to the GRE signal phase are at the focus of this review - tissue structural anisotropy (e.

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Establishing baseline MRI biomarkers for normal brain aging is significant and valuable for separating normal changes in the brain structure and function from different neurological diseases. In this paper for the first time we have simultaneously measured a variety of tissue specific contributions defining R2* relaxation of the gradient recalled echo (GRE) MRI signal in human brains of healthy adults (ages 22 to 74years) and related these measurements to tissue structural and functional properties. This was accomplished by separating tissue (R2t(⁎)) and extravascular BOLD contributions to the total tissue specific GRE MRI signal decay (R2(⁎)) using an advanced version of previously developed Gradient Echo Plural Contrast Imaging (GEPCI) approach and the acquisition and post-processing methods that allowed the minimization of artifacts related to macroscopic magnetic field inhomogeneities, and physiological fluctuations.

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