Publications by authors named "D Yablonskiy"
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.
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.
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.
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.
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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