Characterization of Brain Abnormalities in Lactational Neurodevelopmental Poly I:C Rat Model of Schizophrenia and Depression Using Machine-Learning and Quantitative MRI.

Background: A recent neurodevelopmental rat model, utilizing lactational exposure to polyriboinosinic-polyribocytidilic acid (Poly I:C) leads to mimics of behavioral phenotypes resembling schizophrenia-like symptoms in male offspring and depression-like symptoms in female offspring.

Purpose: To identify mechanisms of neuronal abnormalities in lactational Poly I:C offspring using quantitative MRI (qMRI) tools.

Study Type: Prospective.

DeepEMC-T mapping: Deep learning-enabled T mapping based on echo modulation curve modeling.

Purpose: Echo modulation curve (EMC) modeling enables accurate quantification of T relaxation times in multi-echo spin-echo (MESE) imaging. The standard EMC-T mapping framework, however, requires sufficient echoes and cumbersome pixel-wise dictionary-matching steps. This work proposes a deep learning version of EMC-T mapping, called DeepEMC-T mapping, to efficiently estimate accurate T maps from fewer echoes.

A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla.

Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools.

Probing muscle recovery following downhill running using precise mapping of MRI T relaxation times.

Purpose: Postexercise recovery rate is a vital component of designing personalized training protocols and rehabilitation plans. Tracking exercise-induced muscle damage and recovery requires sensitive tools that can probe the muscles' state and composition noninvasively.

Methods: Twenty-four physically active males completed a running protocol consisting of a 60-min downhill run on a treadmill at -10% incline and 65% of maximal heart rate.

Estimation of subvoxel fat infiltration in neurodegenerative muscle disorders using quantitative multi-T analysis.

MRI's T relaxation time is a valuable biomarker for neuromuscular disorders and muscle dystrophies. One of the hallmarks of these pathologies is the infiltration of adipose tissue and a loss of muscle volume. This leads to a mixture of two signal components, from fat and from water, to appear in each imaged voxel, each having a specific T relaxation time.

Fast and accurate T mapping using Bloch simulations and low-rank plus sparse matrix decomposition.

Purpose: MRI's T relaxation time is one of the key contrast mechanisms for clinical diagnosis and prognosis of pathologies. Mapping this relaxation time, however, involves extensive scan times, which are needed to collect quantitative data, thereby impeding its integration into clinical routine. This study employs a low-rank plus sparse (L + S) signal decomposition approach in order to reconstruct accurate T-maps from highly undersampled multi-echo spin-echo (MESE) MRI data.

Psychophysical Evaluation of Visual vs. Computer-Aided Detection of Brain Lesions on Magnetic Resonance Images.

Background: Magnetic resonance imaging (MRI) diagnosis is usually performed by analyzing contrast-weighted images, where pathology is detected once it reached a certain visual threshold. Computer-aided diagnosis (CAD) has been proposed as a way for achieving higher sensitivity to early pathology.

Purpose: To compare conventional (i.

Mapping of magnetic resonance imaging's transverse relaxation time at low signal-to-noise ratio using Bloch simulations and principal component analysis image denoising.

High-resolution mapping of magnetic resonance imaging (MRI)'s transverse relaxation time (T ) can benefit many clinical applications by offering improved anatomic details, enhancing the ability to probe tissues' microarchitecture, and facilitating the identification of early pathology. Increasing spatial resolutions, however, decreases data's signal-to-noise ratio (SNR), particularly at clinical scan times. This impairs imaging quality, and the accuracy of subsequent radiological interpretation.

Quantification of Intra-Muscular Adipose Infiltration in Calf/Thigh MRI Using Fully and Weakly Supervised Semantic Segmentation.

Infiltration of fat into lower limb muscles is one of the key markers for the severity of muscle pathologies. The level of fat infiltration varies in its severity across and within patients, and it is traditionally estimated using visual radiologic inspection. Precise quantification of the severity and spatial distribution of this pathological process requires accurate segmentation of lower limb anatomy into muscle and fat.

Age Differences in Recovery Rate Following an Aerobic-Based Exercise Protocol Inducing Muscle Damage Among Amateur, Male Athletes.

Compare recovery rates between active young (Y) and middle-aged (MA) males up to 48H post aerobically based, exercise-induced muscle damage (EIMD) protocol. A secondary aim was to explore the relationships between changes in indices associated with EIMD and recovery throughout this timeframe. Twenty-eight Y ( = 14, 26.

Determining the internal orientation, degree of ordering, and volume of elongated nanocavities by NMR: Application to studies of plant stem.

This study investigates the fibril nanostructure of fresh celery samples by modeling the anisotropic behavior of the transverse relaxation time (T) in nuclear magnetic resonance (NMR). Experimental results are interpreted within the framework of a previously developed theory, which was successfully used to model the nanostructures of several biological tissues as a set of water filled nanocavities, hence explaining the anisotropy the T relaxation time in vivo. An important feature of this theory is to determine the degree of orientational ordering of the nanocavities, their characteristic volume, and their average direction with respect to the macroscopic sample.

Correcting for imaging gradients-related bias of T relaxation times at high-resolution MRI.

Purpose: High-resolution animal imaging is an integral part of preclinical drug development and the investigation of diseases' pathophysiology. Quantitative mapping of T relaxation times (qT ) is a valuable tool for both preclinical and research applications, providing high sensitivity to subtle tissue pathologies. High-resolution T mapping, however, suffers from severe underestimation of T values due to molecular diffusion.

Accelerated reconstruction of dictionary-based T relaxation maps based on dictionary compression and gradient descent search algorithms.

Background Quantitative T-relaxation-based contrast maps have shown to be highly beneficial for clinical diagnosis and follow-up. The generation of quantitative maps, however, is impaired by long acquisition times, and time-consuming post-processing schemes. The EMC platform is a dictionary-based technique, which involves simulating theoretical signal curves for different physical and experimental values, followed by matching the experimentally acquired signals to the set simulated ones.

Data-driven algorithm for myelin water imaging: Probing subvoxel compartmentation based on identification of spatially global tissue features.

Purpose: Multicomponent analysis of MRI T relaxation time (mcT ) is commonly used for estimating myelin content by separating the signal at each voxel into its underlying distribution of T values. This voxel-based approach is challenging due to the large ambiguity in the multi-T space and the low SNR of MRI signals. Herein, we present a data-driven mcT analysis, which utilizes the statistical strength of identifying spatially global mcT motifs in white matter segments before deconvolving the local signal at each voxel.

Quantitative platform for accurate and reproducible assessment of transverse (T ) relaxation time.

MRI's transverse relaxation time (T ) is sensitive to tissues' composition and pathological state. While variations in T values can be used as clinical biomarkers, it is challenging to quantify this parameter in vivo due to the complexity of the MRI signal model, differences in protocol implementations, and hardware imperfections. Herein, we provide a detailed analysis of the echo modulation curve (EMC) platform, offering accurate and reproducible mapping of T values, from 2D multi-slice multi-echo spin-echo (MESE) protocols.

Tissue Probability Based Registration of Diffusion-Weighted Magnetic Resonance Imaging.

Background: Current registration methods for diffusion-MRI (dMRI) data mostly focus on white matter (WM) areas. Recently, dMRI has been employed for the characterization of gray matter (GM) microstructure, emphasizing the need for registration methods that consider all tissue types.

Purpose: To develop a dMRI registration method based on GM, WM, and cerebrospinal fluid (CSF) tissue probability maps (TPMs).

Novel multimodal molecular imaging of Vitamin H (Biotin) transporter activity in the murine placenta.

Vitamin H (biotin) is delivered to the fetus transplacentally by an active biotin-transport mechanism and is critical for fetal development. Our objective was to develop a comprehensive MRI technique for mapping biotin transporter activity in the murine placenta. Visualization of transporter activity can employ MRI's unique T*-dependent signal 'off-switch', which is triggered by transporter mediated aggregation of biotinylated contrast agent (b-BSA-Gd-DTPA).

T2 Mapping Values in Postmeniscectomy Knee Articular Cartilage after Running: Early Signs of Osteoarthritis?

Loading on the joints during running may have a deleterious effect on post-partial meniscectomy knee cartilage, leading to osteoarthritis. Utilizing T2-mapping measurements before and after running may enable the observation of changes in the articular cartilage of the postmeniscectomy knees compared with healthy knees. After medial partial meniscectomy, 12 volunteers underwent magnetic resonance imaging (MRI) of the both knees, before and immediately after 30 minutes of running.

A New Method for Cartilage Evaluation in Femoroacetabular Impingement Using Quantitative T2 Magnetic Resonance Imaging: Preliminary Validation against Arthroscopic Findings.

Objective: The outcome of arthroscopic treatment for femoroacetabular impingement (FAI) depends on the preoperative status of the hip cartilage. Quantitative T2 can detect early biochemical cartilage changes, but its routine implementation is challenging. Furthermore, intrinsic T2 variability between patients makes it difficult to define a threshold to identify cartilage lesions.

Analysis of magnetization transfer (MT) influence on quantitative mapping of T relaxation time.

Purpose: Multi-echo spin-echo (MESE) protocol is the most effective tool for mapping T relaxation in vivo. Still, MESE extensive use of radiofrequency pulses causes magnetization transfer (MT)-related bias of the water signal, instigated by the presence of macromolecules (MMP). Here, we analyze the effects of MT on MESE signal, alongside their impact on quantitative T measurements.

New rapid, accurate T quantification detects pathology in normal-appearing brain regions of relapsing-remitting MS patients.

Introduction: Quantitative T mapping may provide an objective biomarker for occult nervous tissue pathology in relapsing-remitting multiple sclerosis (RRMS). We applied a novel echo modulation curve (EMC) algorithm to identify T changes in normal-appearing brain regions of subjects with RRMS (N = 27) compared to age-matched controls (N = 38).

Methods: The EMC algorithm uses Bloch simulations to model T decay curves in multi-spin-echo MRI sequences, independent of scanner, and scan-settings.

Accelerated and motion-robust in vivo T2 mapping from radially undersampled data using bloch-simulation-based iterative reconstruction.

Purpose: Development of a quantitative transverse relaxation time (T2)-mapping platform that operates at clinically feasible timescales by employing advanced image reconstruction of radially undersampled multi spin-echo (MSE) datasets.

Methods: Data was acquired on phantom and in vivo at 3 Tesla using MSE protocols employing radial k-space sampling trajectories. In order to overcome the nontrivial spin evolution associated with MSE protocols, a numerical signal model was precalculated based on Bloch simulations of the actual pulse-sequence scheme used in the acquisition process.

Rapid and accurate T2 mapping from multi-spin-echo data using Bloch-simulation-based reconstruction.

Purpose: Quantitative T2 -relaxation-based contrast has the potential to provide valuable clinical information. Practical T2 -mapping, however, is impaired either by prohibitively long acquisition times or by contamination of fast multiecho protocols by stimulated and indirect echoes. This work presents a novel postprocessing approach aiming to overcome the common penalties associated with multiecho protocols, and enabling rapid and accurate mapping of T2 relaxation values.