Advanced MRI Techniques and Applications

The paper shows acute hyperglycemia increases non-oxidative glucose consumption in specific brain regions without altering cerebral blood flow or oxygen metabolism.

The paper introduces a Python toolbox, SMART_MRS, to simulate common artifacts in GABA-edited MRS data, enhancing the diversity and quality of simulated data.

This paper optimizes PCASL parameters for 7 T whole-brain perfusion imaging, achieving higher SNR efficiency and reduced RF power usage.

This study benchmarks four cervical spinal cord RF coils at 7 T MRI across multiple centers, identifying performance differences and proposing a standardized evaluation protocol.

This paper validates a motion correction technique, DISORDER, for pediatric brain morphometry, showing improved reliability for motion-degraded scans compared to conventional MPRAGE.

This paper demonstrates non-exponential transverse relaxation decay in human subcortical grey matter using MRI, enabling characterization of magnetic inclusions with potential applications in Parkinson's disease.

This paper evaluates the PETRA sequence at 7T for ultrashort-T2* mapping, showing high SNR and acceptable curve-fitting results for sub-millisecond T2* substances.

The paper measures metabolite T1 relaxation times in healthy adults across age groups and finds age-related decreases in several metabolites in specific brain regions.

This paper identifies and mitigates Fuzzy Ripple artifacts in high-resolution fMRI, enabling sub-millimeter resolution and faster acquisition protocols.

This paper develops a PDFF MRI technique to quantify bone marrow fat fraction in mice, showing significant differences with age and radiation, validated by histology.

This paper introduces a rapid fMRI acquisition method, T1234, that provides distortion-matched structural reference data, improving registration accuracy with functional scans.

This study assesses cerebral blood flow responses to hypoxia and hypercapnia using MRI, finding poor reliability in hypoxic CVR and paradoxical responses not explained by CO2 changes.

This study shows that MRI R2* changes reflect inflammation in disconnected brain regions after stroke, both in humans and mice, linking disconnection to iron accumulation and microglial activation.

The paper compares RF coil combination methods for MRS data, finding that noise-decorrelation methods improve SNR for detecting low concentration metabolites like GABA.

The paper develops a non-invasive marmoset holder for small-bore MRI to enable awake fMRI studies and evaluates its ability to capture auditory responses.

DeepPrep accelerates neuroimaging preprocessing by 11-fold using deep learning, outperforming current state-of-the-art methods in scalability and robustness.

The paper uses HP-13C MRI to show increased 13C-lactate signal in brain regions activated during a visual task compared to a control condition.

This study measures NAD+ T1 and T2 relaxation times in human brain using 7 T 1H MRS and quantifies the uncertainty propagation in NAD+ concentration.

The paper develops a new RF pulse shape for CEST MRI using gradient ascent optimization, showing improved contrast in phantoms and live mice compared to Gaussian and Fermi pulses.

This paper demonstrates that zero-echo time (ZTE) imaging can map whole brain activity in mice without signal loss in the amygdala, showing acute and latent activation patterns following noxious stimulation.

The paper provides open-access CAD files and software for marmoset neuroscience apparatus, reducing the need for individual lab development.

This paper introduces BOLDswimsuite, an open-source Python toolbox for forward modeling of the BOLD fMRI signal, providing modular components and flexibility for simulations.

This study uses quantitative susceptibility mapping to distinguish microgliosis and tau deposition in a mouse model of tauopathy by analyzing paramagnetic and diamagnetic susceptibility components.

This paper introduces a method to distinguish BOLD and non-BOLD signals in fMRI by analyzing cross-cortical depth delay patterns, demonstrating its effectiveness with visual task data.

This paper introduces a non-invasive restraint for awake mouse fMRI that is compatible with multi-modal techniques, showing comparable data quality to conventional methods.

This study investigates how venous bias affects hippocampal laminar fMRI responses and establishes a benchmark experiment for robust single-subject activation.

This paper develops a dynamic model and deep learning framework to estimate cerebrospinal fluid velocity from fMRI data, enabling physically interpretable flow measurements.

This paper improves cerebrovascular brain age predictions by harmonizing arterial spin labeling (ASL) features across multiple cohorts using various methods, showing that ASL-specific harmonization enhances model performance.

The paper develops a processing pipeline for arterial spin labelling MRI data from the Human Connectome Project Lifespan and finds age-related differences in cerebral perfusion and transit times.

This study establishes normative trajectories of R1, R2*, and magnetic susceptibility in the basal ganglia across healthy ageing using Gaussian Process Regression.