Advanced MRI Techniques and Applications

MR-AIV reveals in-vivo brain-wide fluid flow with physics-informed AI

This paper introduces MR-AIV, a physics-informed AI method to reconstruct brain-wide fluid velocity fields from MRI, revealing distinct transport mechanisms in health and disease.

TRACC-PHYSIO: Time-domain Resolution-Aligned Cross-Correlation to estimate PHYSIOlogical coupling and time delays in dynamic MRI

TRACC-PHYSIO estimates physiological coupling and time delays in dynamic MRI without requiring fast acquisition, validated through simulations.

Contrast-induced changes in chemical exchange saturation transfer MRI differentiate tumor progression from pseudoprogression

This paper demonstrates that amine-CEST MRI with Gd-DOTA can distinguish macrophages from cancer cells by detecting Gd-DOTA uptake, aiding in differentiating pseudo-progression from true tumor progression in cancer patients.

In Vivo 4D Oxy-Wavelet MRI as a Non-Invasive Biomarker of Brain Mitochondrial Function across the Lifespan

This paper introduces 4D Oxy-wavelet MRI to non-invasively assess mitochondrial function in living brains across the lifespan, validated in mouse models and with human feasibility data.

Beyond iron concentration: iron aggregation shapes quantitative MRI in the human brain

This study uses quantitative MRI to show that iron aggregation, not just concentration, drives MRI contrast changes in ACP patients.

From 3D Time-of-Flight Angiography to Accelerated 4D Arterial Spin Labeling Angiography: A Fast Few-Shot Transfer Learning Approach

This paper develops a fast few-shot transfer learning approach for reconstructing highly accelerated 4D arterial spin labeling angiography using simulated data and minimal experimental data.

Probabilistic Multi-site MR Image Harmonization via Feature Preserving Conditional Generative Adversarial Networks

This paper introduces a feature-preserving conditional GAN for multi-site MRI harmonization, showing improved performance over existing methods.

Quantifying cardiac, respiratory, and slow vasomotion components of CSF motion from fMRI inflow effects

Towards harmonized spectral quantification in MRSI: Comparative analysis of Backward-Linear-Predicted and original 1H-FID-MRSI dephased data

The paper compares Backward-Linear-Prediction (BLP) and original 1H-FID-MRSI data to assess quantification biases caused by acquisition delay and shows BLP improves consistency across different delays.

Quality assessment and control of unprocessed anatomical, functional, and diffusion MRI of the human brain using MRIQC

The paper introduces a protocol for assessing and controlling MRI data quality using MRIQC software, focusing on anatomical, functional, and diffusion MRI scans of the human brain.

Ultrafast fMRI detects age-related changes in harmonics of cardiac pulsations in the brain at 7 T

This paper develops an ultra-fast fMRI method at 7 T to detect age-related changes in cardiac pulsation harmonics in the brain.

MR Spectroscopy without Water Suppression using the Gradient Impulse Response Function

This paper introduces a method to correct artefactual sidebands in non-water-suppressed MR spectroscopy using the Gradient Impulse Response Function, improving metabolite signal recovery.

Manganese Accumulation for Genetically Induced Contrast (MAGIC) MRI in the brain across species

The paper introduces MAGIC MRI, a gene-based reporter system for non-invasive neural tracing in vivo, validated in rodents and rhesus macaques.

Functional MRI of the Human Hippocampus at 10.5T: Pushing the Boundaries of Spatial Resolution

This paper uses 10.5T fMRI to achieve 0.5 mm isotropic resolution, enabling detailed study of hippocampal function and high-precision clinical applications.

Distant Dipoles: A Multi-Parameter and Multi-Objective Analysis of RF Coil Performance For 7T Body MRI

This paper evaluates RF coil performance for 7T MRI using multi-parameter analysis, finding that increasing distance-to-load improves pSAR efficiency and homogeneity with minimal power efficiency loss.

GABA-Edited Magnetic Resonance Spectroscopy Deep Learning Quality Assessment Framework

This paper develops a deep learning framework to improve GABA-edited MRS quality by optimizing transient averaging based on quality scores.

Opposing BOLD signals and oxygen metabolism largely arise from statistical uncertainty in metabolic estimates

The paper reanalyzes BOLD and metabolic data, finding that apparent discordance between BOLD signals and metabolic estimates is due to statistical uncertainty rather than physiological reversal.

Characterization and Validation of Compressed Sensing for Time-of-Flight MRI Angiography of the Human Brain at 3T and 7T

This study evaluates compressed sensing in TOF-MRA at 3T and 7T, finding significant differences in CNR and vessel diameter measurements across CS factors.

Ultra-high field microstructural MRI of living cortical organoids

This paper develops a high-resolution MRI platform for live cortical organoids, revealing microstructural features and temporal changes with 20 µm resolution.

Enabling brain-wide mapping of layer-specific functional connectivity at 3T via layer-dependent fMRI with draining-vein suppression

This paper develops a VN fMRI sequence to enable brain-wide mapping of layer-specific functional connectivity at 3T, showing distinct connectivity patterns in cortical layers.

Structural Characterization of Cardiac Purkinje Fibers Using Inhomogeneous Magnetization Transfer (ihMT): A proof of Concept MRI-Histology Approach

This paper uses ihMT MRI to differentiate subregions of cardiac Purkinje fibers in sheep hearts, showing higher ihMTR in free-running PF compared to insertion points and myocardium, with histology confirming collagen differences.

Robust MR-AIV: A Systematic Study of Robustness Improvement and Sensitivity Analysis of MR-AIV

This paper improves and evaluates MR-AIV, a physics-informed neural network for inferring brain fluid dynamics from MRI, showing stable results across different modeling choices.

MRI-Based Blood Clot Phenotyping: An In Vitro Study

This study shows MRI can predict blood clot composition and contraction state using radiomic features, supporting its use for pre-interventional clot phenotyping.

Bridging the gap with invasive imaging: promises and challenges of a new generation of ultrahigh resolution fMRI

This paper explores the potential and challenges of ultrahigh resolution fMRI at 10.5 Tesla to study cortical layers with improved resolution compared to standard methods.

A Scalable fMRI Estimate of Basal Ganglia Brain Tissue Iron for Use in Developmental and Translational Neuroscience

The paper introduces a scalable method to estimate basal ganglia brain tissue iron using fMRI data, validated across developmental datasets and applicable to large-scale repositories.

Benchmarking the Impact of Anatomical Segmentation on In Vivo Magnetic Resonance Spectroscopy

This study benchmarks how different anatomical segmentation tools affect MRS-derived metabolite concentration estimates in brain imaging.

Mesoscopic whole-brain T2*-weighted and associated quantitative MRI in healthy humans at 10.5 T

This paper demonstrates the feasibility of mesoscopic whole-brain T2*-weighted MRI at 10.5 T using advanced coils and motion-robust sequences, showing improved SNR and quantification precision compared to 7 T.

High-Field Multinuclear MRI Reveals Sodium Relaxation Heterogeneity in Cortical Organoids

This study uses high-field multinuclear MRI to analyze sodium relaxation heterogeneity in cortical organoids, revealing distinct relaxation components and spatial microenvironment variations.

A Numerical Alternative to MR Thermometry for Safety Validation of Multi-Channel RF Transmit Coils

The paper introduces a numerical method to quantify SAR prediction errors for MRI safety validation, avoiding the need for MR thermometry.

A new fMRI quality metric using multi-echo information: Theory, validation and implications

This paper introduces pBOLD, a new fMRI quality metric that quantifies BOLD dominance in multi-echo scans, validates it on datasets, and shows its utility in predicting phenotypes.