Advanced Neuroimaging Techniques and Applications

This study examines how exogenous sex hormones affect white matter aging in postmenopausal women using diffusion MRI data from the UK Biobank, finding steeper aging trajectories in hormone therapy users.

The paper creates a multimodal brain atlas for rhesus macaques combining structural and diffusion imaging data to enable consistent region identification across imaging modalities.

This study characterizes 'plis de passage' in the superior temporal sulcus using geometric features and finds they correlate with increased local structural connectivity.

This paper evaluates the reproducibility and fitting quality of high-resolution diffusion kurtosis imaging (DKI) at 3T using varying b-values and phantom data.

This study meta-analyzes MRI biomarkers of myelin to compare their correlation with histology, finding MT and relaxometry-based measures have the highest correlations.

The paper estimates gray and white matter volumes in human spinal cords using MRI and deep learning, finding small gray matter volumes comparable to a fingertip.

This study correlates diffusion kurtosis imaging (DKI) measurements with neurofilament density in macaque brains, showing higher MK and ND in prefrontal/precentral-postcentral cortex compared to temporal cortex.

This study uses advanced diffusion models and brain-age prediction to analyze white matter microstructure changes across adult lifespan, finding that advanced models provide sensitive measures of age-related changes.

This paper introduces a method to estimate orientation-specific relaxation-diffusion features using nonparametric Monte Carlo MRI signal inversion, enabling detailed analysis of white matter microstructure.

This study compares diffusion MRI metrics in simulated edema and fiber crossing, finding DBSI provides more accurate diffusivity and angle estimates than DTI and other methods.

This study identifies and characterizes the superior frontal longitudinal tract (SFLT) through tractography and postmortem dissection, revealing its anatomical patterns and spatial relationships.

Classifyber improves white matter bundle segmentation by combining atlas, connectivity, and geometry data into a linear model, showing robustness across diverse datasets.

This study applies shape analysis to diffusion MRI tractography data to quantify and compare structural features of human association pathways, revealing lateralization patterns and between-subject variation.

This study examines white matter development in children aged 9-13, finding increases in fibre density linked to puberty, attentional difficulties, and mental health issues.

This paper introduces a scanner harmonization method for diffusion MRI data using adaptive dictionary learning, preserving biological variability while reducing scanner-induced variability.

This paper shows that Nf1 deletion in oligodendrocytes causes brain structural and functional disruptions in mice, which are rescued by NOS inhibition.

This paper develops a data-driven framework using non-negative matrix factorisation to map structural connections in the neonatal brain and generates a cortical parcellation from 323 newborns.

The paper uses multimodal PCA on white matter imaging data to identify structural features linked to reading and age, finding no direct reading skill associations but age-related changes in microstructure.

This study evaluates how different preprocessing steps affect motion-related contamination in diffusion MRI structural connectivity estimates, finding that specific motion correction methods significantly reduce cross-subject correlations between motion and connectivity strength.

This study compares DTI and NODDI biomarkers in mTBI patients to assess white matter changes over time and their association with cognitive recovery.

This study examines age-related changes in the T1w/T2w ratio across the cortical surface in children and adolescents, linking it to cognitive development and sex differences.

This paper introduces a method to estimate multiple fiber orientation distributions in both white and grey matter using tissue-specific response functions and multi-shell diffusion MRI, improving cortical fiber tractography.

This paper introduces a 2D diffusion MRI framework to specifically assess axonal injury and spinal cord microenvironments, showing strong correlation with histological findings.

This paper introduces a novel Diffusion Histology Imaging (DHI) approach combining DBSI and machine learning to improve detection and classification of glioblastoma histopathology features.

This paper uses high-resolution MRI to visualize and characterize the human zona incerta and surrounding brain structures in vivo.

This study uses NODDI to examine age-related changes in neurite density and orientation dispersion in children's white matter, finding increases in density but no change in dispersion.

This paper introduces a Multi-Echo dMRI method to improve SNR and reduce noise bias in post-mortem diffusion MRI, validated on a chimpanzee brain.

The paper optimizes multi-shell diffusion MRI acquisition parameters using a data-driven approach, resulting in a specific protocol for neonatal imaging.

This paper proposes using two-flip angle DW-SSFP data and a Gamma distribution model to correct for B1 inhomogeneity and improve diffusivity estimates in post-mortem human brains at 7T.

This study shows that white matter maturation in the right preSMA correlates with improvements in motor response cancellation, with developmental plateaus around 13-14 years.