Multiparametric MRI dataset for susceptibility-based radiomic feature extraction and analysis.

Multiple sclerosis (MS) is a progressive demyelinating disease impacting the central nervous system. Conventional Magnetic Resonance Imaging (MRI) techniques (e.g.

Generalizing the Enhanced-Deep-Super-Resolution Neural Network to Brain MR Images: A Retrospective Study on the Cam-CAN Dataset.

The Enhanced-Deep-Super-Resolution (EDSR) model is a state-of-the-art convolutional neural network suitable for improving image spatial resolution. It was previously trained with general-purpose pictures and then, in this work, tested on biomedical magnetic resonance (MR) images, comparing the network outcomes with traditional up-sampling techniques. We explored possible changes in the model response when different MR sequences were analyzed.

Active mobility and mental health: A scoping review towards a healthier world.

Research has proven that engaging in active mobility (AM), namely walking and cycling for transportation, significantly enhances physical activity levels, leading to better physical health. It is still unclear whether AM could also offer any mental health benefits. This scoping review aims to provide a comprehensive understanding of the current knowledge on the relationship between AM and mental health, given its crucial role in public health.

Magnetic resonance imaging scoring system of the lower limbs in adult patients with suspected idiopathic inflammatory myopathy.

Purpose: We aim to propose a visual quantitative score for muscle edema in lower limb MRI to contribute to the diagnosis of idiopathic inflammatory myopathy (IIM).

Material And Methods: We retrospectively evaluated 85 consecutive patients (mean age 57.4 ± 13.

Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis.

Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging technique detecting magnetic properties. When analysed with radiomic techniques that exploit its intrinsic quantitative nature, QSM may furnish biomarkers to facilitate early diagnosis of MS and timely assessment of progression.

Methods of diffusion MRI tractography for localization of the anterior optic pathway: A systematic review of validated methods.

The anterior optic pathway (AOP) is a system of three structures (optic nerves, optic chiasma, and optic tracts) that convey visual stimuli from the retina to the lateral geniculate nuclei. A successful reconstruction of the AOP using tractography could be helpful in several clinical scenarios, from presurgical planning and neuronavigation of sellar and parasellar surgery to monitoring the stage of fiber degeneration both in acute (e.g.

Convolutional Neural Network Techniques for Brain Tumor Classification (from 2015 to 2022): Review, Challenges, and Future Perspectives.

Convolutional neural networks (CNNs) constitute a widely used deep learning approach that has frequently been applied to the problem of brain tumor diagnosis. Such techniques still face some critical challenges in moving towards clinic application. The main objective of this work is to present a comprehensive review of studies using CNN architectures to classify brain tumors using MR images with the aim of identifying useful strategies for and possible impediments in the development of this technology.

Multishell Diffusion MR Tractography Yields Morphological and Microstructural Information of the Anterior Optic Pathway: A Proof-of-Concept Study in Patients with Leber's Hereditary Optic Neuropathy.

Tractography based on multishell diffusion-weighted magnetic resonance imaging (DWI) can be used to estimate the course of myelinated white matter tracts and nerves, yielding valuable information regarding normal anatomy and variability. DWI is sensitive to the local tissue microstructure, so tractography can be used to estimate tissue properties within nerve tracts at a resolution of millimeters. This study aimed to test the applicability of the method using a disease with a well-established pattern of myelinated nerve involvement.

Molecular biomarkers correlate with brain grey and white matter changes in patients with mitochondrial m.3243A > G mutation.

Introduction: The mitochondrial DNA (mtDNA) m.3243A > G mutation in the MT-TL1 gene results in a multi-systemic disease, that is commonly associated with neurodegenerative changes in the brain.

Methods: Seventeen patients harboring the m3243A > G mutation were enrolled (age 43.

Brain Structure and Degeneration Staging in Friedreich Ataxia: Magnetic Resonance Imaging Volumetrics from the ENIGMA-Ataxia Working Group.

Objective: Friedreich ataxia (FRDA) is an inherited neurological disease defined by progressive movement incoordination. We undertook a comprehensive characterization of the spatial profile and progressive evolution of structural brain abnormalities in people with FRDA.

Methods: A coordinated international analysis of regional brain volume using magnetic resonance imaging data charted the whole-brain profile, interindividual variability, and temporal staging of structural brain differences in 248 individuals with FRDA and 262 healthy controls.

A deep learning approach for magnetic resonance fingerprinting: Scaling capabilities and good training practices investigated by simulations.

MR fingerprinting (MRF) is an innovative approach to quantitative MRI. A typical disadvantage of dictionary-based MRF is the explosive growth of the dictionary as a function of the number of reconstructed parameters, an instance of the curse of dimensionality, which determines an explosion of resource requirements. In this work, we describe a deep learning approach for MRF parameter map reconstruction using a fully connected architecture.

The Combination of Metabolic Posterior Cingulate Cortical Abnormalities and Structural Asymmetries Improves the Differential Diagnosis Between Primary Progressive Aphasia and Alzheimer's Disease.

Differential diagnosis between primary progressive aphasia (PPA) and Alzheimer's disease (AD) could be difficult if based on clinical grounds alone. We evaluated the combination of proton MR spectroscopy of posterior cingulate cortex (PCC) and quantitative structural imaging asymmetries to differentiate PPA from AD patients. A greater left-lateralized temporo-parietal atrophy (higher accuracy for the PCC, 81.

Brain MRS correlates with mitochondrial dysfunction biomarkers in MELAS-associated mtDNA mutations.

Objective: The purpose of this study was to investigate correlations between brain proton magnetic resonance spectroscopy ( H-MRS) findings with serum biomarkers and heteroplasmy of mitochondrial DNA (mtDNA) mutations. This study enrolled patients carrying mtDNA mutations associated with Mitochondrial Encephalomyopathy, Lactic Acidosis, and Stroke-like episodes (MELAS), and MELAS-Spectrum Syndrome (MSS).

Methods: Consecutive patients carrying mtDNA mutations associated with MELAS and MSS were recruited and their serum concentrations of lactate, alanine, and heteroplasmic mtDNA mutant load were evaluated.

From Neurosurgical Planning to Histopathological Brain Tumor Characterization: Potentialities of Arcuate Fasciculus Along-Tract Diffusion Tensor Imaging Tractography Measures.

Tractography has been widely adopted to improve brain gliomas' surgical planning and guide their resection. This study aimed to evaluate state-of-the-art of arcuate fasciculus (AF) tractography for surgical planning and explore the role of along-tract analyses for characterizing tumor histopathology. High angular resolution diffusion imaging (HARDI) images were acquired for nine patients with tumors located in or near language areas (age: 41 ± 14 years, mean ± standard deviation; five males) and 32 healthy volunteers (age: 39 ± 16 years; 16 males).

Brain functional MRI responses to blue light stimulation in Leber's hereditary optic neuropathy.

Melanopsin retinal ganglion cells (mRGCs) are intrinsically photosensitive photoreceptors contributing both to image and non-image-forming (NIF) functions of the eye. They convey light signal to the brain to modulate circadian entrainment, sleep, alertness, cognition, brightness perception and coarse vision. Given that rods and cones also contribute to all these impacts of light, isolating mRGC visual and NIF roles in humans is challenging so that mRGC functions remains to be fully characterized.

Single-sided NMR to estimate morphological parameters of the trabecular bone structure.

Purpose: Single-sided H-NMR is proposed for the estimation of morphological parameters of trabecular bone, and potentially the detection of pathophysiological alterations of bone structure. In this study, a new methodology was used to estimate such parameters without using an external reference signal, and to study intratrabecular and intertrabecular porosities, with a view to eventually scanning patients.

Methods: Animal trabecular bone samples were analyzed by a single-sided device.

L-Dopa Modulation of Brain Connectivity in Parkinson's Disease Patients: A Pilot EEG-fMRI Study.

Studies of functional neurosurgery and electroencephalography in Parkinson's disease have demonstrated abnormally synchronous activity between basal ganglia and motor cortex. Functional neuroimaging studies investigated brain dysfunction during motor task or resting state and primarily have shown altered patterns of activation and connectivity for motor areas. L-dopa administration relatively normalized these functional alterations.

Stridor-related gray matter alterations in multiple system atrophy: A pilot study.

Introduction: The neuroanatomical substrate of stridor associated with Multiple System Atrophy (MSA) remains unclear. We evaluated stridor-related gray matter (GM) changes in MSA.

Methods: 36 MSA patients underwent standardized nocturnal video-polysomnography and brain MRI.

Along-tract analysis of the arcuate fasciculus using the Laplacian operator to evaluate different tractography methods.

Purpose: We propose a new along-tract algorithm to compare different tractography algorithms in tract curvature mapping and along-tract analysis of the arcuate fasciculus (AF). In particular, we quantified along-tract diffusion parameters and AF spatial distribution evaluating hemispheric asymmetries in a group of healthy subjects.

Methods: The AF was bilaterally reconstructed in a group of 29 healthy subjects using the probabilistic ball-and-sticks model, and both deterministic and probabilistic constrained spherical deconvolution.

Brain functional connectivity in sleep-related hypermotor epilepsy.

Objectives: To evaluate functional connectivity (FC) in patients with sleep-related hypermotor epilepsy (SHE) compared to healthy controls.

Methods: Resting state fMRI was performed in 13 patients with a clinical diagnosis of SHE (age = 38.3 ± 11.

Mitochondrial dysfunction in myotonic dystrophy type 1.

The pathophysiological mechanism linking the nucleotide expansion in the DMPK gene to the clinical manifestations of myotonic dystrophy type 1 (DM1) is still unclear. In vitro studies demonstrate DMPK involvement in the redox homeostasis of cells and the mitochondrial dysfunction in DM1, but in vivo investigations of oxidative metabolism in skeletal muscle have provided ambiguous results and have never been performed in the brain. Twenty-five DM1 patients (14M, 39 ± 11years) underwent brain proton MR spectroscopy (H-MRS), and sixteen cases (9M, 40 ± 13 years old) also calf muscle phosphorus MRS (P-MRS).

Multi-class parkinsonian disorders classification with quantitative MR markers and graph-based features using support vector machines.

Background And Purpose: In this study we attempt to automatically classify individual patients with different parkinsonian disorders, making use of pattern recognition techniques to distinguish among several forms of parkinsonisms (multi-class classification), based on a set of binary classifiers that discriminate each disorder from all others.

Methods: We combine diffusion tensor imaging, proton spectroscopy and morphometric-volumetric data to obtain MR quantitative markers, which are provided to support vector machines with the aim of recognizing the different parkinsonian disorders. Feature selection is used to find the most important features for classification.