Camera-based Prospective Motion Correction in Paediatric Epilepsy Patients Enables EEG-fMRI Localization Even in High-motion States.

Background: EEG-fMRI is a useful additional test to localize the epileptogenic zone (EZ) particularly in MRI negative cases. However subject motion presents a particular challenge owing to its large effects on both MRI and EEG signal. Traditionally it is assumed that prospective motion correction (PMC) of fMRI precludes EEG artifact correction.

Quantitative MRI susceptibility mapping reveals cortical signatures of changes in iron, calcium and zinc in malformations of cortical development in children with drug-resistant epilepsy.

Objective: Malformations of cortical development (MCD), including focal cortical dysplasia (FCD), are the most common cause of drug-resistant focal epilepsy in children. Histopathological lesion characterisation demonstrates abnormal cell types and lamination, alterations in myelin (typically co-localised with iron), and sometimes calcification. Quantitative susceptibility mapping (QSM) is an emerging MRI technique that measures tissue magnetic susceptibility (χ) reflecting it's mineral composition.

Predictors of motor outcome after childhood arterial ischemic stroke.

Aim: To identify clinical and radiological predictors of long-term motor outcome after childhood-onset arterial ischemic stroke (AIS) in the middle cerebral artery (MCA) territory.

Method: Medical records of 69 children (36 females, 33 males; median age at index AIS 3y 3mo, range: 1mo-16y) who presented to Great Ormond Street Hospital with first AIS in the MCA territory were reviewed retrospectively. Cases were categorized using the Childhood AIS Standardized Classification and Diagnostic Evaluation (CASCADE).

Planning stereoelectroencephalography using automated lesion detection: Retrospective feasibility study.

Objective: This retrospective, cross-sectional study evaluated the feasibility and potential benefits of incorporating deep-learning on structural magnetic resonance imaging (MRI) into planning stereoelectroencephalography (sEEG) implantation in pediatric patients with diagnostically complex drug-resistant epilepsy. This study aimed to assess the degree of colocalization between automated lesion detection and the seizure onset zone (SOZ) as assessed by sEEG.

Methods: A neural network classifier was applied to cortical features from MRI data from three cohorts.

Multiparametric mapping in post-mortem perinatal MRI: a feasibility study.

Objectives: To demonstrate feasibility of a 3 T multiparametric mapping (MPM) quantitative pipeline for perinatal post-mortem MR (PMMR) imaging.

Methods: Whole body quantitative PMMR imaging was acquired in four cases, mean gestational age 34 weeks, range (29-38 weeks) on a 3 T Siemens Prisma scanner. A multicontrast protocol yielded proton density, T and magnetic transfer (MT) weighted multi-echo images obtained from variable flip angle (FA) 3D fast low angle single-shot (FLASH) acquisitions, radiofrequency transmit field map and one B field map alongside four MT weighted acquisitions with saturation pulses of 180, 220, 260 and 300 degrees were acquired, all at 1 mm isotropic resolution.

Neuro-Clinical Signatures of Language Impairments after Acute Stroke: A VBQ Analysis of Quantitative Native CT Scans.

Objectives: Ischemic stroke affects language production and/or comprehension and leads to devastating long-term consequences for patients and their families. Previous studies have shown that neuroimaging can increase our knowledge of the basic mechanisms of language recovery. Currently, models for predicting patients' outcomes have limited use in the clinic for the evaluation and optimization of rehabilitative strategies mostly because that are often based on high-resolution magnetic resonance imaging (MRI) data, which are not always possible to carry out in the clinical routine.

MRI profiling of focal cortical dysplasia using multi-compartment diffusion models.

Objective: Focal cortical dysplasia (FCD) lesion detection and subtyping remain challenging on conventional MRI. New diffusion models such as the spherical mean technique (SMT) and neurite orientation dispersion and density imaging (NODDI) provide measurements that potentially produce more specific maps of abnormal tissue microstructure. This study aims to assess the SMT and NODDI maps for computational and radiological lesion characterization compared to standard fractional anisotropy (FA) and mean diffusivity (MD).

Spatial Resolution and Imaging Encoding fMRI Settings for Optimal Cortical and Subcortical Motor Somatotopy in the Human Brain.

There is much controversy about the optimal trade-off between blood-oxygen-level-dependent (BOLD) sensitivity and spatial precision in experiments on brain's topology properties using functional magnetic resonance imaging (fMRI). The sparse empirical evidence and regional specificity of these interactions pose a practical burden for the choice of imaging protocol parameters. Here, we test in a motor somatotopy experiment the impact of fMRI spatial resolution on differentiation between body part representations in cortex and subcortical structures.

The Combination of DAT-SPECT, Structural and Diffusion MRI Predicts Clinical Progression in Parkinson's Disease.

There is an increasing interest in identifying non-invasive biomarkers of disease severity and prognosis in idiopathic Parkinson's disease (PD). Dopamine-transporter SPECT (DAT-SPECT), diffusion tensor imaging (DTI), and structural magnetic resonance imaging (sMRI) provide unique information about the brain's neurotransmitter and microstructural properties. In this study, we evaluate the relative and combined capability of these imaging modalities to predict symptom severity and clinical progression in PD patients.

Radiology of Mummies.

In the past, autoptic examinations were usually performed for research. This type of examination, for obvious reasons, did not appeal to paleopathologists as these procedures potentially damaged the finds destined to musealization. Since the discovery of X-ray, radiology has been used to study mummies as a noninvasive technique.

Flexible proton density (PD) mapping using multi-contrast variable flip angle (VFA) data.

Quantitative proton density (PD) maps measure the amount of free water, which is important for non-invasive tissue characterization in pathology and across lifespan. PD mapping requires the estimation and subsequent removal of factors influencing the signal intensity other than PD. These factors include the T1, T2* relaxation effects, transmit field inhomogeneities, receiver coil sensitivity profile (RP) and the spatially invariant factor that is required to scale the data.

Towards in vivo focal cortical dysplasia phenotyping using quantitative MRI.

Focal cortical dysplasias (FCDs) are a range of malformations of cortical development each with specific histopathological features. Conventional radiological assessment of standard structural MRI is useful for the localization of lesions but is unable to accurately predict the histopathological features. Quantitative MRI offers the possibility to probe tissue biophysical properties in vivo and may bridge the gap between radiological assessment and ex-vivo histology.

Neurobiological origin of spurious brain morphological changes: A quantitative MRI study.

The high gray-white matter contrast and spatial resolution provided by T1-weighted magnetic resonance imaging (MRI) has made it a widely used imaging protocol for computational anatomy studies of the brain. While the image intensity in T1-weighted images is predominantly driven by T1, other MRI parameters affect the image contrast, and hence brain morphological measures derived from the data. Because MRI parameters are correlates of different histological properties of brain tissue, this mixed contribution hampers the neurobiological interpretation of morphometry findings, an issue which remains largely ignored in the community.

New tissue priors for improved automated classification of subcortical brain structures on MRI.

Despite the constant improvement of algorithms for automated brain tissue classification, the accurate delineation of subcortical structures using magnetic resonance images (MRI) data remains challenging. The main difficulties arise from the low gray-white matter contrast of iron rich areas in T1-weighted (T1w) MRI data and from the lack of adequate priors for basal ganglia and thalamus. The most recent attempts to obtain such priors were based on cohorts with limited size that included subjects in a narrow age range, failing to account for age-related gray-white matter contrast changes.

Disentangling in vivo the effects of iron content and atrophy on the ageing human brain.

Evidence from magnetic resonance imaging (MRI) studies shows that healthy aging is associated with profound changes in cortical and subcortical brain structures. The reliable delineation of cortex and basal ganglia using automated computational anatomy methods based on T1-weighted images remains challenging, which results in controversies in the literature. In this study we use quantitative MRI (qMRI) to gain an insight into the microstructural mechanisms underlying tissue ageing and look for potential interactions between ageing and brain tissue properties to assess their impact on automated tissue classification.