ESR Essentials: advanced MR safety in vulnerable patients-practice recommendations by the European Society for Magnetic Resonance in Medicine and Biology.

For every patient, the MR safety evaluation should include the assessment of risks in three key areas, each corresponding to a specific hazard posed by the electromagnetic fields generated by the MR scanner: ferromagnetic attraction and displacement by the static field; stimulation, acoustic noise, and device interaction by the gradient fields; and bulk and focal heating by the radiofrequency field. MR safety guidelines and procedures are typically designed around the "average" patient: adult, responsive, and of typical habitus. For this type of patient, we can safely expect that a detailed history can identify metallic objects inside and outside the body, verbal contact during the scan can detect signs of discomfort from heating or acoustic noise, and safety calculations performed by the scanner can prevent hyperthermia.

A WORLDWIDE ENIGMA STUDY ON EPILEPSY-RELATED GRAY AND WHITE MATTER COMPROMISE ACROSS THE ADULT LIFESPAN.

Objectives: Temporal lobe epilepsy (TLE) is commonly associated with mesiotemporal pathology and widespread alterations of grey and white matter structures. Evidence supports a progressive condition although the temporal evolution of TLE is poorly defined. This ENIGMA-Epilepsy study utilized multimodal magnetic resonance imaging (MRI) data to investigate structural alterations in TLE patients across the adult lifespan.

May anti-seizure medications alter brain structure in temporal lobe epilepsy? A prospective study.

Mild mesial temporal lobe epilepsy (MTLE) patients may remain untreated for a considerable time after disease onset or achieve seizure control with a single anti-seizures medication (ASM). Thus, they represent an optimal population to investigate whether ASMs might have influence on brain structure. We consecutively enrolled 56 mild MTLE patients (22/56 untreated, 34/56 on-monotherapy) and 58 healthy controls, matched for age and gender.

Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study.

Objective: The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current corticocentric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural magnetic resonance imaging in 1602 adults with epilepsy and 1022 healthy controls across 22 sites from the global ENIGMA-Epilepsy working group.

Methods: A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions.

Neuroimaging correlates of postural instability in Parkinson's disease.

Background: Postural instability (PI) is a common disabling symptom in Parkinson's disease (PD), but little is known on its pathophysiological basis.

Objective: In this study, we aimed to identify the brain structures associated with PI in PD patients, using different MRI approaches.

Methods: We consecutively enrolled 142 PD patients and 45 control subjects.

Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study.

Objective: The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current cortico-centric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural MRI in 1,602 adults with epilepsy and 1,022 healthy controls across twenty-two sites from the global ENIGMA-Epilepsy working group.

Methods: A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions.

Morphometry and network-based atrophy patterns in SCN1A-related Dravet syndrome.

Mutations of the voltage-gated sodium channel SCN1A gene (MIM#182389) are among the most clinically relevant epilepsy-related genetic mutations and present variable phenotypes, from the milder genetic epilepsy with febrile seizures plus to Dravet syndrome, a severe developmental and epileptic encephalopathy. Qualitative neuroimaging studies have identified malformations of cortical development in some patients and mild atrophic changes, partially confirmed by quantitative studies. Precise correlations between MRI findings and clinical variables have not been addressed.

Cortical involvement in essential tremor with and without rest tremor: a machine learning study.

Introduction: There is some debate on the relationship between essential tremor with rest tremor (rET) and the classic ET syndrome, and only few MRI studies compared ET and rET patients. This study aimed to explore structural cortical differences between ET and rET, to improve the knowledge of these tremor syndromes.

Methods: Thirty-three ET patients, 30 rET patients and 45 control subjects (HC) were enrolled.

Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection.

Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression.

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide.

Magnetic Resonance Planimetry in the Differential Diagnosis between Parkinson's Disease and Progressive Supranuclear Palsy.

The clinical differential diagnosis between Parkinson's disease (PD) and progressive supranuclear palsy (PSP) is often challenging. The description of milder PSP phenotypes strongly resembling PD, such as PSP-Parkinsonism, further increased the diagnostic challenge and the need for reliable neuroimaging biomarkers to enhance the diagnostic certainty. This review aims to summarize the contribution of a relatively simple and widely available imaging technique such as MR planimetry in the differential diagnosis between PD and PSP, focusing on the recent advancements in this field.

Event-based modeling in temporal lobe epilepsy demonstrates progressive atrophy from cross-sectional data.

Objective: Recent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features.

Methods: We extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1-weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1625 healthy controls from 25 centers.

The impact of one-year COVID-19 containment measures in patients with mesial temporal lobe epilepsy: A longitudinal survey-based study.

Background: We assessed levels of depression, anxiety, stress, anhedonia, somatization, psychological distress, sleep, and life quality in patients with mesial temporal lobe epilepsy (MTLE) after one year of containment measures started in Italy to stem the COVID-19 pandemic.

Methods: We consecutively enrolled 51 patients with MTLE, administering an online survey that compared the year before and after the COVID-19 propagation. We analyzed clinical data (e.

Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study.

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive.