Neuroradiology seminars

Arterial spin labeling (ASL) MRI has become a vital tool in clinical neuroimaging, enabling noninvasive assessment of cerebral perfusion across a range of conditions including stroke, vascular malformations, and brain tumors. With broader clinical adoption, its practical strengths — as well as important limitations — have become increasingly clear.

Identifying a structural brain lesion on MRI is the most important factor that correlates with seizure freedom after surgery in patients suffering from drug-resistant focal epilepsy. By providing better image contrast and higher spatial resolution, structural MRI at 7 Tesla (7T) can lead to lesion detection in about 25% of patients presenting with negative MRI at lower fields. In addition to a better detection/delineation/phenotyping of epileptogenic lesions, higher signal at ultra-high field also facilitates more detailed analyses of several functional and molecular alterations of tissues, susceptible to detect epileptogenic properties even in absence of visible lesions. These advantages but also the technical challenges of 7T MRI in practice will be presented and discussed.

Epilepsy surgery is a safe but underutilised treatment for drug-resistant focal epilepsy. One challenge in the presurgical evaluation of patients with drug-resistant epilepsy are patients considered “MRI negative”, i.e. where a structural brain abnormality has not been identified on MRI. A major pathology in “MRI negative” patients is focal cortical dysplasia (FCD), where lesions are often small or subtle and easily missed by visual inspection. In recent years, there has been an explosion in artificial intelligence (AI) research in the field of healthcare. Automated FCD detection is an area where the application of AI may translate into significant improvements in the presurgical evaluation of patients with focal epilepsy. I will provide an overview of our automated FCD detection work, the Multicentre Epilepsy Lesion Detection (MELD) project and how AI algorithms are beginning to be integrated into epilepsy presurgical planning at Great Ormond Street Hospital and elsewhere around the world. Finally, I will discuss the challenges and future work required to bring AI to the forefront of care for patients with epilepsy.

On Wednesday, November 30th, at noon ET / 6PM CET, we will host Alexandre Boutet and Erik H. Middlebrooks. Alexandre Boutet, MD, PhD, is a neuroradiology fellow at the University of Toronto, and will tell us about “How to become an integral part of the functional neurosurgery team as a radiologist”. Erik H. Middlebrooks, MD, is a Professor and Consultant of Neuroradiology and Neurosurgery and the Neuroradiology Program Director at Mayo Clinic. Beside his scientific presentation about “Bridging the Gap from Research to Clinical Decision Making in Epilepsy Neuromodulation”, he will also give us a glimpse at the “Person behind the science”. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

Late-life cognitive impairment and dementia are heterogeneous and multifactorial conditions driven by a combination of genetic, vascular, and lifestyle-related factors. More than 75% of patients with dementia have evidence of cerebrovascular pathology at autopsy. Cerebrovascular disease lesions can be detected on structural MRI and used as biomarkers to determine the extent of cerebrovascular pathology. These biomarkers are associated with cognitive difficulties and increase the risk of dementia for the same level of neurodegenerative pathology. Given that some of the risk factors for cerebrovascular disease are potentially modifiable, identifying the role of cerebrovascular pathology in aging and neurodegenerative disease populations opens a window for prevention of cognitive decline and dementia.

Dementia with Lewy bodies (DLB) is a synucleinopathy but more than half of patients with DLB also have varying degrees of tau and amyloid-β co-pathology. Identifying and tracking the pathologic heterogeneity of DLB with multi-modal biomarkers is critical for the design of clinical trials that target each pathology early in the disease at a time when prevention or delaying the transition to dementia is possible. Furthermore, longitudinal evaluation of multi-modal biomarkers contributes to our understanding of the type and extent of the pathologic progression and serves to characterize the temporal emergence of the associated phenotypic expression. This talk will focus on the utility of multi-modal imaging in DLB.

In this talk I will present data from imaging studies that we have been conducting for the past 20 years trying to shed light on migraine physiopathology, from anatomical and functional MRI to positron emission tomography.

The normally functioning blood-brain barrier (BBB) regulates the transfer of material between blood and brain. BBB dysfunction has long been recognized in multiple sclerosis (MS), and there is considerable interest in quantifying functional aspects of brain blood vessels and their role in disease progression. Parenchymal water content and its association with volume regulation is important for proper brain function, and is one of the key roles of the BBB. There is convincing evidence that the astrocyte is critical in establishing and maintaining a functional BBB and providing metabolic support to neurons. Increasing evidence suggests that functional interactions between endothelia, pericytes, astrocytes, and neurons, collectively known as the neurovascular unit, contribute to brain water regulation, capillary blood volume and flow, BBB permeability, and are responsive to metabolic demands. Increasing evidence suggests altered metabolism in MS brain which may contribute to reduced neuro-repair and increased neurodegeneration. Metabolically relevant biomarkers may provide sensitive readouts of brain tissue at risk of degeneration, and magnetic resonance offers substantial promise in this regard. Dynamic contrast enhanced MRI combined with appropriate pharmacokinetic modeling allows quantification of distinct features of BBB including permeabilities to contrast agent and water, with rate constants that differ by six orders of magnitude. Mapping of these rate constants provides unique biological aspects of brain vasculature relevant to MS.

The spatial patterning of each neurodegenerative disease relates closely to a distinct structural and functional network in the human brain. This talk will mainly describe how brain network-sensitive neuroimaging methods such as resting-state fMRI and diffusion MRI can shed light on brain network dysfunctions associated with pathology and cognitive decline from preclinical to clinical dementia. I will first present our findings from two independent datasets on how amyloid and cerebrovascular pathology influence brain functional networks cross-sectionally and longitudinally in individuals with mild cognitive impairment and dementia. Evidence on longitudinal functional network organizational changes in healthy older adults and the influence of APOE genotype will be presented. In the second part, I will describe our work on how different pathology influences brain structural network and white matter microstructure. I will also touch on some new data on how brain network integrity contributes to behavior and disease progression using multivariate or machine learning approaches. These findings underscore the importance of studying selective brain network vulnerability instead of individual region and longitudinal design. Further developed with machine learning approaches, multimodal network-specific imaging signatures will help reveal disease mechanisms and facilitate early detection, prognosis and treatment search of neuropsychiatric disorders.

Molecular imaging using Positron Emission Tomography (PET) has become a major biomedical imaging technology. Its application towards characterisation of biochemical processes in disease could enable early detection and diagnosis, development of novel therapies and treatment evaluation. The technology is underpinned by the use of imaging probes radiolabelled with short-lived radioisotopes which can be specific and selective for biological targets in vivo e.g. markers for receptors, protein deposits, enzymes and metabolism. My talk will focus on the increasing development and application of PET imaging to clinical research in neurodegenerative diseases, for which it can be applied to delineate and understand the various pathological components of these disorders.