Speakers: Avner Meoded, MD

Avner Meoded, MD

Pediatric Neuroradiologist
Children’s Mercy
Associate Professor of Radiology
University of Missouri Kansas City

 

Dr. Meoded earned his Doctor of Medicine (MD) degree from the Università degli Studi di Torino in Turin, Italy. He was trained as a resident in Neurology, Neuroradiology and Nuclear Medicine in Israel, Italy, and at John Hopkins University School of Medicine.

Dr. Meoded is an attending pediatric neuroradiologist at Children’s Mercy Hospital, holding an appointment as associate professor of radiology at UMKC. Dr. Meoded is conducting extensive pediatric neuroimaging research He has authored more than 80 papers in peer review medical journals. His work is recognized by experts in the field of neuroradiology and nuclear imaging and received numerous awards including The American Society of Neuroradiology (ASNR) Cornelius G. Dyke memorial award, Fellows Award for Research Excellence (FARE)honored by the NIH and the 2015 Johns Hopkins resident and fellows research award.

His research in the area of neuroimaging, particularly as it relates to the application of advanced, cutting edge, non-invasive imaging modalities for the exploration of various potentially devastating neurological diseases have been remarkable. Dr. Meoded’s findings improved the diagnostic criteria of several, advanced our understanding of the pathogenesis of diseases affecting the brain, and provided potential neuroimaging biomarkers to identify patients who may benefit from targeted therapeutic approaches and to monitor treatment response.

Children’s Brain By Numbers: From Picture To Connectomics

Human brain mapping has been a visual tale of increasing complexity, continuously oscillating between various priorities of data presentation.

MRI is an imaging modality that has played a central role in the assessment of anatomy, physiology/pathophysiology in children non-invasively. As MRI scanners and post processing techniques continue to evolve, our ability to extract greater information and consequently make better-informed decisions about diagnosis, treatment and prognosis for patients relies on developing and optimizing quantitative analysis and data visualization pipelines.
Currently, radiologist routinely collect more study data in a few days than was collected in over an entire year just a decade ago (rich source of information). Much of the information contained within these images remain unexplored due to lack of tools which are capable of analyzing and visualizing large amount of imaging data.

Children with neurological conditions such as epilepsy, traumatic brain injury (TBI), developmental delay, cerebral palsy, brain cancer, and hydrocephalus require precise and early diagnosis to improve treatment outcomes. Quantitative neuroimaging approaches, including automatic brain tissue segmentation, white matter tractography and connectomics, offer valuable clinical insights. Integrating these approaches into routine clinical workflows is essential for improving diagnostic accuracy, treatment planning, and monitoring of neurological conditions, ultimately leading to better health outcomes for the pediatric population.