Room 355 EF

16:00 - 18:00

Moderators:

Hao Huang, Wen-Yih Issac Tseng

Filip Szczepankiewicz¹, Jimmy Lätt², Ronnie Wirestam¹, Alexander Leemans³, Pia Sundgren^2,4, Danielle van Westen^2,4, Freddy Ståhlberg^1,4, and Markus Nilsson^1
1Department of Medical Radiation Physics, Lund University, Lund, Sweden, ²MR Department, Lund University Hospital, Lund, Sweden, ³Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, ⁴Department of Diagnostic Radiology, Lund University, Lund, Sweden

DTI and DKI parameters are commonly used to compare brain tissue in patients and controls. Such comparisons are frequently based on statistical tests, but analysis of statistical power and potential confounders are often overlooked. In this study we use the cingulum to demonstrate how heterogeneity of the variability and structure size at various positions along the structure can influence the diffusion parameters with respect to both statistical power and interpretation of the results.

Julia P. Owen¹, Elysa Marco², Emily Fourie¹, Shivani Desai², Julia Harris², Susanna Hill², and Pratik Mukherjee^1
1Radiology, UCSF, San Francisco, CA, United States, ²Neurology, UCSF, San Francisco, CA, United States

In this work, we present the results from a data-driven analysis of the white matter microstructural changes seen in young males with Sensory Processing Disorder (SPD). We find wide-spread changes in fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD). In addition, we find that the FA and RD of specific regions of white matter correlate strongly with sensory processing and inattention scores derived from a parent questionnaire. The findings in this paper provide new insights into the biological substrates of SPD and also to take the first steps toward an imaging biomarker for diagnosis and outcome prediction.

Mariana Lazar¹, Laura Miles¹, and Jeffrey Donaldson^1
1Department of Radiology, New York University School of Medicine, New York, NY, United States

Atypical white matter (WM) microstructure has been proposed as one of the mechanisms of Autism Spectrum Disorders (ASD). However, the underlying pathophysiology remains poorly understood. In this study we used to Diffusion Kurtosis Imaging and a two-compartment WM diffusion model, which provides metrics that differentially relate to axonal density and myelination, to more precisely characterize WM pathology in a group of young adults with High-Functional ASD. Our data indicates decreased axonal density in the ASD compared to a control typically-developing group, but no significant differences in myelination. Future work will examine WM properties in younger populations.

Gavin P. Winston¹, Mark R. Symms¹, Daniel C. Alexander², John S. Duncan¹, and Hui Zhang^2
1Epilepsy Society MRI Unit & Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, London, United Kingdom, ²Department of Computer Science & Centre for Medical Image Computing, University College London, London, London, United Kingdom

NODDI (neural orientation dispersion and density imaging) is a multi-compartment diffusion model that can distinguish two key variables contributing to FA changes - neurite density and orientation dispersion - with a clinically feasible scan protocol (20 minutes). In patients with epilepsy, identifying the location of the epileptogenic zone is critical in planning surgical treatment but up to 20-30% have normal MRI scans. Many patients have undetected focal cortical dysplasia (FCD). We show that NODDI can detect areas of FCD by identifying areas of reduced intracellular volume fraction (compatible with iontophoretic studies) and may be more sensitive than anatomical imaging.

Matthew DeSalvo¹, Linda Douw¹, Naoaki Tanaka¹, Claus Reinsberger¹, and Steven M. Stufflebeam^1
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States

In this study, we combined high resolution structural MRI with diffusion tensor imaging to study changes in whole-brain structural connectivity and network organization in unilateral mesial temporal lobe epilepsy. Using a graph theoretical approach, we observed increased local connectivity in the ipsilateral temporal lobe as well as widespread bilateral changes in connectivity principally among areas of the default mode network. We hypothesize that these changes in connectivity are due to epileptic activity and relate to certain cognitive and psychiatric symptoms in this condition. We believe that this method will provide a useful tool for diagnosis, prognosis and therapeutic monitoring.

Ali Tabesh^1,2, Jens H. Jensen^1,2, Edward S. Hui^1,2, Maria V. Spampinato^1,2, Jonathan C. Edwards³, Joseph A. Helpern^1,2, and Leonardo Bonilha^2,3
1Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, United States, ²Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, United States, ³Comprehensive Epilepsy Center, Neurosciences, Medical University of South Carolina, Charleston, SC, United States

This study aimed to provide biophysical interpretation of microstructural abnormalities in medial temporal lobe epilepsy (MTLE), and to determine their association with disease severity. Biophysical modeling was performed with a newly developed cerebral microenvironment modeling (CMM) method compatible with diffusional kurtosis imaging. Nineteen patients with MTLE and 28 matched healthy volunteers were studied. The results suggest that diffusion abnormalities in MTLE may be predominantly associated with cerebral neurite loss. Seizure frequency may be related to myelin degradation, gliosis, and possibly other changes in tissue morphology and permeability. CMM markers may potentially enable early identification of patients with medication-refractory MTLE.

David Vaughan^1,2, David A. Raffelt^1,3, Jacques-Donald Tournier^1,3, Graeme Jackson^1,2, and Alan Connelly^1,3
1Brain Research Institute, Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia, ²Department of Neurology, Austin Health, Melbourne, Victoria, Australia, ³Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia

We investigated white matter changes in Temporal Lobe Epilepsy (TLE) both in patients with hippocampal sclerosis and in patients with a normal structural MRI, using diffusion-weighted imaging data to compute the Apparent Fibre Density (AFD). This measure allows group differences to be identified in specific orientations and locations, so that pathological white matter changes may be attributed to fibres having a particular direction, even in regions containing multiple crossing tracts. Significantly decreased AFD is demonstrated in patients with TLE compared to controls, with different patterns of affected tracts seen in the hippocampal sclerosis and lesion-negative groups.

Wanyong Shin¹, Shamseldeen Mahmoud¹, Ken E. Sakaie¹, Banks Sarah², Mark J. Lowe¹, Michael Phillips¹, Michael T. Modic¹, and Charles Bernicks^2
1Radiology Dept., Cleveland Clinic, Cleveland, Ohio, United States, ²Lou Ruvo Center for Brain Health, Cleveland Clinic, Las Vegas, NV, United States

Fighting athletes such as boxers are at risk for traumatic brain injury (TBI). Because diffusion tensor imaging (DTI) is sensitive to microstructure changes in white matter (WM), this technique is often used to investigate WM integrity in patients with TBI. We hypothesized that previous fight exposure would predict DTI values in a fighter population after controlling for individual confounding variables such as (age, weight, and years of education). We found that the number of times a fighter has been knocked out in his career predicted increased longitudinal diffusivity in corpus callosum and fornix regions and increased transverse diffusivity in corpus callosum, fornix, left hippocampus and left posterior corona radiate, leading to the increased mean diffusivity and decreased fractional anisotropy values in the corresponding regions. Our finding suggests that DTI values indicating micro-structural brain damage correlate with the history of fight exposure in a fighter population.

Tong Zhu¹, Eric Blackman², Xing Qiu³, Jeffray Bazarian⁴, Rui Hu³, Eric Rozen⁵, and Jianhui Zhong^1
1Imaging Sciences, University of Rochester, Rochester, NY, United States, ²Physics and Astronomy, University of Rochester, Rochester, NY, United States, ³Biostatistics, University of Rochester, Rochester, NY, United States, ⁴Emergency Medicine, University of Rochester, Rochester, NY, United States, ⁵Athletics and Recreation, University of Rochester, Rochester, NY, United States

The public health impact of brain injury from repetitive sub-concussive head blows during team sport is potentially dramatic, and DTI has been used to study brain injury associated with concussions. In this study, we conducted three longitudinal DTI studies of a group of 10 college football players before and after a regular football season, along with mechanical force data recorded by helmet-embedded sensors throughout the season. Despite a small sample size, the study finds that longitudinal changes in DTI measures and mechanical force show strong significant correlations when comparing pre- and post-season data.

Thomas van Bruggen¹, Hui Zhang², Ofer Pasternak³, Hans-Peter Meinzer¹, Bram Stieltjes⁴, and Klaus Hermann Fritzsche^1,4
1Division of Medical and Biological Informatics, German Cancer Research Center, Heidelberg, Germany, ²Department of Computer Science & Centre for Medical Image Computing, UCL, London, United Kingdom, ³Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, ⁴Division of Quantitative Image-based Disease Characterization, German Cancer Research Center, Heidelberg, Germany

Partial volume effects of different tissue types and cerebrospinal fluid are a major confounding factor of diffusion tensor imaging (DTI). In gray matter, the low diffusion anisotropy makes DTI-based assessment of microstructure even more challenging. Here we apply and compare two multi-compartment techniques, free-water elimination (FWE) and neurite density and orientation dispersion imaging (NODDI), in order to assess hippocampal microstructure in Alzheimer’s disease (AD). Both methods consistently show that seemingly microstructural changes in the tissue are caused by macroscopic changes in the form of an increased isotropically diffusing water compartment.