ISMRM 24th Annual Meeting & Exhibition • 07-13 May 2016 • Singapore

Scientific Session: Diffusion: Making Use of Microstructure Information

Friday Friday, May 13, 2016
Room 324-326
08:00 - 10:00
Moderator: Roger Bourne

Multi-compartment microscopic diffusion anisotropy imaging brought into clinical practice
Enrico Kaden1, Nathaniel D. Kelm2, Robert P. Carson3, Mark D. Does2, and Daniel C. Alexander1
1Centre for Medical Image Computing, University College London, London, United Kingdom, 2Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States, 3Departments of Neurology and Pediatrics, Vanderbilt University, Nashville, TN, United States
This work introduces a multi-compartment model for microscopic diffusion anisotropy imaging using an off-the-shelf pulse sequence achievable on standard clinical scanners. In particular, we will provide estimates of microscopic features specific to the intra- and extra-neurite compartments unconfounded by the effects of fibre crossings and orientation dispersion, which are ubiquitous in the brain. The new imaging technique is demonstrated in a large cohort of healthy young adults as well as for the detection of microstructural tissue alterations in a preclinical animal model of tuberous sclerosis complex.

The lifespan trajectory of white matter microstructure detected by NODDI
Jiaying Zhang1, Aurobrata Ghosh1, Daniel C Alexander1, and Gary Hui Zhang1
1Computer Science and Centre for medical image computing, University College London, London, United Kingdom
The structure and function of human brain evolve across the lifespan. The microstructural white matter changes across lifespan have been studied using Diffusion tensor imaging. Whilst sensitive, DTI parameters have no direct tissue specificity. Here, given the availability of high-quality HCP lifespan dataset, we aim to study the lifespan trajectory of microstructural WM changes using NODDI and evaluate another NODDI fitting framework - Accelerated microstructure imaging via convex optimization (AMICO). We found U-shaped neurite density changes across lifespan and feasibility of AMICO NODDI parameters in capturing the similar lifespan trajectory as the standard fitting. 

Nicholas G Dowell1, Simon L Evans2, Sarah L King2, Naji Tabet3, and Jennifer M Rusted2
1Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Brighton, United Kingdom, 2Psychology, University of Sussex, Brighton, United Kingdom, 3Centre for Dementia Studies, Brighton and Sussex Medical School, Brighton, United Kingdom
The APOE-e4 gene is the best known genetic risk factor for late-onset Alzheimer's Disease. However, carriers of this gene have demonstrated behavioural differences compared to non-carriers on a number of cognitive tasks at young age. In this study, we demonstrate for the first time using the advanced diffusion imaging technique, NODDI, that there are detectable genotype-dependent structural differences in the brain of young healthy volunteers. The strongest differences are in the measure of orientation dispersion (ODI) of neurites, where e4 carriers show higher ODI than non-e4 carriers in the white matter.

Microscopic Anisotropy Imaging at 7T Using Asymmetrical Gradient Waveform Encoding
Filip Szczepankiewicz1, Carl-Fredrik Westin2, Freddy Ståhlberg1, Jimmy Lätt3, and Markus Nilsson4
1Dept. of Medical Radiation Physics, Lund University, Lund, Sweden, 2Dept. of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States, 3Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden, 4Lund University Bioimaging Center, Lund University, Lund, Sweden
Diffusion MRI that goes beyond DTI is challenging at 7T due to the short transverse relaxation time. We address this inherent limitation of 7T by employing asymmetric gradient waveforms for diffusion encoding, and demonstrate that imaging of microscopic diffusion anisotropy is feasible at a 7T system.

Chronic mild stress induces changes in neurite density in the amygdala as revealed by diffusion MRI and validated with novel histological analyses
Ahmad Raza Khan1, Andery Chuhutin1, Ove Wiborg2, Christopher D Kroenke3, Jens R Nyengaard4, Brian Hansen1, and Sune Nørhøj Jespersen1,5
1Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark, 2Centre for Psychiatric Research, Aarhus University, Aarhus, Denmark, 3Advanced Imaging Research Center, Portland, OR, United States, 4Stereology and Electron Microscopy Laboratory, Aarhus University, Aarhus, Denmark, 5Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
Biophysical modelling of diffusion MRI data allows detection of specific tissue microstructures such as neurite density. However, histological validation of MR-derived indication of microstructural alteration is limited due extensive time labour and invasive character, even though histological validation is crucial because it remains the gold standard. The present study applies Matlab based image processing and analysis tools to compute histological neurite density to validate diffusion MRI based neurite density changes in the amygdala of chronic mild stress rat brains. The image processing and analyses provides novel tools to validate diffusion data robustly. 

Altered hippocampal microstructure in the epileptogenic rat brain revealed with diffusion MRI using oscillating field gradients
Manisha Aggarwal1, Olli Gröhn2, and Alejandra Sierra2
1Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2Department of Neurobiology, A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
We investigate changes in the temporal diffusion spectrum sampled using oscillating gradient spin-echo (OGSE) acquisitions at increasing gradient frequencies in the epileptogenic rat brain. PGSE and OGSE data at discrete oscillation frequencies were acquired from pilocarpine-treated and control rat brains (n=5 each) with a spectral resolution of 60 Hz (= 60 Hz, 120 Hz, 180 Hz). Our findings reveal significant changes in the frequency-dependent modulation of apparent diffusion coefficient (ADC) in specific areas of the pilocarpine brain, which were found to correspond to region-specific gliosis and neuronal loss respectively. Using comparison with histological findings, our results show unique sensitivity of OGSE diffusion MRI to probe specific cellular-level alterations in the epileptogenic brain.

Detecting Disrupted-in-Schizophrenia-1 Gene Related Microstructural and Molecular Alterations using Diffusion Kurtosis Imaging and Quantitative Susceptibility Mapping
Nan-Jie Gong1, Russell Dibbs2, Kyle Decker2, Mikhail V. Pletnikov3, and Chunlei Liu1
1Brain Imaging and Analysis Center, Duke University, Durham, NC, United States, 2Center for In Vivo Microscopy, Duke University, Durham, NC, United States, 3Behavioral Neurobiology and Neuroimmunology Laboratory, Johns Hopkins University, Baltimore, MD, United States
DKI method provided sensitive metrics for reflecting microstructural changes in not only the anterior commissure but also relatively isotropic gray matter regions of hippocampus, cerebral cortex and caudate putamen. Further relating DKI findings to molecular compositions measured by QSM enabled clearer interpretations of myelin content and cellular density related mechanisms. Further validations that establish the relationship between imaging metrics and histological measurements such as neuronal cell body density, myelin thickness and g-ratio are needed. 

White Matter Changes in Elderly Patients Suffer from Post-operative Cognition Disorders : Evidence from Diffusion Kurtosis Magnetic Resonance Imaging
Bing Yu1, Na Chang1, Xiaoxue Ge1, Yueren Wang1, and Qiyong Guo1
1Shengjing Hospital of China Medical University, Shenyang, China, People's Republic of
In the present study, we reconstructed the white matter skeleton of the brain using tract-based spatial statistics (TBSS) and compared differences in diffusion kurtosis imaging (DKI) parameters within the skeleton between patients sufferde from postoperative cognitive dysfunction (POCD) and healthy controls to detect white matter abnormalities in POCD.

Rapid Estimation of Spinal Cord Injury Severity in Rats using Double Diffusion Encoded Magnetic Resonance Spectroscopy
Nathan P Skinner1,2,3, Shekar N Kurpad3,4, Brian D Schmit5, L Tugan Muftuler3, and Matthew D Budde3,4
1Biophysics Graduate Program, Medical College of Wisconsin, Milwaukee, WI, United States, 2Medical Scientist Training Program, Medical College of Wisconsin, Milwaukee, WI, United States, 3Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States, 4Clement J. Zablocki Veteran's Affairs Medical Center, Milwaukee, WI, United States, 5Department of Biomedical Engineering, Marquette University, Milwaukee, WI, United States
Diffusion tensor imaging (DTI) is frequently applied to spinal cord injury, yet suffers from poor detection of axonal integrity changes caused by conflicting extracellular processes.  A double diffusion encoding (DDE) sequence was developed for the spinal cord to remove non-neuronal signal contribution by applying a strong diffusion weighting perpendicular to the spinal cord. A parallel diffusion gradient then sampled diffusivity along the spinal cord.  Application in a rat model showed DDE parameters outperformed DTI in sensitivity to injury severity with substantially reduced acquisition and post-processing time.  Thus, this technique shows potential for rapid, sensitive determination of spinal cord injury severity.

Measurement of restricted and hindered anisotropic diffusion tissue compartments in a rat model of Wallerian degeneration
Benoit Scherrer1, Damien Jacobs2, Maxime Taquet1,2, Anne des Rieux3, Benoit Macq2, Sanjay P Prabhu1, and Simon K Warfield1
1Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States, 2ICTEAM, Universite catholique de Louvain, Louvain-La-Neuve, Belgium, 3LDRI, Université catholique de Louvain, Brussels, Belgium
The DIAMOND model has been recently proposed to model the heterogeneity of tissue compartments in diffusion compartment imaging. However, it did not enable the characterization of the intra-axonal volume fraction (IAVF), a critical measure to more accurately characterizing axonal loss in abnormal tissues. In this work we investigated mathematical extensions to DIAMOND that model both the IAVF and the heterogeneous nature of in-vivo tissue. We validated our approach using both Monte-Carlo simulations and histological microscopy with an animal model of Wallerian degeneration. We show that our novel model better predicts the signal and provides additional parameters to further describe tissues.

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