Room 355 BC

13:30 - 15:30

Moderators:

Evren Ozarslan, Dmitriy A. Yablonskiy

Els Fieremans¹, Gregory Lemberskiy², Jens H. Jensen³, and Dmitry S. Novikov^2
1Center for Biomedical Imaging, Department of Radiology, New York University, New York, NY, United States, ²Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, NY, United States, ³Center for Biomedical Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, United States

The random permeable barriers model (RPBM) employs the time-dependence of the diffusion coefficient for quantifying cell size and membrane permeability. As an in vivo validation of the RPBM, we performed time-dependent diffusion measurements in the calf muscle of a healthy volunteer over the course of a weight lifting program. The RPBM yields realistic values for muscle fiber diameter and permeability. Additionally as expected, a significant increase in diameter of the gastrocnemius medialis is observed with training. This work demonstrates the feasibility of the RPBM method in quantifying muscle fiber diameter and permeability, and its sensitivity to microstructural changes.

Ileana Ozana Jelescu¹, Luisa Ciobanu¹, Françoise Geffroy¹, and Denis Le Bihan^1
1NeuroSpin, Gif-sur-Yvette, Essonne, France

The mechanism causing apparent diffusion coefficient (ADC) decrease in brain tissue with ischemia is not yet clearly established. We evaluated ADC evolution at 17.2T, in isolated Aplysia californica neurons and within “tissue” (ganglia), following hypotonic shock or exposure to ouabain. Both types of stress caused an increase in ADC in single cells, and an overall decrease in ADC in the ganglia. Cell swelling was readily measurable with hypotonicity, but less obvious with ouabain. These results do not favor the extension of intracellular space as the origin of the observed ADC decrease at tissue level.

Simon Richardson^1,2, Bernard M. Siow^1,2, Eleftheria Panagiotaki³, Torben Schneider⁴, Mark F. Lythgoe¹, and Daniel C. Alexander^5
1Division of Medicine and Institute of Child Health, UCL Centre for Advanced Biomedical Imaging, University College London, London, United Kingdom, ²Centre for Medical Image Computing, University College London, London, United Kingdom, ³Dept of Medical Phys and Bioengineering, Centre for Medical Image Computing, University College London, London, United Kingdom, ⁴NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, United Kingdom, ⁵Department of Computer Science, Centre for Medical Image Computing, University College London, London, United Kingdom

We compare fixed and viable isolated tissue (VIT) in identical conditions at physiological temperature. We acquired DTI data sets with various acquisition parameters and a rich multi-b-value diffusion weighted MR (DW-MR) dataset for microstructural tissue model fitting. DTI data demonstrated a significant increase in radial diffusivity (RD) in fixed samples in comparison to VIT. Model fitting demonstrated that similar models best explain data from both samples. We conclude from model ranking stability that fixed tissue is a reasonable model for in-vivo, although significant differences in fitted model parameters suggest that water in individual compartments within the tissues behaves quite differently.

Chia-Wen Chiang¹, Yong Wang², Anne H. Cross^3,4, and Sheng-Kwei Song^2,4
1Chemistry, Washington University in Saint Louis, Saint Louis, MO, United States, ²Radiology, Washington University School of Medicine, Saint Louis, MO, United States, ³Neurology, Washington University in St. Louis, Saint Louis, MO, United States, ⁴The Hope Center for Neurological Disorders, Washington University School of Medicine, Saint Louis, MO, United States

Diffusion basis spectrum imaging (DBSI) has been demonstrated to accurately detect and quantify multiple diffusion components resulting from crossing fibers, axonal injury, demyelination, and increased cellularity and water content associated with inflammation in both ex vivo phantom and in vivo animal studies. However, the employed 99-direction diffusion-encoding scheme requires a relatively long scanning time significantly hampering the application to examine living mouse optic nerves or spinal cord white matter tracts. In this study, we proposed a simplified 29-direction diffusion encoding-scheme to greatly reduce the scanning time for in vivo spinal cord and optic nerve studies while preserving the accuracy of DBSI computation. Successful validation of 29-direction scheme will facilitate the potential applications both in clinic and animal study using DBSI.

Yong Wang¹ and Sheng-Kwei Song^1,2
1Radiology, Washington University in St. Louis, Saint Louis, MO, United States, ²The Hope Center for Neurological disorders, Washington University in St. Louis, Saint Louis, MO, United States

Diffusion MRI has been proposed to measure the intra-axonal water diffusion to more accurately reflect axonal integrity. Reasonable intra-axonal water fraction and axial diffusivity have been reported in normal healthy brains, suggesting potential application to patients with central nervous system (CNS) diseases. However, the confounding effect of cellularity surrounding the axons has not been adequately modeled in most of those methods. In this study, Monte Carlo simulation was employed to investigate the effect of varied cellularity surrounding the axons on the intra-axonal water diffusion measurement. Preliminary data suggested that proper modeling of cellularity component is critical to accurately estimate intra-axonal water diffusion, especially for CNS lesions with prominent cell infiltration.

Marco Cavalieri¹, Marco Palombo^1,2, Alessandro Gozzi³, Andrea Gabrielli⁴, Angelo Bifone³, and Silvia Capuani^1,2
1Physics Department, Sapienza University, Rome, Rome, Italy, ²CNR IPCF UOS Roma, Physics Department, Sapienza University, Rome, Rome, Italy, ³Istituto Italiano di Tecnologia, Center for Nanotechnology Innovation, IIT@NEST, Pisa, Pisa, Italy, ⁴CNR-ISC Roma, Sapienza University, Rome, Rome, Italy

The aim of the study was to overcome the “first order approximation” in the stretched-exponential -imaging method, to obtain Anomalous Diffusion  values in the intrinsic  reference frame. To this end, we examined a fixed mouse brain at 7T, by performing conventional DTI and -imaging experiments, and assessing T2*, DTI parameters, DTI main directions, stretched-exponential -imaging parameters, -imaging main directions in various anatomical regions of mouse brain. We show that the  reference frame is not coincident with the conventional diffusion reference frame. Moreover, our results suggest that -imaging may provide information on tissue microstructure beyond and above DTI.

Lauren Burcaw¹, Els Fieremans², and Dmitry S. Novikov^1
1NYUMC, New York, NY, United States, ²New York University, New York, NY, United States

We demonstrate that disorder in the packing geometry of a fiber bundle, such as an axonal tract, is crucial for the time-dependent diffusion. Using fiber phantom measurements and Monte Carlo simulations, we uncover a logarithmic singular behavior at long times, which makes the time dependence of diffusion in the extra-axonal space more pronounced than that coming from water confined inside axons. This singularity translates into linear-in-frequency dependence of OGSE diffusion coefficient at small frequencies, which again dominates over that from confined spaces. As a result, incorporating disorder in axonal packing is crucial for modeling and characterization of axonal tracts.

Michal E. Komlosh^1,2, Dan Benjamini^1,3, Matthew D. Budde⁴, Lynne A. Holtzclaw⁵, Martin J. Lizak⁶, Ferenc Horkay¹, Uri Nevo³, and Peter J. Basser^1
1NICHD/PPITS/STBB, NIH, Bethesda, MD, United States, ²CNRM, USUHS, Bethesda, MD, United States, ³Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel-Aviv University, Tel Aviv, Israel, ⁴Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States, ⁵NICHD/SCBS, NIH, Bethesda, MD, United States,⁶NINDS/MIF, NIH, Bethesda, MD, United States

dPFG MRI was used to characterize the microstructure of an injury model using rat sciatic nerve. Three samples were used in this study, one injured nerve and two controls. A theoretical model was used to fit the resulting dPFG MRI data in order to detect alterations in tissue microstructure.

Björn Lampinen¹, Filip Szczepankiewicz¹, Danielle van Westen², Pia Sundgren², Freddy Ståhlberg^1,2, Jimmy Lätt³, and Markus Nilsson^4
1Department of Medical Radiation Physics, Lund University, Lund, Sweden, ²Department of Diagnostic Radiology, Lund University, Lund, Sweden, ³Center for Medical Imaging and Physiology, Lund University Hospital, Lund, Sweden, ⁴Lund University Bioimaging Center, Lund University, Lund, Sweden

Filter-exchange imaging (FEXI) is based on a double pulsed field gradient (d-PFG) sequence, and provides a fast, non-invasive method for mapping water exchange expressed in its parameter apparent exchange rate (AXR). We used an analytical technique based on the Cramer-Rao Lower Bound to optimize the acquisition protocol. A new protocol is presented which reduces the coefficient of variance (CV) by 30% for measured AXR. With this optimized protocol, comparative studies searching for alterations in the AXR of magnitude three times larger than the inter-subject standard deviation can be performed using as few as four individuals per group with scan time below 15 minutes. This will enable future investigations of AXR as a biomarker for disease and treatment effects.

Edward S. Hui^1,2, Ali Tabesh^1,2, Joseph A. Helpern^1,2, and Jens H. Jensen^1,2
1Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina, United States, ²Dept of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, United States

Diffusion MRI (dMRI) has often been augmented with tissue-specific modeling in order to explicitly relate dMRI data to microstructural properties such as the sizes, orientations, volume fractions, and diffusivities of prescribed cellular compartments. One approach to tissue modeling is to exploit the close link between cytoarhitecture and the non-Gaussanity of water diffusion, which may be obtained with the dMRI technique known as diffusional kurtosis imaging (DKI). In this work, we propose a method, cerebral microenvironment modeling, which generalize the white matter model by Fieremans et al so that specific microstructural properties of the entire brain may be obtained with DKI.