Diffusion: Biophysical Foundations, Accuracy & Reproducibility
Wednesday 22 April 2009
Room 316BC 10:30-12:30


Yaniv Assaf and Sharon S. Peled

10:30 449. Experimentally Measured Intracellular Water at Very Short Diffusion Times
    Kevin D. Harkins1, Jean-Phillipe Galons2, Joe L. Divijak1, Theodore P. Trouard1
Biomedical Engineering, University of Arizona, Tucson, AZ, USA; 2Radiology, University of Arizona, Tucson, AZ, USA
    The apparent diffusion coefficient is a measure of water diffusion in tissue, and is sensitive to cellular properties and tissue integrity. In this work, we present estimates of the intrinsic intracellular diffusivity derived from hollow-fiber bioreactor cell culture measurements using oscillating gradient diffusion measurements at very short diffusion times. The ADC of intracellular approaches 2.0 to 2.4 mm2 /ms as the diffusion time approaches 0 ms.
10:42 450. Permeability and Surface Area of Cell Membranes from the DWI Signal
    Dmitry S. Novikov1, Jens H. Jensen1, Joseph A. Helpern1
Radiology, NYU Medical Center, New York, NY, USA
    Diffusion of water in tissues is strongly restricted on the cellular length scale. The consequence of such a restriction is a ubiquitous non-Gaussian shape of the diffusion-weighted imaging (DWI) signal. We demonstrate how a non-Gaussian shape of the DWI signal can originate solely due to the presence of cell membranes, with no diffusivity difference between the intra- and extra-cellular compartments. We find that the effective diffusivity acquires frequency dependence. We relate the cell membrane permeability and surface-to-volume ratio to experimentally relevant parameters, such as dispersive diffusivity and time-dependent kurtosis.
10:54 451. Fast Monte Carlo Simulations Replace Analytical Tissue Models in Diffusion MRI
    Markus Nilsson1, Erik Alerstam2, Sara Brockstedt3, Ronnie Wirestam1, Freddy Ståhlberg1,4, Jimmy Lätt3
Department of Medical Radiation Physics, Lund University, Lund, Sweden; 2Department of Physics, Lund University, Lund, Sweden; 3MR Department, Center for Medical Imaging and Physiology, Lund University Hospital, Lund, Sweden; 4Department of Diagnostic Radiology, Lund University, Lund, Sweden
    Evaluation of diffusion MRI data obtained with different diffusion times currently involves non-linear fitting of analytical models. These models rely on assumptions about the tissue as well as on mathematical approximations in the derivation of the signal expression. Replacing the non-linear fitting by a lookup database, constructed from fast Monte Carlo simulations, improves and speeds up the evaluations. This novel approach was demonstrated by investigating the estimated posterior distributions for four tissue parameters, i.e. the intracellular volume fraction, the cell diameter, the intracellular exchange time and the apparent diffusion coefficient, given simulated signal-versus-b curves with added noise.
11:06 452. MR Characterization of Compartment Shape Anisotropy (CSA)
    Evren Ozarslan1
STBB / LIMB / NICHD, National Institutes of Health, Bethesda, MD, USA
    Anisotropy observed in diffusion-weighted acquisitions is influenced by the shape of the cells (compartment shape anisotropy, CSA) and any coherence in the alignment of the population of cells (ensemble anisotropy, EA). We show that CSA and EA can be probed simultaneously and differentiated if double pulsed field gradient (double-PFG) sequences are employed. To this end, expressions for the MR signal intensity from capped cylinders with completely arbitrary parameters of the double-PFG sequence are derived. Our findings suggest that simultaneous noninvasive measurements of cell size, eccentricity and orientation distributions may be possible using relatively small gradient strengths.
11:18 453. Feasibility of in Vivo Metabolites Diffusion Tensor Assessment
    Nicolas Kunz1,2, Stéphane Sizonenko2, Rolf Gruetter1,3
Laboratory of functional and metabolic imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; 2Division of Child Growth & Development, Dept. of Pediatrics, University of Geneva, Geneva, Switzerland; 3Department of Radiology, University of Lausanne and Geneva, Switzerland
    DTI is based on water molecules’ diffusion motion, which is present in both intra- and extra-cellular spaces. On the other hand, DW-MRS uses metabolites as diffusion markers by combining MRS with diffusion weighting technique and provides information limited to the intra-cellular compartment. In this study, DW-MRS shows that the principal diffusion directions of the metabolites were aligned to the water along the corpus callosum fibers, and is likely to shed light on the nature of the diffusion signal.
11:30 454. On the Effects of Dephasing Due to Local Gradients in DTI Experiments: Relevance for DTI Fiber Phantoms
    Frederik Bernd Laun1, Sandra Huff1, Bram Stieltjes
1Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Baden-Württemberg, Germany
    Former versions of DTI phantoms could not be oriented arbitrarily towards B0 due to susceptibility induced local gradients. We countered this limitation by matching susceptibilities of restricting structure and fluid. This is achieved by solving sodium chloride. Thus, T2 becomes independent of orientation and diffusion measurements become reliable.
11:42 455. Comparison of DTI Fiber Tracks with Light Microscopy of Myelinated Fibers
    Ann Sunah Choe1,2, Xin Hong1,2, Daniel Christopher Colvin1,2, Iwona Stepniewska3, Zhaohua Ding1,2, Adam W. Anderson1,2
Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; 2Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; 3Department of Psychology, Vanderbilt University, Nashville, TN, USA
    Fibers tracked using Diffusion Tensor Imaging (DTI) are directly compared with myelin stained fibers on a microscopic level. Gold standard measurements of fiber orientation and spread from micrographs enabled us to investigate the challenges of DTI fiber tracking in brain tissue. Limitations due to partial volume averaging and image noise are readily observed.
11:54 456. Correlation Between R2* and FA in Human Brain White Matter
    Tie-Qiang Li1, Masaki Fukunaga2, Peter van Gelderen2, Jeff H. Duyn2
Medical Physics, Karolinska Huddinge, Stockholm, Sweden; 2NINDS, NIH, Bethesda, MD, USA
    High resolution MRI at 7T suggests that T2* contrast may be sensitive to white matter composition and microstructure. In this study, the quantitative correlation between T2* relaxation rate (R2*=1/ T2*) and diffusion fractional anisotropy (FA) in white matter was investigated in a dozen of normal volunteers at 3T and 7T.
12:06 457. Evaluation of Within-Site and Cross-Site Accuracy and Precision of DTI Measurements Through a Multi-Center Human Volunteer Study
    Tong Zhu1, Michelle Gaugh2, Xiaoxu Liu3, Michael Taylor4, Yuen Tso5, Giovanni Schifitto2, Constantin Yiannoutsos6, Bradford Navia7, Jianhui Zhong8
Biomedical Engineering, University of Rochester, Rochester, NY, USA; 2Neurology, University of Rochester, Rochester, NY, USA; 3Electrical Engineeering, University of Rochester, Rochester, NY, USA; 44University of California San Diego, San Diego, CA, USA; 5Stanford University, Stanford, CA, USA; 6Indiana University, Indianapolis, IN, USA; 7Tufts University, Medford, MA, USA; 8Imaging Sciences, University of Rochester, Rochester, NY, USA
    In a typical neuroimaging multicenter DTI study, biases and variations in data due to differences in scanners among sites prevent pooling of data for conventional statistical inferences. This is one of unsolved critical issues we are facing for multi-center DTI studies. In this study, multiple DTI data of a healthy volunteer were acquired at three imaging centers. Precision of DTI measurement of each center was quantified by the bootstrap analysis of measurement uncertainty while the accuracy (bias) of measurement was evaluated by comparing DTI parameters from each site to those from a “super” data set with all data combined. Our study suggests that, while precision level of DTI data from different sites is not significantly affected by the short-term variations of scanners at a site, the bias of DTI data from each site will vary and reduce the statistical power when data from multiple sites are combined together. In order to facilitate the multiple-center DTI study, a routine calibration process to regularly measure the bias level is necessary.
12:18 458.

Statistical Assessment of the Effects of Physiological Noise and Artifacts in a Population Analysis of Diffusion Tensor MRI Data

    Lindsay Walker1, Lin-Ching Chang1,2, Efstathios Kanterakis3, Luke Bloy3, Kristina Simonyan4, Ragini Verma3, Carlo Pierpaoli1
NICHD, NIH, Bethesda, MD, USA; 2Dept of EE & CS, Catholic University of America, Washington, DC, USA; 3Dept of Radiology, University of Pennsylvania, Philadelphia, PA, USA; 4NINDS, NIH, Bethesda, MD, USA
    Corrupted DWI data has an effect on DTI derived quantities. An analysis of the effect of physiological noise on statistical analysis of a population is presented. Comparison of non-robust and RESTORE robust tensor fitting shows significant differences in the mean and variance of anisotropy and mean diffusivity. The effects are regionally varying across the brain, and not the same for different tensor derived metrics. When considering a statistical analysis of a population, the effect of outliers may not be the same for both patient and control groups. Statistically significant results may originate from the presence of outliers instead of pathology.