NMR in Biomedicine

Cover image for Vol. 23 Issue 7

Special Issue: Progress in Diffusion-Weighted Imaging: Concepts, Techniques, and Applications to the Central Nervous System

August 2010

Volume 23, Issue 7

Pages 659–904

Issue edited by: Jens H. Jensen, Joseph A. Helpern

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    14. Current Awareness
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    1. Theoretical models of the diffusion weighted MR signal (pages 661–681)

      Dmitriy A. Yablonskiy and Alexander L. Sukstanskii

      Article first published online: 3 JUN 2010 | DOI: 10.1002/nbm.1520

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      Diffusion MRI plays a very important role in studying biological tissue structure in health and disease. In this review, we discuss theoretical models linking diffusion MRI signal to salient features of tissue microstructure. These models range from the simplest one, where the signal is described in terms of an apparent diffusion coefficient, to rather complicated models, where consideration is given to signals originating from extra- and intracellular spaces and where account is taken of the specific geometry and orientation distribution of cells.

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    1. Effective medium theory of a diffusion-weighted signal (pages 682–697)

      Dmitry S. Novikov and Valerij G. Kiselev

      Article first published online: 29 SEP 2010 | DOI: 10.1002/nbm.1584

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      The complexity of biological tissues prompts the statistical treatment of their properties. Such description aids in the understanding of which tissue characteristics are most relevant for measurement, and hence can be quantified in diffusion-weighted imaging.

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    1. MRI quantification of non-Gaussian water diffusion by kurtosis analysis (pages 698–710)

      Jens H. Jensen and Joseph A. Helpern

      Article first published online: 19 MAY 2010 | DOI: 10.1002/nbm.1518

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      Diffusional kurtosis imaging (DKI) as a method for quantifying water diffusion non-Gaussianity in brain is reviewed. The theoretical underpinnings of DKI are examined in detail, and it is argued that the diffusional kurtosis is a natural indicator of diffusional heterogeneity. In addition, practical aspects of the implementation of DKI on clinical MRI systems are discussed.

  5. Special Issue Research Articles

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    1. Monte Carlo study of a two-compartment exchange model of diffusion (pages 711–724)

      Els Fieremans, Dmitry S. Novikov, Jens H. Jensen and Joseph A. Helpern

      Article first published online: 29 SEP 2010 | DOI: 10.1002/nbm.1577

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      This Monte Carlo study shows that the Kärger model (KM), although highly idealized, can accurately model the diffusion for a realistic tissue model at long times, provided that the compartment diffusivities are time independent and the permeability is sufficiently low such that the exchange between the compartments is barrier limited. The time dependence of the kurtosis allows one to determine the exchange time. The simulations show, however, that, for more permeable membranes, i.e. when the exchange becomes correlated with diffusion, the KM-derived exchange times are overestimated.

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    1. The use of MR-detectable reporter molecules and ions to evaluate diffusion in normal and ischemic brain (pages 725–733)

      Joseph J. H. Ackerman and Jeffrey J. Neil

      Article first published online: 28 JUL 2010 | DOI: 10.1002/nbm.1530

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      Endogenous and exogenous MR-detectable reporter molecules and ions have been used to probe motion in the intra- and extracellular space of cultured cells and intact tissue. Studies show that (i) apparent diffusion coefficient (ADC) values for intracellular and extracellular water are similar and (ii) intracellular ADC decreases in association with brain injury. These results suggest that the brain water ADC decrease that accompanies brain injury is driven primarily by a decrease in the ADC of intracellular water.

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    1. A system and mathematical framework to model shear flow effects in biomedical DW-imaging and spectroscopy (pages 734–744)

      Uri Nevo, Evren Özarslan, Michal E. Komlosh, Cheng Guan Koay, Joelle E. Sarlls and Peter J. Basser

      Article first published online: 29 SEP 2010 | DOI: 10.1002/nbm.1591

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      We use an integrated experimental and theoretical framework to demonstrate how impressed shear flows appears as pseudo-diffusion in magnitude DW MR signals obtained using PFG spin-echo (PGSE) NMR and MRI sequences. We reinterpret the possible causes of signal loss in DWI in-vivo and revise and generalize the previous notion of intra-voxel incoherent motion (IVIM) in order to be able to describe activity driven flows that appear as pseudo-diffusion over multiple length and time scales in living tissues.

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    1. Characterization of tissue structure at varying length scales using temporal diffusion spectroscopy (pages 745–756)

      John C. Gore, Junzhong Xu, Daniel C. Colvin, Thomas E. Yankeelov, Edward C. Parsons and Mark D. Does

      Article first published online: 30 JUL 2010 | DOI: 10.1002/nbm.1531

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      Temporal diffusion spectra were obtained using oscillating gradient waveforms in diffusion-weighted measurements, and represent the manner in which the frequency components of molecular motions vary in different geometrical structures that restrict diffusion. Such spectra reveal information on the relative contributions of spatial restrictions at different distance scales. Computer simulations and experimental data suggest that diffusion spectral measurements may be used to characterize tissue structure, and are more sensitive for the detection of changes at subcellular scales than conventional measurements.

    2. From single-pulsed field gradient to double-pulsed field gradient MR: gleaning new microstructural information and developing new forms of contrast in MRI (pages 757–780)

      Noam Shemesh, Evren Özarslan, Michal E. Komlosh, Peter J. Basser and Yoram Cohen

      Article first published online: 5 AUG 2010 | DOI: 10.1002/nbm.1550

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      The merits and limitations of the single-pulsed field gradient (s-PFG) methodology are briefly reviewed. Then, double-PFG (d-PFG) NMR and MRI methodologies are reviewed, together with basic theoretical foundations and recent advances in the theory that have enabled the accurate extraction of novel microstructural information. We present recent studies validating the theoretical findings on phantoms in which the ground truth is known a priori, a crucial step prior to the application of the methodology in neuronal tissue. Finally, recent findings in d-PFG MRI, which suggest that it may become an important MRI methodology, are reviewed.

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    1. Steady-state diffusion-weighted imaging: theory, acquisition and analysis (pages 781–793)

      Jennifer A. McNab and Karla L. Miller

      Article first published online: 31 MAY 2010 | DOI: 10.1002/nbm.1509

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      Steady-state Diffusion-Weighted imaging (DWI) is highly efficient and compatible with three-dimensional acquisitions, which could enable high-resolution, low-distortion images. However, the same properties that lead to its efficiency make steady-state DWI highly susceptible to motion and create a complicated signal with dependence on T1,T2 and flip angle. Recent developments in gradient hardware, motion-mitigation and signal analysis offer potential solutions to these problems, reviving interest. This review provides an overview of steady-state DWI signal formation, acquisition and analysis.

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    1. Effects of motion and b-matrix correction for high resolution DTI with short-axis PROPELLER-EPI (pages 794–802)

      Murat Aksoy, Stefan Skare, Samantha Holdsworth and Roland Bammer

      Article first published online: 11 MAR 2010 | DOI: 10.1002/nbm.1490

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      The effects of change in b-matrix as a result of patient motion are investigated and correction methods are demonstrated for high-resolution diffusion tensor impaging.

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    1. Twenty-five pitfalls in the analysis of diffusion MRI data (pages 803–820)

      Derek K. Jones and Mara Cercignani

      Article first published online: 29 SEP 2010 | DOI: 10.1002/nbm.1543

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      In this article, we highlight 25 pitfalls in the pipeline used for analysis of diffusion MRI, from pre-processing of raw data, through tensor estimation and extraction of scalar parameters, to group statistical comparisons.

    2. Mapping brain anatomical connectivity using white matter tractography (pages 821–835)

      Mariana Lazar

      Article first published online: 29 SEP 2010 | DOI: 10.1002/nbm.1579

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      White matter tractography techniques have undergone extensive development in the last several years, and have been proven to have the potential to reveal new and important information regarding brain organization. This article reviews the latest developments in this field.

    3. MR diffusion kurtosis imaging for neural tissue characterization (pages 836–848)

      Ed X. Wu and Matthew M. Cheung

      Article first published online: 9 JUL 2010 | DOI: 10.1002/nbm.1506

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      In this work, the theory of diffusion kurtosis and DKI including the directional kurtosis analysis is revisited. Several recent rodent DKI studies from our group are summarized, and DKI and DTI compared for their efficacy in detecting neural tissue alterations. By quantifying both mean and directional kurtoses and diffusivities, DKI may provide improved sensitivity and specificity in MR diffusion characterization of neural tissues.

    4. Diffusion imaging of brain tumors (pages 849–864)

      Stephan E. Maier, Yanping Sun and Robert V. Mulkern

      Article first published online: 29 SEP 2010 | DOI: 10.1002/nbm.1544

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      In most brain tumors, when compared with normal brain tissue, water diffusion measured with conventional diffusion MRI is elevated. The presence of peritumoral edema, which also exhibits an elevated diffusion coefficient, often precludes the delineation of the tumor on the basis of this diffusion information alone. MR diffusion measurements performed over an extended range of diffusion weighting, however, permit the superior separation of malignant brain tumors, peritumoral edema and normal brain tissue.

    5. Diffusion imaging in multiple sclerosis: research and clinical implications (pages 865–872)

      M. Inglese and Maxim Bester

      Article first published online: 29 SEP 2010 | DOI: 10.1002/nbm.1515

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      Diffusion MRI has enhanced our understanding of MS pathophisiology. DTI-derived measures are more specific to the disease pathological processes and sensitive to the diffuse microscopic injury in the normal-appearing brain tissue. DTI-derived measures correlate with physical disability and cognitive impairment and the degree of DTI changes in normal-appearing tissue may have predictive value of the subsequent clinical evolution. DTI-derived measures hold promise as a tool for monitoring treatment response in MS clinical trials.

    6. Love songs, bird brains and diffusion tensor imaging (pages 873–883)

      Geert De Groof and Annemie Van der Linden

      Article first published online: 28 JUL 2010 | DOI: 10.1002/nbm.1551

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      Diffusion tensor imaging (DTI) as a method for quantifying seasonal changes of the songbird brain is reviewed. In this review the song control system of songbirds is introduced as a natural model for brain plasticity. At the same time we point out the added value of the songbird brain model for in vivo diffusion tensor techniques and its derivatives.

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    14. Current Awareness
    1. In vivo diffusion tensor magnetic resonance imaging and fiber tracking of the mouse brain (pages 884–896)

      Laura-Adela Harsan, Dominik Paul, Susanne Schnell, Bjorn W. Kreher, Jürgen Hennig, Jochen F. Staiger and Dominik von Elverfeldt

      Article first published online: 8 MAR 2010 | DOI: 10.1002/nbm.1496

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      In the present study, various mouse brain fiber pathways were identified using in vivo non-invasive DT-MRI. The major white matter tracts were characterized three-dimensionally. The rich connectivity between the amygdala and different brain areas was visualized for the first time non-invasively in the rodent brain, using deterministic and probabilistic fiber tracking. Diffusion tensor derived parameters, such as fractional anisotropy, volume ratio or main eigenvalues allowed quantitative comparisons in-between regions of interest and showed significant differences between various white matter regions.

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