Peter J. Basser, PhD, Head, Section on Tissue Biophysics and Biomimetics
Ferenc Horkay, PhD, Staff Scientist
Carlo Pierpaoli, MD, PhD, Staff Scientist
Lin-Ching Chang, PhD, Postdoctoral Fellow
David Lin, PhD, Postdoctoral Fellow
Cheng Guan Koay, PhD, Visiting Fellow
Michal Komlosh, PhD, Visiting Fellow
Uri Nevo, PhD, Visiting Fellow
Evren Ozarslan, PhD, Visiting Fellow

We try to understand fundamental relationships between function and structure in soft tissues, in "engineered" tissue constructs, and in tissue analogues, focusing on how microstructure, hierarchical organization, composition, and material properties of tissue affect its biological function and dysfunction. Our physical perspective involves physical measurements in tandem with analytical and computational models in order to interrogate biological and physical model systems at different time and length scales. Primarily, we use water to probe both equilibrium and dynamic interactions among tissue constituents over a wide range of time and length scales. To determine the equilibrium osmo-mechanical properties of well-defined model systems, we systematically vary water content or ionic composition. To probe tissue structure and dynamics, we employ small-angle X-ray and neutron scattering, static and dynamic light scattering, and NMR relaxometry. We use mathematical models to understand how essential transport processes (e.g., of mass, charge, momentum) are affected by changes in tissue microstructure and physical properties. The most direct noninvasive means to characterize these transport processes in vivo is with magnetic resonance imaging (MRI) methods, which can characterize normal tissue microstructure and follow its changes in development, degeneration, and aging. Another goal is to translate our new quantitative methodologies from "bench to bedside."

Virtual in vivo tissue biopsy

Basser, Pierpaoli, Komlosh, Nevo, Ozarslan; in collaboration with Aldroubi, Assaf, Barnett, Cohen, Freidlin, Jarisch, Jones, Pajevic, Pikalov

We are continuing to develop novel MR methods that allow us to probe tissue microstructure and diagnose neurological and developmental disorders in vivo. Diffusion Tensor MRI (DT-MRI) is the most mature such technology. With it, we measure a diffusion tensor of water, D, on a pixel-by-pixel basis within tissue. Information derived from D includes the local fiber-tract orientation, the mean-squared distance that water molecules diffuse in any given direction, the orientationally averaged mean diffusivity, and other intrinsic scalar-invariant quantities that are independent of the laboratory coordinate system. These scalar parameters are like quantitative histological "stains" that are "developed" without exogenous contrast agents or dyes. The bulk or orientationally averaged diffusivity has been the most successful imaging parameter proposed to date for identifying ischemic tissue regions in the brain during acute stroke. Furthermore, measures of diffusion anisotropy are useful in identifying white matter degeneration (e.g., Wallerian degeneration) associated with chronic stroke. DT-MRI also provides new information about early developmental changes in cortical gray and white matter, which cannot be detected with other imaging methods.

Currently, we are developing new ways to use MR water diffusion data to perform "virtual in vivo tissue biopsy" of the brain, i.e., to perform detailed structural anatomic studies of the brain. One approach involves MR images that encode nerve fiber orientation by color, allowing us to identify the main association, projection, and commissural white matter pathways in the brain and even to differentiate white matter pathways with similar structure and composition but distinct spatial orientations. To assess anatomical connectivity between different functional brain regions, we developed "DT-MRI fiber tractography" to track nerve fiber tract trajectories by continuously following the direction along which the apparent diffusivity is a maximum. While the reliability of DT-MRI tractography is high in coherently organized primary white matter pathways, artifactual tracts can be generated when following white matter pathways with a more complex underlying fiber topology (e.g., that cross, merge, or branch). To assess the reliability of individual computed tracts, we used point-wise assessment of streamline tractography attributes (PASTA). We are using other MR data and more detailed models of water diffusion in tissue to compensate for artifacts. For example, we are developing a new modeling and experimental framework to describe water diffusion in white matter, enabling us to distinguish between water diffusing within the intra-axonal space and extra-axonal compartments, improving the angular resolution in tract tracing and resolution of fibers that cross.

More recently, we developed an MR method called "Axcaliber" to measure the axon diameter distribution within large fascicles in vivo. We use the resultant information to assess pathological changes in white matter in disease and to segment white matter regions in the brain and spinal cord according to the local diameter distribution of axons. In addition, we applied MR sequences developed originally for applications in materials sciences to probe the correlations between displacements of individual spins within tissue. Along with the more detailed mathematical models of tissue microstructure and morphology that we developed, we can infer more structural information about gray matter than DT-MRI can provide. We are also developing mathematical models of water diffusion in "packs" or arrays of cylinders that resemble fibrous soft tissues, allowing us to relate diffusion properties that we measure in the tissue in the aggregate to important microstructural and anatomical features.

In general, clinical and biological applications of DT-MRI (and of other novel displacement MRI methods) require the development of new mathematical, statistical, and image-sciences concepts and tools that would permit analysis of novel multidimensional data sets. We developed algorithms for continuous, smooth approximation to the discrete, noisy, measured diffusion tensor field data, reducing noise and enabling us to follow fibers more reliably, and recently derived a new Gaussian distribution for tensor-valued random variables, which we used to design "optimal" DT-MRI experiments. In addition, we developed nonparametric empirical (e.g., the Bootstrap) methods for determining features of the statistical distribution of experimental DT-MRI data, most recently, for studying the inherent variability and reliability of white matter fiber tract trajectories. These parametric and nonparametric statistical methods enable us to apply powerful statistical hypothesis tests to a wide range of important biological and clinical questions that previously could be examined only by using ad hoc methods.

MRI study of normal brain development

Pierpaoli, Basser, Chang, Koay, Ozarslan

Many obstacles have impeded developments in neuroimaging research on childhood brain disorders, including difficulties in obtaining data from children given their limited ability to comply with procedures; the lack of an adequate normative database with which to characterize normal brain development and against which to identify and measure aberrant brain development; the lack of adequate image-analysis tools for characterizing developmental changes in the brain; and the lack of adequate means for disseminating and sharing data analytic tools. Several Institutes (NICHD, NIMH, NINDS, and NIDA) have jointly sponsored a multicenter consortium to study brain development in normal, healthy children and adolescents, enrolling approximately 500 children at several clinical centers around the United States. The children range from infants to young adults and will be seen at different times over a six-year period. The consortium is performing MRIs of the brain and relating imaging findings to the results of standardized neuropsychological tests.

In addition to facilitating the study of normal human brain development and providing a necessary, representative, and reliable source of normal control data for studies of children with brain disorders and diseases, the study aims to provide growth curves for normal brain anatomy and to aid in developing novel pediatric neuroimaging tools and methodologies. More information about the study is available at the MRI Study of Normal Brain Development Website: http://www.brain-child.org/.

Our role in the study is to serve as a data-processing center to process and analyze all diffusion tensor MRI (DT-MRI) data acquired by the various clinical centers during the course of the study. A detailed description of our group's specific tasks can be found at http://www.brain-child.org/rcenters/DPC.html. We previously developed methods to warp and register multidimensional diffusion-weighted image data sets obtained from children, both to correct for distortion due to eddy currents and motion artifacts and to permit the data to be mapped to a common template. An important and general finding revealed that image registration itself can alter the statistical properties of image data sets, which must be accounted for in subsequent statistical analysis. We have developed several algorithms that allow DT-MRI data to be imported from the various clinical centers and to be examined for acquisition artifacts. Our approach is also useful in designing optimal diffusion tensor imaging (DTI) experiments and can be applied to obtain parametric statistical distributions of important tensor-derived quantities for use in pediatric imaging applications. More recently, we explored new strategies for assessing the effects of noise propagation from diffusion-weighted images to tensor-derived quantities. In general, these activities all aim at developing and implementing a robust data-processing and analysis "pipeline" to support quantitative clinical DT-MRI studies.

In 2005, the project was awarded Neuroscience Blueprint funds to expand the DTI portion of the study. The original DTI data collection was limited to a 10-minute protocol performed on those subjects able to tolerate additional time in the scanner following the collection of the core structural MRI data. Expansion of the study will increase the quality and quantity of data collected through an additional scanning session fully dedicated to DTI. Additional children in the younger cohort (birth to four years) will also be recruited and scanned with the expanded DTI protocol. Our group designed the expanded DTI protocol and has coordinated its implementation at each acquisition site. The sites are now successfully performing DTI scans with the new protocol.

Biopolymer physics: water-ion-biopolymer interactions

Horkay, Lin, Basser; in collaboration with Geissler, Hecht, Tasaki

To help us understand the nature of physical/chemical interactions taking place in biomolecules and biomolecular assemblies in living systems, we developed an experimental approach to study the biomolecules' and assemblies' structure (morphology) and thermodynamic properties as a function of the length scale (i.e., spatial resolution). The methodology combines low-resolution macroscopic osmotic-swelling pressure measurements and various high-resolution scattering experiments. Macroscopic swelling pressure measurements probe the system in the coarse length-scale regime, providing information about the overall thermodynamic response. Small-angle neutron scattering (SANS), static light scattering (SLS), and dynamic light scattering (DLS) collectively provide information about the sizes of structural elements and their respective contribution to macroscopic osmotic properties. Combining these measurements allows us both to separate the scattering intensity caused by thermodynamic concentration fluctuations from large static superstructures (e.g., aggregates) and determine the length scales of fluctuations that give rise to macroscopic thermodynamic properties. The combined thermodynamic and structural information cannot be obtained by other techniques.

Specifically, we have applied this approach to the effects of multivalent cations, particularly calcium, on the structure and morphology of various biomolecules. Divalent cations are ubiquitous in the biological milieu, yet existing theories do not adequately explain their effect on and interactions with charged polymers or biomolecules. Moreover, experiments to study the interactions are difficult to perform, particularly in solution, because multivalent cations above a low concentration threshold generally cause phase separation or precipitation of charged molecules. As macroscopic phase separation does not occur in cross-linked gels, we overcame the limitation associated with concentration levels by cross-linking our biopolymers, extending the range of ion concentrations over which the system remains stable and can be studied. We applied the new method in pilot studies of cross-linked gels of DNA and of the model synthetic polymer polyacrylic acid. Concentrated DNA solutions and novel DNA gels have never before been investigated with SANS in conjunction with osmotic measurements. Our method also provides a unique framework for analyzing the osmotic and scattering behavior of other biomolecular systems.

We also investigated cross-linked gels of the biopolymer hyaluronic acid to determine the size of the structural elements that contribute to the osmotic concentration fluctuations. We combined small-angle X-ray scattering (SAXS) and SANS to estimate the osmotic modulus of hyaluronic acid solutions in the presence of monovalent and divalent counterions. We also investigated the diffusion processes in biopolymer solutions, using DLS to determine the osmotic modulus independently from the dynamic response.

Functional properties of extracellular matrix

Horkay, Lin, Basser; in collaboration with Washburn

The swelling behavior of cartilage is exquisitely sensitive to biochemical and microstructural changes occurring in development, disease, degeneration, and aging. Knowledge of the mechanisms affecting cartilage hydration (water uptake) is also essential to understanding and predicting cartilage's load-bearing and lubricating ability given that it is primarily the osmotic properties of cartilage's constituents that allow it to resist applied loads and express or imbibe fluid, respectively.

Conversely, we have previously shown that controlled hydration or swelling of cartilage can provide a means of determining functional properties of cartilage's extracellular matrix (ECM), thus permitting the independent measurement of important physical/chemical properties of the collagen network and proteoglycans (PG) within the ECM. This approach involves (1) modeling the ECM as a composite material consisting of two distinct phases: a collagen network and a proteoglycan solution trapped within it; (2) applying various known levels of equilibrium osmotic stress; and (3) using physical-chemical principles and additional experiments to determine a "pressure-volume" relationship for both the PG and collagen phases independently. In pilot studies, we used this approach to determine pressure-volume curves for the collagen network and the PG phases in native and trypsin-treated normal human cartilage specimens as well as in cartilage specimens from osteoarthritic (OA) joints. In both normal and trypsin-treated specimens, collagen network stiffness appeared unchanged, whereas collagen network stiffness declined in the OA specimen. Our findings highlight the role of the collagen network in limiting normal cartilage hydration and ensuring a high PG concentration in the matrix, both of which are essential for effective load bearing in cartilage and lubrication but are lost in OA. The data also suggest that the loss of collagen network stiffness, and not the loss or modification of PGs, may be the incipient event leading to the subsequent disintegration of cartilage observed in OA.

One shortcoming of this approach, however, was that it took many days to analyze a single cartilage specimen, making the technique unsuited to routine pathological analysis or tissue engineering applications. Further, a significant amount of tissue was required to perform the osmotic titration experiments. Therefore, we recently invented and developed a new tissue micro-osmometer to perform such experiments practically and rapidly. The instrument can measure minute amounts of water absorbed by small tissue samples (less than 1 microgram) as a function of the equilibrium activity (pressure) of the surrounding water vapor. A quartz crystal detects the water uptake of a specimen attached to the crystal's surface. The high sensitivity of the crystal's resonance frequency to small changes in the amount of adsorbed water allows us to measure precisely the water mass uptake of the tissue specimen. Varying the equilibrium vapor pressure surrounding the specimen induces controlled changes in the osmotic pressure of the tissue layer. To illustrate the applicability of the new apparatus, we recently measured the swelling pressure of a tissue-engineered cartilage specimen.

The micro-osmometer will eventually permit us to obtain a profile of the osmotic compressibility or stiffness of several cartilage specimens simultaneously as a function of depth from the articular surface to the bone interface. It will also allow us to quantify the contributions of individual components of ECM (such as aggrecan, hyaluronic acid, collagen) to the total osmotic pressure. Moreover, it should allow us to assess the osmotic compatibility and mechanical integrity of developing tissues and tissue-engineered cartilage (or ECM) for improved integration following implantation.

We have recently developed an atomic force microscopy (AFM) technique for mapping the local elastic properties of tissues. We have successfully addressed many of the issues that previously hindered use of the AFM in high-throughput probing of inhomogeneous samples, particularly biological tissues. The technique uses the precise scanning capabilities of a commercial AFM to generate large volumes of compliance data and automatically extracts the relevant elastic properties from the data. In conjunction with results obtained from micro-osmometry and biochemical analysis, AFM will allow us to map spatial variations in the load-bearing capacity of cartilage specimens.

COLLABORATORS

Akram Aldroubi, PhD, Vanderbilt University, Nashville, TN
Yaniv Assaf, PhD, Tel Aviv University, Tel Aviv, Israel
Alan Barnett, PhD, Clinical Brain Disorders Branch, NIMH, Bethesda, MD
Yoram Cohen, PhD, Tel Aviv University, Tel Aviv, Israel
Raisa Freidlin, MS, Computational Bioscience and Engineering Laboratory, CIT, NIH, Bethesda, MD
Erik Geissler, PhD, Laboratoire de Spectrométrie Physique, CNRS, Université Joseph Fourier de Grenoble, Grenoble, France
Mark Hallett, MD, Medical Neurology Branch, NINDS, Bethesda, MD
Anne-Marie Hecht, PhD, Laboratoire de Spectrométrie Physique, CNRS, Université Joseph Fourier de Grenoble, Grenoble, France
Wolfram Jarisch, PhD, LifeStar LLC, Potomac, MD
Stefano Marenco, MD, Clinical Brain Disorders Branch, NIMH, Bethesda, MD
Pedro Miranda, PhD, Universidade de Lisboa, Lisbon, Portugal
Sinisa Pajevic, PhD, Mathematical and Statistical Computing Laboratory, CIT, NIH, Bethesda, MD
Valery Pikalov, PhD, Institute of Theoretical & Applied Mechanics of the Russian Academy of Sciences, Novosibirsk, Russia
Gustavo Rohde, MS, University of Maryland, College Park, MD
Pabitra Sen, PhD, Schlumberger-Doll Research, Ridgefield, CT
Ichiji Tasaki, MD, Laboratory of Cellular and Molecular Regulation, NIMH, Bethesda, MD
Newell Washburn, PhD, NIST, Gaithersburg, MD

For further information, contact pjbasser@helix.nih.gov.