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Tissue Biophysics and Biomimetics

Peter J. Basser, PhD, Head, Section on Tissue Biophysics and Biomimetics
Lin-Ching Chang, PhD, Contractor
Ferenc Horkay, PhD, Staff Scientist
Iren Horkayne-Szakaly, MD, Volunteer
Cheng Guan Koay, PhD, Postdoctoral Fellow
Michal Komlosh, PhD, Contractor
David Lin, PhD, Postdoctoral Fellow
Amritha Nayak, Technical Training Fellow
Uri Nevo, PhD, Volunteer
Alexander Novikov, PhD, Postdoctoral Fellow
Evren Özarslan, PhD, Visiting Fellow
Carlo Pierpaoli, MD, PhD, Staff Scientist
Joelle Sarlls, PhD, Postdoctoral Fellow
Candida Silva, PhD, Volunteer
Ichiji Tasaki, MD, PhD, Volunteer
Lindsay Walker, MS, Contractor

We try to understand fundamental relationships between function and structure in soft tissues, “engineered” tissue constructs, and tissue analogs, specifically how microstructure, hierarchical organization, composition, and material properties of tissue affect biological function and dysfunction. To investigate biological and physical model systems at different time and length scales, we make physical measurements in tandem with analytical and computational models. 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 vary water content or ionic composition. To probe tissue structure and dynamics, we employ small-angle X-ray scattering (SAXS), small-angle neutron scattering (SANS), static light scattering (SLS), dynamic light scattering (DLS), and nuclear magnetic resonance (NMR) relaxometry. We use mathematical models to understand how changes in tissue microstructure and physical properties affect essential transport processes (e.g., mass, charge, and momentum). The most direct non-invasive method for characterizing these transport processes in vivo is magnetic resonance imaging (MRI), which can characterize normal tissue microstructure and follow its changes in development, degeneration, and aging. A goal of our work is to translate our new quantitative methodologies from bench to bedside.

Virtual in vivo tissue biopsy

We are continuing to develop novel in vivo MRI methods to probe tissue microstructure and diagnose neurological and developmental disorders. Diffusion Tensor MRI (DTI) is the most mature technology that we invented and developed. With it, we measure a diffusion tensor of water, D, within an imaging volume, voxel-by-voxel. Information derived from D includes the local fiber-tract orientation, the mean-squared distance that water molecules diffuse in each direction, the orientationally averaged mean diffusivity, and other intrinsic scalar (invariant) quantities that are independent of the laboratory coordinate frame used to make these measurements. The scalar parameters derived from D behave like quantitative histological “stains” but are “developed” without using exogenous contrast agents or dyes. One of these parameters, the bulk or orientationally averaged diffusivity, is the most successful imaging parameter proposed to date for identifying ischemic tissue in the brain during an acute stroke. Measures of diffusion anisotropy (such as the "Fractional Anisotropy" or FA) have been useful in following changes in normally and abnormally developing gray and white matter that cannot be detected with other imaging methods.

We have also pioneered the use of color maps to encode nerve fiber orientation, allowing us to identify the main association, projection, and commissural white matter pathways in the brain and even to distinguish white matter pathways having similar structure and composition but different orientations. To assess anatomical connectivity among various functional brain regions, we developed DTI fiber tractography to track nerve fiber trajectories by continuously following the direction along which the apparent diffusivity is a maximum. While the reliability of DTI tractography is high in coherently organized primary white matter pathways, artifactual tracts may be generated when following white matter pathways with a more complex underlying fiber topology (e.g., pathways that “kiss,” cross, merge, or branch). We have developed a number of approaches to address false positives and false negatives in DTI tractography.

We have proposed several advanced in vivo MR methods to measure fine-microstructural features of nerve fascicles, which previously could be measured only by using laborious histological methods. One approach is CHARMED (Composite Hindered And Restricted Model of Diffusion), a combined experimental and modeling framework that allows us to describe water diffusion in brain white matter. More specifically, CHARMED permits us to distinguish between water diffusing within the intra-axonal spaces and extra-axonal compartments, thereby improving the angular resolution in tract tracing and resolution of fibers that cross. Recently, we extended CHARMED to measure axon diameter distribution within large white matter fascicles. We dubbed this method AxCaliber. After laborious validation studies, we just recently reported the first in vivo measurement of axon diameter distribution in the corpus callosum of the brain of a live rat. This quantity is quite important from a neurophysiological and developmental perspective, because the axon diameter determines nerve conduction velocity, and thus influences the sequencing and rate of information transfer along a nerve pathway.

While gray matter appears featureless in DTI, its microarchitecture is rich and varied within the brain. We have been developing several non-invasive, in vivo methods to "drill down" into the image voxel to measure unique features of gray matter. One goal of this work is to be able to "parcellate" or segment the cerebral cortex in vivo into its distinct "Brodmann areas." To this end, we are developing advanced MRI sequences to probe correlations between microscopic displacements of water molecules within different gray matter regions as well as sophisticated mathematical models describing water displacements to infer key microstructural and morphological features of gray matter. We hope to be able to use these new measurements to be able to follow normal and abnormal development of the cerebral cortex. In another approach, we attempt to characterize features of "anomalous" or fractal diffusion in neuropil.

MRI study of normal brain development

Four NIH Institutes (NICHD, NIMH, NINDS, and NIDA) have jointly sponsored a multicenter study to advance our understanding of brain development in typical, healthy children and adolescents. The study has enrolled approximately 500 children, ranging from infancy to young adulthood, who have been seen at different times over a six-year period (2001–2007) at several clinical centers around the United States. The Brain Development Cooperative Group has acquired brain MRIs in these subjects and is relating their imaging findings to the results of standardized neuropsychological tests.

Our role in this interdisciplinary project is to serve as a DTI data processing center (DPC). We have begun processing and analyzing all DTI data that the various clinical centers acquired during the course of the study. In anticipation, during the past several years, we have been developing and implementing a novel DTI data processing pipeline. Specifically, we have developed procedures for sorting, displaying, and co-registering the raw diffusion-weighted images (DWIs) from which the DTI data are computed. The image registration procedure removes the effects of subject motion and eddy current distortion and aligns the images to a given template with only one interpolation step, ensuring minimal loss of data quality. We also developed a new strategy for robust estimation of diffusion tensors and the quantities derived from them. We undertook the task of registering DTI data to other structural MRI data in the public database by using rigid body and linear (affine) transformations. More recently, we addressed the issue of correcting image distortion originating from the Echo-Planar Image (EPI) acquisition used for DTI.

In 2005, the project received Neuroscience Blueprint funds to expand the DTI portion of the study. The original DTI scan 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. The study’s expansion is increasing the quality and quantity of data collected through longer or additional scanning sessions for older subjects and through the recruitment of new subjects and scanning sessions for the younger cohort. Our group designed the expanded DTI protocol and coordinated its implementation at each acquisition site, completing data collection in 2007. During the past two years, we have been receiving raw DWI data and structural MRI targets for processing through our pipeline. This year, we completed the development of a user-friendly interface and software (TORTOISE) to enable educated lay users to estimate DTI brain volumes from DWI data, correcting for the numerous artifacts described above, as well as to display and analyze the processed DTI data. We plan to release this "pipeline" publicly in the coming months, (e.g., through NITRC http://www.nitrc.org/projects/tortoise). In particular, we also plan to use this advanced processing pipeline to produce high-quality normative DTI data from The Brain Development Cooperative Group to make it publicly available through the BIRN (https://www.nitrc.org/projects/birn/).

Looking forward, to permit analysis of novel MRI data sets, like the one described above, and to enable new clinical and biological applications of DTI (and of other novel displacement MRI methods that we are developing), we need to create new mathematical, statistical, and image-sciences concepts and tools. To date, we have developed algorithms for continuous, smooth approximation to the discrete, noisy, measured DTI field data to reduce noise and enable us to follow fiber tracts more reliably. We proposed a new Gaussian distribution for tensor-valued random variables that we used in designing optimal DTI experiments. In tandem, we have developed non-parametric empirical (e.g., Bootstrap) methods for determining the statistical distribution of DTI-derived quantities in order to study, for example, the inherent variability and reliability of white matter fiber tract trajectories. These parametric and non-parametric statistical methods will eventually enable us to apply powerful statistical hypothesis tests to a wide range of important biological and clinical questions that previously would be examined using ad hoc methods. More recently, we have been developing several empirical methods to describe and reduce the effect of noise on DTI data, and to better quantify variability of DTI data. We have also begun developing a diffusion MRI "phantom" to improve the quality of acquired data in hospital and research sites worldwide. However, much work still needs to be done to be able to draw statistically significant inferences from clinical DTI data, particularly longitudinal and multi-center studies.

Biopolymer physics: water-ion-biopolymer interactions

The study of water/ion/polymer interactions has the potential to contribute to a deeper understanding of ion-mediated structural organization of charged biopolymers and ultimately, functional properties of tissues. Physiological processes are accompanied by changes in the balance of ions and water molecules among fluid compartments within the tissue. Charged macromolecules dissociate in solution forming a macro-ion surrounded by an atmosphere of small mobile counterions. In biopolymer systems, such as polynucleic acids, proteins, and biological membranes, electrostatic interactions often play a key role in determining the phase behavior. We can study these phenomena by making measurements on well-defined model systems (e.g., DNA gels) at different length and time scales using an array of scattering techniques in combination with macroscopic osmotic and mechanical methods. In addition, we are performing simulation studies on polyelectrolyte solutions and hydrogels to determine the effect of ion concentration and ion valence on morphology from the molecular scale, to the nano-, micro-, and macroscales. We are particularly interested in understanding the mechanisms of interactions of Ca²⁺ ions with certain biopolymers, specifically the effect of Ca²⁺ ions on tissue structure and function.

Functional tissue properties arise from processes occurring at cellular and subcellular length scales. Therefore, the physical properties of tissues (e.g., osmotic and mechanical properties, state of hydration, and charge density) must all be characterized on distance scales below 100 nm. Understanding the interaction of polyelectrolytes with ions could help clarify the basic physics of ion binding as well as physical mechanisms affecting a large number of biological processes. In biology, osmotic pressure is particularly important in regulating and mediating physiological processes. To help understand the nature of physical/chemical interactions in biomolecules and biomolecular assemblies, we have developed an experimental approach to study simultaneously their structure (morphology) and thermodynamic properties as a function of the length scale (spatial resolution) by combining macroscopic osmotic swelling pressure measurements and small-angle scattering measurements. Swelling pressure measurements probe the system in the large length scale range, thus providing information on the overall thermodynamic response. SANS and SAXS allow us to investigate biopolymer molecules in their natural environment and to correlate the changes in the environmental conditions (e.g., ion concentration, ion valance, pH, temperature) with physical properties such as molecular conformation and osmotic pressure. SANS and SAXS simultaneously provide information about the size of various structural elements and their respective contribution to the osmotic properties. Combining these measurements allows us to both separate the scattering intensity arising from thermodynamic concentration fluctuations from the intensity scattered by large static superstructures (e.g., aggregates) and determine the length scales governing the macroscopic thermodynamic properties. This thermodynamic and structural information cannot be obtained by other techniques.

Specifically, we have applied this approach to study the effect of multivalent cations, particularly calcium ions, on the structure of various model systems mimicking soft tissues. Divalent cations are ubiquitous in the biological milieu, yet existing theories do not adequately explain their effect on and interactions with charged macromolecules. Moreover, experiments to study these interactions are difficult to perform, particularly in solution, because above a low ion concentration threshold multivalent cations generally cause phase separation or precipitation of charged molecules. Given that macroscopic phase separation does not occur in cross-linked gels, we have overcome this limitation by cross-linking our biopolymers, thus extending the range of ion concentrations over which the system remains stable and can be studied. In pilot studies, this new non-destructive procedure has been used to investigate cross-linked gels of the model synthetic polymer polyacrylic acid and biopolymers such as DNA and hyaluronic acid (HA) to determine the size of the structural elements that contribute to the osmotic concentration fluctuations. We have combined SANS and SAXS to estimate the osmotic modulus of HA solutions in the presence of monovalent and divalent counterions. We studied the diffusion processes in these solutions by DLS and determined the osmotic modulus from the relaxation response. We have developed an experimental procedure to determine the distribution of counterions around charged biopolymer molecules using anomalous SAXS measurements.

Functional properties of extracellular matrix

We are particularly interested in the functional properties of cartilage and other extracellular matrices in terms of their biopolymer constituents and their structure and interactions. Cartilage biopolymers exhibit hierarchical structures organized on multiple length scales, which emerge from molecular and supramolecular self-assemblies. Despite the abundance of information from high-resolution imaging and force measurement on single molecules, little is known about their structural and osmotic properties in physiological conditions. Our goal is to understand and explain the collective behavior of these systems from a knowledge of the properties of their constituents. Understanding the physical and chemical mechanisms affecting cartilage swelling is essential to understanding and predicting its critical functional properties—particularly its load-bearing and lubricating ability, given that they are governed by osmotic and electrostatic forces that strongly depend on tissue hydration.

We intend to gain a self-consistent physical picture of tissue structure/function relationships by measuring various physical/chemical properties of tissues and tissue analogs, at different scales, and using a variety of experimental techniques (e.g., osmometry, SANS, SAXS, neutron spin-echo, SLS, DLS, atomic force microscopy (AFM) and fluorescence correlation spectroscopy).

The swelling behavior of cartilage is sensitive to both biochemical and microstructural changes occurring in development, disease, degeneration, and aging. To study the thermodynamics of cartilage hydration, an array of techniques is required that probes not only a wide range of length scales but is also statistically representative volumes of the sample. Controlled hydration or swelling provides a direct means of determining functional properties of cartilage and of other extracellular matrices. Specifically, we have used controlled hydration of cartilage to measure physical/chemical properties of the collagen network and of the proteoglycans (PG) independently within the extracellular matrix. This approach entailed modeling the cartilage tissue matrix as a composite material consisting of two distinct phases: a collagen network and a concentrated proteoglycan solution trapped within it; applying various known levels of equilibrium osmotic stress; and 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 PG phases in native and in 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 in the OA specimens, collagen network stiffness declined. Our findings highlighted the role of the collagen network in limiting normal cartilage hydration and ensuring a high PG concentration in the matrix, which are both essential for effective load bearing in cartilage and lubrication but are lost in OA. These data also suggest that the loss of collagen network stiffness rather than 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, is that it requires a significant amount of tissue to obtain the osmotic titration curves. This leads to long equilibration times requiring many person-days to study a single cartilage specimen, rendering this approach unsuitable for routine pathological analysis or for use in tissue engineering applications. Recently, we developed a micro-osmometer to perform these experiments in a practical, rapid, and eventually automated manner. This instrument can measure minute amounts of water absorbed by small tissue samples (< 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 its surface. The high sensitivity of its resonance frequency to small changes in the amount of adsorbed water allows us to measure the mass uptake of a tiny tissue specimen precisely. Varying the equilibrium vapor pressure surrounding the specimen induces controlled changes in the osmotic pressure of the tissue layer. To validate the methodology, we used synthetic polymer gels with known osmotic properties.

The micro-osmometer permits us to obtain a profile of the osmotic compressibility or stiffness of multiple cartilage specimens simultaneously as a function of depth from the articular surface to the bone interface. It also allows us to assess the osmotic compatibility and mechanical integrity of developing tissues and of tissue-engineered cartilage (or ECM) with the hope of improving integration and viability following implantation. To demonstrate the applicability of the new apparatus, we measured the swelling pressure of tissue-engineered cartilage specimen.

Moreover, osmotic pressure measurements allow us to quantify the contributions of individual components of ECM (e.g., aggrecan, HA, and collagen) to the total tissue swelling pressure. Our recent osmotic pressure measurements on aggrecan/HA systems showed evidence of self-assembly of the bottlebrush-shaped aggrecan subunits into microgel-like assemblies. We found that aggrecan microgels of several microns in size coexist with smaller associations, as well as individual aggrecan molecules. The results also indicate that, in the presence of HA, the formation of the aggrecan-HA complex at low aggrecan concentrations reduces the osmotic pressure. However, in the physiological concentration range, the osmotic modulus of the aggrecan-HA complex is enhanced with respect to that of the random assemblies of aggrecan bottlebrushes, providing evidence that the aggrecan-HA complex improves the load-bearing function in cartilage.

Our combined static and dynamic scattering measurements (SAXS, SANS, SLS, DLS, neutron spin-echo) demonstrate that aggrecan assemblies exhibit remarkable insensitivity to changes in ionic environment, particularly to calcium ion concentration. This result is consistent with the role of aggrecan as an ion reservoir mediating calcium metabolism in cartilage and bone.

We also developed a method for mapping the local elastic and viscoelastic properties of cartilage using the AFM. Many of the impediments that previously hindered the use of the AFM to probe inhomogeneous samples, particularly biological tissues, have been addressed. The technique utilizes the precise scanning capabilities of a commercial AFM to generate large volumes of compliance data and extracts the relevant elastic properties from the data. In conjunction with results obtained from scattering measurements, micro-osmometry, and biochemical analysis, this technique will allow us to map spatial variations in the osmotic modulus of various tissue samples. Knowledge of the local osmotic properties of cartilage is particularly important, given that the osmotic modulus defines the compressive resistance to external load.

Additional Funding

Besides receiving direct support from the NICHD Intramural Research Program (IRP), since June, 2009, STBB began receiving support from the DoD/CNRM/NIH for studies directed to better understand and characterize traumatic brain injury in animal models and in humans.

Publications

Barazany D, Basser PJ, Assaf Y. In vivo measurement of axon diameter distribution in the corpus callosum of rat brain. Brain 2009 132:1210-1220.
Shemesh N, Özarslan E, Bar-Shir A, Basser PJ, Cohen Y. Observation of restricted diffusion in the presence of a free diffusion compartment: single- and double-PFG experiments. J Magn Reson 2009 200:214-225.
Koay CG, Özarslan E, Basser PJ. A signal transformational framework for breaking the noise floor and its applications in MRI. J Magn Reson 2009 199:94-103.
Horkay F, Lin DC. Mapping the local osmotic modulus of polymer gels. Langmuir 2009 25:8735–8741.
Yin D-W, Horkay F, Douglas JF, de Pablo JJ. Molecular simulation of the swelling of polyelectrolyte gels by monovalent and divalent counterions. J Chem Phys 2008 129:154902.

Collaborators

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
Emilios Dimitriadis, PhD, Division of Bioengineering and Physical Science, NIBIB, NIH, Bethesda, MD
Raisa Freidlin, MS, Computational Bioscience and Engineering Laboratory, CIT, NIH, Bethesda, MD
Erik Geissler, PhD, CNRS, Université Joseph Fourier de Grenoble, Grenoble, France
Anne-Marie Hecht, PhD, CNRS, Université Joseph Fourier de Grenoble, Grenoble, France
Wolfram Jarisch, PhD, LifeStar LLC, Potomac, MD
Richard Leapman, PhD, Laboratory of Bioengineering and Physical Science, NIBIB, Bethesda, MD
Stefano Marenco, PhD, 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 and Applied Mechanics of the Russian Academy of Sciences, Novosibirsk, Russia
Bradley Roth, PhD, Oakland University Department of Physics
Brain Development Cooperative Group

Contact

For more information, email pjbasser@helix.nih.gov or visit stbb.nichd.nih.gov.

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