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Quantitative Imaging and Tissue Sciences

• Peter J. Basser, PhD, Head, Section on Quantitative Imaging and Tissue Sciences
• Ferenc Horkay, PhD, Staff Scientist
• Julian Rey, PhD, Postdoctoral Intramural Research Training Award Fellow
• Nathan Williamson, PhD, Postdoctoral Intramural Research Training Award Fellow
• Velencia Witherspoon, PhD, Postdoctoral Intramural Research Training Award Fellow
• Alexandru Avram, PhD, Collaborating Scientist funded via the Henry Jackson Foundation and the Center for Neuroscience and Regenerative Medicine
• Michal Komlosh, PhD, Collaborating Scientist funded via the Henry Jackson Foundation and the Center for Neuroscience and Regenerative Medicine
• Magdoom Kulam, PhD, Collaborating Scientist funded via the Henry Jackson Foundation and the Center for Neuroscience and Regenerative Medicine
• Alexandros Chremos, PhD, Collaborating Contract Scientist
• Rea Ravin, PhD, Collaborating Contract Scientist
• Kadharbatcha Saleem, PhD, Collaborating Contract Scientist
• Teddy Cai, BS, Predoctoral Intramural Research Training Award Fellow, NIH OxCam Program
• Hiya Sawhney, BS, Postbaccalaureate Intramural Research Training Associate

In our tissue-sciences research, we strive to understand fundamental relationships between function and structure in living tissues. Specifically, we are interested in how tissue microstructure, hierarchical organization, composition, and material and transport properties all work together to affect biological function or dysfunction. We investigate biological and physical model systems at various length and time scales, performing biophysical measurements and developing novel physical/mathematical models (including molecular dynamics [MD] and continuum models) to explain their functional properties and behavior. Inextricably connected with these activities is our study of water and its interactions with macromolecules and ions in biological media. Experimentally, we use water to probe tissue structure and function from nanometers to centimeters and from microseconds to lifetimes. Our armamentarium includes small-angle neutron scattering (SANS), small-angle X-ray scattering (SAXS), static light scattering (SLS), dynamic light scattering (DLS), atomic force microscopy (AFM), osmometry, and multi-dimensional nuclear magnetic resonance (NMR) relaxometry and diffusometry. A goal is to develop a self-consistent picture of system behavior across length and time scales. Armed with this understanding, we develop research tools that can be translated from bench-based quantitative methodologies to the bedside biomarkers to aid in diagnosis and therapy.

Our activities dovetail with our basic and applied research in quantitative imaging, which is intended to generate measurements and maps of intrinsic physical quantities, including diffusivities, relaxivities, exchange rates, etc., rather than produce qualitative ‘weighted’ MR images conventionally used in radiology. At a basic level, our work is directed toward making critical ‘invisible’ biological structures and processes ‘visible.’ Our quantitative imaging group uses knowledge of physics, engineering, applied mathematics, imaging and computer sciences, as well as key insights gleaned from our tissue-sciences research, to discover, vet, and develop novel quantitative imaging biomarkers that can detect changes in tissue composition, microstructure, and/or microdynamics with high sensitivity and specificity. The ultimate translational goal is to assess normal and abnormal developmental trajectories, diagnose childhood diseases and disorders, and characterize degeneration and trauma (such as mild traumatic brain injury). MRI is our imaging modality of choice because it is so well suited to many applications critical to the NICHD mission; it is non-invasive, non-ionizing, usually requires no exogenous contrast agents or dyes, and is generally deemed safe and effective for use with mothers, fetuses, and children in both clinical and research settings. Critical to this enterprise is our ability to follow water as it diffuses through complex media as a probe of its microstructure, and to assess water's interactions with biomolecules to identify distinct water compartments in tissues.

One of our translational goals, what we mean by “quantitative imaging,” has been to transform clinical MRI scanners into scientific instruments capable of producing reproducible, accurate, and precise imaging data with which to measure and map useful imaging biomarkers for various clinical applications, including single scans, longitudinal, and multi-site studies, personalized medicine, and genotype/phenotype correlation studies, as well as for populating imaging databases with high-quality normative data. From a more basic perspective, another goal has been to apply our various MRI tools and methodologies to advance neuroscience, providing new methods to explore brain structure/function relationships and architecture, such as “imaging” the human connectome.

In vivo MRI histology

The most mature in vivo MRI histological technology that we invented, developed, and clinically translated is Diffusion Tensor MRI (DTI), by which we measure and map D, a diffusion tensor of water, throughout an imaging volume. Information derived from this quantity includes white-matter fiber-tract orientation, the orientationally averaged mean apparent diffusion constant (mADC) or mean diffusivity (MD), and other intrinsic scalar (invariant) quantities. Such imaging parameters have been used by radiologists and neuroscientists as non-invasive quantitative histological ‘stains’ that are obtained by probing endogenous tissue water in vivo without requiring any exogenous contrast agents or dyes. In neuro-radiology, the mADC is the most widely used diffusion imaging parameter to identify ischemic areas in the brain during acute stroke and to follow cancer patients’ responses to therapy. With improvements in whole-body MRI, the mADC is becoming widely used to diagnose cancers, such as multiple myeloma, and assess disease progression and response to therapy. The measures of diffusion anisotropy we first proposed (e.g., the fractional anisotropy or FA) are also widely used to follow changes in normally and abnormally developing white matter and in many other clinical and neuroscience applications, such as brain white-matter visualization. Our group also pioneered the use of fiber direction–encoded color (DEC) maps to display the orientation of white matter pathways in the brain. To assess anatomical connectivity among various cortical and deep-brain gray-matter areas, we also proposed and developed DTI ‘Streamline’ Tractography, which is used by neuroscientists to track white-matter pathways to help establish ‘anatomical connectivity,' to help neurosurgeons plan brain surgeries and radiation oncologists plan radiation dosing, so as to spare ‘eloquent’ areas of the brain. Such advances in medical imaging also helped inspire several large federally funded research initiatives, including the NIH Human Connectome Project (HCP) and, more recently, the NIH Brain Initiative.

More recently, we invented and developed a family of advanced in vivo diffusion MRI methods to measure fine-scale microstructural features of axons and fascicles (also known as ‘microstructure imaging’), which otherwise could only be assessed using laborious ex vivo histological or pathological methods. Such features are generally orders of magnitude smaller than the imaging voxel, but remarkably can still be fleshed out using these advanced techniques. For example, we have been developing efficient means for performing ‘k- and q-space MRI’ in the living human brain, such as ‘Mean Apparent Propagator’ (MAP) MRI, an approach that can detect subtle microstructural and architectural features in both gray and white matter at micron-scale resolution. MAP MRI also subsumes DTI, as well as providing a bevy of new in vivo quantitative imaging biomarkers to measure and map. We also developed CHARMED MRI, which measures the average axon diameter (AAD), and AxCaliber MRI, which measures the axon-diameter distribution (ADD) along white-matter pathways, and we reported the first in vivo measurement of ADDs within the rodent corpus callosum. The ADD is functionally important, given that axon diameter is a critical determinant of conduction velocity and therefore the rate at which information is transmitted along axon bundles, and helps to determine the latencies or time delays of neural impulses between and among different brain areas. This led us to propose a novel MRI–based method to measure the ‘latency connectome,’ including a latency matrix that reports conduction times between different brain areas. We also developed a companion mathematical theory to explain the observed ADDs in different fascicles, suggesting that they represent a trade-off between maximizing information flow and minimizing metabolic demands. We developed novel multiple pulsed-field gradient (mPFG) methods and demonstrated their feasibility in vivo on conventional clinical MRI scanners as a further means to extract quantitative features in the central nervous system (CNS), such as the AAD and other features of cell-size distribution and cell shape.

Although gray matter appears featureless in the brain with DTI, its microstructure and architecture are rich and varied throughout the brain, not only along the brain's cortical surface, but also within and among its various cortical layers and the brain's deep gray-matter. To target this tissue, we have been developing several non-invasive, in vivo methods to measure unique features of cortical gray-matter microstructure and architecture that are plainly visible in electron micrographs (EM) but currently invisible in conventional MRI. One example is diffusion tensor distribution (DTD) MRI, in which we use a normal tensor-variate distribution, which we were the first to propose, to characterize heterogeneity within complex tissue voxels. One of our long-term goals is to ‘parcellate’ or segment the cerebral cortex in vivo into its approximately 500 distinct cytoarchitechtonic areas using non-invasive imaging methods. To this end, we are developing advanced MRI sequences and analysis pipelines to assess variability in tissue properties in the cortex, and others that probe correlations among relaxivities and diffusivities of different water pools there. In the latter case, we use multi-dimensional MRI relaxometry– and diffusometry–based methods to study water mobility and diffusion in gray and white matter. We continue to work to translate these and other methods to the clinic to help identify changes in normal and abnormal development, as well as in inflammation and trauma. Along these lines, we made excellent progress in previous years developing radiological-pathological correlations between MR and neuropathological images of TBI tissue specimens as a way to identify potential quantitative imaging biomarkers of injury or inflammation that have the potential to detect TBI in vivo. We are in the process of migrating many of these methods both to pre-clinical and clinical applications.

Quantitative MRI biomarker development

Clinical MRI still lacks the quantitative character of CT. The scope of conventional MRI clinical applications is limited to revealing either gross morphological features or focal abnormalities. Clinical MRI also often lacks the biological specificity necessary for developing robust and reliable imaging ‘biomarkers.’ In particular, MRI assessment of normal brain development and developmental disorders has benefited greatly from the introduction of ‘quantitative’ clinical MRI techniques, with which one measures and maps meaningful intrinsic physical quantities or chemical variables that possess physical units and can be compared among different tissue regions. Quantitative MRI methods such as DTI also increase sensitivity, providing a basis for monitoring subtle changes that occur, e.g., during the progression or remission of disease, by comparing measurements in a single subject against normative values obtained from a healthy population. Quantitative MRI methods should continue to advance ‘precision imaging’ studies, in which MRI phenotypic and genotypic data can be meaningfully incorporated and used for improved diagnosis and prognosis assessments.

To advance our quantitative imaging activities, we developed numerical and statistical methods, including algorithms that generate a continuous, smooth approximation to the discrete, noisy, measured DTI field data, so as to reduce noise, and which allowed us to implement ‘Streamline’ Tractography. We proposed a novel Gaussian distribution for the tensor-valued random variables that we use to design optimal DTI experiments and interpret their results. In tandem, we developed non-parametric empirical (e.g., Bootstrap) methods to determine the statistical distribution of DTI–derived quantities in order to study, e.g., the inherent variability and reliability of computed white-matter trajectories, enabling us to apply powerful hypothesis tests to assess the statistical significance of findings in a wide range of important biological and clinical applications that had previously been tested using ad hoc statistical methods. We are also developing novel methods to register different brain volumes and to generate group-average DTI data or atlases from various subject populations, based on the Kullback-Leibler divergence and other distance metrics, like the “earthmover's distance”.

Previously, we carried out clinical studies that utilize novel quantitative MRI acquisition and analysis methods and whose aim is to improve accuracy and reproducibility of diagnosis and to detect and follow normal and abnormal development. One early example is the NIH Study of Normal Brain Development, jointly sponsored by the NICHD, NIMH, NINDS, and NIDA, which was initiated in 1998 and intended to advance our understanding of normal brain development in typical healthy children and adolescents. The Brain Development Cooperative Group is still publishing, primarily by mining the rich high-quality MRI data, many of which our lab processed, serving as the DTI Data-Processing Center (DPC). The processed DTI data collected from the project were uploaded into a database and made publicly available through the National Database for Autism Research (NDAR). Our collaborator Carlo Pierpaoli, who spearheaded this work, continues to support, update, and disseminate the processing and analysis software called “TORTOISE,” which grew out of this effort and which can be downloaded from http://www.tortoisedti.org. A continuation of this effort to improve our ability to follow normal trajectories in pediatric brain development has been through a collaboration between the Bill and Melinda Gates Foundation and NICHD. Our role in this project is to develop new MRI pulse sequences and analysis pipelines to probe the state of different water populations in the developing brain. They have the potential to become quantitative imaging biomarkers suitable to follow pediatric brain development.

Traumatic Brain Injury (TBI) represents a significant public health challenge for our pediatric population, but also for young men and women who serve in the military. Our involvement in TBI research, particularly in detecting mild TBI (mTBI), has continued to expand through partnerships with various Department of Defense (DoD) entities. Diffusion MRI (dMRI) provides essential information to aid in the assessment of TBI, but conventional dMRI methods have lacked sufficient specificity. To improve the accuracy and reproducibility of MAP–MRI findings, we developed a data-processing pipeline, and, in collaboration with scientists at the DoD Military Traumatic Brain Injury Initiative (MTBI), performed the first normative MAP–MRI studies, and applied this new and powerful method to detect tissue damage in brains of individuals who have suffered TBI, extending our NICHD TORTOISE pipeline to be able to analyze MAP–MRI data. We have been employing promising multi-dimensional MRI relaxometry-diffusometry methods to study the etiology of various types of TBI, in collaboration with the USUHS Neuropathology Research Division and under the auspices of MTBI, and to improve the correlation and integration of neuropathology and neuro-radiological imaging data, so as to speed the deployment of new MRI methods to assess TBI. We also partnered with MTBI to study ways to measure very slow flows that occur during glymphatic transport, a mechanism the brain uses to wash away harmful macromolecules, just as the lymphatic system uses in other organs. With our partners at the University of Arizona, this research is providing experimental data to enable us to migrate these imaging approaches to the clinic, to be able to assess normal and pathological glymphatic transport in vivo.

We are also collaborating with Sara Inati, who studies focal epilepsy, a devastating disorder that is difficult to detect using conventional neuro-radiological methods. We are developing and testing various new MRI–based methods that we believe may reveal pathological microstructural features and changes in architectural organization of the brain in this disorder, for example, in cortical dysplasia, to improve localization and assessment of cortical lesions. One method we developed and believe has potential in this indication is diffusion tensor distribution (DTD) MRI. We are currently testing the utility of this approach on Sara Inati's patient cohort.

Previously, we have been collaborating with Roberto Romero and Mark Haacke to develop novel fetal brain MR imaging applications. Currently, it is challenging to measure quantitative imaging biomarkers in utero, particularly with diffusion MRI, owing to large-scale fetal and maternal motion during the scanning session, and the difficulty in acquiring image volumes with a sufficient field-of-view, quality, and spatial resolution in a clinically feasible amount of time. Our lab has been developing novel approaches to address each of these critical issues. The closure of NICHD's Perinatology program in Detroit last fiscal year, however, has interrupted this research, which we hope to be able restart at another institution.

Biopolymer physics: Water-ion-biopolymer interactions

Remarkably, despite their crucial role in biology, little is known about the physical underpinnings of water-ion-biopolymer interactions, particularly in the physiological ionic-strength regime. To determine the effect of ions on the structure and dynamics of key biopolymers, we developed a multi-scale experimental framework by combining macroscopic techniques (osmotic swelling-pressure measurements and mechanical measurements) with high-resolution scattering methods (e.g., SANS and SAXS, SLS and DLS), which probe the structure and interactions over a broad range of length and time scales. Macroscopic swelling-pressure measurements provide information on the overall thermodynamic response of the system, while SANS, SAXS, SLS and DLS allow us to investigate biopolymers at molecular and atomic through supramolecular length scales and to quantify the effect of changes in the environment (e.g., ion concentration, ion valance, pH, temperature) on the structure and interactions among biopolymers, water, and ions. Studies carried out on well defined model systems that mimic essential features of tissues provide important insights that cannot be obtained from experimental studies made on biological systems themselves. Mathematical models based on well established polymer-physics concepts and, more recently, molecular dynamics (MD) simulation and continuum mechanics make it possible to design experiments to quantify and explain aspects of tissue behavior and thus the underlying molecular and macroscopic mechanisms that govern key aspects of a tissue's normal functional properties.

Offshoots of these basic studies have led to numerous novel MRI phantom designs to support our quantitative imaging program, including diffusion MRI phantoms, which we use to calibrate scanners to assure the quality and fidelity of the imaging data in single-subject, longitudinal, and multi-site studies. For instance, our U.S. Patent for a ‘Phantom for diffusion MRI imaging’ is now incorporated in the CaliberMRI phantom, enabling quantitative diffusion MRI studies at a myriad of clinical sites worldwide. Our colleagues at NIST Boulder have incorporated our polyvinylpyrrolidone (PVP) polymer into their own diffusion MRI NIST standard. We used various glass microcapillary array (GCA) geometries to mimic features of white matter pathways and to interrogate our AxCaliber and dPFG MRI models. We also developed a variety of NMR and MRI phantoms, such as a 3-D printed polymeric phantom, which possess various salient features of cell or tissue systems, such as microscopic anisotropy, providing data with which to test the validity of our models and experimental designs. We are also developing novel polymer gel phantoms to calibrate water exchange experiments designed to follow water moving between different microenvironments.

Measuring and mapping functional properties of extracellular matrix

Extracellular Matrix (ECM) is the tissue that holds organs together and mediates virtually all transport processes taking place in organs, such as the transport of charge, mass, momentum, and energy. Physiologically, one cannot underestimate its importance. We study interactions among the main ECM components, often using cartilage as a model system because it is aneural, avascular, and almost acellular. In cartilage ECM, collagen (type II) is organized into fiber bundles that form a network that entraps the major proteoglycan (PG), a bottlebrush-shaped aggrecan. The biomechanical behavior of cartilage and other ECMs reflects their molecular composition and microstructure, which change during development, disease, degeneration, and aging. To determine tissue structure/function relationships, we measure various physical/chemical properties of ECM tissues and tissue analogs at different length and time scales, using a variety of complementary static and dynamic experimental techniques, e.g., osmometry, SANS, SAXS, neutron spin-echo (NSE), SLS, DLS, and AFM. As an example, understanding the physical and chemical mechanisms affecting cartilage swelling (hydration) is essential to predicting its load-bearing and lubricating ability, which are mainly governed by osmotic and electrostatic forces. To quantify the effect of hydration on cartilage properties, we previously developed a novel tissue micro-osmometer to perform precise and rapid measurements on small tissue samples (less than 1 microgram) as a function of the equilibrium water activity (vapor pressure). We also make osmotic pressure measurements to determine how the individual components of cartilage ECM (e.g., aggrecan and collagen) contribute to the total load-bearing capacity of the tissue. We also demonstrated that aggrecan-hyaluronic aggregates self-assemble into microgel particles, contributing to the improved dimensional stability and lubricating ability of the tissue. We further found that aggrecan is highly insensitive to changes in the ionic environment, particularly to divalent cations such as calcium, which is critical for maintaining the tissue's mechanical integrity and allowing aggrecan to serve as a calcium-ion reservoir in cartilage and bone.

More recently, to model cartilage ECM, we invented and developed a new biomimetic composite material consisting of polyacrylic acid (PAA) microgel particles dispersed and embedded within a polyvinyl alcohol (PVA) gel network or matrix. PAA mimics the proteoglycan phase (i.e., hyaluronic-aggrecan complexes), while PVA mimics the fibrous collagen network phase entrapping them. Remarkably, the PVA/PAA biomimetic model system reproduces not only the shape of the cartilage swelling pressure curves, but also the numerical stiffness values reported for healthy and osteo-arthritic human cartilage samples. Studies on these model composite hydrogels yield invaluable insights into how macromolecular factors (matrix stiffness, swelling pressure, fixed-charge density, etc.) affect the tissue's macroscopic mechanical/swelling properties, and ultimately its remarkable load-bearing and lubricating abilities, and their loss in various diseases and disorders, including osteoarthritis.

We are now attempting to translate our understanding of the structure-function relationships of ECM components to develop and design novel non-invasive MRI methods, with the aim of inferring ECM composition, patency, and functional properties in vivo. Our goal is to use MRI for early diagnosis of diseases of cartilage and other tissue and organs to follow normal and abnormal ECM development, which entails making components of ECM (e.g., collagen and PGs) that are ‘invisible’ to MR ‘visible’ so as to predict the functional properties of the composite tissue, such as its load-bearing ability. An obstacle is that protons bound to immobile species (e.g., collagen) are largely invisible with conventional MRI methods. However, magnetization exchange (MEX) MRI (as well as other related methods) now make it possible to detect the bound protons indirectly by transferring their magnetization first to the abundant free water protons surrounding them. It also enables us to estimate collagen content in tissue quantitatively. In previous pilot studies with Uzi Eliav (deceased) and Ed Mertz, we applied the new MEX MRI method to determine the concentration and distribution of the main macromolecular constituents in bovine femoral-head cartilage samples. The results were qualitatively consistent with those obtained by histological techniques, such as high-definition infrared (HDIRI) spectroscopic imaging. Our novel approach has the potential to map tissue structure and functional properties in vivo and non-invasively. Recently, we have been developing molecular dynamics (MD)–based models of cartilage and cartilage ECM analogs in order to interpret our experimental findings in terms of molecular interactions and processes.

We have also been employing several novel MR methodologies to characterize ECM properties using our one-sided NMR systems to study water relaxation, diffusion, and exchange processes. Most recently, Velencia Witherspoon has been using these approaches to study the organization and structure of fascia. Our specialized NMR profilers are ideally suited to these tasks, as they can probe layered media, such as cartilage and fascia, using ultra-thin slices, almost as thin as an optical microscope provides.

Patents

1. Peter J Basser, Dan H Benjamini. Multi-dimensional spectroscopic NMR and MRI using marginal distributions external link. US Patent 11,415,652, 2022.
2. Magdoom Mohamed Kulam Najmudeen, Peter J. Basser, Michal E. Komlosh. Time efficient, multi-pulsed field gradient (MPFG) MRI without concomitant gradient field artifacts. US publication number: 20230266418, August 24, 2023

Additional Funding

• “Connectome 2.0: Developing the next generation human MRI scanner for bridging studies of the micro-, meso- and macro-connectome.” NIH BRAIN Initiative-funded 1U01EB026996-01
• “Neuroradiology/Neuropathology Correlation/Integration Core.” 309698-4.01-65310, (CNRM-89-9921)

Publications

1. Avram AV, Saleem KS, Komlosh ME, Yen CC, Ye FQ, Basser PJ. High-resolution cortical MAP-MRI reveals areal borders and laminar substructures observed with histological staining. NeuroImage 2022 264:119653.
2. Saleem KS, Avram AV, Yen CC, Magdoom KN, Schram V, Basser PJ. Multimodal anatomical mapping of subcortical regions in Marmoset monkeys using high-resolution MRI and matched histology with multiple stains. NeuroImage 2023 281:120311.
3. Magdoom KN, Avram AV, Sarlls JE, Dario G, Basser PJ. A novel framework for in-vivo diffusion tensor distribution MRI of the human brain. NeuroImage 2023 271:120003.
4. Williamson NH, Ravin R, Cai TX, Falgairolle M, O’Donovan MJ, Basser PJ. Water exchange rates measure active transport and homeostasis in neural tissue. PNAS Nexus 2023 2(3):056.
5. Benjamini D, Priemer DS, Perl DP, Brody DL, Basser PJ. Mapping astrogliosis in the individual human brain using multidimensional MRI. Brain 2023 146:1212–1226.
6. Horkay F, Basser PJ, Geissler E. Ion-induced changes in DNA gels. Soft Matter 2023 19(28):5405–5415.

Collaborators

• Emilios Dimitriadis, PhD, Division of Bioengineering and Physical Science, NIBIB, Bethesda, MD
• Jack Douglas, PhD, NIST, Gaithersburg, MD
• David Feinberg, PhD, University of California, Berkeley, CA
• R. Douglas Fields, PhD, Section on Nervous System Development and Plasticity, NICHD, Bethesda, MD
• Raisa Freidlin, PhD, Signal Processing and Instrumentation Section, CIT, NIH, Bethesda, MD
• Dario Gasbarra, PhD, University of Helsinki, Helsinki, Finland
• Mark R. Gilbert, MD, Neuro-Oncology Branch, Center for Cancer Research, NCI, Bethesda, MD
• Mark Haacke, PhD, Wayne State University School of Medicine, Detroit, MI
• Mark Hallett, MD, PhD, Human Motor Control Section, NINDS, Bethesda, MD
• Iren Horkayne-Szakaly, MD, Joint Pathology Center, Defense Health Agency, Silver Spring, MD
• Susie Huang, MD, PhD, Martinos Center, Harvard Medical School, Boston, MA
• Beth Hutchinson, PhD, University of Arizona, Tucson, AZ
• Sara Inati, MD, Electroencephalography (EEG) Section, NINDS, Bethesda, MD
• Edward L. Mertz, PhD, Section on Physical Biochemistry, NICHD, Bethesda, MD
• Michael O'Donovan, MD, PhD, Developmental Neurobiology Section, NINDS, Bethesda, MD
• Evren Özarslan, PhD, Linköping University, Linköping, Sweden
• Sinisa Pajevic, PhD, Section on Critical Brain Dynamics, NIMH, Bethesda, MD
• Daniel Perl, MD, Uniformed Services University of the Health Sciences, Bethesda, MD
• Carlo Pierpaoli, MD, PhD, Section on Quantitative Medical Imaging, NIBIB, Bethesda, MD
• Dietmar Plenz, PhD, Section on Critical Brain Dynamics, NIMH, Bethesda, MD
• Tom Pohida, MS, Signal Processing and Instrumentation Section, CIT, NIH, Bethesda, MD
• Randall Pursley, MS, Signal Processing and Instrumentation Section, CIT, NIH, Bethesda, MD
• Roberto Romero, MD, D(Med)Sci, Perinatology Research Branch, Wayne State University, Detroit, MI
• Joelle Sarlls, PhD, In Vivo NMR Center, NINDS, Bethesda, MD
• Brain Development Cooperative Group, Various

Contact

For more information, email basserp@mail.nih.gov or visit https://www.nichd.nih.gov/research/atNICHD/Investigators/basser.

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