F. M. Kirby Research Center for Functional Brain Imaging
At the Kennedy Krieger Institute

Technological Research Development

As a national research resource center, we focus on developing technological resources in the following areas:
  • TRD1: Quantitative functional MRI (fMRI)
  • TRD2: Brain Chemistry by MR Spectroscopy and Imaging (MRS/MRI)
  • TRD3: Identification and Characterization of Brain Connections
  • TRD4: Algorithms for Anatomical Brain Analysis

Diffusion tensor imaging allows us to create images of fiber tracts, which relay information throughout the nervous system.
Citation: S. Wakana, H. Jiang, L.M. Nagae-Poetscher, P.C.M. van Zijl, and S. Mori, "Fiber-tract Based Atlas of Human White Matter Anatomy", Radiology, 230, 77-87 (2004)..

TRD1: Quantitative functional MRI (fMRI)

Principal Investigator:
The past decade has seen the advance of functional MRI (fMRI) methodologies useful for non-invasive study of brain activity. These developments have revolutionized cognitive neuroscience, and MRI has become a popular tool for investigations in human neuroscience. However, MRI is fundamentally a low-sensitivity technique; the same factors (e.g., low energy per photon) that make MRI non-invasive also render it insensitive, and so the spatial resolution, temporal resolution, and signal-to-noise of fMRI are relatively poor. One way to increase the sensitivity of MRI is to increase the static magnetic field. Our research center opened with a 1.5 Tesla scanner, then added a 3.0 Tesla scanner. We are now preparing for a 7.0 Tesla scanner, which will further increase signal-to-noise. Optimization of 7.0 Tesla scanning is required, to "trade" these signal-to-noise increases for increases in spatial or temporal resolution, as appropriate.

Functional MRI yields large data sets in which the time courses of voxels have been sensitized to the hemodynamic sequelae of brain activation. These "brain movies" must then be analyzed to yield spatial and temporal summaries. Standard analytic approaches employ voxel-wise tests of a priori hypotheses. Exploratory data analysis, on the other hand, approaches these large data sets without specific prior hypotheses, and aims to discover within the data features reporting upon the organization of brain activity. In particular, spatial independent component analysis (s-ICA, or just ICA) seeks to express an fMRI data set as a sum of products of spatial maps and their respective time courses, such that the maps are drawn from statistically independent distributions, consistent with the princple of modular organization of brain function.

ICA of fMRI data often reveals brain activations which, because they do not smoothly follow paradigm events, may not be predicted by a "bottom-up" approach, and are therefore omitted from standard hypothesis-testing analyses. However, such unanticipated components must be evaluated for specificity: Are they hemodynamic sequelae of neuronal activity, or are they artifacts (e.g., respiration, cardiac pulsations, head motion)?

Also, ICA can be applied to fMRI data acquired during rich naturalistic behaviors -- such as simulated automobile driving [see figure], movie-watching, sleep, or the "resting state" -- which do not lend themselves to analysis with standard approaches. This may be especially valuable in clinical populations who would have difficulty complying with conventional brain imaging paradigms.

The developments proposed (optimization of 7.0 T scanning; evaluation of independent components of fMRI data; development of approaches to rich naturalistic behaviors) serve the ultimate aim of improving the utility of fMRI for investigations in basic and clinical neuroscience.

Related Publications
An Illustration of fMRI.

Hypothesized neural substrates of simulated driving. Functional MRI data were acquired during epochs of simulated driving, and analyzed using ICA. From: VD Calhoun, JJ Pekar, VB McGinty, T Adali, TD Watson, & GD Pearlson. "Different Activation Dynamics in Multiple Neural Systems During Simulated Driving." Human Brain Mapping 16:158 (2002).

TRD2: Brain Chemistry by MR Spectroscopy and Imaging (MRS/MRI)

Principal Investigators:
Physiological imaging techniques such as magnetic resonance spectroscopy (MRS), magnetization transfer and blood volume imaging allow insights into central nervous system function, that are not available from conventional structural imaging modalities. These methods allow neuroscientists to investigate brain metabolism, protein content, pH, and hemodynamics of the brain under different conditions, as well as promising to provide clinicians (neurologists, psychiatrists, radiologists and others) with diagnostic and treatment monitoring tools.

Although some of these techniques are reaching technical maturity, others are still in their infancy, and much work still needs to be done to improve spatial resolution and sensitivity, and reduce scan time. This is particularly true for the study of disorders of childhood, which is the major focus of the F.M. Kirby Center. For instance, proton spectroscopy of the spine is still and unexplored, despite the enormous importance of the spine in many disabling diseases. Also, proton MRS of the brain at very high fields show terrific promise because of its higher signal-to-noise ratio (SNR) and resolution compared to lower fields, many technical challenges need to be overcome before it can be routinely applied in children. The first aim of this project therefore focuses on technique development for quantitative proton MR spectroscopic imaging (MRSI) of the brain and cervical spinal cord at 3T and 7T. As MRSI moves to higher resolution, larger matrix sizes and increased spatial coverage result in longer scan times. A major effort in this project is the development of parallel-encoded (e.g. SENSE) and other MRSI schemes for improved MRSI performance and reduced scan times. Integral to this effort is the ongoing development of software for both data acquisition and processing; this software is developed interactively with our collaborators, and is designed to meet the data processing needs of our service projects, as well as being available for download to the scientific community.


Examples in the figures show:

    A high resolution SENSE-MRSI scan (5 minute scan time) of a normal brain:
    MRS in the Normal Brain

    A high resolution SENSE-MRSI scan (5 minute scan time) of patients with HIV:
    MRS in Patient with HIV

    A high resolution SENSE-MRSI scan (5 minute scan time) of a high grade brain tumor:
    MRS in Patient with High Grade Brain Tumor

    MRSI of the cervical spine in a patient with multiple sclerosis (MS):
    MRS in the Spine of a Patient with Multiple Sclerosis

    An example of SENSE-MRSI of the normal human brain at 7T:
    MRS in the Normal Brain at 7T
Another type of 'physiological' imaging involves 'magnetization transfer' (MT), where image contrast is generated by saturating molecules which exchange with the water signal being imaged. Conventional magnetization transfer imaging looks at the exchange between broad macromolecule signals off-resonance from the water signal; however, by selective irradiation at specific frequencies, it is possible to investigate exchange processes between water and amide protons, for the most part found in the backbone of proteins and peptides in vivo. The amount of magnetization transfer depends on a number of factors, but by appropriate experiment design, it is possible to investigate protein density, pH and other processes. This project involves technique development to optimize amide proton transfer (APT) imaging and conventional MT on 3T and 7T scanners. The role of MT/APT imaging in various neurological diseases (brain tumors, demyelinating diseases) is under active investigation with our collaborators and service projects. Finally, MRI is increasingly being used for the measurement of cerebral blood flow and blood volume, and over the last few years we have developed a non-invasive method to measure blood volume, called vascular-space occupancy (VASO) imaging. Recent calculations and data acquisitions have shown that the VASO contrast also contains a perfusion contribution, which with appropriate modeling and protocol design can be used to estimate both blood flow and blood volume; this technique is called VAscular Space Labeling (VASL). In this project, develop VASO and VASL are being developed to allow quantification of blood flow and blood volume in patients. These methods, which have relatively low SNR because of the low blood volume of normal brain, will become especially relevant at higher field where improved SNR is expected.

The work is driven by, and actively collaborates with, several NIH-funded projects focused on pediatric neurological disorders, including Rett Syndrome, perinatal hypoxia, cerebral palsy, coma, trauma (both in the brain and spine), pediatric brain tumors and the effect radiation therapy, and adrenoleukodystrophy (ALD). In addition, it also supports NIH funded projects in adults, on stroke, Alzheimer's disease, multiple sclerosis, and brain tumors.

Related Publications

TRD3: Identification and Characterization of Brain Connections

Principal Investigator:
The relationship between brain structure and complex behavior is governed by large scale neurocognitive networks. The availability of a noninvasive technique that can visualize the neuronal projections connecting the functional centers should therefore provide new keys to the understanding of brain function.
DTI: Fiber Tracking

3D reconstruction of projection fibers in a human brain. Fibers were reconstructed from a DTI dataset with 2.2mm isotropic resolution. The cortical-brainstem connections are shown in light blue color and a subset of fibers that connect the motor cortex and the pyramidal tracts in the caudal pons level are painted white. Red purple , red and blue purple indicate anterior, superior, and posterior thalamic radiations. The light green, green, and yellow structures are globus pallidus, caudate, and thalamus. Ventricles are shown in gray.

The overall goal of this project is to develop and provide state-of-the-art technology for diffusion tensor imaging (DTI) that can be applied to the study of white matter diseases and other diseases that affect the integrity of white matter structures. This technique yields two types of data that have previously been inaccessible. First, it provides so called anisotropy maps, the information in which is related to axonal structure, fiber density and myelination. Second, using high-resolution DTI and a newly-designed tracking approach we have recently shown that neuronal pathways can be probed in situ in the human brain. Atlases can be found on the CMRM Website.

The functional meaning of the DTI findings will be evaluated by correlating them to clinical and pathological findings of various diseases through our collaborations. Some diseases of interest are mental retardation, Rett syndrome, ALS, Schizophrenia, stroke and brain cancer.

Related Publications

TRD4: Algorithms for Anatomical Brain Analysis

Principal Investigator: To see the description for TRD4, please see the CIS website.

Related Publications