Following an extensive period of testing protocols that focused on the number of directions of data acquisition required, number of repetitions in order to maximize signal to noise properties in the images, and availability of pulse sequence algorithms, we finalized a protocol for the study of probabilisitic white matter tracts and have begun research using this protocol at all participating sites. In order to begin this research we had to obtain pulse sequence code from a variety of different sources, and install and implement it on different platforms and different scanners across the consortium. We are anticipating exciting results from the analysis of white matter tracts in the human brain in a large population and the comparison of these results with post mortem microscopic white matter analyses using differential myelin stains.
Diffusion Tensor Imaging
The mission of this project is to establish a common DTI protocol and to test the quality of DTI data from participating sites. This is an important first step toward generation of a large normal DTI database and probabilistic white matter atlas.
Establishment of Diffusion Tensor Imaging Database
ICBM is collaborating with MITRE on developing database software that will be needed for the creation of the DTI human white matter database. We have implemented the first version of the software that allows sites to send their DTI data to Johns Hopkins, and performs co-registration of the diffusion-weighted images.
Comparison Between DTI- and Histology-Based White Matter Delineation
In a collaborative study Johns Hopkins University (JHU) and the Institute of Medicince, Jülich (IMJ) are performing a validation study of DTI-based tract reconstruction by comparing DTI and histology-based techniques.
Figure 1. Quality of DTI data acquired with our common protocol V2.
Creating the Probabilistic White Matter Atlas
Johns Hopkins University (JHU) has a DTI database of normal subjects acquired under the Human Brain Project (RO1 AG10012). JHU is collaborating with the Montreal Neurological Institute group to generate a probabilistic atlas in MNI-ICBM and JHU DTI coordinates. We have created our first atlas using a simple linear transformation using the AIR algorithm. An example of a 15-subject average map in the JHU DTI coordinate is shown in Figure 3 (link here). More
ICBM has long realized the importance in automatically vectorizing the MR angiographic and venographic information contained in MR image stack. In brief, vectorized MR angiography and venography allow a comprehensive quantitative analysis of essential morphometric parameters (branching topology, three-dimensional geometry, internal and group variability).
Because of the large number of scans being collected in ICBM, it is important that vectorization be carried out automatically (algorithmically) as opposed to manually (which is still routine in neuronal morphology studies). More