Richard D. King, M.D., Ph.D.
Assistant Professor in Neurology
UT Southwestern Medical Center
Lab: UTD Center for Brain Health
2200 W Mockingbird
Dallas, TX 75235
Main: 214-905-3007
Fax: 972-883-3231
Email: King-Lab@UTSouthwestern.edu
The purpose of the King Lab is to develop and demonstrate clinical utility of a novel method to quantify differences in the cerebral cortical structure of patients with Alzheimer’s Disease (AD). AD is associated with a significant decrease in cortical volume in numerous brain regions such as the medial temporal and posterior parietal lobes.
In our laboratory, we use three-dimensional fractal analysis of high-contrast T1-weighted magnetic resonance (MR) images to compute a quantitative metric called fractal dimension. Fractal dimension, or FD, is a measure that quantifies the shape complexity of the surface of the brain using relatively simple computational algorithms. FD is modified by parameters such as gyrification patterns and cortical thickness. Dimensionality can be global (f3D) or local (Lf3D). These measures (f3D and Lf3D) will be used
to characterize differences in the dimensionality of the cerebral cortex between patients with mild-moderate Alzheimer's disease and age-matched controls.
We use a number of tools including FreeSurfer (a software suite for image segmentation), Fractal Dimension Calculator (a freely available image analysis program), and our custom fractal dimension calculator for 3-D surfaces. We are using software in Objective C on Mac platform using Cocoa.
Past research has been done on two-dimensional fractal analysis, examining the cortical ribbon in different coronal and axial slices within the cerebral cortex. The fractal analysis yielded a quantitative metric that separated patients with normal cognition from those with moderate to advanced degenerative disease based on neuropsychologic testing. This novel application of fractal analysis may be useful for quantifying changes in shape not only in Alzheimer’s disease, but also in other neurological diseases associated with cerebral atrophy. Analysis of cortical fractal dimension may improve the quality of neuroimaging biomarkers when combined with other complementary structural analysis methods
The long-term goal of this project is to incorporate this fractal assessment of cortical shape into routine clinical practice. Changes in fractal dimension could serve as surrogate biomarkers for disease progression. In addition, patterns of local fractal dimensionality could be useful in differential diagnosis (such as frontal AD from Frontotemporal dementia) or in making a diagnosis earlier in the disease course.
