Visualizing patterns of neurological disease progression with PET

Phoebe G. Spetsieris; Vijay Dhawan; James R. Moeller; David Eidelberg

doi:10.1117/12.174403

1 May 1994 Visualizing patterns of neurological disease progression with PET

Phoebe G. Spetsieris, Vijay Dhawan, James R. Moeller, David Eidelberg

Proceedings Volume 2168, Medical Imaging 1994: Physiology and Function from Multidimensional Images; (1994) https://doi.org/10.1117/12.174403
Event: Medical Imaging 1994, 1994, Newport Beach, CA, United States

Abstract

By applying non-conventional statistical analysis and visualization techniques to PET data obtained from a combined group of patients and normals, we are able to illustrate topographic covariance profiles unique to the disease at various stages of progression. Each profile represents a neuroanatomical regional network that is not discernible in the unprocessed data sets using standard analytical methods. The magnitude of a profile's manifestation in a given subject is expressed as a subject score which can correlate with independent clinical disease severity measures such as quantitative rigidity and bradykinesia ratings in Parkinson's disease. To create representations of these profiles a semi-automated routine is used which first generates a 2D pseudocolor map of the network where each region is weighted in accordance with its relative contribution to the overall profile. This representation is then transformed to a 3D isometric form so that the metabolic topography becomes more visually apparent. To fully perceive the evolving topographical pattern from initial to final stages of the disease, intermediate stages of disease progression are derived by interpolation to create a smooth progression of images that are displayed in an animated sequence.

Citation Download Citation

Phoebe G. Spetsieris, Vijay Dhawan, James R. Moeller, and David Eidelberg "Visualizing patterns of neurological disease progression with PET", Proc. SPIE 2168, Medical Imaging 1994: Physiology and Function from Multidimensional Images, (1 May 1994); https://doi.org/10.1117/12.174403

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