Evan D. Morris

Evan D. Morris, PhD has been working in the field of PET and functional imaging for 20 years. He specializes in kinetic modeling of dynamic image data. He was trained as a biomedical engineer and before that as a chemical engineer. In the past, he has taught courses at the undergraduate and graduate levels in Medical Imaging, Tracer Kinetics, Biomedical Transport, and Biomedical Ethics, among others. Morris joined the Yale PET Center as Co-Director of the Imaging Section in the fall of 2009.

 

Dr Morris and his students have been working on kinetic models to estimate the dynamics of endogenous neurotransmitters from PET data. Their most recent publication appeared in Neuroimage in 2010. It demonstrates a novel analysis strategy for creating the first ever “movies” of dopamine action in the living brain. Altered neurotransmitter kinetics may explain the mechanism of addiction of some drugs. This work uses knowledge of numerical methods, biochemistry, image and signal processing, parameter estimation, and programming. A collection of papers to result from this project can be downloaded as a zip file here. The work was funded by the Whitaker Foundation and the National Institute on Alcohol Abuse and Alcoholism.

 

Morris and his colleagues at Indiana University have focused much of their efforts on the use of PET to understand what makes drugs and alcohol addictive. It is the first demonstration in humans of the neurochemistry of reward prediction error. This work uses knowledge of neuropsychology, image processing, experimental study design, neurochemistry, and kinetic modeling.

 

Morris is currently interested in the use of PET imaging (of people and animals) with neuroreceptor tracers to understand and improve treatments for Parkinson’s disease, alcoholism, smoking, and drug abuse.

 

Other recent interests of Prof Morris:

Small animal imaging. A recent paper details the design and validation of a stereotactic head-holder for imaging two rats in a PET scanner at the same time. The paper was published in Journal of Neuroscience Methods.

 

Direct reconstruction of PET data to parametric images. This work was a collaboration with colleagues at Purdue University and used knowledge of kinetic modeling, imaging physics, optimization and algorithm design. It yielded the first working algorithm to create parametric images of the four kinetic parameters of the two-tissue model directly from raw (sinogram) data. The primary paper to result from this collaboration was published in IEEE Transactions on Medical Imaging.