Dr. Glenn Wells

Biography

Dr. Glenn Wells Adjunct Research Professor University of Ottawa Heart Institute, Cardiac Imaging, 1st Floor 40 Ruskin Street Ottawa, ON, K1Y 4W7

Research Interest

My research interests are in the physics of multi-modality imaging with nuclear medicine: the combination of multi-slice X-ray computed tomography (CT) with positron emission tomography (PET) and single-photon emission computed tomography (SPECT). Nuclear medicine imaging is a 3D medical imaging technology that is used to diagnose and evaluate a wide variety of diseases including cancer and heart disease. The technique uses radioactively-labelled compounds that are injected into the patient. Based on how the compound is processed by the body, the images of the distribution of radioactivity can tell us how well the different organs are working and show us where there are abnormalities. Multi-modal cameras such as PET/CT and SPECT/CT are recent advances in medical imaging technology that combine two types of imaging in a single device. These cameras provide exquisite anatomical images from CT accurately aligned with nuclear medicine functional images from PET or SPECT. Beyond just providing pretty pictures, these cameras offer new opportunities for using the CT information to improve the PET or SPECT images. I am studying the effects of respiratory motion on cardiac imaging with PET/CT and developing methods to compensate or correct for these effects in order to improve the quality of images produced by this important diagnostic tool. Movement of the chest during breathing introduces motion blurring into our images and can lead to a mis-alignment between the CT and PET data causing further errors. I am pursuing new methods of acquiring and processing the pictures that corrects these problems. I am also investigating methods of enhancing image quality with SPECT/CT through a more accurate integration of functional and anatomical data. The CT images have a wealth of information that is currently not being considered in the processing of the SPECT images. A more complete integration of these two data sets will produce a “whole” that is “greater than the sum of its parts”.