Stroke is the leading cause of adult disability and third leading cause of death in the United States with approximately 700,000 new or recurrent strokes each year. Perfusion Computed Tomography (PCT) provides maps of parameters such as cerebral blood flow, volume and transit times. These parameters can be used to distinguish between ischemic and hemorrhagic stroke, to determine the location and extent of the hypoperfused area, and also to differentiate between the irreversibly damaged and salvageable tissue. We will investigate the feasibility of implementing PCT on a mobile, flat-panel detector, cone-beam CT (CBCT) system. Using such a platform will address two shortcomings of current PCT technology: lack of whole-brain coverage and limited accessibility in the emergency department and intensive care unit. We will focus on two issues: 1) relatively low scanning speed of flat-panel-based CBCT, which may hamper temporal sampling of contrast dynamics; and 2) increased projection noise and limited dynamic range of flat-panel detectors. In this project we will first experimentally investigate the characteristics of flat- panel detectors for imaging iodine enhanced vessels with respect to image noise and contrast. In the second stage of the research we will develop and validate a model- based, iterative algorithm for reconstruction of dynamic projection data acquired with relatively slowly rotating systems.
Stroke is the leading cause of adult disability and third leading cause of death in the United States with approximately 700,000 new or recurrent strokes each year. The mobile flat-panel-based CT system capable of perfusion imaging proposed here will allow for rapid assessment of neurovascular function of the whole brain directly in the emergency department. This tool may bring about improvements in stroke diagnosis and provide important support for treatment decisions, thus greatly improving outcome for acute strokes victims. ? ? ?
