Testing ASPECTS Reliability Using Color Coded Algorithm Enhanced Gray- White Matter Non Contrast CT
Date
2018-07-09
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Abstract
The Alberta Stroke Program Early CT Score (ASPECTS) is widely used to assess and diagnose Acute Ischemic Stroke Patients (AIS). Inter-rater reliability for ASPECTS however, is very poor even amongst physicians with extensive expertise. Much of this limitation has to do with the lack of agreement amongst physicians in identifying Early Ischemic Changes (EIC) on Non- Contrast Computed Tomography (NCCT) scans. This lack of agreement is due to the extremely subtle findings that the human eye is exposed to on gray scale NCCT scans during the acute period of ischemia. We therefore sought to use post processing algorithms to develop Color- Coded Algorithm Enhanced Gray- White Matter (AEGWM) NCCT scans. Increased differentiation between Gray- White matter on AEGWM NCCT scans was developed to act as a powerful imaging tool allowing for better delineation of EIC for AIS patients. In this thesis I investigated the utility of AEGWM NCCT scans for the purposes of detecting EIC in AIS patients. Overall, we found that AEGWM scans performed better as opposed to gray scale NCCT scans when using DWI as ground truth. In addition, inter rater agreement increased consistently across raters of all levels of expertise while using AEGWM scans. Although with some limitations, the use of AEGWM scans may be a promising research direction to pursue for future work.
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Keywords
Stroke, Imaging, NCCT, ASPECTS, Neurology
Citation
Hafeez, M. (2018). Testing ASPECTS Reliability Using Color Coded Algorithm Enhanced Gray- White Matter Non Contrast CT (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/32352