Variability of clinical CT perfusion measurements in patients with carotid stenosis |
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Authors: | Aquilla S Turk Allison Grayev Howard A Rowley Aaron S Field Patrick Turski Kari Pulfer Rajat Mukherjee Victor Haughton |
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Institution: | (1) Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, WI, USA;(2) Department of Neurosurgery, University of Wisconsin Hospital and Clinics, Madison, WI, USA;(3) Department of Neurology, University of Wisconsin Hospital and Clinics, Madison, WI, USA;(4) Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, USA;(5) Department of Statistics, University of Wisconsin–Madison, Madison, WI, USA;(6) 600 Highland Ave., CSC E3/372, Madison, WI 53792, USA |
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Abstract: | Introduction CT perfusion imaging (pCT) may be used to detect and monitor hemodynamic abnormalities due to cerebrovascular disease. The
magnitude of variability in clinical measurements has been insufficiently evaluated. The purpose of this study was to measure
the long-term variability of clinical pCT measurements in patients with cerebrovascular disease.
Methods pCT parameters were calculated for the cerebral hemisphere contralateral to a carotid stenosis before and after stent treatment
of stenosis in 33 consecutive patients. Mean transit time (MTT), cerebral blood flow (CBF), and cerebral blood volume (CBV)
calculated from pCT data from both a small and large region of interest (ROI) using both manual and automated methods were
compared before and after stent treatment. Differences between the first and second measurement were tested for statistical
significance with at-test. Variability was calculated as the standard deviation of the differences divided by the mean of the pre- and post-stent
treatment values. To adjust for proportional bias, the Bland–Altman analysis was applied.
Results The differences between the two measurements of MTT, CBF, and CBV averaged 2.5 to 7.7% when a manual method was used and was
higher with automatic methods (p > 0.07). The variability of the values was 18% for MTT, 19% for CBV, and 25% for CBF with the large ROI and the manual method
of calculation. The magnitude was larger when the small ROI and automatic methods were employed.
Conclusion Longitudinal measurements of MTT, CBV, or CBF by pCT may vary by 20–25%. To detect changes in treatment-related changes in
perfusion, pCT studies must be designed to achieve statistical significance based on this variability. |
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Keywords: | Computed tomography Perfusion imaging |
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