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.
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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