Variability of clinical CT perfusion measurements in patients with carotid stenosis
Aquilla S Turk1, Allison Grayev, Howard A Rowley
1Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, WI, USA. aturk@uwhealth.org
Insights
Clinical CT perfusion imaging (pCT) measurements for cerebrovascular disease can vary significantly over time. Understanding this long-term variability is crucial for accurately assessing treatment effects in patients.
Area of Science:
- Neurology
- Radiology
- Medical Imaging
Background:
- Cerebrovascular disease necessitates monitoring hemodynamic abnormalities.
- CT perfusion imaging (pCT) is a tool for detecting and monitoring these abnormalities.
- The long-term variability of pCT clinical measurements requires thorough evaluation.
Purpose of the Study:
- To quantify the long-term variability of clinical pCT measurements.
- To assess pCT measurement variability in patients with cerebrovascular disease.
Main Methods:
- pCT parameters (MTT, CBF, CBV) were measured in 33 patients with carotid stenosis before and after stenting.
- Measurements were taken using small and large regions of interest (ROIs) with manual and automated methods.
- Statistical analysis included t-tests and Bland-Altman analysis to assess variability.
Main Results:
- Variability was 18% for MTT, 19% for CBV, and 25% for CBF using a large ROI and manual calculation.
- Manual methods showed average differences of 2.5-7.7%, with higher differences using automated methods.
- Smaller ROIs and automated methods resulted in greater variability.
Conclusions:
- Longitudinal pCT measurements of MTT, CBV, and CBF can exhibit 20-25% variability.
- pCT study designs must account for this inherent variability to detect statistically significant treatment-related changes.
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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