JVIR twitter

Monday, June 8, 2015

“Eyeballing” It May Not Be As Reliable As We Tell Ourselves

Thousands of peripheral vascular interventional procedures are performed annually to characterize, prevent, and treat consequences of atherosclerosis leading to arterial stenosis. A simple visual estimation (SVE) of the degree of stenosis is often used to determine if treatment is necessary. This study was performed to evaluate the reliability, accuracy and agreement of SVE compared to manual caliper measurements with regard to stenosis severity. This is a retrospective review of images of iliofemoral and carotid arterial lesions, with caliper measurements of stenotic images obtained prior to SVE evaluation. SVE was performed by 23 interventionists of different subspecialties and varying years of experience and compared to the caliper measurement. Correlation among estimates (reliability) was high for both intrareader and interreader image evaluation. Accuracy of visual estimate within 5% of the caliper measurement was 28.3 % overall, however highest for severe stenosis at 52.8%. Agreement as determined by whether SVE and caliper measurement of an image placed it in the same category of stenosis was 64% overall, and highest for severe stenosis at 92.6%. The findings of this study demonstrate SVE is a reliable but inaccurate method for determining degree of stenosis.

Comment:
The study points out the inaccuracy of SVE, which could lead to misclassification of a lesion resulting in inappropriate course of treatment. However, SVE allows for a reliable assessment of significant stenosis (>50%), highlighting its use as a potential screening tool.


Click here to see the full abstract


Note–Entries are counts (n) and percentages (%) of visual estimates within 5% of caliper measurement.


Citation: Rajebi, M. R. et al. Reliability and Accuracy of Simple Visual Estimation in Assessment of Peripheral Arterial Stenosis. Journal of Vascular and Interventional Radiology 26, 890–896 (2015).


Post author: Jamie Doster MD, Radiology Resident, University of Virginia

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