J Borst1, H A Marquering2, M Kappelhof3, T Zadi4, A C van Dijk4, P J Nederkoorn5, R van den Berg3, A van der Lugt4, C B L M Majoie3. 1. From the Departments of Radiology (J.B., H.A.M., M.K., R.v.d.B., C.B.L.M.M.) j.borst@amc.uva.nl. 2. From the Departments of Radiology (J.B., H.A.M., M.K., R.v.d.B., C.B.L.M.M.) Biomedical Engineering and Physics (H.A.M.). 3. From the Departments of Radiology (J.B., H.A.M., M.K., R.v.d.B., C.B.L.M.M.). 4. Department of Radiology (T.Z., A.C.v.D., A.v.d.L.), Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands. 5. Neurology (P.J.N.), Academic Medical Center, Amsterdam, the Netherlands.
Abstract
BACKGROUND AND PURPOSE: Semiautomatic measurement of ICA stenosis potentially increases observer reproducibility. In this study, we assessed the diagnostic accuracy and interobserver reproducibility of a commercially available semiautomatic ICA stenosis measurement on CTA and estimated the agreement among different software packages. MATERIALS AND METHODS: We analyzed 141 arteries from 90 patients with TIA or ischemic stroke. Manual stenosis measurements were performed by 2 neuroradiologists. Semiautomatic measurements by using 4 methods (3mensio and comparable software from Philips, TeraRecon, and Siemens) were performed by 2 observers. Diagnostic accuracy was estimated by comparing semiautomatic with manual measurements. Interobserver reproducibility and agreement between different packages was assessed by calculation of the intraclass correlation coefficient and Bland-Altman 95% limits of agreement. False-negative classifications were retrospectively inspected by a neuroradiologist. RESULTS: There was no significant difference in the diagnostic performance of the 4 semiautomatic methods. The sensitivity for detecting ≥50% and ≥70% degree of stenosis was between 76% and 82% and 46% and 62%, respectively. Specificity and overall diagnostic accuracy were between 92% and 97% and 85% and 90%, respectively. The interobserver intraclass correlation coefficient was between 0.83 and 0.96 for semiautomatic measurements and 0.81 for manual measurement. The limits of agreement between each pair of semiautomatic packages ranged from -18%-24% to -33%-31%. False-negative classifications were caused by ulcerative plaques and observer variation in stenosis and reference measurements. CONCLUSIONS: Semiautomatic methods have a low-to-good sensitivity and a good specificity and overall diagnostic accuracy. The high interobserver reproducibility makes semiautomatic stenosis measurement valuable for clinical practice, but semiautomatic measurements should be checked by an experienced radiologist.
BACKGROUND AND PURPOSE: Semiautomatic measurement of ICA stenosis potentially increases observer reproducibility. In this study, we assessed the diagnostic accuracy and interobserver reproducibility of a commercially available semiautomatic ICA stenosis measurement on CTA and estimated the agreement among different software packages. MATERIALS AND METHODS: We analyzed 141 arteries from 90 patients with TIA or ischemic stroke. Manual stenosis measurements were performed by 2 neuroradiologists. Semiautomatic measurements by using 4 methods (3mensio and comparable software from Philips, TeraRecon, and Siemens) were performed by 2 observers. Diagnostic accuracy was estimated by comparing semiautomatic with manual measurements. Interobserver reproducibility and agreement between different packages was assessed by calculation of the intraclass correlation coefficient and Bland-Altman 95% limits of agreement. False-negative classifications were retrospectively inspected by a neuroradiologist. RESULTS: There was no significant difference in the diagnostic performance of the 4 semiautomatic methods. The sensitivity for detecting ≥50% and ≥70% degree of stenosis was between 76% and 82% and 46% and 62%, respectively. Specificity and overall diagnostic accuracy were between 92% and 97% and 85% and 90%, respectively. The interobserver intraclass correlation coefficient was between 0.83 and 0.96 for semiautomatic measurements and 0.81 for manual measurement. The limits of agreement between each pair of semiautomatic packages ranged from -18%-24% to -33%-31%. False-negative classifications were caused by ulcerative plaques and observer variation in stenosis and reference measurements. CONCLUSIONS: Semiautomatic methods have a low-to-good sensitivity and a good specificity and overall diagnostic accuracy. The high interobserver reproducibility makes semiautomatic stenosis measurement valuable for clinical practice, but semiautomatic measurements should be checked by an experienced radiologist.
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