Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2008
Clinical-sonographic index (CSI): a novel transcranial Doppler diagnostic model for middle cerebral artery stenosis.
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Jung Keun-Hwa, Lee Yong-Seok
Аннотация
BACKGROUND: Transcranial Doppler sonography is useful for the diagnosis of middle cerebral artery (MCA) stenosis. Although the previous studies have focused on the elevated mean flow velocity (MFV) or asymmetry of MFV, the lack of clinical correlation might limit diagnostic accuracy. We try to develop and validate a new diagnostic model including more comprehensive clinical and sonographic parameters.
METHODS: Consecutive patients with magnetic resonance angiography (MRA)-verified MCA stenosis were included, and compared with control subjects with normal MCA. The age, sex, corresponding symptoms (CS) to sonographic side, diabetes mellitus (DM), and hypertension were included for analysis. As sonographic parameters, MFV (cm/sec), asymmetry index (AI,%), and difference of pulsatility index (DeltaPI) were analyzed. Clinical-sonographic index (CSI) model was built with significant parameters by multivariate logistic regression analysis.
RESULTS: One hundred and seven patients (M:F = 53:54, age: 61.6 +/- 11.6 years), and 100 control subjects (M:F = 49:51, age: 54.9 +/- 14.5 years) were included. In logistic regression, MFV (odds ratio [OR], 1.057; 95% confidence interval [95% CI], 1.030-1.084), AI (OR, 1.067; 95% CI, 1.031-1.104), DeltaPI (OR, 41.754; 95% CI, 2.771-626.999), CS (OR, 15.904; 95% CI, 5.055-50.042), and DM (OR, 3.949; 95% CI, 1.132-13.783) were independent predictors of MCA stenosis. CSI was simplified for clinical use, CSI = MFV(cm/sec) + 3 * AI (%) + 180 *DeltaPI + 90 * CS(presence = 1, absence = 0) + 30 * DM (presence = 1, absence = 0). The area under the receiver operator characteristic (ROC) curve of MCA stenosis versus MFV, DeltaPI, AI, and CSI was .641, .668, .865 and .953. According to ROC curve, cut-off point for MCA stenosis was suggested as CSI > 180 (sensitivity: 87%, specificity: 92%).
CONCLUSION: CSI might be useful to enhance diagnostic accuracy.
METHODS: Consecutive patients with magnetic resonance angiography (MRA)-verified MCA stenosis were included, and compared with control subjects with normal MCA. The age, sex, corresponding symptoms (CS) to sonographic side, diabetes mellitus (DM), and hypertension were included for analysis. As sonographic parameters, MFV (cm/sec), asymmetry index (AI,%), and difference of pulsatility index (DeltaPI) were analyzed. Clinical-sonographic index (CSI) model was built with significant parameters by multivariate logistic regression analysis.
RESULTS: One hundred and seven patients (M:F = 53:54, age: 61.6 +/- 11.6 years), and 100 control subjects (M:F = 49:51, age: 54.9 +/- 14.5 years) were included. In logistic regression, MFV (odds ratio [OR], 1.057; 95% confidence interval [95% CI], 1.030-1.084), AI (OR, 1.067; 95% CI, 1.031-1.104), DeltaPI (OR, 41.754; 95% CI, 2.771-626.999), CS (OR, 15.904; 95% CI, 5.055-50.042), and DM (OR, 3.949; 95% CI, 1.132-13.783) were independent predictors of MCA stenosis. CSI was simplified for clinical use, CSI = MFV(cm/sec) + 3 * AI (%) + 180 *DeltaPI + 90 * CS(presence = 1, absence = 0) + 30 * DM (presence = 1, absence = 0). The area under the receiver operator characteristic (ROC) curve of MCA stenosis versus MFV, DeltaPI, AI, and CSI was .641, .668, .865 and .953. According to ROC curve, cut-off point for MCA stenosis was suggested as CSI > 180 (sensitivity: 87%, specificity: 92%).
CONCLUSION: CSI might be useful to enhance diagnostic accuracy.