Stroke Genetics Network (SiGN) study: design and rationale for a genome-wide association study of ischemic stroke subtypes.

BACKGROUND AND PURPOSE: Meta-analyses of extant genome-wide data illustrate the need to focus on subtypes of ischemic stroke for gene discovery. The National Institute of Neurological Disorders and Stroke SiGN (Stroke Genetics Network) contributes substantially to meta-analyses that focus on specific subtypes of stroke. METHODS: The National Institute of Neurological Disorders and Stroke SiGN includes ischemic stroke cases from 24 genetic research centers: 13 from the United States and 11 from Europe. Investigators harmonize ischemic stroke phenotyping using the Web-based causative classification of stroke system, with data entered by trained and certified adjudicators at participating genetic research centers. Through the Center for Inherited Diseases Research, the Network plans to genotype 10,296 carefully phenotyped stroke cases using genome-wide single nucleotide polymorphism arrays and adds to these another 4253 previously genotyped cases, for a total of 14,549 cases. To maximize power for subtype analyses, the study allocates genotyping resources almost exclusively to cases. Publicly available studies provide most of the control genotypes. Center for Inherited Diseases Research-generated genotypes and corresponding phenotypes will be shared with the scientific community through the US National Center for Biotechnology Information database of Genotypes and Phenotypes, and brain MRI studies will be centrally archived. CONCLUSIONS: The Stroke Genetics Network, with its emphasis on careful and standardized phenotyping of ischemic stroke and stroke subtypes, provides an unprecedented opportunity to uncover genetic determinants of ischemic stroke.

Diagnostic accuracy of noncontrast CT imaging markers in cerebral venous thrombosis.

OBJECTIVE: To assess the added diagnostic value of semiquantitative imaging markers on noncontrast CT scans in cerebral venous thrombosis (CVT). METHODS: In a retrospective, multicenter, blinded, case-control study of patients with recent onset (<2 weeks) CVT, 3 readers assessed (1) the accuracy of the visual impression of CVT based on a combination of direct and indirect signs, (2) the accuracy of attenuation values of the venous sinuses in Hounsfield units (with adjustment for hematocrit levels), and (3) the accuracy of attenuation ratios of affected vs unaffected sinuses in comparison with reference standard MRI or CT angiography. Controls were age-matched patients with (sub)acute neurologic presentations. RESULTS: We enrolled 285 patients with CVT and 303 controls from 10 international centers. Sensitivity of visual impression of thrombosis ranged from 41% to 73% and specificity ranged from 97% to 100%. Attenuation measurement had an area under the curve (AUC) of 0.78 (95% confidence interval [CI] 0.74-0.81). After adjustment for hematocrit, the AUC remained 0.78 (95% CI 0.74-0.81). The analysis of attenuation ratios of affected vs unaffected sinuses had AUC of 0.83 (95% CI 0.8-0.86). Adding this imaging marker significantly improved discrimination, but sensitivity when tolerating a false-positive rate of 20% was not higher than 76% (95% CI 0.70-0.81). CONCLUSION: Semiquantitative analysis of attenuation values for diagnosis of CVT increased sensitivity but still failed to identify 1 out of 4 CVT. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that visual analysis of plain CT with or without attenuation measurements has high specificity but only moderate sensitivity for CVT.