Intracranial dural arteriovenous fistulas: Diagnosis and evaluation with 64-detector row CT angiography

Chung Wei Lee, Adam Huang, Yao Hung Wang, Chung Yi Yang, Ya Fang Chen, Hon Man Liu

研究成果: 雜誌貢獻期刊論文同行評審

39 引文 斯高帕斯(Scopus)


Purpose: To analyze the diagnostic effectiveness and application of computed tomographic (CT) angiography by using a new algorithm (hybrid CT angiography) in dural arteriovenous fistulas (AVFs). Materials and Methods: Institutional review board approval was obtained for retrospectively postprocessing the raw data from CT angiography by using hybrid CT, which is a mixture of a bone subtraction and masking method for bone removal. The study included 22 patients with 24 dural AVFs and 14 control subjects. The grades in patients with dural AVF determined with hybrid CT angiography and digital subtraction angiography (DSA) were compared, and hybrid CT angiography was applied as a tool for planning endovascular treatment. The adjusted Wald method was used to estimate confidence intervals (CIs), and the Cohen κ statistic was used to assess interobserver agreement. Results: Hybrid CT angiography in the 24 dural AVFs revealed asymmetric sinus enhancement in 22 lesions (92%), engorged arteries in 19 (79%), transosseous enhanced vessels in 19 (79%), engorged extracranial veins in 13 (54%), engorged cortical veins in seven (29%), and sinus thrombosis in four (17%). In all 24 lesions, at least two of six imaging signs for diagnosis of dural AVFs were present. The κ test analysis revealed a high level of interobserver agreement ( k, 0.56-1.00) in reading the diagnostic imaging signs. The observed agreement between DSA and readers was 100% in the cavernous sinus region and in hypoglossal and clival lesions and 78%-89% in the transverse sigmoid sinus. The overall sensitivity, specificity, positive predictive value, and negative predictive value were 0.93 (95% CI: 0.85, 0.97), 0.98 (95% CI: 0.93, 1.00), 0.97 (95% CI: 0.90, 0.99), and 0.95 (95% CI: 0.90, 0.98), respectively. Conclusion: Hybrid CT angiography is a promising tool for the diagnosis of dural AVF. It can provide key information necessary for treatment planning.

頁(從 - 到)219-228
出版狀態已出版 - 7月 2010


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