INTRODUCTION: The purpose of this study was to evaluate the usefulness of CT digital subtraction angiography (CTDSA) by using 320-detector row CT in the diagnosis and classification of cerebral dural arteriovenous fistula (dAVF) and comparing it with DSA as the standard reference. METHODS: A total of 29 CTDSA/DSA from 25 patients with dAVF were retrospectively evaluated by two neuroradiologists. The presence, Cognard classification, and feeding arteries of dAVFs on CTDSA were assessed according to DSA. RESULTS: DSA depicted 33 dAVFs in 28 cases. By consensus reading, CTDSA correctly detected 32 dAVFs in 27 cases and properly graded 31 lesions. The intermodality agreement for the presence and classification of dAVFs was excellent (kappa = 0.955 and 0.921, respectively). CTDSA detected 77 of 109 feeding arteries (70.6%) in 25 cases. The intermodality agreement for the feeding arteries was good (kappa = 0.713). CONCLUSION: Although CTDSA is limited in temporal and spatial resolution in comparison with DSA, it is an effective non-invasive tool for the detection and classification of dAVF.
INTRODUCTION: The purpose of this study was to evaluate the usefulness of CT digital subtraction angiography (CTDSA) by using 320-detector row CT in the diagnosis and classification of cerebral dural arteriovenous fistula (dAVF) and comparing it with DSA as the standard reference. METHODS: A total of 29 CTDSA/DSA from 25 patients with dAVF were retrospectively evaluated by two neuroradiologists. The presence, Cognard classification, and feeding arteries of dAVFs on CTDSA were assessed according to DSA. RESULTS: DSA depicted 33 dAVFs in 28 cases. By consensus reading, CTDSA correctly detected 32 dAVFs in 27 cases and properly graded 31 lesions. The intermodality agreement for the presence and classification of dAVFs was excellent (kappa = 0.955 and 0.921, respectively). CTDSA detected 77 of 109 feeding arteries (70.6%) in 25 cases. The intermodality agreement for the feeding arteries was good (kappa = 0.713). CONCLUSION: Although CTDSA is limited in temporal and spatial resolution in comparison with DSA, it is an effective non-invasive tool for the detection and classification of dAVF.
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