Transradial cerebral angiography: predicting left ICA selective angiography success using pre-diagnostic aortic arch factors

Background Transradial cerebral angiography (TRA) is a convenient but challenging procedure, particularly for selecting the left internal carotid artery (ICA) and vertebral artery. Objective To predict the selection of the left ICA using CT and MR images acquired before TRA. Methods Overall, 306 patients with TRA were enrolled and divided into either the group with success (264 patients) or the failure (42 patients) group. The following anatomical factors were measured: A1 (subclavian artery angle), A2 (right subclavian–innominate artery angle), A3 (innominate–left common carotid artery angle), D1 (aorta to right subclavian artery length), and D2 (innominate-to-left common carotid artery length). Results The median values for A1, A2, A3, D1, and D2 were 81.57° (IQR 69.26–94.14), 147.03° (125.73–161.09), 24.73 (15.85–37.72°), 34.73 mm (29.68–38.48), and 13.15 mm (11.33–15.64), respectively, with significant differences observed between the successful and failure groups in A3 (26.88° vs 15.50°; P<0.001), D1 (34.24 mm vs 37.62 mm; P<0.001), and D2 (12.78 mm vs 14.91 mm; P<0.001). The aortic arch type did not affect success (P=0.134), while patients in the failure group were significantly older (P<0.001). A predictive logistic regression model was developed, revealing differing factor impacts when controlling variables. The model (area under the curve 0.87) highlights data complexity and enables user-friendly prediction of left ICA-selective TRA success ( https://je0000000342227505.shinyapps.io/icatra/ ). Conclusion This study demonstrated that the success of left ICA selective angiography can be predicted using aortic arch images, providing a basis for the extension of TRA.