The ALADIN Multicenter Trial demonstrated remarkable performance of Viz LVO in its ability to accurately, consistently and rapidly detect large vessel occlusions (LVOs) retrospectively on 875 CTA images. Viz LVO detected anterior LVOs, extending from ICA-T to MCA-M1, with a sensitivity of 90% and a specificity of 86%. Hence, establishing Viz LVO as the most accurate LVO detection algorithm currently available in the United States. Further, Viz LVO detected the presence of an LVO and notified stroke specialists within 5 minutes of receiving the CTA images.
The ALADIN Single Center Trial assessed the performance of Viz LVO on CTA imaging in 223 patients through a single center prospective cohort and retrospective analysis. With a maximum runtime of fewer than five minutes, Viz LVO detected ICA-T and MCA-M1 LVOs with an AUC of 0.91, as well as a sensitivity of 95.7% and specificity of 85.9%. To the best of our knowledge, this is the first A.I. algorithm for detecting intracranial LVOs.