Abstract TP204: Performance of Rapidai NCCT Stroke Software in Colombia's Early Stroke System: Preliminary Results

Abstract

Background: Automated stroke solutions in developing countries have the potential to reduce healthcare gaps. This study assesses the performance of the RAPID NCCT Stroke module compared to local neuroradiologists’ evaluation of acute stroke. Methods: Rapid NCCT stroke is a new multi-module AI tool that simultaneously evaluates non-contrast CT scans (NCCT) for ICH (any subtype, volume >0.4 ml), the ASPECT score, and suspicion of LVO (i.e., intracranial ICA or horizontal segment of the MCA). The software determines suspicion of LVO based on an algorithm that evaluates the hyperdense MCA sign and early ischemic changes in the MCA territory. Consensus readings were defined by three blinded neuroradiologists based on a subset of Non-contrast CTs obtained between January 2013 to December 2018 at Fundacion Santa Fe De Bogota University Hospital. The overall diagnostic performance of the RAPID NCCT was compared to the assessments made by the neuroradiologists. Results: 179 total stroke cases with technically adequate NCCT scans were identified. Based on the consensus of the neuroradiologists, these cases included 151 ischemic strokes, 27 ICHs >0.4 ml, 1 ICH <0.4 ml, and 28 LVO cases (verified by CT angiography). The Rapid NCCT Stroke module demonstrated high specificity (96%), NPV (98%), and accuracy (95%) for the detection of ICH. For determining the ASPECT score, the software had a specificity of 93% and an NPV of 76%. Seventy percent of the CTA-verified LVOs were detected from NCCT alone with a specificity and NPV of 82%. Conclusions: The RAPID NCCT Stroke software displayed promising results for the early identification of ICH and characterization of ischemic strokes. The software identified 70% of the LVOs from NCCT alone. This tool can potentially enhance patient outcomes by bridging healthcare gaps in evolving stroke systems. Multicenter studies in additional Latin American countries are needed for further validation.