RapidAI presented 28 scientific abstracts at ISC 2026
RapidAI announced details of 28 scientific abstracts accepted at the International Stroke Conference (ISC) 2026, held February 4-6, at the Ernest N. Morial Convention Center in New Orleans.
The abstracts spanned aneurysm monitoring, ischemic stroke detection, advanced imaging visualization, and radiology workflow optimization. Findings reflect the impact of deep clinical AI delivered through the Rapid Enterprise platform, designed to scale across radiology and acute workflows.
The clinical data demonstrates how RapidAI’s clinically validated, FDA-cleared AI solutions can improve diagnostic performance, reduce interpretation time, and deliver measurable efficiency and economic gains for stroke teams and radiology departments. Rapid’s Deep Clinical AI, delivers real results by providing not just triage notifications but also visualization, localization, characterization, and tracking changes over time.
The following abstracts highlight this approach and were presented at ISC:
- Artificial Intelligence Augments Radiologists Capabilities in Tracking Aneurysm Growth Over Time:
- The abstract evaluated longitudinal aneurysm measurements using RapidAI’s Aneurysm platform and compared them with neuroradiologists' interpretations.
- Rapid detected 46% more clinically significant growth compared with neuroradiologists alone (27/28 incidents of aneurysm growth detected by Rapid vs. 14/28 aneurysms for neuroradiologists alone).
- Reduced Interpretation Time, Improved Detection Accuracy of High-Grade Stenosis and Occlusions using Lumina 3D: A Multi-Reader, Multi-Case Study:
- The study assessed the impact of Lumina 3D, Rapid’s automated 3D head-and-neck reconstructions, on stroke occlusion and stenosis detection and interpretation time.
- Across 20 cases involving 24 occlusions and 11 stenoses, diagnostic accuracy improved from 76.1% without Lumina 3D to 85.6% with Lumina 3D, a 9% improvement (p = 0.0004).
- Interpretation time decreased by an average of 34 seconds per case (p<0.05), with general radiologists achieving time savings of more than 1 minute per case.
- Improving Efficiency and CT Technologists’ Workflow using Lumina 3D, an AI-Enhanced CT Head and Neck Reconstruction Solution
- With the shortage of CT techs nationwide, time savings and efficiency is increasingly important for diagnostic centers to keep up with the increase in imaging demands.
- Abstract evaluating operational performance of CT techs before and after the implementation of Lumina 3D.
- Prior to deployment, manual reconstructions averaged 31 minutes per patient. Following implementation, automated reconstructions required 7 minutes, resulting in a 77.4% reduction in technologist time, or 24 minutes saved per image.
- Based on monthly CTA volumes, the time savings translated to approximately 81.6 hours saved per month, enabling 108 additional scans and generating an estimated $43,000 in additional monthly imaging revenue. The results demonstrate how AI-driven automation can expand imaging capacity while reducing staff workload.
RapidAI also highlighted three abstracts based on data from its collaboration with the Florida Stroke Registry.
