Elucid Bio: Study Demonstrates that AI Technology is Better Predictor of Stroke than Traditional Methods

vascuCAP® Software Study Was Led by Dr. Brajesh Lal

July 1, 2020

Elucid Bio, maker of the FDA-cleared and CE-marked vascuCAP® software, announced today that its novel artificial intelligence (AI) technology demonstrated an over 70 percent improvement in accuracy of stroke prediction as compared to stenosis-based guidelines over a six-year time period. The interim results of the CRISP trial will be presented on Thursday, July 2, during Scientific Session 9 at the Society for Vascular Surgery conference, SVS Online Summer 2020.

The study, led by Dr. Brajesh Lal, Director of both the University of Maryland’s Center for Vascular Diagnostics and the NIH Vascular Imaging Core Facility, with participation by the Cleveland Clinic, Weill-Cornell, and Case Western, sought to improve prediction of Major Adverse Neurological Events (MANE; stroke, transient ischemic attack, and amaurosis fugax) by applying AI to traditional carotid imaging using the Elucid Bio vascuCAP software.

Vascucap By Elucid Key Image
On the left is a CT scan of the carotid artery. On the right, Elucid Bio’s vascuCAP® software transforms the CT scan into a 3D visualization and quantitation of plaque tissue composition and structural measurements. vascuCAP was validated in the CRISP trial to inform highly accurate prediction of Major Adverse Neurological Events such as stroke.

Stroke remains the leading cause of disability in the United States and is the 5th leading cause of death. Current risk assessment for patients with carotid atherosclerosis relies primarily on assessing the degree of stenosis. More reliable risk stratification has the potential to improve patient selection for more aggressive treatment for MANE by incorporating a combination of carotid plaque geometry, plaque tissue composition, patient demographics and clinical insights.

“These study results demonstrate that the vascuCAP’s artificial intelligence algorithms for risk stratification in carotid atherosclerosis are a better predictor of stroke than stenosis assessment alone,” stated Dr. Lal. “Implementing this predictive model on asymptomatic patients in the clinical setting could help identify and inform treatment for those at high-risk for future major adverse neurological events.”

“The results of the CRISP trial provide further validation of the potential impact of our vascuCAP software to improve risk assessment for stroke,” commented Blake Richards, CEO of Elucid Bio. “These data should foster confidence to increase clinical adoption of vascuCAP.”

The Elucid Bio technology is currently in clinical use and may have applications for informing risk for COVID-19 patients who have been experiencing strokes at a significantly higher rate. The software can identify endothelial damage, a subtle, but potentially deadly effect of COVID-19 that can cause blood clotting that leads to stroke.

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