Advancing CCTA-Based Cardiovascular Care with Deep Learning: Highlights from Keya Medical’s SCCT 2025 Symposium

by | Aug 7, 2025 | All News, Conferences

Keya Medical Symposium at SCCT25 in Montreal

At SCCT25 in Montreal, Keya Medical had the privilege of hosting our sponsored symposium “The New World of Cardiovascular Care With CCTA: Deep Learning for Ischemia & Plaque Today – What Brings Tomorrow?” A heartfelt thank-you to our panel of expert clinical partners, who are not only leaders in cardiovascular care but also current users of our FDA-cleared, fully reimbursed DeepVessel FFR solution.

Moderator

  • Dr. Dinesh Kalra, Chief, Division of Cardiovascular Medicine, University of Louisville

Panelists

  • Dr. Irfan Shafique, President, Forward Healthcare Consultant
  • Dr. John A. Rumberger, Medical Director, Corazon Imaging
  • Dr. Scott D. Flamm, Medical Director, Precision Image Analysis

First Head-to-Head Comparison of DeepVessel FFR and FFRct

Dr. Dinesh Kalra (University of Louisville) presented the TRIPLE FFR study—the first U.S. head-to-head comparison of two FDA-cleared CT FFR tools in patients with 40–90% stenosis. In 58 patients across two centers, DeepVessel FFR matched HeartFlow FFRct in diagnostic performance, underscoring its clinical reliability and alignment with 2021 ACC/AHA and SCCT consensus guidelines.

Both HeartFlow’s FFRct and Keya Medical’s DeepVessel FFR (DVFFR) measurements were benchmarked against invasive instantaneous wave-free ratio (iFR) in 87 vessel segments (>2 mm diameter). The findings confirm that both AI-driven FFR tools reliably identify flow-limiting stenoses in line with 2021 ACC/AHA and SCCT guidelines. As noninvasive physiology gains traction in clinical workflows, this direct comparison paves the way for larger, diverse population trials to refine tool selection, optimize patient pathways, and ultimately improve outcomes in CAD management.

Head-to-head comparison of FFRCT and DVFFR-accuracy, sensitivity, Specificity, PPV, and NPV.

View SCCT Abstract

Reference
Patel Prabhakar A et al. “A Head to head Comparison of Two Deep Learning Techniques for FFR Assessment from CCTA.” J Cardiovasc Comput Tomogr. 2025;19(4 Suppl):S? (Abstract 2025 A 363 SCCT). Available at: https://www.sciencedirect.com/journal/journal-of-cardiovascular-computed-tomography/vol/19/issue/4/suppl/S

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