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Gus Iversen, Editor in Chief | December 10, 2025
Siemens Healthineers has launched Syngo.CT Coronary Cockpit, a new software application designed to assist clinicians in diagnosing and managing coronary artery disease (CAD) using coronary CT imaging.
The tool was unveiled at RSNA 2025 and is now available on the Syngo.via platform, supporting both dual-source and photon-counting CT systems.
The software applies automated, AI-driven plaque analysis to quantify and characterize coronary artery plaque burden. This supports risk assessment and can help guide percutaneous coronary intervention (PCI) planning. According to the company, the goal is to provide physicians with greater insight ahead of catheterization procedures, potentially reducing unnecessary invasive testing.
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“There is a lot of information that is locked within CT images,” said Dr. Balint Szilveszter of Semmelweis University in Budapest. “Syngo.CT Coronary Cockpit is an automated tool that provides a fast approach to unlock this information to include it in our everyday clinical routine. The information can be used for optimizing medical therapy or to plan PCI procedures before even entering the cath lab.”
The software leverages AI to segment, label and visualize plaque features, including size, morphology, and composition. These capabilities are intended to enhance diagnostic confidence and support more informed treatment decisions, whether medical or interventional.
Coronary CT angiography (CCTA), particularly with photon-counting and dual-source CT scanners such as Siemens’ Naeotom Alpha, has increasingly been used as a frontline diagnostic tool. Recent studies cited by the company suggest that such imaging can significantly reduce referrals for diagnostic angiography, lower costs, and shorten hospital stays.
Syngo.CT Coronary Cockpit integrates with Siemens Healthineers' CT systems to deliver high temporal resolution and improve workflow across the CAD care pathway. By providing detailed coronary information prior to PCI, the software may aid in decisions related to lesion preparation and stent planning.
