Keya Medical was invited to deliver a virtual academic lecture to more than 130 imaging departments in honor of the newly established Northern Jiangsu People’s Hospital Medical Imaging Alliance. The online live broadcast brought together leading researchers, professors, and clinicians to discuss the advantages of non-invasive CT-FFR.

The Medical Imaging Alliance was established on Aug. 28 with 47 member units participating in the first group. According to Dr. Jing Ye, chairman of the Medical Imaging Alliance, the alliance intends to improve the ability of medical institutions to serve patients and reduce the unnecessary waste of medical resources. By partnering with Keya Medical, the team will conduct a series of special lectures to actively engage members of the program in conversations related to AI and medical imaging, strengthening the expertise of program members through regular academic exchanges. Keya Medical will present scientific research and technical advantages in the field of artificial intelligence applied in medical imaging to help support progress in the industry.

Non-invasive CT-FFR

Yongzhen Cui, a representative of Keya Medical and technical expert in the Engineering Center, delivered a presentation on how artificial intelligence applied to coronary CT angiography (CTA) is bringing a new generation of non-invasive CT-FFR products to clinical use.

DEEPVESSEL FFR, Keya Medical’s product that uses deep learning to perform a non-invasive physiological functional assessment of the coronary arteries, is the first medical imaging AI product in China to receive regulatory approval from the National Medical Products Administration (NMPA). DEEPVESSEL FFR is currently the only product in China to receive both a CE-mark and an approval from the NMPA. Using the product, clinicians can automatically calculate the FFR value at any location on the coronary artery tree to further enhance the detection ability and processing speed of CT-FFR.

This non-invasive comprehensive evaluation of the coronary arteries using deep learning can help clinicians formulate personalized treatment plans for patients while avoiding the unnecessary costs and complications that can be incurred from invasive procedures.
Following the seminar, attendees shared that they would apply their new knowledge to provide patients with better diagnosis and treatment of coronary artery disease moving forward.