We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




AI Solution Identifies Previously Undetected Cardiovascular Risk from Routine Chest CT Scans

By MedImaging International staff writers
Posted on 05 Oct 2023
Print article
Image: HealthCCSng is an FDA-cleared and CE marked tool designed specifically for cardiac health assessment (Photo courtesy of 123RF)
Image: HealthCCSng is an FDA-cleared and CE marked tool designed specifically for cardiac health assessment (Photo courtesy of 123RF)

Coronary artery calcium (CAC) scoring is a strong predictor of future heart-related incidents, with those in the highest calcium category facing a more than 20-fold increased risk of a cardiac event. Multiple studies have reinforced the link between detected coronary artery calcium and the severity of heart disease. Now, researchers using an artificial intelligence (AI)--powered solution to evaluate routine CT scans have found that over half of the patients were unaware they had moderate to severe CAC levels, which are known markers for future cardiac events.

HealthCCSng, an AI-powered solution created by Nanox.AI (Neve Ilan, Israel), makes use of medical imaging data from standard chest CT scans to automatically determine and assess CAC levels. This tool aids healthcare providers in identifying previously undiagnosed patients with cardiovascular issues and helps to categorize them for targeted preventive measures and treatments. By doing so, it directs patients onto suitable care pathways aimed at either preventing or reducing the likelihood of future heart-related incidents, through early detection and risk assessment.

In the study, the HealthCCSng software was used to gauge CAC levels from regular, non-contrast chest CT scans. Two radiologists then qualitatively evaluated these categorizations. The categories for patient CAC levels were defined as low (CAC 0-99), moderate (CAC 100-399), and severe (CAC greater than 400). Exceptions were made for individuals with specific medical histories or artifacts. Out of the 326 qualified patients who took part in the study between January and July 2023, 101 (or 31%) had severe CAC, 88 (or 27%) had moderate CAC, and 137 (or 42%) had low CAC. Patients found to have severe CAC were referred to specialized cardiology clinics for a comprehensive evaluation and treatment plan, while those with low and moderate CAC levels were advised to consult their primary care doctors for more detailed assessments and medical guidance.

“The patients in this study received routine CT scans that had nothing to do with a cardiac concern. Nanox’s AI technology can enable physicians to route these unsuspecting individuals with high CAC levels to the appropriate care pathways and treatment,” said Professor Ran Kornowski, Director of the Cardiology Center at Beilinson Hospital, who led the study. “While the study’s findings were staggering, we are encouraged by the important role AI can play in early risk identification and prevention of cardiac events.”

“HealthCCSng’s ability to detect hidden cardiovascular risks from routine CT scans offers a significant stride toward preventive cardiac care,” said Dr. Orit Wimpfheimer, Chief Medical Officer of Nanox.AI. “Given the global prominence of cardiovascular disease as the leading cause of mortality and the fact that nearly half of patients realize their condition only after an initial heart attack, leveraging such technologies for general population screening and early detection is absolutely imperative.”

Related Links:
Nanox.AI

New
Mobile X-Ray Machine
MARS 15 / 30
40/80-Slice CT System
uCT 528
Silver Member
X-Ray QA Meter
T3 AD Pro
Portable Color Doppler Ultrasound Scanner
DCU10

Print article

Channels

MRI

view channel
Image: An AI tool has shown tremendous promise for predicting relapse of pediatric brain cancer (Photo courtesy of 123RF)

AI Tool Predicts Relapse of Pediatric Brain Cancer from Brain MRI Scans

Many pediatric gliomas are treatable with surgery alone, but relapses can be catastrophic. Predicting which patients are at risk for recurrence remains challenging, leading to frequent follow-ups with... Read more

Nuclear Medicine

view channel
Image: In vivo imaging of U-87 MG xenograft model with varying mass doses of 89Zr-labeled KLG-3 or isotype control (Photo courtesy of L Gajecki et al.; doi.org/10.2967/jnumed.124.268762)

Novel Radiolabeled Antibody Improves Diagnosis and Treatment of Solid Tumors

Interleukin-13 receptor α-2 (IL13Rα2) is a cell surface receptor commonly found in solid tumors such as glioblastoma, melanoma, and breast cancer. It is minimally expressed in normal tissues, making it... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.