In a major breakthrough for cardiovascular diagnostics, Russian scientists have developed a cutting-edge AI-powered program that rapidly analyzes heart CT scans to detect early signs of heart disease.

The innovation promises to save doctors time, improve diagnostic accuracy, and enable faster treatment, potentially saving lives.

Developed by the Research Institute of Cardiology at the Tomsk Research Medical Centre and Tomsk Polytechnic University, the program leverages artificial intelligence to automatically assess the volume and density of epicardial fat, fatty tissue surrounding the heart that plays a key role in both protecting the organ and signaling potential heart problems.

According to the official website of the Russian Academy of Sciences (RAS), which partnered with TV BRICS to release the report, this fatty tissue is more than just structural padding. It actively participates in metabolic processes and releases substances that influence inflammation.

Crucially, changes in its volume or density often serve as early indicators of cardiovascular disease. Until now, cardiologists had to manually analyze dozens of CT scan images, a process that was both time-consuming and heavily reliant on specialist expertise.

However, the new AI tool completes the analysis in just 22 seconds per scan, with an accuracy rate comparable to that of a seasoned professional.

According to the Head of the Radiology Department at the Research Institute of Cardiology and a Doctor of Medical Sciences, Dr. Konstantin Zavadovsky, “This saves the doctor’s time and allows changes to be detected at an early stage. It helps to prescribe treatment faster and select therapy more accurately.”

The software, now patented, represents a fusion of advanced AI algorithms and clinical cardiology, paving the way for smarter, faster, and more personalized heart disease treatment.

Notably, as cardiovascular disease continues to be the leading cause of death globally, innovations like this AI program could mark a turning point in early detection and intervention strategies.

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