A lot of effort goes into figuring out how we can predict health problems before they happen. We look at blood pressure, cholesterol and blood sugar and analyze whether they mean we’re at increased risk of strokes, heart attacks or diabetes. But what about cardiac inflammation? We know that’s a major contributing factor to many cardiac events, but it’s also very hard to detect. Well, until now (https://longevity.technology/news/new-ai-tech-predicts-cardiac-events-due-to-coronary-inflammation/).
Caristo Diagnostics has been conducting a major study involving around 40,000 participants into coronary computed tomography angiography (CCTA) imaging biomarkers over a period of between 2 and 7 years. It just published the results in the Lancet. They suggest that it may be possible to assess cardiac risk without obstructive coronary heart disease, all through the measurement of cardiac inflammation.
The Oxford Risk Factors And Non-invasive imaging (ORFAN) study used its computed tomography to analyze fat tissue, whether it was around the heart, in the blood vessels or subcutaneous. Caristo Diagnostics provided its unique CaRi-Heart technology, complete with advanced AI, to calculate what’s known as a perivascular fat attenuation index (FAI) score from the scans.
Patients who did not have obstructive coronary heart disease, coronary plaques or other traditional risk cardiac risk factors were still at increased risk of an adverse cardiac event, fatal or non-fatal, if they had a high FAI score – in some cases, by as much as a 9.5-fold margin. For some participants, the cardiac event could be predicted a decade in advance. For 45% of patients, this led to clinicians changing their approach to treatment to specifically target cardiac inflammation.
ORFAN is the largest-ever study of its kind, and it’s still growing. Eventually there will be data from as many as 250,000 participants in the registry, with patients located around the world. What we have so far are still just initial results, with more research needed to develop better predictive tools, make them accessible to more patients and clinicians, and find the most useful ways to apply the results.
With the help of CaRi-Heart and its FAI scores, we could be able to predict cardiac risk in patients whose other scans seem completely normal long before they experience any cardiac event. This has major implications for early diagnosis, management and treatment, hopefully giving more patients a chance at long and healthy lives.
