Philips (NYSE: PHG) shared new clinical data supporting its AI-powered 3D Auto Color Flow Quantification (CFQ) technology for measuring mitral regurgitation.
Mitral regurgitation is a common heart condition in which the mitral valve does not close tightly, allowing blood to leak or flow backward. This can lead to a number of risks for the patient, including heart failure and death.
To plan timely treatment, an accurate assessment of blood flow and disease severity is essential, according to a Philips news release posted yesterday.
In an ongoing, multicenter international study, investigators have been comparing Philips technology to the traditional quantitative approaches using cardiac magnetic resonance imaging to confirm accuracy.
Findings so far — shared last week at the European Society of Cardiology Congress — suggest that Philips’ new approach may make it easier to assess and monitor patients with mitral regurgitation over time.
The 3D Auto CFQ algorithm works by using transesophageal echocardiography, an ultrasound test that creates images of the heart from a device inside the esophagus, to reconstruct and track the regurgitant convergence zone when the heart muscles contract.
Current recommended approaches, like the two-dimensional proximal isovelocity surface area (PISA) method analyzed in the study, rely on geometric assumptions and single-frame measurements, which can limit accuracy, according Philips.
Philips 3D technology accounts for changes in regurgitant orifice area and multiple regurgitant jets, giving a more comprehensive understanding of the amount of blood leaking from the valve.
By deepening and hastening clinicians’ understanding of the patient’s condition, Philips’ new technology may support faster care decisions in cases where disease presentation previously made this more difficult, according to the news release.
“Accurate quantification of mitral regurgitation is essential for clinical decision making, yet conventional approaches have well-recognized limitations,” said Dr. Victoria Delgado, MD, PhD, Hospital University Germans Trias i Pujol in Badalona, Spain, in a news release. “By providing measurements that more closely match cardiac magnetic resonance than conventional 2D PISA-based methods, these findings suggest AI-powered 3D Auto CFQ may help clinicians more consistently quantify mitral regurgitation across a wider variety of disease presentation.”
