Computer model + 3D imaging challenge FFR as cath lab tool

Using 3D imaging and computer models to allow fast computation, researchers developed a method they propose may be safer, more efficient and cost less than traditional wire-based fractional flow reserve (FFR) calculations for assessing coronary stenosis.

The research group led by Shenxian Tu, MD, of Leiden University Medical Center in the Netherlands, used 3D quantitative coronary angiography (QCA) in conjunction with Thrombolysis in Myocardial Infarction (TIMI) frame count to calculate mean volumetric flow rate at hyperemia and assessed against wire-based FFR. Patients in this study had moderate stenosis.

They found good correlation and agreement between their computed FFR (FFRQCA) and traditional FFR. When a discrimination limit of less than or equal to 0.8 was applied to 77 of the vessels reviewed, they found 18 true positives, 50 true negatives, four false positives and five false negatives, with an overall accuracy of 88 percent. Tu et al reported sensitivity and specificity of 78 percent and 93 percent, respectively. Positive and negative predictive values were found to be 82 percent and 91 percent, respectively.

Compared to minimal lumen area and percent diameter stenosis, 64 percent and 68 percent respectively, the accuracy of QCA-derived FFR was determined to be much better at discriminating the clinical significance in lesions.

3D QCA was found to be a faster method than FFR calculated with CT data; FFRQCA was able to be analyzed in 10 minutes or less, while FFRCT took up to 24 hours with mixed results.

Among the benefits discussed by Tu et al, FFRQCA could be used for diagnostic purposes on more patients than the traditional wire method with fewer risks. Wire-based FFR is precise, but has the added cost of wires and other supplies and comes with hazards.

Among those encouraged by the findings of Tu and colleagues were Alexandra J. Lansky, MD, and Cody Pietras, BSc, of Yale University School of Medicine in New Haven, Conn. Lansky and Pietras wrote in an editorial that this method “has the potential to reduce the barrier to physiological assessment in the catheterization laboratory, and expand its clinical utility be reducing unnecessary revascularization of insignificant lesions and enabling identification of additional clinically significant lesions.”

Tu et al and the editorial writers agreed that confirmation of accuracy and generalizability to real-world situations are imperative, as is validation in more complex lesions.

Tu et al added that while the 10-minute processing time is an improvement over other methods, it must be shortened further to be accepted as a routine clinical means of assessing stenosis. Also, while it is understood to be a less expensive method, should FFRQCA prove to be a method that translates into clinical practice, actual cost-savings over wire-based FFR would need to be calculated.

The study and editorial were published in the July issue of the Journal of the American College of Cardiology: Cardiovascular Interventions.

Around the web

Several key trends were evident at the Radiological Society of North America 2024 meeting, including new CT and MR technology and evolving adoption of artificial intelligence.

Ron Blankstein, MD, professor of radiology, Harvard Medical School, explains the use of artificial intelligence to detect heart disease in non-cardiac CT exams.

Eleven medical societies have signed on to a consensus statement aimed at standardizing imaging for suspected cardiovascular infections.