Coronary fractional flow reserve derived from intravascular ultrasound imaging: Validation of a new computational method of fusion between anatomy and physiology. Issue 2 (12th September 2018)

• Record Type: Journal Article
• Authors: Bezerra, Cristiano G.; Hideo‐Kajita, Alexandre; Bulant, Carlos A.; Maso‐Talou, Gonzalo D.; Mariani, Jose; Pinton, Fabio A.; Falcão, Breno A. A.; Esteves‐Filho, Antônio; Franken, Marcelo; Feijóo, Raúl A.; Kalil‐Filho, Roberto; Garcia‐Garcia, Hector M.; Blanco, Pablo J.; Lemos, Pedro A.
• Is Part Of: Catheterization and cardiovascular interventions. Volume 93:Issue 2(2019)
• Page Start: 266
• Page End: 274
• Publication Date: 2018-09-12
• Subjects: computational fluid dynamics -- coronary blood flow/physiology/microvascular function -- coronary artery disease -- fractional flow reserve -- imaging intravascular ultrasound -- interventional devices/innovation -- quantitative coronary angiography -- three‐dimensional coronary models; Heart -- Diseases -- Diagnosis -- Periodicals; Cardiac catheterization -- Periodicals; 616.1207572
• DOI: 10.1002/ccd.27822
• Languages: English
• ISSNs: 1522-1946

Abstract

Abstract: Objectives: To evaluate the diagnostic performance of a novel computational algorithm based on three‐dimensional intravascular ultrasound (IVUS) imaging in estimating fractional flow reserve (IVUSFR ), compared to gold‐standard invasive measurements (FFRINVAS ). Background: IVUS provides accurate anatomical evaluation of the lumen and vessel wall and has been validated as a useful tool to guide percutaneous coronary intervention. However, IVUS poorly represents the functional status (i.e., flow‐related information) of the imaged vessel. Methods: Patients with known or suspected stable coronary disease scheduled for elective cardiac catheterization underwent FFRINVAS measurement and IVUS imaging in the same procedure to evaluate intermediate lesions. A processing methodology was applied on IVUS to generate a computational mesh condensing the geometric characteristics of the vessel. Computation of IVUSFR was obtained from patient‐level morphological definition of arterial districts and from territory‐specific boundary conditions. FFRINVAS measurements were dichotomized at the 0.80 threshold to define hemodynamically significant lesions. Results: A total of 24 patients with 34 vessels were analyzed. IVUSFR significantly correlated ( r = 0.79; P < 0.001) and showed good agreement with FFRINVAS, with a mean difference of −0.008 ± 0.067 ( P = 0.47). IVUSFR presented an overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 91%, 89%, 92%, 80%, and 96%, respectively, to detect significant stenosis. Conclusion: The computational processing of IVUSFR is a new method that allows the evaluation of the functional significance of coronary stenosis in an accurate way, enriching the anatomical information of grayscale IVUS.