Computed Tomography Coronary Plaque Characteristics Predict Ischemia Detected by Invasive Fractional Flow Reserve. Issue 6 (21st November 2021)

• Record Type: Journal Article
• Authors: Velangi, Pratik S.; Maharaj, Valmiki; Athwal, Satyajit S.; Bartos, Jason A.; Markowitz, Jeremy; Duval, Sue; Nijjar, Prabhjot S.
• Is Part Of: Journal of thoracic imaging. Volume 36:Issue 6(2021)
• Page Start: 360
• Page End: 366
• Publication Date: 2021-11-21
• Subjects: coronary computed tomography -- ischemia -- plaque -- fractional flow reserve; Chest -- Radiography -- Periodicals; Chest -- Diseases -- Diagnosis -- Periodicals; 617.540757
• DOI: 10.1097/RTI.0000000000000543
• Languages: English
• ISSNs: 0883-5993

Abstract

Abstract : Supplemental Digital Content is available in the text. Abstract : Purpose: Coronary computed tomography angiography (CCTA) plaque quantification has been proposed to be of incremental value in the prediction of ischemia, although prior studies have shown conflicting results. We aimed to determine whether CCTA plaque features assessed on a commercial vendor platform predict invasive fractional flow reserve (FFR)/instantaneous wave-free ratio (IFR). Methods: Consecutive patients who underwent CCTA for evaluation of suspected stable coronary artery disease followed by invasive coronary physiology testing within 60 days at a single academic center were identified retrospectively. Semiautomated plaque quantification of the vessel proximal to the location of FFR/IFR measurement was carried out in TeraRecon, along with simple visual assessment for high-risk plaque features of positive remodeling, spotty calcification, low-attenuation plaque (LAP), and lesion length. Ischemia was defined by FFR ≤0.80 or IFR ≤0.89. Results: A total of 134 patients (62% male, mean age 62±10 y) were included in this study. On univariate logistic regression, the following visual plaque analysis parameters were predictive of ischemia: positive remodeling (odds ratio [OR] with 95% confidence interval [CI]: 4.96; 2.25-10.95; P <0.001), lesion length (OR for every 1 mm with 95% CI: 1.24; 1.14-1.34; P <0.001), spotty calcification (OR with 95% CI: 6.67; 1.67-26.64; P =0.007), and LAP (OR with 95% CI: 30; 3.78-246; P =0.001). None of the semiautomated plaque quantification parameters, such as noncalcified plaque volume or LAP volume, were predictive of ischemia. On stepwise multivariable logistic regression, lesion length (OR with 95% CI: 1.25; 1.14-1.37; P <0.0001) and LAP (OR with 95% CI: 43; 4.4-438; P =0.001) were significant predictors of ischemia, improving the area under the curve of CCTA from 0.53 to 0.87. Conclusions: Simple visual plaque assessment for high-risk plaque features improved the performance of CCTA to predict ischemia. Semiautomated plaque quantification performed on a commercial vendor platform was not predictive of ischemia.