Determinants of Rejection Rate for Coronary CT Angiography Fractional Flow Reserve Analysis

Abstract

oronary artery disease is a major cause of mortality and morbidity, and its management consumes a large portion of health care budgets (1). Several noninvasive tests are commonly used as gatekeepers to invasive coronary angiography. Despite the frequent use of noninvasive functional stress testing, the prevalence of obstructive coronary artery disease at elective invasive coronary angiography is low (2,3). Coronary CT angiography is an alternative anatomically based imaging modality used to assess coronary artery disease. However, because of its limited positive predictive value, it can lead to increased downstream use of invasive coronary angiography (4-6). Recently, participant-specific coronary CT angiography data have been combined with computational fluid dynamic models, allowing for noninvasive determination of the fractional flow reserve derived from coronary CT angiography (FFR CT). This correlates well with invasive FFR and reduces rates of invasive coronary angiography use compared with coronary CT angiography alone (7,8). In these previous trials,

Computed tomographic evaluation of myocardial ischemia

“…However, recent studies have shown that the performance of CT-FFR in patients with high coronary calcium score is superior to that of CTA alone [130,136]. The rates of rejection on CT-FFR analysis in the ADVANCE registry and in a large clinical cohort were 2.9% and 8.4%, respectively [137]. CT-FFR is currently not suitable for patients with stenting or CABG.…”

Improving CT-Derived Fractional Flow Reserve Analysis: A Quality Improvement Initiative

“…Initial rejection rates for FFRCT analysis reported throughout the literature range from 13% to 33%, with significant cardiac motion commonly cited as a reason for rejection [ 4 , 6 ]. Pontone et al found that temporal resolution, section thickness, and heart rate are independent predictors of rejection for CCTA FFRCT analysis [ 5 , 9 ]. They postulated that their own study had a low rejection rate of 2.9% because of the use of dual-source technology and wide-coverage single-source scanners.…”

“…Although FFRCT has been shown to be a valuable tool in the evaluation of intermediate-range stenosis on CCTA, the analysis is highly sensitive to scanning protocol and artifacts [ 4 ]. It has been shown that image quality of CCTA is closely associated with the heart rate at the time of study acquisition [ 5 ]. The rejection rate of FFRCT in the literature ranges from 2% to 33% mainly due to differences in imaging acquisition, study incompletion such as missing best diastolic or systolic reconstructions for myocardial segmentation, patient-specific factors including body habitus and motion, and artifacts including calcium blooming, motion, and low contrast [ 4 , 6 ].…”

Machine Learning for Assessment of Coronary Artery Disease in Cardiac CT: A Survey

“…An important remaining step toward clinical application of FFR CT lies in performance evaluation specifically for subjects around the FFR threshold of 0.8, which were shown to be most challenging (90). Furthermore, a recent study showed that not all CCTA exams are suitable for FFR CT analysis (78).…”

“…et al(77) further demonstrated additional prognostic value of CT morphological index for the method proposed by Itu et al(55). Wang et al(50) proposed to use a recurrent ANN that can model long-range dependencies between segments.Both conventional CFD-based FFR CT and the methods proposed in Wang et al(50) andItu et al (55) are based only on the geometry of the coronary artery tree model, and are thus susceptible to errors by the segmentation method used to obtain this model(78). Instead, Dey et al(52) proposed to combine geometric features with semi-automatically obtained plaque and attenuation gradient measurements to identify arteries with functionally significant stenosis.…”