Simplified Models of Non-Invasive Fractional Flow Reserve Based on CT Images

Abstract

Invasive fractional flow reserve (FFR) is the gold standard to assess the functional coronary stenosis. The non-invasive assessment of diameter stenosis (DS) using coronary computed tomography angiography (CTA) has high false positive rate in contrast to FFR. Combining CTA with computational fluid dynamics (CFD), recent studies have shown promising predictions of FFRCT for superior assessment of lesion severity over CTA alone. The CFD models tend to be computationally expensive, however, and require several hours for completing analysis. Here, we introduce simplified models to predict noninvasive FFR at substantially less computational time. In this retrospective pilot study, 21 patients received coronary CTA. Subsequently a total of 32 vessels underwent invasive FFR measurement. For each vessel, FFR based on steady-state and analytical models (FFRSS and FFRAM, respectively) were calculated non-invasively based on CTA and compared with FFR. The accuracy, sensitivity, specificity, positive predictive value and negative predictive value were 90.6% (87.5%), 80.0% (80.0%), 95.5% (90.9%), 88.9% (80.0%) and 91.3% (90.9%) respectively for FFRSS (and FFRAM) on a per-vessel basis, and were 75.0%, 50.0%, 86.4%, 62.5% and 79.2% respectively for DS. The area under the receiver operating characteristic curve (AUC) was 0.963, 0.954 and 0.741 for FFRSS, FFRAM and DS respectively, on a per-patient level. The results suggest that the CTA-derived FFRSS performed well in contrast to invasive FFR and they had better diagnostic performance than DS from CTA in the identification of functionally significant lesions. In contrast to FFRCT, FFRSS requires much less computational time.

A study of noninvasive fractional flow reserve derived from a simplified method based on coronary computed tomography angiography in suspected coronary artery disease

“…All the procedures followed the Society of Cardiovascular Computed Tomography guidelines [20]. Oral beta-blockers were administered, targeting a heart rate of <60 beats/min.…”

Estimating the accuracy of a reduced‐order model for the calculation of fractional flow reserve (FFR)

“…Approaches based on 3D models also include the work of Morris et al and others. 11,[19][20][21][22] Methodologies based on reduced-order or 1D models typically solve for a single axial component of velocity, area, and/or pressure with an assumed profile function and require the use of empirical pressure loss formulations, 23 or else are combined with 3D models. These include the work of Renker et al and others.…”

“…31 Additional measurements, such as brachial pressure, can be used to derive aortic pressure and incorporated into more complex heart and coronary models; see related studies [16][17][18]36 and variants. 24,[26][27][28][29][30] Other boundary condition strategies include the prescription of pressure at the inlet, coupled with Windkessel models at the outlets 11 or steady-state simulations with uniform pressure and/or flow derived from imaging data 21,22 or else measured from 3D QCA and TIMI (thrombolysis in myocardial infarction) frame count. 20 In the present work, we demonstrate the feasibility of using CCTA imaging data and coronary flow simulations entirely based on reduced-order models to predict physiological measures such as FFR.…”

“…The inlet flow waveform is depicted in Figure 4, the coronary model in Figure 2. For each case, we assumed that hyperaemic microcirculatory resistance was identical to that of the reference case (no stenosis); see for instance Taylor et al 36 See also Morris et al and others 11,19,21 who use a "one-size-fits-all" approach. The coronary model is adapted from previously published models.…”

Diagnosis of cardiac allograft vasculopathy Challenges and opportunities

“…This invasive procedure adds time (especially in side branches and coronaries with complex anatomy (103)) and cost to the procedure and hence limits utility in everyday clinical practice. Recent improvements in the fractional flow reserve (FFR) method rely on the use of computational fluid dynamics (CFD) techniques in 3D models obtained from noninvasive computed tomography angiography or invasive quantitative coronary angiography (104,105). These studies report improvement in the diagnostic accuracy of the fractional flow reserve (FFR) method in predicting lesion-specific ischemia, with accuracy values of 86-88%.…”