Better Diagnosis of Functionally Significant Intermediate Sized Narrowings Using Intravascular Ultrasound-Minimal Lumen Area and Coronary Computed Tomographic Angiography-Based Myocardial Segmentation

Association of Coronary Computed Tomography-Defined Myocardial Bridge With Pre- and Post-Procedural Fractional Flow Reserve in Patients Undergoing Elective Percutaneous Coronary Intervention

BACKGROUND

Myocardial bridge (MB) is a common coronary anomaly characterized by a tunneled course through the myocardium. Coronary computed tomography angiography (CCTA) can identify MB. The impact of MB detected by CCTA on coronary physiological parameters before and after percutaneous coronary intervention (PCI) is unknown.Methods and Results: We investigated 141 consecutive patients who underwent pre-PCI CCTA and fractional flow reserve (FFR)-guided elective PCI for de novo single proximal lesions in the left anterior descending artery (LAD). We compared clinical demographics and physiological parameters between patients with and without CCTA-defined MB. MB was identified in 46 (32.6%) patients using pre-PCI CCTA. The prevalence of diabetes was higher among patients with MB. Median post-PCI FFR values were significantly lower among patients with than without MB (0.82 [interquartile range 0.79-0.85] vs. 0.85 [interquartile range 0.82-0.89]; P=0.003), whereas pre-PCI FFR values were similar between the 2 groups. Multivariable linear regression analysis revealed that the presence of MB and greater left ventricular mass volume in the LAD territory were independently associated with lower post-PCI FFR values. Multivariable logistic regression analysis also revealed that the presence of MB and lower pre-PCI FFR values were independent predictors of post-PCI FFR values ≤0.80.

CONCLUSIONS

CCTA-defined MB independently predicted both lower post-PCI FFR as a continuous variable and ischemic FFR as a categorical variable in patients undergoing elective PCI for LAD.

A comprehensive approach to prediction of fractional flow reserve from deep-learning-augmented model

The underuse of invasive fractional flow reserve (FFR) in clinical practice has motivated research towards non-invasive prediction of FFR. Although the non-invasive derivation of FFR (FFRCT) using computational fluid dynamics (CFD) principles has become a common practice, its clinical application has been limited due to the considerable time required for computation of resulting changes in haemodynamic conditions. An alternative to CFD technology is incorporating a neural network into the computational process to reduce the time necessary for running an effective model. In this study we propose a cascade of data-driven and physic-based neural networks (DP-NN) for predicting FFR (DL-FFRCT). The first network of cascade network DP-NN includes geometric features, and the second network includes physical features. We compare the differences between data-driven neural network (D-NN) and DP-NN for predicting FFR. The training and testing datasets were obtained by solving the three-dimensional incompressible Navier-Stokes equations. Coronary flow and geometric features were used as inputs to train D-NN. In DP-NN the training process involves first training a D-NN to output resting ΔP as one input feature to the DP-NN. Secondly, the physics-based microcirculatory resistance as another input feature to the DP-NN. Using clinically measured FFR as the "gold standard", we validated the computational accuracy of DL-FFRCT in 77 patients. Compared to D-NN, DP-NN improved the prediction of ΔP (R2 = 0.87 vs. R2 = 0.92). Statistical analysis demonstrated that the diagnostic accuracy of DL-FFRCT was not inferior to FFRCT (85.71 % vs. 88.3 %) and the computational time was reduced by a factor of approximately 3000 (4.26 s vs. 3.5 h). DP-NN represents a near real-time, interpretable, and highly accurate deep-learning network, which contributes to the development of high-performance computational methods for haemodynamics. We anticipate that DP-NN will enable near real-time prediction of DL-FFRCT in personalized narrow blood vessels and provide guidance for cardiovascular disease treatments.

Physiological Approach for Coronary Artery Bifurcation Disease: Position Statement by Korean, Japanese, and European Bifurcation Clubs

Coronary artery bifurcation lesions are frequently encountered in cardiac catheterization laboratories and are associated with more complex procedures and worse clinical outcomes than nonbifurcation lesions. Therefore, anatomical and physiological assessment of bifurcation lesions before, during, and after percutaneous coronary intervention is of paramount clinical importance. Physiological assessment can help interventionalists appreciate the hemodynamic significance of coronary artery disease and guide ischemia-directed revascularization. However, it is important to understand that the physiological approach for bifurcation disease is more important than simply using physiological indexes for its assessment. This joint consensus document by the Korean, Japanese, and European bifurcation clubs presents the concept of a physiological approach for coronary bifurcation lesions, as well as current knowledge, practical tips, pitfalls, and future directions of applying physiological indexes in bifurcation percutaneous coronary intervention. This document aims to guide interventionalists in performing appropriate physiology-based assessments and treatment decisions for coronary bifurcation lesions.

Association of quantitative flow ratio-derived microcirculatory indices with anatomical-functional discordance in intermediate coronary lesions

Discrepancy between coronary lesion severity and functional significance has always been a relevant issue in the management of patients undergoing coronary angiography and/or revascularization. We sought to investigate the relationship between quantitative flow ratio (QFR)-derived microcirculatory indices and anatomical-functional mismatch/reverse mismatch in intermediate coronary lesions. Intravascular ultrasound (IVUS) imaging and QFR were analyzed in 117 de novo intermediate coronary lesions. Lesions with QFR ≤ 0.8 were considered hemodynamically significant. Anatomical significance of the lesions was defined according to the best cutoff value of combined IVUS parameters for predicting QFR ≤ 0.8. QFR-derived microcirculatory indices including contrast-flow QFR minus fixed-flow QFR (cQFR-fQFR), hyperemic flow velocity and angiography-derived index of microcirculatory resistance (IMR_angio) were calculated. The best cutoff values of IVUS parameters for predicting QFR ≤ 0.8 were minimum lumen area (MLA) 3.1mm² and plaque burden (PB) 70%, with area under the curve of 0.635 and 0.703, respectively. The total discordance rate of lesion functional significance between IVUS and QFR assessments was 26.5%, with 21 lesions (17.9%) being classified as mismatch (MLA ≤ 3.1mm² and PB ≥ 70% and QFR > 0.8) and 10 lesions (8.5%) as reverse-mismatch (MLA > 3.1 mm² or PB < 70% and QFR ≤ 0.8). At multivariate analysis, IMR_angio was identified as an independent predictor of mismatch (OR1.675, 95%CI:1.176-2.386, P = 0.004), whereas hyperemic flow velocity was identified as an independent predictor of reverse-mismatch (OR 1.233, 95%CI:1.073-1.416, P = 0.003). In intermediate coronary lesions, although MLA 3.1mm² and PB 70% determined by IVUS are predictive of QFR-defined functional significance, the discordance rate remains substantial. QFR-derived microcirculatory indices are independently associated with anatomical-functional discordance between IVUS and QFR assessments.

Pre-percutaneous Coronary Intervention Pericoronary Adipose Tissue Attenuation Evaluated by Computed Tomography Predicts Global Coronary Flow Reserve After Urgent Revascularization in Patients With Non-ST-Segment-Elevation Acute Coronary Syndrome

Background

Impaired global coronary flow reserve (g‐CFR) is related to worse outcomes. Inflammation has been postulated to play a role in atherosclerosis. This study aimed to evaluate the relationship between pre‐procedural pericoronary adipose tissue inflammation and g‐CFR after the urgent percutaneous coronary intervention in patients with first non–ST‐segment–elevation acute coronary syndrome.

Methods and Results

Phase‐contrast cine‐magnetic resonance imaging was performed to obtain g‐CFR by quantifying coronary sinus flow at 1 month after percutaneous coronary intervention in a total of 116 first non–ST‐segment–elevation acute coronary syndrome patients who underwent pre‐percutaneous coronary intervention computed tomography angiography. On proximal 40‐mm segments of 3 major coronary vessels on computed tomography angiography, pericoronary adipose tissue attenuation was assessed by the crude analysis of mean computed tomography attenuation value. The patients were divided into 2 groups with and without impaired g‐CFR divided by the g‐CFR value of 1.8. There were significant differences in age, culprit lesion location, N‐terminal pro‐B‐type natriuretic peptide levels, high‐sensitivity C‐reactive protein (hs‐CRP) levels, mean pericoronary adipose tissue attenuation between patients with impaired g‐CFR and those without (g‐CFR, 1.47 [1.16, 1.68] versus 2.66 [2.22, 3.28]; P<0.001). Multivariable logistic regression analysis revealed that age (odds ratio [OR], 1.060; 95% CI, 1.012–1.111, P=0.015) and mean pericoronary adipose tissue attenuation (OR, 1.108; 95% CI, 1.026–1.197, P=0.009) were independent predictors of impaired g‐CFR (g‐CFR <1.8).

Conclusions

Mean pericoronary adipose tissue attenuation, a marker of perivascular inflammation, obtained by computed tomography angiography performed before urgent percutaneous coronary intervention, but not hs‐CRP, a marker of systemic inflammation was significantly associated with g‐CFR at 1‐month after revascularization. Our results may suggest the pathophysiological mechanisms linking perivascular inflammation and g‐CFR in patients with non–ST‐segment–elevation acute coronary syndrome.

Impact of pericoronary adipose tissue inflammation on left ventricular hypertrophy and regional physiological indices in stable coronary artery disease patients with preserved systolic function

Systemic low-grade inflammation has been shown to be associated with left ventricular hypertrophy (LVH). However, the relationship between pericoronary adipose tissue attenuation (PCATA) and both LVH and regional physiological indices remains unknown. This study aimed to evaluate the association of PCATA with LVH and regional physiological indices in stable coronary artery disease (CAD) patients with preserved systolic function. A total of 114 CAD patients who underwent coronary CT angiography (CTA) and invasive physiological tests showing ischemia due to a single de novo lesion were included in the study. On proximal 40-mm segments of all three major coronary vessels on CTA, PCATA was assessed by the crude analysis of the mean CT attenuation value [- 190 to - 30 Hounsfield units [HU)] and the culprit vessel PCATA was used for the analysis. Regional physiological indices were invasively obtained by pressure-temperature sensor-tipped wire. The patients were divided into three groups by culprit vessel PCATA tertiles, and clinical, CTA-derived, and physiological indices were compared. Univariable and multivariable analyses were further performed to determine the predictors of LVH. Angiographic stenosis severity, culprit lesion locations, culprit vessel fractional flow reserve, coronary flow reserve, index of microcirculatory resistance, total and target vessel coronary calcium score, and biomarkers including high-sensitivity C-reactive protein were not different among the groups. The left ventricular (LV) mass, LV mass index (LVMI), and LV mass at risk were all significantly different in the three groups with the greatest values in the highest tertile group (all, P < 0.05). On multivariable analysis, male gender, NT-proBNP, and PCATA were independent predictors of LVMI. Culprit vessel PCATA was significantly associated with LVMI, but not with regional physiology in CAD patients with functionally significant lesions and preserved systolic function. Our results may offer insight into the pathophysiological mechanisms linking pericoronary inflammation and LVH to worse prognosis.

Impact of Subtended Myocardial Mass Assessed by Coronary Computed Tomographic Angiography-Based Myocardial Segmentation

Although decision-making for revascularization is based on the extent of ischemic myocardium, the prognostic implication of supplying myocardial territories has not yet been studied. To evaluate the clinical impact of the coronary artery-based myocardial segmentation (CAMS)-derived myocardial volume subtended to the poststenotic segment, and to determine clinically relevant coronary lesions, coronary computed tomography angiography, invasive coronary angiography, and preprocedure fractional flow reserve (FFR) data were analyzed in 664 deferred lesions (in 577 patients) and 401 treated lesions (in 369 patients) with drug-eluting stent implantation, respectively. Using CAMS method, the myocardial volume subtended to a stenotic coronary segment (V_sub) was assessed. The primary composites included target vessel-related major adverse cardiac event (MACE) including cardiac death, myocardial infarction, and target vessel revascularization over 3 years. Independent predictors of 3-year MACE in deferred lesions were V_sub (adjusted hazard ratio [HR] 1.02), FFR (adjusted HR per 0.1 = 0.60), and distal reference luminal diameter (adjusted HR 2.04, all p < 0.05). A V_sub ≥ 36.2cc was predictive of MACE in deferred lesions with a sensitivity 72% and a specificity 67% (area under curve 0.71, 95% confidence interval 0.67 to 0.74, p < 0.001). V_sub was not associated with target vessel-related MACE. For the prediction of FFR < 0.80, the area under curve of V_sub/MLD⁴ > 6.3 was greater than those of angiographic diameter stenosis (0.78 vs 0.69) and minimal luminal diameter (0.78 vs 0.71), (all p < 0.05). CAMS-derived V_sub predicted 3-year clinical outcomes in untreated coronary lesions, and improved the diagnostic performance of angiography-derived parameters to identify ischemia-producing lesions.

Machine learning assessment of myocardial ischemia using angiography: Development and retrospective validation

BACKGROUND

Invasive fractional flow reserve (FFR) is a standard tool for identifying ischemia-producing coronary stenosis. However, in clinical practice, over 70% of treatment decisions still rely on visual estimation of angiographic stenosis, which has limited accuracy (about 60%-65%) for the prediction of FFR < 0.80. One of the reasons for the visual-functional mismatch is that myocardial ischemia can be affected by the supplied myocardial size, which is not always evident by coronary angiography. The aims of this study were to develop an angiography-based machine learning (ML) algorithm for predicting the supplied myocardial volume for a stenosis, as measured using coronary computed tomography angiography (CCTA), and then to build an angiography-based classifier for the lesions with an FFR < 0.80 versus ≥ 0.80.

METHODS AND FINDINGS

A retrospective study was conducted using data from 1,132 stable and unstable angina patients with 1,132 intermediate lesions who underwent invasive coronary angiography, FFR, and CCTA at the Asan Medical Center, Seoul, Korea, between 1 May 2012 and 30 November 2015. The mean age was 63 ± 10 years, 76% were men, and 72% of the patients presented with stable angina. Of these, 932 patients (assessed before 31 January 2015) constituted the training set for the algorithm, and 200 patients (assessed after 1 February 2015) served as a test cohort to validate its diagnostic performance. Additionally, external validation with 79 patients from two centers (CHA University, Seongnam, Korea, and Ajou University, Suwon, Korea) was conducted. After automatic contour calibration using the caliber of guiding catheter, quantitative coronary angiography was performed using the edge-detection algorithms (CAAS-5, Pie-Medical). Clinical information was provided by the Asan BiomedicaL Research Environment (ABLE) system. The CCTA-based myocardial segmentation (CAMS)-derived myocardial volume supplied by each vessel (right coronary artery [RCA], left anterior descending [LAD], left circumflex [LCX]) and the myocardial volume subtended to a stenotic segment (CAMS-%Vsub) were measured for labeling. The ML for (1) predicting vessel territories (CAMS-%LAD, CAMS-%LCX, and CAMS-%RCA) and CAMS-%Vsub and (2) identifying the lesions with an FFR < 0.80 was constructed. Angiography-based ML, employing a light gradient boosting machine (GBM), showed mean absolute errors (MAEs) of 5.42%, 8.57%, and 4.54% for predicting CAMS-%LAD, CAMS-%LCX, and CAMS-%RCA, respectively. The percent myocardial volumes predicted by ML were used to predict the CAMS-%Vsub. With 5-fold cross validation, the MAEs between ML-predicted percent myocardial volume subtended to a stenotic segment (ML-%Vsub) and CAMS-%Vsub were minimized by the elastic net (6.26% ± 0.55% for LAD, 5.79% ± 0.68% for LCX, and 2.95% ± 0.14% for RCA lesions). Using all attributes (age, sex, involved vessel segment, and angiographic features affecting the myocardial territory and stenosis degree), the ML classifiers (L2 penalized logistic regression, support vector machine, and random forest) predicted an FFR < 0.80 with an accuracy of approximately 80% (area under the curve [AUC] = 0.84-0.87, 95% confidence intervals 0.71-0.94) in the test set, which was greater than that of diameter stenosis (DS) > 53% (66%, AUC = 0.71, 95% confidence intervals 0.65-0.78). The external validation showed 84% accuracy (AUC = 0.89, 95% confidence intervals 0.83-0.95). The retrospective design, single ethnicity, and the lack of clinical outcomes may limit this prediction model's generalized application.

CONCLUSION

We found that angiography-based ML is useful to predict subtended myocardial territories and ischemia-producing lesions by mitigating the visual-functional mismatch between angiographic and FFR. Assessment of clinical utility requires further validation in a large, prospective cohort study.

Diagnostic performance of machine-learning-based computed fractional flow reserve (FFR) derived from coronary computed tomography angiography for the assessment of myocardial ischemia verified by invasive FFR

To explore the diagnostic performance of a machine-learning-based (ML-based) computed fractional flow reserve (cFFR) derived from coronary computed tomography angiography (CCTA) in identifying ischemia-causing lesions verified by invasive FFR in catheter coronary angiography (ICA). We retrospectively studied 117 intermediate coronary artery lesions [40-80% diameter stenosis (DS)] from 105 patients (mean age 62 years, 32 female) who had undergone invasive FFR. CCTA images were used to compute cFFR values on the workstation. DS and the myocardium jeopardy index (MJI) of coronary stenosis were also assessed with CCTA. The diagnostic performance of cFFR was evaluated, including its correlation with invasive FFR and its diagnostic accuracy. Then, its performance was compared to that of combined DS and MJI. Of the 117 lesions, 36 (30.8%) had invasive FFR ≤ 0.80; 22 cFFR were measured as true positives and 74 cFFR as true negatives. The average time of cFFR assessment was 18 ± 7 min. The cFFR correlated strongly to invasive FFR (Spearman's coefficient 0.665, p < 0.01). When diagnosing invasive FFR ≤ 0.80, the accuracy of cFFR was 82% with an AUC of 0.864, which was significantly higher than that of DS (accuracy 75%, AUC 0.777, p = 0.013). The AUC of cFFR was not significantly different from that of combined DS and MJI (0.846, p = 0.743). cFFR ≤ 0.80 based on CCTA showed good diagnostic performance for detecting ischemia-producing lesions verified by invasive FFR. The short calculation time required renders cFFR promising for clinical use.

Meta-analysis and systematic review of intravascular ultrasound versus angiography-guided drug eluting stent implantation in left main coronary disease in 4592 patients

Background

Although several meta-analyses have demonstrated the utility of intravascular ultrasound (IVUS) in guiding drug-eluting stent (DES) implantation compared to angiography-guidance, there has been a dearth of evidence in the left main coronary artery (LMCA) lesion subset.

Methods

We performed a meta-analysis to compare clinical outcomes of IVUS versus conventional angiography guidance during implantation of DES for patients with LMCA disease. Pubmed, Cochrane Library, Embase were searched.

Results

A total of 1002 publications were reviewed; and finally, seven clinical studies - one prospective randomized controlled trial and six observational studies with 4592 patients (1907 IVUS-guided and 2685 angiography-guided) - were included in the meta-analysis. IVUS guidance was associated with a significant reduction in major adverse cardiac events (relative ratio [RR] 95% CI 0.61; 95% confidence interval [CI] 0.53 to 0.70; P < 0.001), all-cause death (RR 0.55; 95% CI 0.42 to 0.71; P < 0.001), cardiac death (RR 0.45; 95% CI 0.32 to 0.62; P < 0.001), myocardial infarction (RR 0.66; 95% CI 0.55 to 0.80; P < 0.001), and stent thrombosis (RR 0.48; 95% CI 0.27 to 0.84; P = 0.01) compared with angiographic guidance. However, there was no significant difference regarding target lesion revascularization (RR 0.60; 95% CI 0.31 to 1.18; P = 0.099) and target vessel revascularization (RR 0.64; 95% CI 0.26 to 1.56; P = 0. 322).

Conclusions

Compared to angiographic guidance, IVUS-guided DES implantation was associated with better clinical outcomes for patients with LMCA lesions, especially hard endpoints of death, myocardial infarction, and stent thrombosis.

Myocardial segmentation based on coronary anatomy using coronary computed tomography angiography: Development and validation in a pig model

OBJECTIVES

To validate a method for performing myocardial segmentation based on coronary anatomy using coronary CT angiography (CCTA).

METHODS

Coronary artery-based myocardial segmentation (CAMS) was developed for use with CCTA. To validate and compare this method with the conventional American Heart Association (AHA) classification, a single coronary occlusion model was prepared and validated using six pigs. The unstained occluded coronary territories of the specimens and corresponding arterial territories from CAMS and AHA segmentations were compared using slice-by-slice matching and 100 virtual myocardial columns.

RESULTS

CAMS more precisely predicted ischaemic area than the AHA method, as indicated by 95% versus 76% (p < 0.001) of the percentage of matched columns (defined as percentage of matched columns of segmentation method divided by number of unstained columns in the specimen). According to the subgroup analyses, CAMS demonstrated a higher percentage of matched columns than the AHA method in the left anterior descending artery (100% vs. 77%; p < 0.001) and mid- (99% vs. 83%; p = 0.046) and apical-level territories of the left ventricle (90% vs. 52%; p = 0.011).

CONCLUSIONS

CAMS is a feasible method for identifying the corresponding myocardial territories of the coronary arteries using CCTA.

KEY POINTS

• CAMS is a feasible method for identifying corresponding coronary territory using CTA • CAMS is more accurate in predicting coronary territory than the AHA method • The AHA method may underestimate the ischaemic territory of LAD stenosis.

A systematic review of imaging anatomy in predicting functional significance of coronary stenoses determined by fractional flow reserve

Fractional flow reserve (FFR) is the current gold standard to assess the physiological significance of coronary stenoses. With the development of coronary imaging techniques, several anatomic parameters have been investigated in vivo and their associations with FFR have been studied. The aim of this review is to summarize the accuracy of anatomic parameters derived by the present coronary imaging techniques including invasive coronary angiography, coronary computed tomography angiography, intravascular ultrasound and optical coherence tomography, in predicting a significant FFR. The impact of patient characteristics, lesion locations, variability of FFR and imaging resolution on the predictive ability are discussed.

Influence of scan technique on intracoronary transluminal attenuation gradient in coronary CT angiography using 128-slice dual source CT: multi-beat versus one-beat scan

The purpose of our study was to investigate the impact of temporal uniformity and adjustment by the contrast opacification enhancement in the aorta on the performance of transluminal attenuation gradient (TAG) for obstructive coronary artery disease. A total of 274 coronary arteries from 94 patients who underwent both multi- and single-beat scan using 128-slice scanner at the same time were enrolled. TAG and corrected coronary opacification (CCO) of both scan technique were compared against obstructive coronary arteries defined by diameter stenosis ≥50%. In per-vessel analysis, both TAG and CCO were slight but significantly different between multi- and single-beat scan in overall (-13.3 vs. -14.3 HU/10 mm; 0.31 vs. 0.38; p < 0.05, all). However, the difference was evident only in right coronary artery (p < 0.05) but not in left coronary arteries (p = NS). Correlation coefficient value are more than 0.8 for all coronary arteries (0.84) and each of the three vessels (RCA: 0.87, LAD: 0.84, LCX: 0.81) in TAG in single-beat versus multi-beat scans (p < 0.0001). Radiation exposure was significantly lower in single-beat scan compared to multi-beat scan (0.9 vs. 3.7 mSv, p < 0.001). TAGs of multi- and single beat scans well correlated each other in all coronary arteries and were not affected by temporal non-uniformity.