Perivascular fat attenuation for predicting adverse cardiac events in stable patients undergoing invasive coronary angiography

BackgroundInflammation surrounding the coronary arteries can be non-invasively assessed using pericoronary adipose tissue attenuation (PCAT). While PCAT holds promise for further risk stratification of patients with low coronary artery disease (CAD) prevalence, its value in higher risk populations remains unknown.MethodsCORE320 enrolled patients referred for invasive coronary angiography with known or suspected CAD. Coronary computed tomography angiography (CCTA) images were collected for 381 patients for whom clinical outcomes were assessed 5 years after enrollment. Using semi-automated image analysis software, PCAT was obtained and normalized for the right coronary (RCA), left anterior descending (LAD), and left circumflex arteries (LCx). The association between PCAT and major adverse cardiovascular events (MACE) during follow up was assessed using Cox regression models.ResultsThirty-seven patients were excluded due to technical failure. For the remaining 344 patients, median age was 62 (interquartile range, 55–68) with 59% having ≥1 coronary artery stenosis of ≥50% by quantitative coronary angiography. Mean attenuation values for PCAT in RCA, LAD, and LCx were ?74.9, ?74.2, and ?71.2, respectively. Hazard ratios and 95% confidence intervals (CI) for normalized PCAT in the RCA, LAD, and LCx for MACE were 0.96 (CI: 0.75–1.22, p ?= ?0.71), 1.31 (95% CI: 0.96–1.78, p ?= ?0.09), and 0.98 (95% CI: 0.78–1.22, p ?= ?0.84), respectively. For death, stroke, or myocardial infarction only, hazard ratios were 0.68 (0.44–1.07), 0.85 (0.56–1.29), and 0.57 (0.41–0.80), respectively.ConclusionsIn patients referred for invasive coronary angiography with suspected CAD, PCAT did not predict MACE during long term follow up. Further studies are needed to understand the relationship of PCAT with CAD risk.     

The effect of patient and imaging characteristics on coronary CT angiography assessed pericoronary adipose tissue attenuation and gradient

BackgroundCoronary CT angiography (CCTA) pericoronary adipose tissue (PCAT) markers are promising indicators of inflammation.ObjectiveTo determine the effect of patient and imaging parameters on the associations between non-calcified plaque (NCP) and PCAT attenuation and gradient.MethodsThis was a single-center, retrospective analysis of consecutive patients with stable chest pain who underwent CCTA and had zero calcium scores. CCTA images were evaluated for the presence of NCP, obstructive stenosis, segment stenosis and involvement score (SSS, SIS), and high-risk plaque (HRP). PCAT markers were assessed using semi-automated software. Uni- and multivariable regression models correcting for patient and imaging characteristics between plaque and PCAT markers were evaluated.ResultsOverall, 1652 patients had zero calcium score (mean age: 51 years ?± ?11 [SD], 871 women); PCAT attenuation values ranged between ?123 HU and ?51 HU, and 649 patients had plaque. In univariable analysis, the presence of NCP, SSS, SIS, and HRP were associated with PCAT attenuation (2, 1, 1, 6 HU; respectively; p ?< ?.001 all); while obstructive stenosis was not (1 HU, p ?= ?.58). In multivariable analysis, none of the plaque markers were associated with PCAT attenuation (0 HU p ?= ?.93, 0 HU p ?= ?.39, 1 HU p ?= ?.18, 2 HU p ?= ?.10, 1 HU p ?= ?.71, respectively), while patient and imaging characteristics showed significant associations, such as: male sex (1 HU, p ?= ?.003), heart rate [1/min] (?0.2 HU, p ?< ?.001), 120 ?kVp (8 HU, p ?< ?.001) and pixel spacing [mm³] (32 HU, p ?< ?.001). Similar results were observed for PCAT gradient.ConclusionPCAT markers were significantly associated with NCP, however the associations did not persist following correction for patient and imaging characteristics.     

Influence of operator expertise and coronary luminal segmentation technique on diagnostic performance,precision and reproducibility of reduced-order CT-derived fractional flow reserve technique

BackgroundOnsite workstation-based CT-derived Fractional-Flow-Reserve (CT-FFR) is accurate in assessing hemodynamic-significance of coronary stenoses. We aim to describe the influence of operator expertise and luminal-segmentation technique on the diagnostic performance, precision and reproducibility of CT-FFR in identifying hemodynamically-significant stenosis (FFR≤0.8).MethodsForty-eight consecutive stable-patients (86 vessels) with suspected CAD underwent research indicated invasive-FFR and 320-detector CT-coronary-angiography (CTA). CT-FFR was derived using reduced-order model on standard desktop-computer. Semi-automated coronary luminal segmentation was performed using focused-technique with manual adjustments at regions of stenosis and calcification or comprehensive-technique with manual adjustments along the entire course of the vessel. CT-FFR analysis was performed using 3 blinded operators; core-laboratory engineer using focused-technique and radiographer and cardiologist using the comprehensive-technique. Diagnostic performance was assessed by area under receiver-operating-curve (AUC). Precision with invasive FFR was determined by Bland-Altman analysis, and reproducibility by intraclass-correlation-coefficient (ICC).ResultsDiagnostic performance was comparable among operators (Engineer: AUC = 0.88, Radiographer 0.84; Cardiologist 0.87; P = 0.59). Coronary luminal-segmentation time was shortest using focused technique (engineer 6:17 ± 2.43 min), compared with comprehensive technique (cardiologist 14.83 ± 7.09, radiographer 24.74 ± 12.65; P < 0.001). Use of focused technique was associated with widest limits of agreement (LOA) with FFR and moderate intra-operator reproducibility (engineer LOA -0.20-0.33; ICC 0.66), when compared with the comprehensive technique which demonstrated narrower LOA and excellent reproducibility [radiographer (LOA -0.17-0.20, ICC = 0.91) and cardiologist (LOA-0.15-0.23, ICC = −0.93)]ConclusionA workstation-based CT-FFR technique was reproducible with high and comparable diagnostic performance among operators with different expertise. A comprehensive luminal segmentation technique was the most time-consuming and associated with the highest reproducibility and precision with FFR.     

Influence of coronary stenosis location on diagnostic performance of machine learning-based fractional flow reserve from CT angiography

BackgroundCompared with invasive fractional flow reserve (FFR), coronary CT angiography (cCTA) is limited in detecting hemodynamically relevant lesions. cCTA-based FFR (CT-FFR) is an approach to overcome this insufficiency by use of computational fluid dynamics. Applying recent innovations in computer science, a machine learning (ML) method for CT-FFR derivation was introduced and showed improved diagnostic performance compared to cCTA alone. We sought to investigate the influence of stenosis location in the coronary artery system on the performance of ML-CT-FFR in a large, multicenter cohort.MethodsThree hundred and thirty patients (75.2% male, median age 63 years) with 502 coronary artery stenoses were included in this substudy of the MACHINE (Machine Learning Based CT Angiography Derived FFR: A Multi-Center Registry) registry. Correlation of ML-CT-FFR with the invasive reference standard FFR was assessed and pooled diagnostic performance of ML-CT-FFR and cCTA was determined separately for the following stenosis locations: RCA, LAD, LCX, proximal, middle, and distal vessel segments.ResultsML-CT-FFR correlated well with invasive FFR across the different stenosis locations. Per-lesion analysis revealed improved diagnostic accuracy of ML-CT-FFR compared with conventional cCTA for stenoses in the RCA (71.8% [95% confidence interval, 63.0%–79.5%] vs. 54.8% [45.7%–63.8%]), LAD (79.3 [73.9–84.0] vs. 59.6 [53.5–65.6]), LCX (84.1 [76.0–90.3] vs. 63.7 [54.1–72.6]), proximal (81.5 [74.6–87.1] vs. 63.8 [55.9–71.2]), middle (81.2 [75.7–85.9] vs. 59.4 [53.0–65.6]) and distal stenosis location (67.4 [57.0–76.6] vs. 51.6 [41.1–62.0]).ConclusionIn a multicenter cohort with high disease prevalence, ML-CT-FFR offered improved diagnostic performance over cCTA for detecting hemodynamically relevant stenoses regardless of their location.     

Higher coronary artery calcium score is associated with increased risk of atrial fibrillation recurrence after catheter ablation

BackgroundCoronary artery calcium score (CACS) is associated with an increased risk of atrial fibrillation (AF) development, but scarce data are available regarding the impact on AF recurrence. This study aims to assess the impact of CACS on AF recurrence following catheter ablation.MethodsRetrospective study of patients with AF undergoing cardiac computed tomography (CCT) before ablation (2017–2019). Patients with coronary artery disease (CAD), significant valvular heart disease and previous catheter ablation were excluded. A cut-off of CACS ≥ 100 was used according to literature.ResultsA total of 311 patients were included (median age 57 [48, 64] years, 65% men and 21% with persistent AF). More than half of the patients had a CACS > 0 (52%) and 18% a CACS ≥ 100. Patients with CACS ≥ 100 were older (64 [59, 69] vs 55 [46, 63] years, p ?< ?0.001), had more frequently hypertension (68% vs 42%, p ?< ?0.001) and diabetes mellitus (21% vs 10%, p ?= ?0.020). During a median follow-up of 34 months (12–57 months), 98 patients (32%) had AF recurrence. CACS ≥ 100 was associated with increased risk of AF recurrence (unadjusted Cox regression: hazard ratio [HR] 2.0; 95% confidence interval [CI], 1.3–3.1, p ?= ?0.002). After covariate adjustment, CACS ≥ 100 and persistent AF remained independent predictors of AF recurrence (HR, 1.7; 95% CI, 1.0–2.8, p ?= ?0.039 and HR, 2.0; 95% CI, 1.3–3.2, p ?= ?0.004, respectively).ConclusionAn opportunistic evaluation of CACS could be an important tool to improve clinical care considering that CACS ≥ 100 was independently associated with a 69% increase in the risk of AF recurrence after first catheter ablation.     

Are risk factors necessary for pretest probability assessment of coronary artery disease? A patient similarity network analysis of the PROMISE trial

BackgroundPretest probability (PTP) calculators utilize epidemiological-level findings to provide patient-level risk assessment of obstructive coronary artery disease (CAD). However, their limited accuracies question whether dissimilarities in risk factors necessarily result in differences in CAD. Using patient similarity network (PSN) analyses, we wished to assess the accuracy of risk factors and imaging markers to identify ≥50% luminal narrowing on coronary CT angiography (CCTA) in stable chest-pain patients.MethodsWe created four PSNs representing: patient characteristics, risk factors, non-coronary imaging markers and calcium score. We used spectral clustering to group individuals with similar risk profiles. We compared PSNs to a contemporary PTP score incorporating calcium score and risk factors to identify ≥50% luminal narrowing on CCTA in the CT-arm of the PROMISE trial. We also conducted subanalyses in different age and sex groups.ResultsIn 3556 individuals, the calcium score PSN significantly outperformed patient characteristic, risk factor, and non-coronary imaging marker PSNs (AUC: 0.81 vs. 0.57, 0.55, 0.54; respectively, p ?< ?0.001 for all). The calcium score PSN significantly outperformed the contemporary PTP score (AUC: 0.81 vs. 0.78, p ?< ?0.001), and using 0, 1–100 and ?> ?100 cut-offs provided comparable results (AUC: 0.81 vs. 0.81, p ?= ?0.06). Similar results were found in all subanalyses.ConclusionCalcium score on its own provides better individualized obstructive CAD prediction than contemporary PTP scores incorporating calcium score and risk factors. Risk factors may not be able to improve the diagnostic accuracy of calcium score to predict ≥50% luminal narrowing on CCTA.     

Accuracy of ultra-high–resolution computed tomography with a 0.3-mm detector for quantitative assessment of coronary artery stenosis grading in comparison with conventional computed tomography: A phantom study

BackgroundThe development of ultra-high–resolution CT (U-HRCT) is expected to improve the accuracy of coronary stenosis evaluation. This study aimed to evaluate the accuracy of the stenosis severities of coronary artery phantoms estimated using U-HRCT by comparing them to those estimated with conventional CT.MethodsCoronary artery phantoms with non-calcified and calcified lesions were scanned with conventional CT (64-row ?× ?0.625 ?mm) and U-HRCT (32-row ?× ?0.3125 ?mm). The coronary artery phantoms had lumen diameters of 2.0, 3.0, and 4.0 ?mm with non-calcified lesions representing 0%, 25%, 50%, and 75% stenosis and 3.0 and 4.0 ?mm with calcified lesions representing 0%, 25%, 50%, and 75% stenosis. The lumen diameters at the stenotic and non-stenotic regions were measured, and the stenosis severities were compared with the true values.ResultsFor non-calcified lesions, conventional CT significantly underestimated the stenosis severity in the phantom showing 75% stenosis with lumen diameters of 2.0 and 3.0 ?mm (p ?< ?0.05), while the estimated stenosis severities were not significantly different from the true values at all settings with U-HRCT. For the calcified lesions, conventional CT overestimated the stenosis severities at all settings (p ?< ?0.05), while U-HRCT yielded estimations closer to the true values, although still with some overestimation (p ?< ?0.05).ConclusionBy using U-HRCT, the estimated stenosis severities of the coronary artery with non-calcified lesion become almost equal to the true value, while those with calcified lesion are still overestimated although they become closer to the true value.     

CT multivessel aggregate stenosis score: A novel point-of-care tool for predicting major adverse cardiac events

BackgroundWe evaluated the utility of a novel 15-point multivessel aggregate stenosis (MVAS) score for predicting major adverse cardiac events (MACE) in low-risk patients with suspected ischaemic symptoms undergoing CTCA. Prognostic performance was compared with the Coronary Artery Disease Reporting and Data System (CAD-RADS) classification and the 16-point Segment Involvement Score (SIS).Methods772 consecutive patients underwent CTCA and coronary artery calcification scoring (CACS) from 2010 to 2015. Coronary artery disease severity was calculated according to CAD-RADS class (0–5 ?± ?vulnerability modifier), the SIS (0–16), and an MVAS score (0–15) based on the aggregate stenosis severity in all 4 coronary vessels (maximum 12 points) plus the presence of any high-risk plaque features (additional 3 points). 52 patients were referred directly for coronary angiography based on CTCA findings and were excluded; the remainder were followed-up for 64.6 ?± ?19.1 months.Results54 ?MACE were observed in 720 patients (7.5%); MACE patients had higher CAD-RADS class (3.92 ?± ?0.7 vs 0.91 ?± ?1.2, p ?< ?0.0001), SIS (4.59 ?± ?2.7 vs 0.79 ?± ?1.2, p ?< ?0.0001), and MVAS scores (10.1 ?± ?1.7 vs 1.7 ?± ?2.1, p ?< ?0.0001). Adjusted Cox proportional hazards analysis identified CAD-RADS class (HR 2.96 (2.2–4), p ?< ?0.0001), SIS (HR 1.29 (1.2–1.4, p ?< ?0.0001), and MVAS score (HR 1.82 (1.6–2.1), p ?< ?0.0001) as predictors of MACE. Adjusted receiver operating characteristic (ROC) analysis found MVAS a more powerful predictor of MACE than CAD-RADS and SIS (AUC: 0.92 vs 0.84 vs 0.83, p ?= ?0.018).ConclusionsCAD-RADS and SIS are reliable predictors of MACE, and the MVAS score provided incremental prognostic data. MVAS may potentiate risk stratification, particularly in institutions without advanced plaque analysis software.     

Increased coronary pericoronary adipose tissue attenuation in diabetic patients compared to non-diabetic controls: A propensity score matching analysis

BackgroundPericoronary adipose tissue (PCAT) attenuation is an indicator of active inflammation of perivascular adipose tissue, which is supposed to increase in diabetic patients. We aimed to investigate the PCAT attenuation values and high-risk plaque (HRP) features in diabetic and non-diabetic subjects with different stenotic extents.MethodsConsecutive type 2 diabetes patients and non-diabetic patients with chest pain and intermediate pre-test probability of coronary artery disease (CAD) were prospectively enrolled and underwent coronary computed tomography angiography (CCTA). At per-patient level, PCAT attenuation values of three major epicardial coronary vessels, as well as HRP features were measured. PCAT attenuation values and HRP features were compared between diabetic and non-diabetic subjects according to the presence or absence of obstructive stenosis.Results1700 patients (mean age: 65.5 ?± ?11.7, 940 males) were divided into two groups according to presence of obstructive stenosis on CCTA. Propensity score matching was performed in further analysis. RCA_PCAT was significantly higher in diabetic subjects than that in non-diabetic subjects, regardless of the presence of obstructive stenosis (?83.60 ?± ?9.51 HU vs. ?88.58 ?± ?9.37 HU, p ?< ?0.001) or absence of obstructive stenosis (?83.70 ?± ?10.32 HU vs. ?88.76 ?± ?8.28 HU, p ?< ?0.001). In contrast, HRP features were more commonly presented in diabetic patients with obstructive stenosis than in those without obstructive stenosis. According to subgroup analysis based on acquisition tube voltage, RCA_PCAT was the only parameter showing consistent difference between diabetic and non-diabetic patients.ConclusionsRCA_PCAT was significantly higher in diabetic patients than that in non-diabetic patients regardless of stenotic severity and plaque vulnerability.     

Predictive value of the coronary artery calcium score and advanced plaque characteristics: Post hoc analysis of the PREDICT registry

BackgroundWhether coronary plaque characteristics assessed in coronary computed tomography angiography (CCTA) in association with the coronary artery calcium score (CACS) have predictive value for coronary events is unclear. We aimed to examine the predictive value of the CACS and plaque characteristics for the occurrence of coronary events.MethodsAmong 2802 patients who were analyzed in the PREDICT registry, 2083 with suspected coronary artery disease (CAD) were studied using post hoc analysis. High-risk plaques were defined as having ≥2 adverse characteristics, such as low computed tomographic attenuation, positive remodeling, spotty calcification, and napkin-ring sign. An adjudicative composite of coronary events (cardiac death, nonfatal acute coronary syndrome, and coronary revascularization ≥3 months after indexed CCTA) were analyzed.ResultsSeventy-three (3.5%) patients had coronary events and 313 (15.0%) had high-risk plaques. Multivariate Cox proportional hazard analysis showed that high-risk plaques remained an independent predictor of coronary events (adjusted hazard ratio [HR] 1.95, 95% confidence interval [CI] 1.13–3.34, P ?= ?0.0154), as well as the log-transformed CACS (adjusted HR 1.24, 95% CI 1.11–1.39, P ?= ?0.0002) and the presence of obstructive stenosis (adjusted HR 5.63, 95% CI 3.22–10.12, P 0.0001). In subgroup analyses, high-risk plaques were independently predictive only in the low CACS class (<100).ConclusionThis study shows that assessment of adverse features by coronary plaque imaging independently predicts coronary events in patients with suspected CAD and a low CACS. Our findings suggest that the clinical value of high-risk plaques to CACS and stenosis assessment appears marginal.     

CT assessment of the left atrial appendage post-transcatheter occlusion – A systematic review and meta analysis

BackgroundTransesophageal echocardiography (TEE) is the standard imaging modality used to assess the left atrial appendage (LAA) after transcatheter device occlusion. Cardiac computed tomography angiography (CCTA) offers an alternative non-invasive modality in these patients. We aimed to conduct a comparison of the two modalities.MethodsWe performed a comprehensive systematic review of the current literature pertaining to CCTA to establish its usefulness during follow-up for patients undergoing LAA device closure. Studies that reported the prevalence of inadequate LAA closure on both CCTA and TEE were further evaluated in a meta-analysis. 19 studies were used in the systematic review, and six studies were used in the meta-analysis.ResultsThe use of CCTA was associated with a higher likelihood of detecting LAA patency than the use of TEE (OR, 2.79, 95% CI 1.34–5.80, p ?= ?0.006, I² ?= ?70.4%). There was no significant difference in the prevalence of peridevice gap ≥5 ?mm (OR, 3.04, 95% CI 0.70–13.17, p ?= ?0.13, I² ?= ?0%) between the two modalities. Studies that reported LAA assessment in early and delayed phase techniques detected a 25%–50% higher prevalence of LAA patency on the delayed imaging.ConclusionCCTA can be used as an alternative to TEE for LAA assessment post occlusion. Standardized CCTA acquisition and interpretation protocols should be developed for clinical practice.     

Diagnostic concordance and discordance between angiography-based quantitative flow ratio and fractional flow reserve derived from computed tomography in complex coronary artery disease

BackgroundBoth quantitative flow ratio (QFR) and fractional flow reserve derived from computed tomography (FFR_CT) have shown significant correlations with invasive wire-based fractional flow reserve. However, the correlation between QFR and FFR_CT is not fully investigated in patients with complex coronary artery disease (CAD). The aim of this study is to investigate the correlation and agreement between QFR and FFR_CT in patients with de novo three-vessel disease and/or left main CAD.MethodsThis is a post-hoc sub-analysis of the international, multicenter, and randomized SYNTAX III REVOLUTION trial, in which both invasive coronary angiography and coronary computed tomography angiography were prospectively obtained prior to the heart team discussion. QFR was performed in an independent core laboratory and compared with FFR_CT analyzed by HeartFlow?. The correlation and agreement between QFR and FFR_CT were assessed per vessel. Furthermore, independent factors of diagnostic discordance between QFR and FFR_CT were evaluated.ResultsOut of 223 patients, 40 patients were excluded from this analysis due to the unavailability of FFR_CT and/or QFR, and a total of 469 vessels (183 patients) were analyzed. There was a strong correlation between QFR and FFR_CT (R ?= ?0.759; p ?< ?0.001), and the Bland-Altman analysis demonstrated a mean difference of ?0.005 and a standard deviation of 0.116. An independent predictor of diagnostic concordance between QFR and FFR_CT was the lesion location in right coronary artery (RCA) (odds ratio 0.395; 95% confidence interval 0.174–0.894; P ?= ?0.026).ConclusionIn patients with complex CAD, QFR and FFR_CT were strongly correlated. The location of the lesion in RCA was associated with the highest diagnostic concordance between QFR and FFR_CT.     

Mortality impact of low CAC density predominantly occurs in early atherosclerosis: explainable ML in the CAC consortium

BackgroundMachine learning (ML) models of risk prediction with coronary artery calcium (CAC) and CAC characteristics exhibit high performance, but are not inherently interpretable.ObjectivesTo determine the direction and magnitude of impact of CAC characteristics on 10-year all-cause mortality (ACM) with explainable ML.MethodsWe analyzed asymptomatic subjects in the CAC consortium. We trained ML models on 80% and tested on 20% of the data with XGBoost, using clinical characteristics ?+ ?CAC (ML 1) and additional CAC characteristics of CAC density and number of calcified vessels (ML 2). We applied SHAP, an explainable ML tool, to explore the relationship of CAC and CAC characteristics with 10-year all-cause and CV mortality.Results2376 deaths occurred among 63,215 patients [68% male, median age 54 (IQR 47–61), CAC 3 (IQR 0–94.3)]. ML2 was similar to ML1 to predict all-cause mortality (Area Under the Curve (AUC) 0.819 vs 0.821, p ?= ?0.23), but superior for CV mortality (0.847 vs 0.845, p ?= ?0.03).Low CAC density increased mortality impact, particularly ≤0.75. Very low CAC density ≤0.75 was present in only 4.3% of the patients with measurable density, and 75% occurred in CAC1-100. The number of diseased vessels did not increase mortality overall when simultaneously accounting for CAC and CAC density.ConclusionCAC density contributes to mortality risk primarily when it is very low ≤0.75, which is primarily observed in CAC 1–100. CAC and CAC density are more important for mortality prediction than the number of diseased vessels, and improve prediction of CV but not all-cause mortality. Explainable ML techniques are useful to describe granular relationships in otherwise opaque prediction models.     

Impact of membranous septum length on pacemaker need with different transcatheter aortic valve replacement systems: The INTERSECT registry

BackgroundNew permanent pacemaker implantation (new-PPI) remains a compelling issue after Transcatheter Aortic Valve Replacement (TAVR). Previous studies reported the relationship between a short MS length and the new-PPI post-TAVR with a self-expanding THV. However, this relationship has not been investigated in different currently available THV. Therefore, the aim of this study was to investigate the association between membranous septum (MS)-length and new-PPI after TAVR with different Transcatheter Heart Valve (THV)-platforms.MethodsWe included patients with a successful TAVR-procedure and an analyzable pre-procedural multi-slice computed tomography. MS-length was measured using a standardized methodology. The primary endpoint was the need for new-PPI within 30 days after TAVR.ResultsIn total, 1811 patients were enrolled (median age 81.9 years [IQR 77.2–85.4], 54% male). PPI was required in 275 patients (15.2%) and included respectively 14.2%, 20.7% and 6.3% for Sapien3, Evolut and ACURATE-THV(p ?< ?0.01).Median MS-length was significantly shorter in patients with a new-PPI (3.7 ?mm [IQR 2.2–5.1] vs. 4.1 ?mm [IQR 2.8–6.0], p ?= ?<0.01). Shorter MS-length was a predictor for PPI in patients receiving a Sapien3 (OR 0.87 [95% CI 0.79–0.96], p ?= ?<0.01) and an Evolut-THV (OR 0.91 [95% CI 0.84–0.98], p ?= ?0.03), but not for an ACURATE-THV (OR 0.99 [95% CI 0.79–1.21], p ?= ?0.91). By multivariable analysis, first-degree atrioventricular-block (OR 2.01 [95% CI 1.35–3.00], p = <0.01), right bundle branch block (OR 8.33 [95% CI 5.21–13.33], p = <0.01), short MS-length (OR 0.89 [95% CI 0.83–0.97], p ?< ?0.01), annulus area (OR 1.003 [95% CI 1.001–1.005], p ?= ?0.04), NCC implantation depth (OR 1.13 [95% CI 1.07–1.19] and use of Evolut-THV(OR 1.54 [95% CI 1.03–2.27], p ?= ?0.04) were associated with new-PPI.ConclusionMS length was an independent predictor for PPI across different THV platforms, except for the ACURATE-THV. Based on our study observations within the total cohort, we identified 3 risk groups by MS length: MS length ≤3 ?mm defined a high-risk group for PPI (>20%), MS length 3–7 ?mm intermediate risk for PPI (10–20%) and MS length > 7 ?mm defined a low risk for PPI (<10%). Anatomy-tailored-THV-selection may mitigate the need for new-PPI in patients undergoing TAVR.     

Deep learning with convolutional neural network for estimation of the characterisation of coronary plaques: Validation using IB-IVUS

IntroductionDeep learning approaches have shown high diagnostic performance in image classifications, such as differentiation of malignant tumors and calcified coronary plaque. However, it is unknown whether deep learning is useful for characterizing coronary plaques without the presence of calcification using coronary computed tomography angiography (CCTA). The purpose of this study was to compare the diagnostic performance of deep learning with a convolutional neural network (CNN) with that of radiologists in the estimation of coronary plaques.MethodsWe retrospectively enrolled 178 patients (191 coronary plaques) who had undergone CCTA and integrated backscatter intravascular ultrasonography (IB-IVUS) studies. IB-IVUS diagnosed 81 fibrous and 110 fatty or fibro-fatty plaques. We manually captured vascular short-axis images of the coronary plaques as Portable Network Graphics (PNG) images (150 × 150 pixels). The display window level and width were 100 and 700 Hounsfield units (HU), respectively. The deep-learning system (CNN; GoogleNet Inception v3) was trained on 153 plaques; its performance was tested on 38 plaques. The area under the curve (AUC) obtained by receiver operating characteristic analysis of the deep learning system and by two board-certified radiologists was compared.ResultsWith the CNN, the AUC and the 95% confidence interval were 0.83 and 0.69–0.96, respectively; for radiologist 1 they were 0.61 and 0.42–0.80; for radiologist 2 they were 0.68 and 0.51–0.86, respectively. The AUC for CNN was significantly higher than for radiologists 1 (p = 0.04); for radiologist 2 it was not significantly different (p = 0.22).ConclusionDL-CNN performed comparably to radiologists for discrimination between fatty and fibro-fatty plaque on CCTA images.Implications for practiceThe diagnostic performance of the CNN and of two radiologists in the assessment of 191 ROIs on CT images of coronary plaques whose type corresponded with their IB-IVUS characterization was comparable.     

Repeatability of quantitative pericoronary adipose tissue attenuation and coronary plaque burden from coronary CT angiography

BackgroundHigh pericoronary adipose tissue (PCAT) attenuation and non-calcified plaque burden (NCP) measured from coronary CT angiography (CTA) have been implicated in future cardiac events. We aimed to evaluate the interobserver and intraobserver repeatability of PCAT attenuation and NCP burden measurement from CTA, in a sub-study of the prospective SCOT-HEART trial.MethodsFifty consecutive CTAs from participants of the CT arm of the prospective SCOT-HEART trial were included. Two experienced observers independently measured PCAT attenuation and plaque characteristics throughout the whole coronary tree from CTA using semi-automatic quantitative software.ResultsWe analyzed proximal segments in 157 vessels. Intraobserver mean differences in PCAT attenuation and NCP plaque burden were ?0.05HU and 0.92% with limits of agreement (LOA) of ±1.54 and ± 5.97%. Intraobserver intraclass correlation coefficients (ICC) for PCAT attenuation and NCP burden were excellent (0.999 and 0.978). Interobserver mean differences in PCAT attenuation and NCP plaque burden were 0.13HU [LOA ±1.67HU] and ?0.23% (LOA ±9.61%). Interobserver ICC values for PCAT attenuation and NCP burden were excellent (0.998 and 0.944).ConclusionPCAT attenuation and NCP burden on CTA has high intraobserver and interobserver repeatability, suggesting they represent a repeatable and robust method of quantifying cardiovascular risk.     

Coronary CTA enhanced with CTA based FFR analysis provides higher diagnostic value than invasive coronary angiography in patients with intermediate coronary stenosis

BackgroundCTA based FFR, a software based application, enhances diagnostic value of coronary computed tomography angiography (CTA) examination. However it remains unknown whether it improves accuracy over the gold standard of invasive coronary angiography (ICA) in predicting functionally significant coronary stenosis. The aim of our study was to compare diagnostic accuracies of coronary CTA, CTA based FFR, and ICA, with invasive FFR as the reference standard in patients with intermediate stenosis on CTA.Methods96 intermediate stenoses (50–90%) from 90 subjects, with intermediate pre-test probability of CAD, who underwent coronary CTA were analyzed. Each patient had subsequent ICA with FFR. CTA based FFR (cFFR v2.1, Siemens) analysis was performed on-site. The stenoses with invasive FFR≤0.8 were considered hemodynamically significant.Results41/96 stenoses were hemodynamically significant (FFR≤0.8). While the area under ROC curves (AUC) for identification of significant stenosis evaluated on QCA (0.653), visual ICA (0.652), qCTA (0.690) and visual CTA (0.660) did not significantly differ, the AUC for CTA based FFR (0.835) was significantly higher (p = 0.004, p = 0.004, p = 0.010, p = 0.007, respectively). The accuracies of CTA based FFR, qCTA and QCA were 76%, 63% and 58% respectively.ConclusionOur results suggest that diagnostic potential of routine coronary CTA, augmented with CTA based FFR analysis, is superior to ICA in patients with intermediate stenosis.     

Right ventricular dysfunction by computed tomography associates with outcomes in severe aortic stenosis patients undergoing transcatheter aortic valve replacement

BackgroundAlthough cardiac computed tomography angiography (CCTA) assessment of right ventricular dysfunction (RVD) is feasible, the incremental prognostic value remains uncertain in patients undergoing transcatheter aortic valve replacement (TAVR) evaluation. This study sought to determine the incremental clinical utility of RVD identification by CCTA while accounting for clinical and echocardiographic parameters.MethodsPatients who underwent multiphasic ECG-gated functional CCTA using dual-source system for routine TAVR planning were evaluated. Biphasic contrast protocol injection allowed for biventricular contrast enhancement. CCTA-based RVD was defined as right ventricular ejection fraction (RVEF) ?< ?50%. The association of CCTA-RVD with all-cause mortality and the composite outcome of death or heart failure hospitalization after TAVR was evaluated and examined for its incremental utility beyond clinical risk assessment and echocardiographic parameters.ResultsA total of 502 patients were included (median [IQR] age, 82 [77 to 87] years; 56% men) with a median follow-up of 22 [16 to 32] months. Importantly, 126 (25%) patients were identified as having RVD by CCTA that was not identified by echocardiography. CCTA-defined RVD predicted death and the composite outcome in both univariate analyses (HR for mortality, 2.15; 95% CI, 1.44–3.22; p ?< ?0.001; HR for composite outcome, 2.11; 95% CI, 1.48–3.01; p ?< ?0.001) and in multivariate models that included clinical risk factors and echocardiographic findings (HR for mortality, 1.74; 95% CI, 1.11–2.74; p ?= ?0.02; HR for composite outcome, 1.63; 95% CI, 1.09–2.44; p ?= ?0.02).ConclusionsFunctional CCTA assessment pre-TAVR correctly identified 25% of patients with RVD that was not evident on 2D echocardiography. The presence of RVD on CCTA independently associates with clinical outcomes post-TAVR.     

Accuracy of RESOLVE score derived from coronary computed tomography versus visual angiography to predict side branch occlusion in percutaneous bifurcation intervention

IntroductionVisually estimated angiographic V-RESOLVE score was developed as a simple and accurate prediction tool for side branch (SB) occlusion in patients undergoing coronary bifurcation intervention. Data on the use of coronary computed tomography angiography (coronary CTA) for guiding percutaneous coronary intervention in bifurcation lesions is scarce.ObjectivesWe aimed to validate the ability of quantitative CTA-derived RESOLVE score for predicting SB occlusion in coronary bifurcation intervention and to compare its predictive value with that of the angiography-based V-RESOLVE score.MethodsWe included 363 patients with 400 bifurcation lesions. Angiographic V-RESOLVE score and CTA-derived RESOLVE score were calculated utilizing the weights from the QCA-based RESOLVE score. The scoring systems were divided into quartiles, and classified as the non-high-risk group and the high-risk group. Accuracy was assessed using areas under the receiver-operator characteristic curve (AUC). SB occlusion was defined as any decrease in Thrombolysis in Myocardial Infarction flow grade (including the absence of flow) in the SB after main vessel stenting.ResultsIn total, 28 SB occlusions (7%) occurred. CTA-derived RESOLVE and V-RESOLVE scores achieved comparable predictive accuracy (0.709 vs. 0.752, respectively, p = 0.531) for predicting SB occlusion, and the analysis of AUC for each constituent element of the scores did not show any significant difference between CTA and visual angiography. The total net reclassification index was −18.6% (p = 0.194), and there were no significant differences in the rates of SB occlusion in the non-high-risk group (4.9% vs. 3.8%, p = 0.510) and the high-risk group (13.8% vs. 18.6%, p = 0.384) between CTA-derived RESOLVE and V-RESOLVE scores.ConclusionsThe quantitative CTA-derived RESOLVE score is an accurate and reliable alternative to the visually estimated angiographic V-RESOLVE score for prediction of SB occlusion in coronary bifurcation intervention.Clinical trial registrationURL: https://www.clinicaltrials.gov. Unique identifier: NCT03709836.     

Validation of deep-learning image reconstruction for coronary computed tomography angiography: Impact on noise,image quality and diagnostic accuracy

BackgroundAdvances in image reconstruction are necessary to decrease radiation exposure from coronary CT angiography (CCTA) further, but iterative reconstruction has been shown to degrade image quality at high levels. Deep-learning image reconstruction (DLIR) offers unique opportunities to overcome these limitations. The present study compared the impact of DLIR and adaptive statistical iterative reconstruction-Veo (ASiR-V) on quantitative and qualitative image parameters and the diagnostic accuracy of CCTA using invasive coronary angiography (ICA) as the standard of reference.MethodsThis retrospective study includes 43 patients who underwent clinically indicated CCTA and ICA. Datasets were reconstructed with ASiR-V 70% (using standard [SD] and high-definition [HD] kernels) and with DLIR at different levels (i.e., medium [M] and high [H]). Image noise, image quality, and coronary luminal narrowing were evaluated by three blinded readers. Diagnostic accuracy was compared against ICA.ResultsNoise did not significantly differ between ASiR-V SD and DLIR-M (37 vs. 37 HU, p = 1.000), but was significantly lower in DLIR-H (30 HU, p < 0.001) and higher in ASiR-V HD (53 HU, p < 0.001). Image quality was higher for DLIR-M and DLIR-H (3.4–3.8 and 4.2–4.6) compared to ASiR-V SD and HD (2.1–2.7 and 1.8–2.2; p < 0.001), with DLIR-H yielding the highest image quality. Consistently across readers, no significant differences in sensitivity (88% vs. 92%; p = 0.453), specificity (73% vs. 73%; p = 0.583) and diagnostic accuracy (80% vs. 82%; p = 0.366) were found between ASiR-V HD and DLIR-H.ConclusionDLIR significantly reduces noise in CCTA compared to ASiR-V, while yielding superior image quality at equal diagnostic accuracy.