Quantitative flow ratio versus fractional flow reserve for Heart Team decision-making in multivessel disease: the randomised, multicentre DECISION QFR trial.

BACKGROUND: Vessel-level physiological data derived from pressure wire measurements are one of the important determinant factors in the optimal revascularisation strategy for patients with multivessel disease (MVD). However, these may result in complications and a prolonged procedure time. AIMS: The feasibility of using the quantitative flow ratio (QFR), an angiography-derived fractional flow reserve (FFR), in Heart Team discussions to determine the optimal revascularisation strategy for patients with MVD was investigated. METHODS: Two Heart Teams were randomly assigned either QFR- or FFR-based data of the included patients. They then discussed the optimal revascularisation mode (percutaneous coronary intervention [PCI] or coronary artery bypass grafting [CABG]) for each patient and made treatment recommendations. The primary endpoint of the trial was the level of agreement between the treatment recommendations of both teams as assessed using Cohen's kappa. RESULTS: The trial included 248 patients with MVD from 10 study sites. Cohen's kappa in the recommended revascularisation modes between the QFR and FFR approaches was 0.73 [95% confidence interval {CI} : 0.62-0.83]. As for the revascularisation planning, agreements in the target vessels for PCI and CABG were substantial for both revascularisation modes (Cohen's kappa=0.72 [95% CI: 0.66-0.78] and 0.72 [95% CI: 0.66-0.78], respectively). The team assigned to the QFR approach provided consistent recommended revascularisation modes even after being made aware of the FFR data (Cohen's kappa=0.95 [95% CI:0.90-1.00]). CONCLUSIONS: QFR provided feasible physiological data in Heart Team discussions to determine the optimal revascularisation strategy for MVD. The QFR and FFR approaches agreed substantially in terms of treatment recommendations.

Efficacy of human experts and an automated segmentation algorithm in quantifying disease pathology in coronary computed tomography angiography: A head-to-head comparison with intravascular ultrasound imaging.

BACKGROUND: Coronary computed tomography angiography (CCTA) analysis is currently performed by experts and is a laborious process. Fully automated edge-detection methods have been developed to expedite CCTA segmentation however their use is limited as there are concerns about their accuracy. This study aims to compare the performance of an automated CCTA analysis software and the experts using near-infrared spectroscopy-intravascular ultrasound imaging (NIRS-IVUS) as a reference standard. METHODS: Fifty-one participants (150 vessels) with chronic coronary syndrome who underwent CCTA and 3-vessel NIRS-IVUS were included. CCTA analysis was performed by an expert and an automated edge detection method and their estimations were compared to NIRS-IVUS at a segment-, lesion-, and frame-level. RESULTS: Segment-level analysis demonstrated a similar performance of the two CCTA analyses (conventional and automatic) with large biases and limits of agreement compared to NIRS-IVUS estimations for the total atheroma (ICC: 0.55 vs 0.25, mean difference:192 (-102-487) vs 243 (-132-617) and percent atheroma volume (ICC: 0.30 vs 0.12, mean difference: 12.8 (-5.91-31.6) vs 20.0 (0.79-39.2). Lesion-level analysis showed that the experts were able to detect more accurately lesions than the automated method (68.2 â€‹% and 60.7 â€‹%) however both analyses had poor reliability in assessing the minimal lumen area (ICC 0.44 vs 0.36) and the maximum plaque burden (ICC 0.33 vs 0.33) when NIRS-IVUS was used as the reference standard. CONCLUSIONS: Conventional and automated CCTA analyses had similar performance in assessing coronary artery pathology using NIRS-IVUS as a reference standard. Therefore, automated segmentation can be used to expedite CCTA analysis and enhance its applications in clinical practice.

Novel near-infrared spectroscopy-intravascular ultrasound-based deep-learning methodology for accurate coronary computed tomography plaque quantification and characterization.

Aims: Coronary computed tomography angiography (CCTA) is inferior to intravascular imaging in detecting plaque morphology and quantifying plaque burden. We aim to, for the first time, train a deep-learning (DL) methodology for accurate plaque quantification and characterization in CCTA using near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS). Methods and results: Seventy patients were prospectively recruited who underwent CCTA and NIRS-IVUS imaging. Corresponding cross sections were matched using an in-house developed software, and the estimations of NIRS-IVUS for the lumen, vessel wall borders, and plaque composition were used to train a convolutional neural network in 138 vessels. The performance was evaluated in 48 vessels and compared against the estimations of NIRS-IVUS and the conventional CCTA expert analysis. Sixty-four patients (186 vessels, 22 012 matched cross sections) were included. Deep-learning methodology provided estimations that were closer to NIRS-IVUS compared with the conventional approach for the total atheroma volume (ΔDL-NIRS-IVUS: -37.8 ± 89.0 vs. ΔConv-NIRS-IVUS: 243.3 ± 183.7 mm3, variance ratio: 4.262, P < 0.001) and percentage atheroma volume (-3.34 ± 5.77 vs. 17.20 ± 7.20%, variance ratio: 1.578, P < 0.001). The DL methodology detected lesions more accurately than the conventional approach (Area under the curve (AUC): 0.77 vs. 0.67, P < 0.001) and quantified minimum lumen area (ΔDL-NIRS-IVUS: -0.35 ± 1.81 vs. ΔConv-NIRS-IVUS: 1.37 ± 2.32 mm2, variance ratio: 1.634, P < 0.001), maximum plaque burden (4.33 ± 11.83% vs. 5.77 ± 16.58%, variance ratio: 2.071, P = 0.004), and calcific burden (-51.2 ± 115.1 vs. -54.3 ± 144.4, variance ratio: 2.308, P < 0.001) more accurately than conventional approach. The DL methodology was able to segment a vessel on CCTA in 0.3 s. Conclusions: The DL methodology developed for CCTA analysis from co-registered NIRS-IVUS and CCTA data enables rapid and accurate assessment of lesion morphology and is superior to expert analysts (Clinicaltrials.gov: NCT03556644).

Evolution of Echocardiography-Derived Hemodynamic Force Parameters After Cardiac Resynchronization Therapy.

Echocardiography-derived hemodynamic forces (HDF) allow calculation of intraventricular pressure gradients from routine transthoracic echocardiographic images. The evolution of HDF after cardiac resynchronization therapy (CRT) has not been investigated in large cohorts. The aim was to assess HDF in patients with heart failure implanted with CRT versus healthy controls. HDF were assessed before and 6 months after CRT. The following HDF parameters were calculated: (1) apical-basal strength, (2) lateral-septal strength, (3) the ratio of lateral-septal to apical-basal strength ratio, and (4) the force vector angle (1 and 2 representing the magnitude of HDF, 3 and 4 representing the orientation of HDF). In the propulsive phase of systole, the apical-basal impulse and the systolic force vector angle were measured. A total of 197 patients were included (age 64 ± 11 years, 62% male), with left ventricular ejection fraction ≤35%, QRS duration ≥130 ms and left bundle branch block. The magnitude of HDF was significantly lower and the orientation was significantly worse in patients with heart failure versus healthy controls. Immediately after CRT implantation, the apical-basal impulse and systolic force vector angle were significantly increased. Six months after CRT, improvement of apical-basal strength, lateral-septal to apical-basal strength ratio and the force vector angle occurred. When CRT was deactivated at 6 months, the increase in the magnitude of apical-basal HDF remained unchanged while the systolic force vector angle worsened significantly. In conclusion, HDF in CRT recipients reflect the acute effect of CRT and the effect of left ventricular reverse remodeling on intraventricular pressure gradients. Whether HDF analysis provides incremental value over established echocardiographic parameters, remains to be determined.

Inter- and intra-observer reproducibility of CT-Leaman score by an independent core lab.

To assess the reproducibility of CT-based Leaman score (CT-LeSc). CT-LeSc can non-invasively quantify total coronary atherosclerotic burden and is an independent long-term predictor of cardiac events. Its calculation however relies on the subjective assessment of lesions using coronary computed tomography angiography and therefore is subject to intra- and inter-observer variability. Inter-observer reproducibility was assessed by calculating the CT-LeSc in 50 patients randomly selected from the SYNTAX III REVOLUTION and ABSORB trials by two separate teams, each made up of two cardiologists, who reported results by consensus. For intra-observer reproducibility, the CT-LeSc was calculated in same 50 patients on two occasions eight weeks apart, by the same team of two cardiologists. The level of agreement was measured by the weighted kappa statistic, with intra- and inter-observer variability used to evaluate the CT-LeSc's reproducibility. The variables evaluated by weighted kappa statistics were total number of lesions; number of calcified lesions; number of non-calcified lesions; number of mixed lesions; number of obstructive lesions; number of non-obstructive lesions; and the total CT-LeSc in increments of ten and five. During assessment of inter-observer variability the mean ± standard deviation (SD) CT-LeSc calculated by the first and second team was 15.36 ± 5.57 versus 15.24 ± 5.16. The mean of the differences (precision) was 0.97, with a SD (accuracy) 1.17. The inter-observer variability was lowest for Leaman score in increments of five (weighted kappa 0.93), and highest for the total number of calcified lesions (weighted kappa 0.66). During assessment of intra-observer variability, the mean ± SD CT-LeSc were 16.61 ± 5.28 versus 16.82 ± 5.55. The mean ± SD of the differences was 1.28 ± 1.02. The intra-observer variability was the lowest for Leaman score in increments of five (weighted kappa 0.93), and the highest for the total number of lesions and calcified lesions (weighted kappa 0.65). CT-LeSc has substantial to near-perfect agreement for reproducibility.

Angiography and optical coherence tomography derived shear stress: are they equivalent in my opinion?

Advances in image reconstruction using either single or multimodality imaging data provide increasingly accurate three-dimensional (3D) patient's arterial models for shear stress evaluation using computational fluid dynamics (CFD). We aim to evaluate the impacts on endothelial shear stress (ESS) derived from a simple image reconstruction using 3D-quantitative coronary angiography (3D-QCA) versus a multimodality reconstruction method using optical coherence tomography (OCT) in patients' vessels treated with bioresorbable scaffolds. Seven vessels at baseline and five-year follow-up of seven patients from a previous CFD investigation were retrospectively selected for a head-to-head comparison of angiography-derived versus OCT-derived ESS. 3D-QCA significantly underestimated the minimum stent area [MSA] (-2.38mm2) and the stent length (-1.46 mm) compared to OCT-fusion method reconstructions. After carefully co-registering the region of interest for all cases with a sophisticated statistical method, the difference in MSA measurements as well as the inability of angiography to visualise the strut footprint in the lumen surface have translated to higher angiography-derived ESS than OCT-derived ESS (1.76 Pa or 1.52 times for the overlapping segment). The difference in ESS widened with a more restricted region of interest (1.97 Pa or 1.63 times within the scaffold segment). Angiography and OCT offer two distinctive methods of ESS calculation. Angiography-derived ESS tends to overestimate the ESS compared to OCT-derived ESS. Further investigations into ESS analysis resolution play a vital role in adopting OCT-derived ESS.

The diagnostic performance of quantitative flow ratio and perfusion imaging in patients with prior coronary artery disease.

AIMS: In chronic coronary syndrome (CCS) patients with documented coronary artery disease (CAD), ischaemia detection by myocardial perfusion imaging (MPI) and an invasive approach are viable diagnostic strategies. We compared the diagnostic performance of quantitative flow ratio (QFR) with single-photon emission computed tomography (SPECT), positron emission tomography (PET), and cardiac magnetic resonance imaging (CMR) in patients with prior CAD [previous percutaneous coronary intervention (PCI) and/or myocardial infarction (MI)]. METHODS AND RESULTS: This PACIFIC-2 sub-study evaluated 189 CCS patients with prior CAD for inclusion. Patients underwent SPECT, PET, and CMR followed by invasive coronary angiography with fractional flow reserve (FFR) measurements of all major coronary arteries (N = 567), except for vessels with a sub-total or chronic total occlusion. Quantitative flow ratio computation was attempted in 488 (86%) vessels with measured FFR available (FFR ≤0.80 defined haemodynamically significant CAD). Quantitative flow ratio analysis was successful in 334 (68%) vessels among 166 patients and demonstrated a higher accuracy (84%) and sensitivity (72%) compared with SPECT (66%, P < 0.001 and 46%, P = 0.001), PET (65%, P < 0.001 and 58%, P = 0.032), and CMR (72%, P < 0.001 and 33%, P < 0.001). The specificity of QFR (87%) was similar to that of CMR (83%, P = 0.123) but higher than that of SPECT (71%, P < 0.001) and PET (67%, P < 0.001). Lastly, QFR exhibited a higher area under the receiver operating characteristic curve (0.89) than SPECT (0.57, P < 0.001), PET (0.66, P < 0.001), and CMR (0.60, P < 0.001). CONCLUSION: QFR correlated better with FFR in patients with prior CAD than MPI, as reflected in the higher diagnostic performance measures for detecting FFR-defined, vessel-specific, significant CAD.

Prognostic implications of left ventricular inward displacement assessed by cardiac magnetic resonance imaging in patients with myocardial infarction.

Risk stratification of patients with ischemic heart disease (IHD) still depends mainly on the left ventricular ejection fraction (LVEF). LV inward displacement (InD) is a novel parameter of LV systolic function, derived from feature tracking cardiac magnetic resonance (CMR) imaging. We aimed to investigate the prognostic impact of InD in patients with IHD and prior myocardial infarction. A total of 111 patients (mean age 57 ± 10, 86% male) with a history of myocardial infarction who underwent CMR were included. LV InD was quantified by measuring the displacement of endocardially tracked points towards the centreline of the LV during systole with feature tracking CMR. The endpoint was a composite of all-cause mortality, heart failure hospitalization and arrhythmic events. During a median follow-up of 142 (IQR 107-159) months, 31 (27.9%) combined events occurred. Kaplan-Meier analysis demonstrated that patients with LV InD below the study population median value (23.0%) had a significantly lower event-free survival (P < 0.001). LV InD remained independently associated with outcomes (HR 0.90, 95% CI 0.84-0.98, P = 0.010) on multivariate Cox regression analysis. InD also provided incremental prognostic value to LVEF, LV global radial strain and CMR scar burden. LV InD, measured with feature tracking CMR, was independently associated with outcomes in patients with IHD and prior myocardial infarction. LV InD also provided incremental prognostic value, in addition to LVEF and LV global radial strain. LV InD holds promise as a pragmatic imaging biomarker for post-infarct risk stratification.

An optical coherence tomography and endothelial shear stress study of a novel bioresorbable bypass graft.

Endothelial shear stress (ESS) plays a key role in the clinical outcomes in native and stented segments; however, their implications in bypass grafts and especially in a synthetic biorestorative coronary artery bypass graft are yet unclear. This report aims to examine the interplay between ESS and the morphological alterations of a biorestorative coronary bypass graft in an animal model. Computational fluid dynamics (CFD) simulation derived from the fusion of angiography and optical coherence tomography (OCT) imaging was used to reconstruct data on the luminal anatomy of a bioresorbable coronary bypass graft with an endoluminal "flap" identified during OCT acquisition. The "flap" compromised the smooth lumen surface and considerably disturbed the local flow, leading to abnormally low ESS and high oscillatory shear stress (OSI) in the vicinity of the "flap". In the presence of the catheter, the flow is more stable (median OSI 0.02384 versus 0.02635, p < 0.0001; maximum OSI 0.4612 versus 0.4837). Conversely, OSI increased as the catheter was withdrawn which can potentially cause back-and-forth motions of the "flap", triggering tissue fatigue failure. CFD analysis in this report provided sophisticated physiological information that complements the anatomic assessment from imaging enabling a complete understanding of biorestorative graft pathophysiology.