Computed tomography coronary angiography assessment of left main coronary artery stenosis severity.

BACKGROUND: Angiographic assessment of left main coronary artery (LMCA) stenosis severity can be unreliable. In cases of ambiguity, intravascular ultrasound (IVUS) can be utilised with a minimal lumen area (MLA) of ≥6 â€‹mm2 an accepted threshold for safe deferral of revascularization. We sought to assess whether quantitative computer tomography coronary angiography (CTCA) measures could assist clinicians making LMCA revascularization decisions when compared with IVUS as gold standard. METHODS: Consecutive patients undergoing IVUS assessment of angiographically intermediate LMCA stenosis were included. All patients had undergone 320-slice CTCA <90 days prior to IVUS imaging. Offline quantitative assessment of IVUS- and CT-derived measures were undertaken with the cohort divided into those with significant (s-LMCA) versus non-significant (ns-LMCA) disease using the accepted IVUS threshold. RESULTS: Fifty-eight patients were included, with no difference in mean age (61.5 â€‹± â€‹12.2 vs. 59.7 â€‹± â€‹11.9 years, p â€‹= â€‹0.57), diabetic status (24.2% vs 16.0%, p â€‹= â€‹0.44) or other baseline demographics between groups. Patients with ns-LMCA had larger CT luminal area (8.64 â€‹± â€‹3.91 vs. 5.41 â€‹± â€‹1.54 â€‹mm2, p â€‹< â€‹0.001), larger minimal lumen diameter (MLD) (3.25 â€‹± â€‹0.74 vs. 2.56 â€‹± â€‹0.38 â€‹mm, p â€‹< â€‹0.001) and lower area stenosis (45.74 â€‹± â€‹18.10 vs. 60.93 â€‹± â€‹14.68%, p â€‹= â€‹0.001). There was a significant positive correlation between CTCA and IVUS MLA (r â€‹= â€‹0.68, p â€‹< â€‹0.001) and MLD (r â€‹= â€‹0.67, p â€‹< â€‹0.001). ROC analysis demonstrated CTCA MLA cut-off <8.29 â€‹mm2 provides the greatest negative predictive value and sensitivity in predicting the presence of significant LMCA disease. CONCLUSION: CTCA derived MLA and MLD have a strong correlation with IVUS. A CTCA derived MLA cut-off <8.29 â€‹mm2 showed greatest clinical utility for predicting the need for further assessment, based on IVUS gold standard.

Cardiologists' knowledge and perceptions of the seasonal influenza immunisation.

BACKGROUND: Seasonal influenza immunisation reduces cardiovascular events in high-risk patients, but 50% do not receive routine immunisation. The perceptions and current role of cardiologists in recommending and prescribing influenza immunisation has not been well described. METHODS: We used an exploratory sequential mixed methods design. Semi-structured interviews of 10 cardiologists were performed to identify themes for quantitative evaluation. 63 cardiologists undertook quantitative evaluation in an online survey. The interviews and surveys addressed (a) attitudes and behaviours regarding influenza immunisation and (b) preventative care in cardiology. RESULTS: One quarter (25.4%, n = 16) of cardiologists recommended influenza immunisation to all patients. Less than half (49.2%, n = 31) recommended influenza immunisation to secondary prevention patients. Almost 1/3 of respondents (31.7%, n = 20) were uncertain or unaware of the guidelines regarding influenza immunisation and patients with cardiac disease. Most cardiologists believed that general practitioners were responsible for ensuring patients received influenza immunisation (76.2%, n = 48). CONCLUSIONS: Despite reducing cardiovascular events in high-risk patients, influenza immunisation is not widely recommended by cardiologists. Further clinician education is needed to address the knowledge gaps which prevent recommendation and uptake of this guideline directed treatment.

Inter-software and inter-scan variability in measurement of epicardial adipose tissue: a three-way comparison of a research-specific, a freeware and a coronary application software platform.

OBJECTIVES: Epicardial adipose tissue (EAT) is a proposed marker of cardiovascular risk; however, clinical application may be limited by variability in post-processing software platforms. We assessed inter-vendor agreement of EAT volume (EATv) and attenuation on both contrast-enhanced (CE) and non-contrast CT (NCT) using a standard coronary CT reporting software (Vitrea), an EAT research-specific software (QFAT) and a freeware imaging software (OsiriX). METHODS: Seventy-six consecutive patients undergoing simultaneous CE and NCT had complete volumetric EAT measurement. Between-software, within-software NCT vs. CE, and inter- and intra-observer agreement were evaluated with analysis by ANOVA (with post hoc adjustment), Bland-Altman with 95% levels of agreement (LoA) and intraclass correlation coefficient (ICC). RESULTS: Mean EATv (freeware 53 ± 31 mL vs. research 93 ± 43 mL vs. coronary 157 ± 64 mL) and attenuation (freeware - 72 ± 25 HU vs. research - 75 ± 3 HU vs. coronary - 61 ± 10 HU) were significantly different between all vendors (ANOVA p < 0.001). EATv was consistently higher in NCT vs. CE for all software packages, with most reproducibility found in research software (bias 26 mL, 95% LoA: 2 to 56 mL), compared to freeware (bias 11 mL 95% LoA: - 46 mL to 69 mL) and coronary software (bias 10 mL 95% LoA: - 127 to 147 mL). Research software had more comparable NCT vs. CE attenuation (- 75 vs. - 72 HU) compared to freeware (- 72 vs. - 57 HU) and coronary (- 61 vs. - 39 HU). Excellent inter-observer agreement was seen with research (ICC 0.98) compared to freeware (ICC 0.73) and coronary software (ICC 0.75) with narrow LoA on Bland-Altman analysis. CONCLUSION: There are significant inter-vendor differences in EAT assessment. Our study suggests that research-specific software has better agreement and reproducibility compared to freeware or coronary software platforms. KEY POINTS: • There are significant differences between EAT volume and attenuation values between software platforms, regardless of scan type. • Non-contrast scans routinely have higher mean EAT volume and attenuation; however, this finding is only consistently seen with research-specific software. • Of the three analyzed packages, research-specific software demonstrates the highest reproducibility, agreement, and reliability for both inter-scan and inter-observer agreement.

Atrial fibrillation in cancer survivors - a systematic review and meta-analysis.

BACKGROUND: Atrial fibrillation (AF) is a common cardiac complication during cancer treatment. It is unclear if cancer survivors have increased AF risk when compared to the population. AF screening is now recommended in patients ≥65 years, however there are no specific recommendations in the oncology population. We sought to compare the AF detection rate of cancer survivors compared to the general population. METHODS: We searched the Pubmed, Embase and Web of Science databases using search terms related to AF and cancer mapped to subject headings. We included English language studies, limited to adults > 18 years who were > 12 months post completion of cancer treatment. Using a random-effects model we calculated the overall AF detection rate. Meta-regression analysis was performed to assess for potential causes for study heterogeneity. RESULTS: Sixteen studies were included in the study. The combined AF detection rate amongst all the studies was 4.7% (95% C.I 4.0-5.4%), which equated to a combined annualised AF rate of 0.7% (95% C.I 0.1-0.98%). There was significant heterogeneity between studies (I2 = 99.8%, p < 0.001). In the breast cancer cohort (n = 6 studies), the combined annualised AF rate was 0.9% (95% C.I 0.1-2.3%), with significant heterogeneity (I2 = 99.9%, p < 0.001). CONCLUSION: Whilst the results should be interpreted with caution due to study heterogeneity, AF rates in patients with cancer survival >12 months were not significantly increased compared to the general population. STUDY REGISTRATION: Open Science Framework - DOI: https://doi.org/10.17605/OSF.IO/APSYG .

Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems.

OBJECTIVE: We aimed to evaluate the effectiveness of utilizing artificial intelligence (AI) to quantify the extent of pneumonia from chest CT scans, and to determine its ability to predict clinical deterioration or mortality in patients admitted to the hospital with COVID-19 in comparison to semi-quantitative visual scoring systems. METHODS: A deep-learning algorithm was utilized to quantify the pneumonia burden, while semi-quantitative pneumonia severity scores were estimated through visual means. The primary outcome was clinical deterioration, the composite end point including admission to the intensive care unit, need for invasive mechanical ventilation, or vasopressor therapy, as well as in-hospital death. RESULTS: The final population comprised 743 patients (mean age 65  ±â€¯ 17 years, 55% men), of whom 175 (23.5%) experienced clinical deterioration or death. The area under the receiver operating characteristic curve (AUC) for predicting the primary outcome was significantly higher for AI-assisted quantitative pneumonia burden (0.739, p = 0.021) compared with the visual lobar severity score (0.711, p < 0.001) and visual segmental severity score (0.722, p = 0.042). AI-assisted pneumonia assessment exhibited lower performance when applied for calculation of the lobar severity score (AUC of 0.723, p = 0.021). Time taken for AI-assisted quantification of pneumonia burden was lower (38 ± 10 s) compared to that of visual lobar (328 ± 54 s, p < 0.001) and segmental (698 ± 147 s, p < 0.001) severity scores. CONCLUSION: Utilizing AI-assisted quantification of pneumonia burden from chest CT scans offers a more accurate prediction of clinical deterioration in patients with COVID-19 compared to semi-quantitative severity scores, while requiring only a fraction of the analysis time. ADVANCES IN KNOWLEDGE: Quantitative pneumonia burden assessed using AI demonstrated higher performance for predicting clinical deterioration compared to current semi-quantitative scoring systems. Such an AI system has the potential to be applied for image-based triage of COVID-19 patients in clinical practice.

Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional long short-term memory networks.

Purpose: Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in coronavirus disease 2019 (COVID-19) patients but are not part of clinical routine because the required manual segmentation of lung lesions is prohibitively time consuming. We aim to automatically segment ground-glass opacities and high opacities (comprising consolidation and pleural effusion). Approach: We propose a new fully automated deep-learning framework for fast multi-class segmentation of lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional long short-term memory (ConvLSTM) networks. Utilizing the expert annotations, model training was performed using five-fold cross-validation to segment COVID-19 lesions. The performance of the method was evaluated on CT datasets from 197 patients with a positive reverse transcription polymerase chain reaction test result for SARS-CoV-2, 68 unseen test cases, and 695 independent controls. Results: Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score of 0.89 ± 0.07 ; excellent correlations of 0.93 and 0.98 for ground-glass opacity (GGO) and high opacity volumes, respectively, were obtained. In the external testing set of 68 patients, we observed a Dice score of 0.89 ± 0.06 as well as excellent correlations of 0.99 and 0.98 for GGO and high opacity volumes, respectively. Computations for a CT scan comprising 120 slices were performed under 3 s on a computer equipped with an NVIDIA TITAN RTX GPU. Diagnostically, the automated quantification of the lung burden % discriminate COVID-19 patients from controls with an area under the receiver operating curve of 0.96 (0.95-0.98). Conclusions: Our method allows for the rapid fully automated quantitative measurement of the pneumonia burden from CT, which can be used to rapidly assess the severity of COVID-19 pneumonia on chest CT.

Diagnostic performance of quantitative flow ratio, non-hyperaemic pressure indices and fractional flow reserve for the assessment of coronary lesions in severe aortic stenosis.

Background: Quantitative flow ratio (QFR) may be used to assess the functional significance of coronary lesions. Only limited validation exists for this technology in the setting of severe aortic stenosis. Methods: A prospective study was performed on patients who were being considered for transcatheter aortic valve implantation. QFR analysis was performed (Medis Medical Imaging System, Leiden, The Netherlands) and compared to invasive measurements of haemodynamic assessment [fractional flow reserve (FFR), instantaneous wave-free ratio (iFR), diastolic pressure ratio during the wave-free period (dPR) and distal arterial pressure/arterial pressure (Pd/Pa)]. Results: A total of 35 patients were included in the study. Mean age was 75.5±6.5 and mean aortic valve gradient was 44.3±11.8 mmHg. There were 57 vessels analysed. The mean FFR was 0.83±0.10 and 22 vessels (39%) had a functionally significant FFR ≤0.80. QFR demonstrated a discriminatory power to predict functionally significant FFR [area under the receiver operating characteristic curve (AUC), 0.92; 95% confidence interval (CI): 0.84 to 1.00], representing a sensitivity of 73%, specificity of 91%, positive predictive value of 84%, negative predictive value of 84% and an accuracy of 84%. QFR also demonstrated a discriminatory power to predict functionally significant iFR ≤0.89 (AUC =0.92; 95% CI: 0.85 to 0.99), dPR ≤0.89 (AUC =0.90; 95% CI: 0.83 to 0.98) and Pd/Pa ≤0.92 (AUC =0.89; 95% CI: 0.80 to 0.97). Conclusions: QFR demonstrates acceptable diagnostic performance in patients with severe aortic stenosis when both FFR and non-hyperaemic pressure indices are used as reference standards.

Breast arterial calcification and epicardial adipose tissue volume, but not density are independently associated with cardiovascular risk.

BACKGROUND: Mammographically detected breast arterial calcification (BAC) has been proposed as surrogate marker for coronary artery disease (CAD) in women. Epicardial adipose tissue (EAT) and peri-coronary adipose tissue (PCAT) are inflammatory fat depots linked to atherogenesis. BAC has demonstrated association with inflammation, therefore we aimed to determine the association between BAC, EAT and PCAT. METHODS: Single-centre, retrospective, cross-sectional study of women with digital mammography and coronary computed tomography angiography (CCTA). EAT and PCAT were quantitively assessed using semi-automated software. Patient demographics and cardiovascular risk factors were obtained from medical records and mammograms reviewed for BAC. Pre-test cardiovascular risk was determined with CAD Consortium Score. Chi-square, t-test and Mann-Whitney U tests were used to assess between group differences. Multivariable linear and logistic regression modelling was conducted to adjust for confounders. RESULTS: Among 153 patients (age 61, SD 11) included in this study, BAC was present in 37 (24%) patients. BAC-positive patients had higher EAT volume (EATv) (110.2 mL, SD 41 mL vs 94.4 mL, SD 41 mL, p = 0.02) but this association was not significant after adjusting for cardiovascular risk factors (p = 0.26). BAC did not associate with EAT density or PCAT. BAC and EATv were strongly associated with cardiovascular risk and CAD independent of each other: CV risk (BAC OR 7.55 (3.26-18.49), p < 0.001, EATv OR 1.02 (1.01-1.03), p < 0.001), CAD presence (BAC OR 4.26 (1.39-13), p = 0.01; EATv OR 1.01 (1.0-1.03), p = 0.04). CONCLUSION: BAC and EATv are independent predictors of CV risk and CAD, but don't independently associate with each other, the relationship confounded by shared cardiovascular risk factors. BAC doesn't appear to associate with adipose tissue density and its presence may be cumulative result of long-term exposure to CV risk factors.

Predictive Utility of Left Heart Catheterization Indices for Left Ventricular Thrombus Formation After Anterior ST-Elevation Myocardial Infarction.

BACKGROUND: Left ventricular thrombus (LVT) has a 5% incidence after anterior ST-elevation myocardial infarction (STEMI). Multiple risk factors predispose to LVT formation, including left ventricular systolic dysfunction and infarct size, however measurable predictors during index left heart catheterization (LHC) have not been determined. METHODS: We performed a retrospective analysis of patients presenting between January 2010 and September 2017 with anterior STEMI who had in-hospital transthoracic echocardiography (TTE). LHC variables that were assessed included coronary anatomy, location of culprit stenosis, presence of diffuse stenosis, number of severely diseased vessels, apical akinesis on left ventriculogram (LVG), left ventricular end diastolic pressure, and success of percutaneous coronary intervention (PCI). RESULTS: Of 598 consecutive anterior STEMI patients, records and inpatient TTE results were available in 425 patients. The incidence of LVT was 6.8% (n = 29). After multivariate adjustment, severe triple vessel coronary disease (OR = 8.27, CI = 2.97-23.00, p ≤0.001), apical akinesis on LVG (OR = 6.74, CI = 1.48-30.73, p = 0.014), wrap-around left anterior descending (LAD) anatomy (OR = 5.10, CI = 1.97-13.23, p = 0.001), and failure of recanalization after PCI (OR = 3.94, CI = 1.06-14.66, p = 0.04) were predictors for LVT formation. The combined negative predictive value (NPV) for the absence of these four indices was 99.2%. CONCLUSION: Severe triple vessel disease, apical akinesis on LVG during index admission, wrap-around LAD, and failure of recanalization after PCI are associated with increased risk of LVT formation after anterior STEMI. The high NPV for the absence of these indices could serve as a risk stratification tool for LVT risk to guide early TTE utilization.

Metal stents are safe and cost-effective for preoperative biliary drainage in resectable pancreaticobiliary tumours.

BACKGROUNDS: To compare the complication rates and overall costs of self-expandable metal stents (SEMS) and plastic stents (PS) in clinically indicated preoperative biliary drainage (PBD) prior to a pancreatoduodenectomy (PD). METHODS: We conducted an Australian multicentre retrospective cohort study using the databases of four tertiary hospitals. Adult patients who underwent clinically indicated endoscopic PBD prior to PD from 2010 to 2019 were included. Rates of complications attributable to PBD, surgical complications and pre-operative endoscopic re-intervention were calculated. Costing data were retrieved from our Financial department. RESULTS: Among the 157 included patients (mean age 66.6 ± 9.8 years, 45.2% male), 49 (31.2%) received SEMS and 108 received PS (68.8%). Baseline bilirubin was 187.5 ± 122.6 µmol/L. Resection histopathology showed mainly adenocarcinoma (93.0%). Overall SEMS was associated less complications (12.2% vs. 28.7%, p = 0.02) and a lower pre-operative endoscopic re-intervention rate (4.3 vs. 20.8%, p = 0.03) compared with PS. There was no difference in post-PD complication rates. On multivariate logistic regression analysis, stent type was an independent risk factor of PBD complication (OR of SEMS compared to PS 0.24, 95% CI 0.07-0.79, p = 0.02) but not for any secondary outcome measures. Upfront material costs were $56USD for PS and $1991USD for SEMS. Accounting for rates of complications, average costs were similar ($3110USD for PS and $3026USD for SEMS). CONCLUSION: In resectable pancreaticobiliary tumours, SEMS for PBD was associated with reduced risk of overall PBD-related complications and pre-surgical endoscopic reintervention rates and was comparable to PS in terms of overall cost.

Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional LSTM networks.

Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in Coronavirus disease 2019 (COVID-19) patients, but are not part of the clinical routine since required manual segmentation of lung lesions is prohibitively time-consuming. We propose a new fully automated deep learning framework for quantification and differentiation between lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional Long Short-Term Memory (LSTM) networks. Utilizing the expert annotations, model training was performed using 5-fold cross-validation to segment ground-glass opacity and high opacity (including consolidation and pleural effusion). The performance of the method was evaluated on CT data sets from 197 patients with positive reverse transcription polymerase chain reaction test result for SARS-CoV-2. Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score coefficient of 0.876 ± 0.005; excellent correlations of 0.978 and 0.981 for ground-glass opacity and high opacity volumes. In the external validation set of 67 patients, there was dice score coefficient of 0.767 ± 0.009 as well as excellent correlations of 0.989 and 0.996 for ground-glass opacity and high opacity volumes. Computations for a CT scan comprising 120 slices were performed under 2 seconds on a personal computer equipped with NVIDIA Titan RTX graphics processing unit. Therefore, our deep learning-based method allows rapid fully-automated quantitative measurement of pneumonia burden from CT and may generate the big data with an accuracy similar to the expert readers.

Ethnic differences in coronary anatomy, left ventricular mass and CT-derived fractional flow reserve.

BACKGROUND: Studies have observed higher incidence of cardiovascular mortality in South Asians (SA), and lower prevalence in East Asians (EA), compared with Caucasians. These observations are not entirely explained by ethnic differences in cardiovascular risk factors and mechanistic factors such as variations in cardiac anatomy and physiology may play a role. This study compared ethnic differences in CT-assessed left ventricular (LV) mass, coronary anatomy and non-invasive fractional flow reserve (FFRCT). METHODS: Three-hundred symptomatic patients (age 59 ± 7.9, male 51%) underwent clinically-mandated CT-coronary-angiography (CTA) were matched for age, gender, BMI and diabetes (100 each ethnicity). Assessment of coronary stenosis, luminal dimensions and vessel dominance was performed by independent observers. LV mass, coronary luminal volume and FFRCT were quantified by blinded core-laboratory. A sub-analysis was performed on patients (n = 187) with normal/minimal disease (0-25% stenosis). RESULTS: Stenosis severity was comparable across ethnic groups. EA demonstrated less left-dominant circulation (2%) compared with SA (8.2%) and Caucasians (10.1%). SA compared with EA and Caucasians demonstrated smallest indexed LV mass, coronary luminal volumes and dimensions. EA compared with Caucasians had comparable indexed LV mass, coronary luminal dimensions and highest luminal volumes. The latter was driven by higher prevalence of right-dominance including larger and longer right posterior left ventricular artery. FFRCT in the left anterior descending artery (LAD) was lowest in SA (0.87) compared with EA (0.89; P = 0.009) and Caucasians (0.89; P < 0.001), with no difference in other vessels. All observed differences were consistent in patients with minimal disease. CONCLUSION: This single-centre study identified significant ethnic differences in CT-assessed LV mass, coronary anatomy and LAD FFRCT. These hypotheses generating results may provide a mechanistic explanation for ethnic differences in cardiovascular outcomes and require validation in larger cohorts.

Feasibility and Validity of Computed Tomography-Derived Fractional Flow Reserve in Patients With Severe Aortic Stenosis: The CAST-FFR Study.

BACKGROUND: Coronary artery disease is common in patients with severe aortic stenosis. Computed tomography-derived fractional flow reserve (CT-FFR) is a clinically used modality for assessing coronary artery disease, however, its use has not been validated in patients with severe aortic stenosis. This study assesses the safety, feasibility, and validity of CT-FFR in patients with severe aortic stenosis. METHODS: Prospectively recruited patients underwent standard-protocol invasive FFR and coronary CT angiography (CTA). CTA images were analyzed by central core laboratory (HeartFlow, Inc) for independent evaluation of CT-FFR. CT-FFR data were compared with FFR (ischemia defined as FFR ≤0.80). RESULTS: Forty-two patients (68 vessels) underwent FFR and CTA; 39 patients (92.3%) and 60 vessels (88.2%) had interpretable CTA enabling CT-FFR computation. Mean age was 76.2±6.7 years (71.8% male). No patients incurred complications relating to premedication, CTA, or FFR protocol. Mean FFR and CT-FFR were 0.83±0.10 and 0.77±0.14, respectively. CT calcium score was 1373.3±1392.9 Agatston units. On per vessel analysis, there was positive correlation between FFR and CT-FFR (Pearson correlation coefficient, R=0.64, P<0.0001). Sensitivity, specificity, positive predictive value, and negative predictive values were 73.9%, 78.4%, 68.0%, and 82.9%, respectively, with 76.7% diagnostic accuracy. The area under the receiver-operating characteristic curve for CT-FFR was 0.83 (0.72-0.93, P<0.0001), which was higher than that of CTA and quantitative coronary angiography (P=0.01 and P<0.001, respectively). Bland-Altman plot showed mean bias between FFR and CT-FFR as 0.059±0.110. On per patient analysis, the sensitivity, specificity, positive predictive, and negative predictive values were 76.5%, 77.3%, 72.2%, and 81.0% with 76.9% diagnostic accuracy. The per patient area under the receiver-operating characteristic curve analysis was 0.81 (0.67-0.95, P<0.0001). CONCLUSIONS: CT-FFR is safe and feasible in patients with severe aortic stenosis. Our data suggests that the diagnostic accuracy of CT-FFR in this cohort potentially enables its use in clinical practice and provides the foundation for future research into the use of CT-FFR for coronary evaluation pre-aortic valve replacement.

Epicardial adipose tissue is associated with extent of pneumonia and adverse outcomes in patients with COVID-19.

AIM: We sought to examine the association of epicardial adipose tissue (EAT) quantified on chest computed tomography (CT) with the extent of pneumonia and adverse outcomes in patients with coronavirus disease 2019 (COVID-19). METHODS: We performed a post-hoc analysis of a prospective international registry comprising 109 consecutive patients (age 64 ±â€¯16 years; 62% male) with laboratory-confirmed COVID-19 and noncontrast chest CT imaging. Using semi-automated software, we quantified the burden (%) of lung abnormalities associated with COVID-19 pneumonia. EAT volume (mL) and attenuation (Hounsfield units) were measured using deep learning software. The primary outcome was clinical deterioration (intensive care unit admission, invasive mechanical ventilation, or vasopressor therapy) or in-hospital death. RESULTS: In multivariable linear regression analysis adjusted for patient comorbidities, the total burden of COVID-19 pneumonia was associated with EAT volume (ß = 10.6, p = 0.005) and EAT attenuation (ß = 5.2, p = 0.004). EAT volume correlated with serum levels of lactate dehydrogenase (r = 0.361, p = 0.001) and C-reactive protein (r = 0.450, p < 0.001). Clinical deterioration or death occurred in 23 (21.1%) patients at a median of 3 days (IQR 1-13 days) following the chest CT. In multivariable logistic regression analysis, EAT volume (OR 5.1 [95% CI 1.8-14.1] per doubling p = 0.011) and EAT attenuation (OR 3.4 [95% CI 1.5-7.5] per 5 Hounsfield unit increase, p = 0.003) were independent predictors of clinical deterioration or death, as was total pneumonia burden (OR 2.5, 95% CI 1.4-4.6, p = 0.002), chronic lung disease (OR 1.3 [95% CI 1.1-1.7], p = 0.011), and history of heart failure (OR 3.5 [95% 1.1-8.2], p = 0.037). CONCLUSIONS: EAT measures quantified from chest CT are independently associated with extent of pneumonia and adverse outcomes in patients with COVID-19, lending support to their use in clinical risk stratification.

The assessment of intermediate coronary lesions using intracoronary imaging.

Intermediate coronary artery stenosis, defined as visual angiographic stenosis severity of between 30-70%, is present in up to one quarter of patients undergoing coronary angiography. Patients with this particular lesion subset represent a distinct clinical challenge, with operators often uncertain on the need for revascularization. Although international guidelines appropriately recommend physiological pressure-based assessment of these lesions utilizing either fractional flow reserve (FFR) or quantitative flow ratio (QFR), there are specific clinical scenarios and lesion subsets where the use of such indices may not be reliable. Intravascular imaging, mainly utilizing intravascular ultrasound (IVUS) and optical coherence tomography (OCT) represents an alternate and at times complementary diagnostic modality for the evaluation of intermediate coronary stenoses. Studies have attempted to validate these specific imaging measures with physiological markers of lesion-specific ischaemia with varied results. Intravascular imaging however also provides additional benefits that include portrayal of plaque morphology, guidance on stent implantation and sizing and may portend improved clinical outcomes. Looking forward, research in computational fluid dynamics now seeks to integrate both lesion-based physiology and anatomical assessment using intravascular imaging. This review will discuss the rationale and indications for the use of intravascular imaging assessment of intermediate lesions, while highlighting the current limitations and benefits to this approach.

Non-hyperaemic pressure ratios to guide percutaneous coronary intervention.

The use of fractional flow reserve (FFR) in guiding revascularisation improves patient outcomes and has been well-established in clinical guidelines. Despite this, the uptake of FFR has been limited, likely attributable to the perceived increase in procedural time and use of hyperaemic agents that can cause patient discomfort. This has led to the development of instantaneous wave-free ratio (iFR), an alternative non-hyperaemic pressure ratio (NHPR). Since its inception, the use of iFR has been supported by an increasing body of evidence and is now guideline recommended. More recently, other commercially available NHPRs including diastolic hyperaemia-free ratio and resting full-cycle ratio have emerged. Studies have demonstrated that these indices, in addition to mean distal coronary artery pressure to mean aortic pressure ratio, are mathematically analogous (with specific nuances) to iFR. Additionally, there is increasing data demonstrating the equivalent diagnostic performance of alternative NHPRs in comparison with iFR and FFR. These NHPRs are now integral within most current pressure wire systems and are commonly available in the catheter laboratory. It is therefore key to understand the fundamental differences and evidence for NHPRs to guide appropriate clinical decision-making.

Fractional Flow Reserve following Percutaneous Coronary Intervention.

Fractional flow reserve (FFR) is routinely used to determine lesion severity prior to percutaneous coronary intervention (PCI). However, there is an increasing recognition that FFR may also be useful following PCI to identify mechanisms leading to restenosis and the need for repeat revascularization. Post-PCI FFR is associated with the presence and severity of stent under-expansion and may help identify peri-stent-related complications. FFR pullback may also unmask other functionally significant lesions within the target vessel that were not appreciable on angiography. Recent studies have confirmed the prognostic utility of performing routine post-PCI FFR and suggest possible interventional targets that would improve stent durability. In this review, we detail the theoretical basis underlying post-PCI FFR, provide practical tips to facilitate measurement, and discuss the growing evidence supporting its use.

Angiographic Functional Scoring of Coronary Artery Disease Predicts Mortality in Patients With Severe Aortic Stenosis Undergoing TAVR.

BACKGROUND/PURPOSE: Coronary artery disease (CAD) is common in patients undergoing transcatheter aortic valve replacement (TAVR), although its prognostic significance is questionable. Significant CAD stratified using SYNTAX score (SS) has been associated with greater mortality, yet it is unknown whether the functional impact of CAD also impacts outcomes in this cohort. DILEMMA score (DS) is a validated angiographic functional scoring tool that correlates with fractional flow reserve and instantaneous wave-free ratio. This study sought to assess the functional impact of CAD on outcomes in patients undergoing TAVR for severe aortic stenosis (AS). METHODS/MATERIALS: 229 patients were included in this analysis. Patients underwent angiographic DS and SS and were classified using predefined values. The primary endpoint was one-year all-cause mortality, with secondary endpoints of 30-day major adverse cardiac and cerebrovascular events (MACCE). RESULTS: The mean age was 83.9 ± 0.5 years (55.0% female), with 11.8% all-cause mortality. CAD defined by ≥30% stenosis in any vessel was not associated with adverse outcomes (HR = 1.08, p = 0.84). However, the risk of one-year mortality was greater in patients with either SS > 9 (20.8% vs. 9.4%, HR 2.34, p = 0.03) or DS > 2 (18.4% vs. 8.5%, HR = 2.28, p = 0.03). Both scoring systems were also associated with 30-day MACCE (both p < 0.05). After multivariate adjustment, independent predictors of one-year mortality were DS > 2 (HR = 2.29, p = 0.04), left ventricular ejection fraction <50% (HR 2.66, p = 0.04) and COPD (HR 2.43, p = 0.04). CONCLUSION: Our results demonstrate that angiographic functional scoring is independently predictive of both 12-month mortality and 30-day MACCE following TAVR.

The Natural history of Epicardial Adipose Tissue Volume and Attenuation: A long-term prospective cohort follow-up study.

Epicardial adipose tissue (EAT) is associated with cardiovascular risk. The longitudinal change in EAT volume (EATv) and density (EATd), and potential modulators of these parameters, has not been described. We prospectively recruited 90 patients with non-obstructive coronary atherosclerosis on baseline computed tomography coronary angiography (CTCA) performed for suspected coronary artery disease to undergo a repeat research CTCA. EATv in millilitres (mL) and EATd in Hounsfield units (HU) were analysed and multivariable regression analysis controlling for traditional cardiovascular risk factors (CVRF) performed to assess for any predictors of change. Secondary analysis was performed based on statin therapy. The median duration between CTCA was 4.3years. Mean EATv increased at follow-up (72 ± 33 mL to 89 ± 43 mL, p < 0.001) and mean EATd decreased (baseline -76 ± 6 HU vs. -86 ± 5 HU, p < 0.001). There were no associations between baseline variables of body mass index, age, sex, hypertension, hyperlipidaemia, diabetes or smoking on change in EATv or EATd. No difference in baseline, follow-up or delta EATv or EATd was seen in patients with (60%) or without baseline statin therapy. In this select group of patients, EATv consistently increased and EATd consistently decreased at long-term follow-up and these changes were independent of CVRF, age and statin use. Together with the knowledge of strong associations between EAT and cardiac disease, these findings may suggest that EAT is an independent parameter rather than a surrogate for cardiovascular risk.