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Cardiac imaging has a pivotal role in the prevention, diagnosis and treatment of ischaemic heart disease. SPECT is most commonly used for clinical myocardial perfusion imaging, whereas PET is the clinical reference standard for the quantification of myocardial perfusion. MRI does not involve exposure to ionizing radiation, similar to echocardiography, which can be performed at the bedside. CT perfusion imaging is not frequently used but CT offers coronary angiography data, and invasive catheter-based methods can measure coronary flow and pressure. Technical improvements to the quantification of pathophysiological parameters of myocardial ischaemia can be achieved. Clinical consensus recommendations on the appropriateness of each technique were derived following a European quantitative cardiac imaging meeting and using a real-time Delphi process. SPECT using new detectors allows the quantification of myocardial blood flow and is now also suited to patients with a high BMI. PET is well suited to patients with multivessel disease to confirm or exclude balanced ischaemia. MRI allows the evaluation of patients with complex disease who would benefit from imaging of function and fibrosis in addition to perfusion. Echocardiography remains the preferred technique for assessing ischaemia in bedside situations, whereas CT has the greatest value for combined quantification of stenosis and characterization of atherosclerosis in relation to myocardial ischaemia. In patients with a high probability of needing invasive treatment, invasive coronary flow and pressure measurement is well suited to guide treatment decisions. In this Consensus Statement, we summarize the strengths and weaknesses as well as the future technological potential of each imaging modality.Cardiac imaging has a pivotal role in the prevention, diagnosis and treatment of ischaemic heart disease. In this Consensus Statement, the authors summarize the use of SPECT, PET, MRI, echocardiography, CT and invasive coronary flow and pressure measurement, and describe the relative strengths and weaknesses of each modality.

ObjectivesTo develop and evaluate a fully automatic method to measure diameters of the ascending and descending aorta on non-ECG-gated, non-contrast computed tomography (CT) scans.Material and methodsThe method combines multi-atlas registration to obtain seed points, aorta centerline extraction, and an optimal surface segmentation approach to extract the aorta surface around the centerline. From the extracted 3D aorta segmentation, the diameter of the ascending and descending aorta was calculated at cross-sectional slices perpendicular to the extracted centerline, at the level of the pulmonary artery bifurcation, and at 1-cm intervals up to 3 cm above and below this level. Agreement with manual annotations was evaluated by dice similarity coefficient (DSC) for segmentation overlap, mean surface distance (MSD), and intra-class correlation (ICC) of diameters on 100 CT scans from a lung cancer screening trial. Repeatability of the diameter measurements was evaluated on 617 baseline-one year follow-up CT scan pairs.ResultsThe agreement between manual and automatic segmentations was good with 0.95 ± 0.01 DSC and 0.56 ± 0.08 mm MSD. ICC between the diameters derived from manual and from automatic segmentations was 0.97, with the per-level ICC ranging from 0.87 to 0.94. An ICC of 0.98 for all measurements and per-level ICC ranging from 0.91 to 0.96 were obtained for repeatability.ConclusionThis fully automatic method can assess diameters in the thoracic aorta reliably even in non-ECG-gated, non-contrast CT scans. This could be a promising tool to assess aorta dilatation in screening and in clinical practice.Key Points• Fully automatic method to assess thoracic aorta diameters.• High agreement between fully automatic method and manual segmentations.• Method is suitable for non-ECG-gated CT and can therefore be used in screening.

Chronic kidney disease accelerates both atherosclerosis and arterial calcification. The aim of the present study was to explore whether maximal carotid plaque thickness (cPTmax) was increased in patients with chronic kidney disease compared to controls and associated with cardiovascular disease and severity of calcification in the carotid and coronary arteries. The study group consisted of 200 patients with chronic kidney disease stage 3 from the Copenhagen Chronic Kidney Disease Cohort and 121 age- and sex-matched controls. cPTmax was assessed by ultrasound and arterial calcification by computed tomography scanning. Carotid plaques were present in 58% of patients (n = 115) compared with 40% of controls (n = 48), p = 0.002. Among participants with plaques, cPTmax (median, interquartile range) was significantly higher in patients compared with controls (1.9 (1.4-2.3) versus 1.5 (1.2-1.8) mm), p = 0.001. Cardiovascular disease was present in 9% of patients without plaques (n = 85), 23% of patients with cPTmax 1.0-1.9 mm (n = 69) and 35% of patients with cPTmax >1.9 mm (n = 46), p = 0.001. Carotid and coronary calcium scores >400 were present in 0% and 4%, respectively, of patients with no carotid plaques, in 19% and 24% of patients with cPTmax 1.0-1.9 mm, and in 48% and 53% of patients with cPTmax >1.9 mm, p<0.001. This is the first study showing that cPTmax is increased in patients with chronic kidney disease stage 3 compared to controls and closely associated with prevalent cardiovascular disease and severity of calcification in both the carotid and coronary arteries.

Persons living with HIV (PLWH) may have increased incidence of cardiovascular events and longer QTc intervals than uninfected persons. We aimed to investigate the incidence and risk factors of de novo major electrocardiogram (ECG) abnormalities and QTc prolongation in well-treated PLWH. We included virologically suppressed PLWH without major ECG abnormalities, who attended the 2-year follow-up in the Copenhagen comorbidity in HIV infection (COCOMO) study. ECGs were categorized according to Minnesota Code Manual. We defined de novo major ECG abnormalities as new major Minnesota Code Manual abnormalities. Prolonged QTc was defined as QTc > 460 ms in females and QTc > 450 ms in males. Of 667 PLWH without major ECG abnormalities at baseline, 34 (5%) developed de novo major ECG abnormalities after a median of 2.3 years. After adjustment, age (RR: 1.57 [1.08–2.28] per decade older), being underweight (RR: 5.79 [1.70–19.71]), current smoking (RR: 2.34 [1.06–5.16]), diabetes (RR: 3.89 [1.72–8.80]) and protease inhibitor use (RR: 2.45 [1.27–4.74) were associated with higher risk of getting de novo major ECG abnormalities. Of PLWH without prolonged QTc at baseline, only 11 (1.6%) participants developed de novo prolonged QTc. Five percent of well-treated PLWH acquired de novo major ECG abnormalities and protease inhibitor use was associated with more than twice the risk of de novo major ECG abnormalities. De novo prolonged QTc was rare and did not seem to constitute a problem in well-treated PLWH.

To determine via meta-analysis the diagnostic accuracy of 64-slice computed tomography coronary angiography (CTA) for assessment of significant obstructive coronary artery stenosis at different coronary artery calcium score (CACS) levels. Data of 12,053 versus 5,890 segments, 906 versus 758 arteries and 1,120 versus 514 patients in low versus high CACS subgroups from 19 eligible studies were compared. The per-patient prevalence of coronary artery disease was 48% versus 68%, respectively. Subgroups were stratified by different CACS thresholds ranging from 100 to 400. Meta-analyses of per-patient data comparing overall low versus high CACS subgroups resulted in a sensitivity of 97.5 (95.5–99)% versus 97 (94.5–98.5)%, specificity of 85 (82–88)% versus 66.5 (58–74.5)%, diagnostic odds ratio of 153 (81–290) versus 40 (20–83), positive predictive value of 85 (82–87)% versus 86 (84–88)%, negative predictive value of 97.5 (95–99)% versus 91 (88–94)% and overall accuracy of 91% versus 89% with 95% confidence interval, respectively. The drop in specificity was significant ( P  = 0.035), while the sensitivity and overall accuracy were insignificantly changed ( P  > 0.05). Meta-analyses of independent subgroups at CACS levels ≤10 and ≤100 demonstrated high specificities of 90 (94–100)% and 88.5 (81–91.5)%, whereas at CACS levels ≥400 the specificity declined significantly to 42 (28–56)% but with consistently retained high sensitivity of 97.5 (94–99)%. The specificity of CTA decreases with increasing CACS, while the sensitivity remains high independent of that. The suggested CACS thresholds are arbitrary and do not necessarily warrant cancelling angiography. Diagnostic studies are needed to explore whether a specific CACS threshold may serve as a pre-angiographic gatekeeper to prevent likely equivocal angiographies.

ObjectivesTo develop and evaluate a multi-task deep-learning (DL) model for automated segment-level coronary artery calcium (CAC) scoring on non-contrast computed tomography (CT) for precise localization and quantification of calcifications in the coronary artery tree.MethodsThis study included 1514 patients (mean age, 60.0 ± 10.2 years; 56.0% female) with stable chest pain from 26 centers participating in the multicenter DISCHARGE trial (NCT02400229). The patients were randomly assigned to a training/validation set (1059) and a test set (455). We developed a multi-task neural network for performing the segmentation of calcifications on the segment level as the main task and the segmentation of coronary artery segment regions with weak annotations as an auxiliary task. Model performance was evaluated using (micro-average) sensitivity, specificity, F1-score, and weighted Cohen’s κ for segment-level agreement based on the Agatston score and performing interobserver variability analysis.ResultsIn the test set of 455 patients with 1797 calcifications, the model assigned 73.2% (1316/1797) to the correct coronary artery segment. The model achieved a micro-average sensitivity of 0.732 (95% CI: 0.710–0.754), a micro-average specificity of 0.978 (95% CI: 0.976–0.980), and a micro-average F1-score of 0.717 (95% CI: 0.695–0.739). The segment-level agreement was good with a weighted Cohen’s κ of 0.808 (95% CI: 0.790–0.824), which was only slightly lower than the agreement between the first and second observer (0.809 (95% CI: 0.798–0.845)).ConclusionAutomated segment-level CAC scoring using a multi-task neural network approach showed good agreement on the segment level, indicating that DL has the potential for automated coronary artery calcification classification.Critical relevance statementMulti-task deep learning can perform automated coronary calcium scoring on the segment level with good agreement and may contribute to the development of new and improved calcium scoring methods.Key PointsSegment-level coronary artery calcium scoring is a tedious and error-prone task.The proposed multi-task model achieved good agreement with a human observer on the segment level.Deep learning can contribute to the automation of segment-level coronary artery calcium scoring.

Vascular access and closure remain a challenge in transcatheter aortic valve replacement (TAVR). This single-center study aimed to report the incidence, predictive factors, and clinical outcomes of access-related vascular injury and subsequent vascular intervention. During a 30-month period, 365 patients underwent TAVR and 333 patients (94%) were treated by true percutaneous transfemoral approach. Of this latter group, 83 patients (25%) had an access-related vascular injury that was managed by the use of a covered self-expanding stent (n = 49), balloon angioplasty (n = 33), or by surgical intervention (n = 1). In 16 patients (5%), the vascular injury was classified as a major vascular complication. Absence of a preprocedural computed tomography angiography (CTA) of the iliofemoral arteries (OR 2.04, p = 0.007) and female gender (OR 2.18, p = 0.004) were independent predictors of the need for access-related vascular intervention. In addition, a high sheath/common femoral artery ratio as measured on preoperative CTA was associated with a higher rate of post-TAVR vascular intervention. The radiation dose, iodine contrast volume, transfusion need, length of hospitalization, and 30-day mortality were not significantly different between patients with versus without access-related vascular intervention. In conclusion, access-related vascular intervention in patients who underwent transfemoral-TAVR is not uncommon. Female gender and a high sheath/common femoral artery ratio are risk factors for access-related vascular injury, whereas preprocedural planning with CTA of the access vessels may reduce the risk of vascular injury. Importantly, most access-related vascular injuries may be treated by percutaneous techniques with similar clinical outcomes to patients without vascular injuries.

Background Classical risk scoring systems underestimate the risk of cardiovascular disease in chronic kidney disease (CKD). Coronary artery calcium score (CACS) has improved prediction of cardiovascular events in patients with CKD. The maximal carotid plaque thickness (cPTmax) measured in ultrasound scans of the carotid arteries has demonstrated similar predictive value as CACS in the general population. This is the first study to investigate whether cPTmax can predict cardiovascular events in CKD and to compare the predictive value of cPTmax and CACS in CKD. Method Two hundred patients with CKD stage 3 from the Copenhagen CKD Cohort underwent ultrasound scanning of the carotid arteries. The assessment consisted of locating plaque and measuring the thickest part of the plaque, cPTmax. Based on the distribution of cPTmax, the participants were divided into 3 groups: No plaques, cPTmax 1.0–1.9 mm and cPTmax > 1.9 mm (median cPTmax = 1.9 mm among patients with plaques). To measure CACS, 175 of the patients underwent a non-contrast CT scan of the coronary arteries. The follow-up time spanned between the ultrasound scan and a predefined end-date or the time of first event, defined as a composite of major cardiovascular events or death of any cause (MACE). Results The median follow-up time was 5.4 years during which 45 patients (22.5%) developed MACE. In a Cox-regression adjusted for classical cardiovascular risk factors, patients with cPTmax > 1.9 mm had a significantly increased hazard ratio of MACE (HR 3.2, CI: 1.1–9.3), p  = 0.031) compared to patients without plaques. C-statistics was used to evaluate models for predicting MACE. The improvement in C-statistics was similar for the two models including classical cardiovascular risk factors plus cPTmax (0.247, CI: 0.181–0.312) and CACS (0.243, CI: 0.172–0.315), respectively, when compared to a model only controlled for time since baseline (a Cox model with no covariates). Conclusion Our results indicate that cPTmax may be useful for predicting MACE in CKD. cPTmax and CACS showed similar ability to predict MACE.

Background Left ventricular mass (LVM) is an independent risk factor for the prediction of cardiac events. Its assessment is a clinically important diagnostic procedure in cardiology and may be performed by Computed Tomography (CT). The aim of this study was to assess the correlation between the cardiac left ventricular shell volume (LVShV) determined by postmortem Computed Tomography (PMCT) and the anatomic LVM obtained at autopsy and to calculate the myocardial tissue density. Methods A total of 109 deceased individuals were examined with a 64-slice CT scanner and LVShV was determined. At autopsy, the left ventricle was dissected and weighted. The correlation between LVShV and the anatomic LVM was analysed. Asymmetric left ventricular (LV) hypertrophy was recorded. Inter-observer variability was evaluated, and a density value for myocardial tissue was calculated. Results The mean age of the deceased was 55 ± 16 years, and 58% was men. We found 30 cases of asymmetric LV hypertrophy. A highly positive correlation existed between LVShV and anatomic LVM (r = 0.857; p  < 0.0001), regardless of hypertrophy, asymmetric hypertrophy and gender. The mean difference in the inter-observer variability for LVShV assessment was - 4.4 ml (95% CI: -26.4; 17.6). A linear regression analysis was performed, resulting in a value of 1.265 g/ml for myocardial tissue density. Applying the hitherto used myocardial tissue density of 1.055 g/ml underestimated the anatomic LVM by 18.1% ( p  < 0.0001). Conclusion PMCT is a helpful tool for the assessment of LVM, and LVShV is highly correlated with LVM as assessed by subsequent autopsy. The correlation between the two was independent of gender, hypertrophy and LV asymmetric hypertrophy. We found a higher myocardial tissue density of 1.265 g/ml compared to previous studies. We show that PMCT combined with autopsy may contribute not only to anatomical but also clinical knowledge.

Quantitative computed tomography (QCT) provides important prognostic information of coronary atherosclerosis. We investigated intraobserver and interobserver QCT reproducibility in asymptomatic individuals, patients with acute chest pain without acute coronary syndrome (ACS), and patients with acute chest pain and ACS. Fifty patients from each cohort, scanned between 01/02/2010-14/11/2013 and matched according to age and gender, were retrospectively assessed for inclusion. Patients with no coronary artery disease, previous coronary artery bypass graft surgery, and poor image quality were excluded. Coronary atherosclerosis was measured semi-automatically by 2 readers. Reproducibility of minimal lumen area (MLA), minimal lumen diameter (MLD), area stenosis, diameter stenosis, vessel remodeling, plaque eccentricity, plaque burden, and plaque volumes was assessed using concordance correlation coefficient (CCC), Bland-Altman, coefficient of variation, and Cohen's kappa. A total of 84 patients (63 matched) were included. Intraobserver and interobserver reproducibility estimates were acceptable for MLA (CCC = 0.94 and CCC = 0.91, respectively), MLD (CCC = 0.92 and CCC = 0.86, respectively), plaque burden (CCC = 0.86 and CCC = 0.80, respectively), and plaque volume (CCC = 0.97 and CCC = 0.95, respectively). QCT detected area and diameter stenosis ≥50%, positive remodeling, and eccentric plaque with moderate-good intraobserver and interobserver reproducibility (kappa: 0.64-0.66, 0.69-0.76, 0.46-0.48, and 0.41-0.62, respectively). Reproducibility of plaque composition decreased with decreasing plaque density (intraobserver and interobserver CCC for dense calcium (>0.99; 0.98), fibrotic (0.96; 0.93), fibro-fatty (0.95; 0.91), and necrotic core tissue (0.89; 0.84). Reproducibility generally decreased with worsening clinical risk profile. Semi-automated QCT of coronary plaque morphology is reproducible, albeit with some decline in reproducibility with worsening patient risk profile.