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We thank Dr Renker and colleagues for their interest in our manuscript examining temporal trends in the utilisation of cardiovascular imaging and their association with costs and healthcare outcomes

BackgroundIn 2016, the National Institute for Health and Care Excellence Clinical Guideline Number 95 (“Chest pain of recent onset”) (CG95) recommended coronary computed tomography angiography (CCTA) as the first-line test for possible angina.ObjectivesThe purpose of this study was to determine the impact of temporal trends in imaging use on outcomes for coronary artery disease (CAD) following the CG95 recommendations.MethodsInvestigations from 2012 to 2018 were extracted from a national database and linked-hospital admission and mortality registries. Growth rates were adjusted for population size, with image modality use, cardiovascular hospital admissions, and mortality compared using Kendall’s rank correlation. The impact of CG95 was assessed using an interrupted time-series analysis.ResultsA total of 1,909,314 investigations for CAD were performed, with an annualized per capita growth of 4.8%. Costs were £0.35 million/100,000 population/year with an increase of 2.8%/year mirroring inflation (2.5%/year). CG95 was associated with a rise in CCTA (exp[β]: 1.10; 95% CI: 1.03-1.18), no change in myocardial perfusion imaging, and a potential modest fall (exp[β]: 0.997; 95% CI: 0.993-1.00]) in invasive coronary angiography. There was an apparent trend between computed tomography angiography growth and invasive catheter angiography reduction across regions (Kendall Tau: −0.19; P = 0.08). CCTA growth was associated with a reduction in cardiovascular mortality (Kendall Tau: −0.21; P = 0.045), and ischemic heart disease deaths (Kendall Tau: −0.22; P = 0.042), with an apparent trend with reduced all-cause mortality (Kendall Tau: −0.19; P = 0.07).ConclusionsImaging investigations for CAD are increasing. Greater regional increases in CCTA were associated with fewer hospitalizations for myocardial infarction and a more rapid decline in CAD mortality.

BACKGROUND: Solitary pulmonary nodules (SPNs) measuring 8 to 30 mm in diameter require further workup to determine the likelihood of malignancy. RESEARCH QUESTION: What is the diagnostic performance of a lung cancer prediction convolutional neural network (LCP-CNN) in SPNs using unenhanced and contrast-enhanced CT imaging compared with the current clinical workup? STUDY DESIGN AND METHODS: This was a post hoc analysis of the Single Pulmonary Nodule Investigation: Accuracy and Cost-Effectiveness of Dynamic Contrast Enhanced Computed Tomography in the Characterisation of Solitary Pulmonary Nodules trial, a prospective multicenter study comparing the diagnostic accuracy of dynamic contrast-enhanced (DCE) CT imaging with PET imaging in SPNs. The LCP-CNN was designed and validated in an external cohort. LCP-CNN-generated risk scores were created from the noncontrast and contrast-enhanced CT scan images from the DCE CT imaging. The gold standard was histologic analysis or 2 years of follow-up. The area under the receiver operating characteristic curves (AUC) were calculated using LCP-CNN score, maximum standardized uptake value, and DCE CT scan maximum enhancement and were compared using the DeLong test. RESULTS: Two hundred seventy participants (mean ± SD age, 68.3 ± 8.8 years; 49% women) underwent PET with CT scan imaging and DCE CT imaging with CT scan data available centrally for LCP-CNN analysis. The accuracy of the LCP-CNN on the noncontrast images (AUC, 0.83; 95% CI, 0.79-0.88) was superior to that of DCE CT imaging (AUC, 0.76; 95% CI, 0.69-0.82; P = .03) and equal to that of PET with CT scan imaging (AUC, 0.86; 95% CI, 0.81-0.90; P = .35). The presence of contrast resulted in a small reduction in diagnostic accuracy, with the AUC falling from 0.83 (95% CI, 0.79-0.88) on the noncontrast images to 0.80 to 0.83 after contrast (P < .05 for 240 s after contrast only). INTERPRETATION: An LCP-CNN algorithm provides an AUC equivalent to PET with CT scan imaging in the diagnosis of solitary pulmonary nodules. TRIAL REGISTRATION: ClinicalTrials.gov Identifier; No.: NCT02013063.

Patrick SK Liu-Shiu-Cheong,1,2 Brian J Lipworth,3 Jonathan R Weir-McCall,1,4 J Graeme Houston,5 Allan D Struthers1 1Division of Molecular and Clinical Medicine, University of Dundee, Dundee DD1 9SY, UK; 2Department of Respiratory Medicine, Victoria Hospital, NHS Fife, Kirkcaldy KY2 5AH, UK; 3Scottish Centre for Respiratory Research, Medical Research Institute, University of Dundee, Dundee DD1 9SY, UK; 4Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; 5Imaging Science and Technology, University of Dundee, Dundee DD1 9SY, UKCorrespondence: Brian J LipworthScottish Centre for Respiratory Research, Medical Research Institute, University of Dundee, Ninewells Hospital, Dundee DD1 9SY, United KingdomTel +44 1382 383188Email b.j.lipworth@dundee.ac.ukBackground: Oxidative stress (OS) has been implicated in the development of pulmonary hypertension (PH) and ventricular hypertrophy. Xanthine oxidase is a well-recognised source of reactive oxygen species, which lead to OS. The aim of this proof of concept study was to assess whether allopurinol (xanthine oxidase inhibitor) would reduce right ventricular mass (RVM) in patients with PH-associated chronic lung disease (PH-CLD).Methods: We conducted a randomised, double-blind, parallel-group, placebo-controlled trial in patients with PH-CLD (93% COPD, 7% IPF) who were randomly assigned to receive allopurinol or placebo for 12 months. The primary outcome was the mean change in RVM, as assessed by cardiac magnetic resonance imaging (CMRI). Secondary outcomes included quality of life (QOL), spirometry and six-minute walk test (6MWT).Results: Seventy-one patients were recruited: mean age 71 years, mean pulmonary arterialpressure 30 mm Hg, FEV1 60% and resting SpO2 96%. After 12 months, there was no significant difference in the change in RVM from baseline (allopurinol 1.85g vs placebo 0.97g with mean difference 0.88g, CI − 4.77 to 3.01, p =0.7). There were also no significant changes in other cardiac parameters measured on MRI, in QOL, spirometry and 6MWT. Subgroup analysis showed that allopurinol significantly reduced RVM compared to placebo with -6.16g vs 0.75g and mean difference 6.92g (CI 1.14 to 12.69, p = 0.02) in COPD patients with more severe airflow limitation.Conclusion: Allopurinol had no overall impact on patients with PH-CLD but had potential benefit in COPD patients with more severe airflow limitation.Keywords: pulmonary hypertension, right ventricle, allopurinol, chronic lung disease

Fractional flow reserve derived from CT is a rapidly developing technique, with an increasing burden of literature supporting its potential role in the workup of patients suspected of having coronary artery disease.

BACKGROUND: CT measurement of supra-annular area (SA) has been proposed as an alternative to annular area (AA) for sizing of trancatheter valves in biscuspid aortic valves (BAV). This study examines the reproducibility of SA and AA measurements and their potential impact on downstream transcatheter heart valve sizing and clinical outcomes. METHODS: 44 consecutive patients (mean age: 73 ± 15 years, 57% male) undergoing CTA with subsequent SAPIEN 3 valve insertion for severe bicuspid aortic stenosis (AS) were included. AA was measured at the basal ring. SA was measured by generating a circle defined by the intercommisural distance. AA and SA were measured by 2 independent observers. Baseline characteristics, TAVR procedural data, and discharge echocardiography data were collected. RESULTS: The SA was significantly larger than the AA (562 ± 146mm2 vs. 518 ± 112mm2,p = 0.013). Interobserver agreement was high using both techniques (ICC AA = 0.98,p < 0.001; SA = 0.80,p < 0.001), but with narrower limits of agreement with AA measurements (mean difference (limits of agreement): AA = -3mm2 (22; 19), SA = -16mm2 (-92; 76)). AA-based device sizing demonstrated substantial agreement with final valve inserted (κ = 0.72,p < 0.001), while SA demonstrated fair agreement (κ = 0.40,p < 0.001). There was no difference in post TAVR gradients, paravalvular leakage or valve success between patients with concordant sizing between AA and SA, and those in whom SA would have suggested an alternate valve size. CONCLUSIONS: Supra-annular sizing is less reproducible than annular sizing, with no difference in procedural complication rates in patients in whom supra-annular sizing would have altered the device size used. These results suggest no role for supra-annular sizing in current clinical practice.

Transcatheter mitral valve replacement (TMVR) has emerged as a promising technique for the treatment of these patients with severe mitral valve disease and high or prohibitive surgical risk. Early experience with TMVR has shown a high rate of technical success and promising reductions in the severity of mitral regurgitation sustained out to 1 year post procedure. Despite this, procedural complications remain high, with the most common and significant of these being valve embolization, left ventricualr outflow tract (LVOT) obstruction and paravalvular leakage (PVL). It is this currently unanswered question that Morris et al. start to address in this issue of the Journal. They use the same annular segmentation and valve simulation as already proposed to predict LVOT obstruction, but use it to focus instead on examining the residual gap left between the base of the simulated transcatheter valve and the mitral leaflets or surgical prosthesis.

The 14th Annual Scientific Meeting of the SCCT, held from July 11 to July 14 in Baltimore, MA, was attended by 830 attendees from 31 countries, with a program that included 45 sessions, and 26 exhibitors. This article summarizes several of the key themes and topics that were presented at this meeting, and provides an overview of the technical advances that are likely to impact future clinical practice in cardiovascular computed tomography.

OBJECTIVE: The aim of the current study was to determine the effects of gadolinium contrast agent on right (RV) and left ventricular (LV) volumetric, aortic flow and pulse wave velocity (PWV) quantification using manual, semi-automatic and fully automatic analysis techniques. METHODS: 61 participants free from known cardiovascular disease were recruited. Cardiac MR was performed on a 3 T scanner. A balanced steady-state free precession stack was acquired of the ventricles with phase contrast imaging of the aorta performed pre- and post-administration of 10 ml 0.5 mmol ml-1 gadoterate meglumine. The images were analysed manually, and using a semi-automated and a fully automated technique. RESULTS: 54 completed the study. Gadolinium-based contrast administration significantly increase the signal-to-noise ratio (pre: 830 ± 398 vs post: 1028 ± 540, p = 0.003) with no significant change in contrast-to-noise ratio (pre: 583 ± 302 vs post: 559 ± 346, p = 0.54). On LV analysis, post-contrast analysis yielded significantly higher end systolic volume (54 ± 20 vs 57 ± 18 ml, p = 0.04), and lower ejection fraction (59 ± 9 vs 57 ± 8%, p = 0.023). On RV analysis, gadolinium contrast resulted in no significant differences. Similar results were seen using the semi-automated and fully-automated techniques but with a larger magnitude of difference. Conversely, using both manual and software analysis aortic flow and PWV quantification proved robust to the effects of contrast agent producing only small non-significant differences. CONCLUSION: Gadolinium contrast administration significantly alters LV endocardial contour detection with this effect amplified when using semi-automated analysis techniques. In comparison, RV and PWV analysis is robust to these effects. Advances in knowledge: Contrast administration alters LV quantification but not flow analysis. However, these differences are small.

BACKGROUND: Pulmonary pulse wave velocity (PWV) allows the non-invasive measurement of pulmonary arterial stiffening, but has not previously been assessed in COPD. The aim of the current study was to assess PWV in COPD and its association with right ventricular (RV) remodelling. METHODS: Fifty-eight participants with COPD underwent pulmonary function tests, 6-min walk test and cardiac MRI, while 21 healthy controls (HCs) underwent cardiac MRI. Thirty-two COPD patients underwent a follow-up MRI to assess for longitudinal changes in RV metrics. Cardiac MRI was used to quantify RV mass, volumes and PWV. Differences in continuous variables between the COPD and HC groups was tested using an independent t-test, and associations between PWV and right ventricular parameters was examined using Pearson's correlation coefficient. RESULTS: Those with COPD had reduced pulsatility (COPD (mean±SD):24.88±8.84% vs. HC:30.55±11.28%, p=0.021), pulmonary acceleration time (COPD:104.0±22.9ms vs. HC: 128.1±32.2ms, p

The TASCFORCE study (Tayside Screening for Cardiovascular Events) was funded by the Souter Charitable Foundation and the Chest, Heart and Stroke Scotland Charity. The SUMMIT study (Surrogate Markers of Micro- and Macrovascular Hard End-Points for Innovative Diabetes Tools) was supported by the Innovative Medicines Initiative (the SUMMIT consortium, IMI-2008/115006). The initial stages of the CaPS (Caerphilly Prospective Study) was funded by the MRC with a grant from the British Heart Foundation funding the measurement of the pulse wave velocity. The statistician was funded by TENOVUS, Tayside. J.R. Weir-McCall is supported by the Wellcome Trust through the Scottish Translational Medicine and Therapeutics Initiative (Grant no. WT 085664) in the form of a Clinical Research Fellowship. C.M. McEniery is supported by the NIHR (National Institute of Health Research) Cambridge Biomedical Research Centre. Current distance measurement techniques for pulse wave velocity (PWV) calculation are susceptible to intercenter variability. The aim of this study was to derive and validate a formula for this distance measurement. Based on carotid femoral distance in 1183 whole-body magnetic resonance angiograms, a formula was derived for calculating distance. This was compared with distance measurements in 128 whole-body magnetic resonance angiograms from a second study. The effects of recalculation of PWV using the new formula on association with risk factors, disease discrimination, and prediction of major adverse cardiovascular events were examined within 1242 participants from the multicenter SUMMIT study (Surrogate Markers of Micro- and Macrovascular Hard End-Points for Innovative Diabetes Tools) and 825 participants from the Caerphilly Prospective Study. The distance formula yielded a mean error of 7.8 mm (limits of agreement =−41.1 to 56.7 mm; P

Contract grant sponsor: Souter Charitable Trust, and Chest, Heart and Stroke Scotland; Contract grant sponsor: Wellcome Trust; contract grant number: WT 085664 (Clinical Research Fellowship to J.W-McC.) Purpose: To scan a volunteer population using 3.0T magnetic resonance imaging (MRI). MRI of the left ventricular (LV) structure and function in healthy volunteers has been reported extensively at 1.5T. Materials and Methods: A population of 1528 volunteers was scanned. A standardized approach was taken to acquire steady-state free precession (SSFP) LV data in the short-axis plane, and images were quantified using commercial software. Six observers undertook the segmentation analysis. Results: Mean values (±standard deviation, SD) were: ejection fraction (EF) = 69 ± 6%, end diastolic volume index (EDVI) = 71 ± 13 ml/m2 , end systolic volume index (ESVI) = 22 ± 7 ml/m2 , stroke volume index (SVI) = 49 ± 8 ml/m2 , and LV mass index (LVMI) = 55 ± 12 g/m2 . The mean EF was slightly larger for females (69%) than for males (68%), but all other variables were smaller for females (EDVI 68v77 ml/m2 , ESVI 21v25 ml/m2 , SVI 46v52 ml/m2 , LVMI 49v64 g/m2, all P < 0.05). The mean LV volume data mostly decreased with each age decade (EDVI males: -2.9 ± 1.3 ml/m2 , females: -3.1 ± 0.8 ml/m2 ; ESVI males: -1.3 ± 0.7 ml/m2 , females: -1.7 ± 0.5 ml/m2 ; SVI males: -1.7 ± 0.9 ml/m2 , females: -1.4 ± 0.6 ml/m2 ; LVMI males: -1.6 ± 1.1 g/m2 , females: -0.2 ± 0.6 g/m2 but the mean EF was virtually stable in males (0.6 ± 0.6%) and rose slightly in females (1.2 ± 0.5%) with age. Conclusion: LV reference ranges are provided in this population-based MR study at 3.0T. The variables are similar to those described at 1.5T, including variations with age and gender. These data may help to support future population-based MR research studies that involve the use of 3.0T MRI scanners. Publisher PDF

Machine learning methods offer great promise for fast and accurate detection and prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest radiographs (CXR) and chest computed tomography (CT) images. Many articles have been published in 2020 describing new machine learning-based models for both of these tasks, but it is unclear which are of potential clinical utility. In this systematic review, we consider all published papers and preprints, for the period from 1 January 2020 to 3 October 2020, which describe new machine learning models for the diagnosis or prognosis of COVID-19 from CXR or CT images. All manuscripts uploaded to bioRxiv, medRxiv and arXiv along with all entries in EMBASE and MEDLINE in this timeframe are considered. Our search identified 2,212 studies, of which 415 were included after initial screening and, after quality screening, 62 studies were included in this systematic review. Our review finds that none of the models identified are of potential clinical use due to methodological flaws and/or underlying biases. This is a major weakness, given the urgency with which validated COVID-19 models are needed. To address this, we give many recommendations which, if followed, will solve these issues and lead to higher-quality model development and well-documented manuscripts.

BACKGROUND: Epicardial adipose tissue (EAT) is an emerging cardio-metabolic risk factor and has been shown to correlate with adverse cardiovascular (CV) outcome; however the underlying pathophysiology of this link is not well understood. The aim of this study was to evaluate the relationship between EAT and a comprehensive panel of cardiovascular risk biomarkers and pulse wave velocity (PWV) and indexed left ventricular mass (LVMI) in a cohort of patients with cardiovascular disease (CVD) and diabetes compared to controls. METHODS: One hundred forty-five participants (mean age 63.9 ± 8.1 years; 61% male) were evaluated. All patients underwent cardiovascular magnetic resonance (CMR) examination and PWV. EAT measurements from CMR were performed on the 4-chamber view. Blood samples were taken and a range of CV biomarkers was evaluated. RESULTS: EAT measurements were significantly higher in the groups with CVD, with or without T2DM compared to patients without CVD or T2DM (group 1 EAT 15.9 ± 5.5 cm2 vs. group 4 EAT 11.8 ± 4.1 cm2, p = 0.001; group 3 EAT 15.1 ± 4.3 cm2 vs. group 4 EAT 11.8 ± 4.1 cm2, p = 0.024). EAT was independently associated with IL-6 (beta 0.2, p = 0.019). When added to clinical variables, both EAT (beta 0.16, p = 0.035) and IL-6 (beta 0.26, p = 0.003) were independently associated with PWV. EAT was significantly associated with LVMI in a univariable analysis but not when added to significant clinical variables. CONCLUSIONS: In patients with cardio-metabolic disease, EAT was independently associated with PWV. EAT may be associated with CVD risk due to an increase in systemic vascular inflammation. Whether targeting EAT may reduce inflammation and/or cardiovascular risk should be evaluated in prospective studies.

Purpose To quantify the burden and distribution of asymptomatic atherosclerosis in a population with a low to intermediate risk of cardiovascular disease. Materials and Methods Between June 2008 and February 2013, 1528 participants with 10-year risk of cardiovascular disease less than 20% were prospectively enrolled. They underwent whole-body magnetic resonance (MR) angiography at 3.0 T by using a two-injection, four-station acquisition technique. Thirty-one arterial segments were scored according to maximum stenosis. Scores were summed and normalized for the number of assessable arterial segments to provide a standardized atheroma score (SAS). Multiple linear regression was performed to assess effects of risk factors on atheroma burden. Results A total of 1513 participants (577 [37.9%] men; median age, 53.5 years; range, 40-83 years) completed the study protocol. Among 46 903 potentially analyzable segments, 46 601 (99.4%) were interpretable. Among these, 2468 segments (5%) demonstrated stenoses, of which 1649 (3.5%) showed stenosis less than 50% and 484 (1.0%) showed stenosis greater than or equal to 50%. Vascular stenoses were distributed throughout the body with no localized distribution. Seven hundred forty-seven (49.4%) participants had at least one stenotic vessel, and 408 (27.0%) participants had multiple stenotic vessels. At multivariable linear regression, SAS correlated with age (B = 3.4; 95% confidence interval: 2.61, 4.20), heart rate (B = 1.23; 95% confidence interval: 0.51, 1.95), systolic blood pressure (B = 0.02; 95% confidence interval: 0.01, 0.03), smoking status (B = 0.79; 95% confidence interval: 0.44, 1.15), and socioeconomic status (B = -0.06; 95% confidence interval: -0.10, -0.02) (P < .01 for all). Conclusion Whole-body MR angiography identifies early vascular disease at a population level. Although disease prevalence is low on a per-vessel level, vascular disease is common on a per-participant level, even in this low- to intermediate-risk cohort. © RSNA, 2018 Online supplemental material is available for this article.

Radiomics, quantitative feature extraction from radiological images, can improve disease diagnosis and prognostication. However, radiomic features are susceptible to image acquisition and segmentation variability. Ideally, only features robust to these variations would be incorporated into predictive models, for good generalisability. We extracted 93 radiomic features from carotid artery computed tomography angiograms of 41 patients with cerebrovascular events. We tested feature robustness to region-of-interest perturbations, image pre-processing settings and quantisation methods using both single- and multi-slice approaches. We assessed the ability of the most robust features to identify culprit and non-culprit arteries using several machine learning algorithms and report the average area under the curve (AUC) from five-fold cross validation. Multi-slice features were superior to single for producing robust radiomic features (67 vs. 61). The optimal image quantisation method used bin widths of 25 or 30. Incorporating our top 10 non-redundant robust radiomics features into ElasticNet achieved an AUC of 0.73 and accuracy of 69% (compared to carotid calcification alone [AUC: 0.44, accuracy: 46%]). Our results provide key information for introducing carotid CT radiomics into clinical practice. If validated prospectively, our robust carotid radiomic set could improve stroke prediction and target therapies to those at highest risk.

BACKGROUND: Pulmonary pulse wave velocity (PWV) allows the non-invasive measurement of pulmonary arterial stiffening, but has not previously been assessed in COPD. The aim of the current study was to assess PWV in COPD and its association with right ventricular (RV) remodelling. METHODS: Fifty-eight participants with COPD underwent pulmonary function tests, 6-min walk test and cardiac MRI, while 21 healthy controls (HCs) underwent cardiac MRI. Thirty-two COPD patients underwent a follow-up MRI to assess for longitudinal changes in RV metrics. Cardiac MRI was used to quantify RV mass, volumes and PWV. Differences in continuous variables between the COPD and HC groups was tested using an independent t-test, and associations between PWV and right ventricular parameters was examined using Pearson's correlation coefficient. RESULTS: Those with COPD had reduced pulsatility (COPD (mean±SD):24.88±8.84% vs. HC:30.55±11.28%, p=0.021), pulmonary acceleration time (COPD:104.0±22.9ms vs. HC: 128.1±32.2ms, p

Funder: School of Clinical Medicine, University of Cambridge; doi: http://dx.doi.org/10.13039/501100007552, Funder: Frank Edward Elmore Fund, Funder: National Institute for Health Research (NIHR) Imperial Biomedical Research Centre, Funder: British Heart Foundation Cambridge Centre of Research Excellence, Funder: Royal College of Surgeons of England; doi: http://dx.doi.org/10.13039/501100000297, Funder: Cancer Research UK; doi: http://dx.doi.org/10.13039/501100000289, Funder: AstraZeneca Oncology R, Funder: National Institute for Health Research; doi: http://dx.doi.org/10.13039/501100000272, Funder: Leverhulme Trust; doi: http://dx.doi.org/10.13039/501100000275, Funder: Cantab Capital Institute for the Mathematics of Information, Funder: Alan Turing Institute; doi: http://dx.doi.org/10.13039/100012338, Funder: NIHR Cambridge Biomedical Research Centre, Funder: Higher Education Funding Council for England; doi: http://dx.doi.org/10.13039/501100000384, Radiomics, quantitative feature extraction from radiological images, can improve disease diagnosis and prognostication. However, radiomic features are susceptible to image acquisition and segmentation variability. Ideally, only features robust to these variations would be incorporated into predictive models, for good generalisability. We extracted 93 radiomic features from carotid artery computed tomography angiograms of 41 patients with cerebrovascular events. We tested feature robustness to region-of-interest perturbations, image pre-processing settings and quantisation methods using both single- and multi-slice approaches. We assessed the ability of the most robust features to identify culprit and non-culprit arteries using several machine learning algorithms and report the average area under the curve (AUC) from five-fold cross validation. Multi-slice features were superior to single for producing robust radiomic features (67 vs. 61). The optimal image quantisation method used bin widths of 25 or 30. Incorporating our top 10 non-redundant robust radiomics features into ElasticNet achieved an AUC of 0.73 and accuracy of 69% (compared to carotid calcification alone [AUC: 0.44, accuracy: 46%]). Our results provide key information for introducing carotid CT radiomics into clinical practice. If validated prospectively, our robust carotid radiomic set could improve stroke prediction and target therapies to those at highest risk.

Introduction Dynamic contrast-enhanced CT (DCE-CT) and positron emission tomography/CT (PET/CT) have a high reported accuracy for the diagnosis of malignancy in solitary pulmonary nodules (SPNs). The aim of this study was to compare the accuracy and cost-effectiveness of these. Methods In this prospective multicentre trial, 380 participants with an SPN (8–30 mm) and no recent history of malignancy underwent DCE-CT and PET/CT. All patients underwent either biopsy with histological diagnosis or completed CT follow-up. Primary outcome measures were sensitivity, specificity and overall diagnostic accuracy for PET/CT and DCE-CT. Costs and cost-effectiveness were estimated from a healthcare provider perspective using a decision-model. Results 312 participants (47% female, 68.1±9.0 years) completed the study, with 61% rate of malignancy at 2 years. The sensitivity, specificity, positive predictive value and negative predictive values for DCE-CT were 95.3% (95% CI 91.3 to 97.5), 29.8% (95% CI 22.3 to 38.4), 68.2% (95% CI 62.4% to 73.5%) and 80.0% (95% CI 66.2 to 89.1), respectively, and for PET/CT were 79.1% (95% CI 72.7 to 84.2), 81.8% (95% CI 74.0 to 87.7), 87.3% (95% CI 81.5 to 91.5) and 71.2% (95% CI 63.2 to 78.1). The area under the receiver operator characteristic curve (AUROC) for DCE-CT and PET/CT was 0.62 (95% CI 0.58 to 0.67) and 0.80 (95% CI 0.76 to 0.85), respectively (p Conclusions PET/CT has a superior diagnostic accuracy to DCE-CT for the diagnosis of SPNs. Combining both techniques improves the diagnostic accuracy over either test alone and could be cost-effective.

Background Coronary artery fractional flow reserve (FFR) derived from CT angiography (FFTCT) enables functional assessment of coronary stenosis. Prior clinical trials showed 13%-33% of coronary CT angiography studies had insufficient quality for quantitative analysis with FFRCT. Purpose To determine the rejection rate of FFRCT analysis and to determine factors associated with technically unsuccessful calculation of FFRCT. Materials and Methods Prospectively acquired coronary CT angiography scans submitted as part of the Assessing Diagnostic Value of Noninvasive FFRCT in Coronary Care (ADVANCE) registry (https://ClinicalTrials.gov: NCT02499679) and coronary CT angiography series submitted for clinical analysis were included. The primary outcome was the FFRCT rejection rate (defined as an inability to perform quantitative analysis with FFRCT). Factors that were associated with FFRCT rejection rate were assessed with multiple linear regression. Results In the ADVANCE registry, FFRCT rejection rate due to inadequate image quality was 2.9% (80 of 2778 patients; 95% confidence interval [CI]: 2.1%, 3.2%). In the 10 621 consecutive patients who underwent clinical analysis, the FFRCT rejection rate was 8.4% (n = 892; 95% CI: 6.2%, 7.2%; P < .001 vs the ADVANCE cohort). The main reason for the inability to perform FFRCT analysis was the presence of motion artifacts (63 of 80 [78%] and 729 of 892 [64%] in the ADVANCE and clinical cohorts, respectively). At multivariable analysis, section thickness in the ADVANCE (odds ratio [OR], 1.04; 95% CI: 1.001, 1.09; P = .045) and clinical (OR, 1.03; 95% CI: 1.02, 1.04; P < .001) cohorts and heart rate in the ADVANCE (OR, 1.05; 95% CI: 1.02, 1.08; P < .001) and clinical (OR, 1.06; 95% CI: 1.05, 1.07; P < .001) cohorts were independent predictors of rejection. Conclusion The rates for technically unsuccessful CT-derived fractional flow reserve in the ADVANCE registry and in a large clinical cohort were 2.9% and 8.4%, respectively. Thinner CT section thickness and lower patient heart rate may increase rates of completion of CT fractional flow reserve analysis. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Sakuma in this issue.

ObjectiveThis cross-sectional observational study sought to describe variations in CT in the context of transcatheter aortic valve implantation (CT-TAVI) as currently performed in the UK.Methods408 members of the British Society of Cardiovascular Imaging were invited to complete a 27-item online CT-TAVI survey.Results47 responses (12% response rate) were received from 40 cardiac centres, 23 (58%) of which performed TAVI on-site (TAVI centres). Only six respondents (13%) performed high-volume activity (>200 scans per year) compared with 13 (28%) performing moderate (100–200 scans per year) and 27 (59%) performing low (0–99 scans per year) volume activity. Acquisition protocols varied (41% retrospective, 12% prospective with wide padding, 47% prospective with narrow padding), as did the phase of reporting (45% systolic, 37% diastolic, 11% both, 6% unreported). Median dose length product was 675 mGy.cm (IQR 477–954 mGy.cm). Compared with non-TAVI centres, TAVI centres were more likely to report minimum iliofemoral luminal diameter (n=25, 96% vs n=7, 58%, p=0.003) and optimal tube angulation for intervention (n=12, 46% vs n=1, 8%, p=0.02).ConclusionsThis national survey formally describes current CT-TAVI practice in the UK. High-volume activity was only present at one in seven cardiac CT centres. There is wide variation in scan acquisition, scan reporting and radiation dose exposure in cardiac CT centres.