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AIMS: Remote dielectric sensing (ReDS) enables quick estimation of lung fluid content. To examine if ReDS is superior to other methods in detecting acute heart failure.METHODS AND RESULTS: We included consecutive patients with dyspnoea from the emergency departments at Bispebjerg Hospital, Copenhagen, and performed ReDS, low-dose chest computed tomography (CT), echocardiogram, lung ultrasound, NT-Pro-brain natriuretic peptide (NT-proBNP), and a Boston score evaluation (chest X-ray and clinical signs). ReDS values >35% were used as a cut-off to diagnose pulmonary congestion. Acute heart failure was adjudicated by experts' review of health records but independently of ReDS values. Sub-analyses investigated ReDS in acute heart failure patients with congestion on CT. We included 97 patients within a median of 4.8 h from admittance: 25 patients (26%) were ReDS-positive and 39 (40%) had adjudicated acute heart failure (21 with and 18 without CT congestion). Heart failure patients had median ReDS 33%, left ventricular ejection fraction 48%, and NT-proBNP 2935 ng/L. A positive ReDS detected heart failure with 46% sensitivity, 88% specificity, and 71% accuracy. The AUC for ReDS was like the Boston score (P = 0.88) and the lung ultrasound score (P = 0.74). CT-congested heart failure patients had higher ReDS values than patients without heart failure (median 38 vs. 28%, P < 0.001). Heart failure patients without CT-congestion had ReDS values like patients without heart failure (mean 30 vs. 28%, P = 0.07).CONCLUSION: ReDS detects acute heart failure similarly to the Boston score and lung ultrasound score, and ReDS primarily identifies the acute heart failure patients who have congestion on a chest CT.

Background: Pulmonary congestion is a key component of heart failure (HF) that chest computed tomography (CT) can detect. However, no guideline describes which of many anticipated CT signs are most associated with HF in patients with undifferentiated dyspnea. Methods: In a prospective observational single-center study, we included consecutive patients ≥ 50 years admitted with acute dyspnea to the emergency department. Patients underwent immediate clinical examination, blood sampling, echocardiography, and CT. Two radiologists independently evaluated all images. Acute HF (AHF) was adjudicated by an expert panel blinded to radiology images. LASSO and logistic regression identified the independent CT signs of AHF. Results: Among 232 patients, 102 (44%) had AHF. Of 18 examined CT signs, 5 were associated with AHF (multivariate odds ratio, 95% confidence interval): enlarged heart (20.38, 6.86–76.16), bilateral interlobular thickening (11.67, 1.78–230.99), bilateral pleural effusion (6.39, 1.98–22.85), and increased vascular diameter (4.49, 1.08–33.92). Bilateral ground-glass opacification (2.07, 0.95–4.52) was a consistent fifth essential sign, although it was only significant in univariate analysis. Eighty-eight (38%) patients had none of the five CT signs corresponding to a 68% specificity and 86% sensitivity for AHF, while two or more of the five CT signs occurred in 68 (29%) patients, corresponding to 97% specificity and 67% sensitivity. A weighted score based on these five CT signs had an 0.88 area under the curve to detect AHF. Conclusions: Five CT signs seem sufficient to assess the risk of AHF in the acute setting. The absence of these signs indicates a low probability, one sign makes AHF highly probable, and two or more CT signs mean almost certain AHF.

Background: Chest x-ray is central in screening and diagnosis of tuberculosis. However, sputum culture remains gold standard for diagnosis. Aim: To establish the rate of normal chest x-rays in tuberculosis patients found by spot sputum culture screening, and compare them to a group identified through passive case finding. Method: Chest x-rays from 39 culture-positive patients, identified by spot sputum culture screening in Copenhagen from 2012 to 2014, were included in the study (spot sputum culture group(SSC)). 39 normal chest x-rays from persons screened by mobile x-ray, and 39 chest x-rays from tuberculosis-patients identified through passive case finding(PCF) were anonymised and randomised. Two respiratory physicians and two radiologists assessed the chest x-rays. Results: The normal chest x-ray rate was higher in the non-tuberculosis control group (median = 32 (82.1%), range = 74.4% – 100%), compared to the SSC group (median = 7 (17.9%), range = 10.3% – 33.3%), and the PCF controls (median = 3(7.7%), range = 2.6% – 15.4%). In the SSC group 14 (35.9%) were categorized as normal by at least one study participant. Conclusion: A substantial minority of patients diagnosed with tuberculosis by spot sputum culture screening, and through passive case finding would not have been identified with chest x-ray alone, highlighting that a normal chest x-ray does not exclude pulmonary tuberculosis.

The advent of computed tomography screening for lung cancer will increase the incidence of ground-glass opacity (GGO) nodules detected and referred for diagnostic evaluation and management. GGO nodules remain a diagnostic challenge; therefore, a more systematic approach is necessary to ensure correct diagnosis and optimal management. Here we present the latest advances in the radiologic imaging and pathology of GGO nodules, demonstrating that radiologic features are increasingly predictive of the pathology of GGO nodules. We review the current guidelines from the Fleischner Society, the National Comprehensive Cancer Network, and the British Thoracic Society. In addition, we discuss the management and follow-up of GGO nodules in the light of experience from screening trials. Minimally invasive tissue biopsies and the marking of GGO nodules for surgery are new and rapidly developing fields that will yield improvements in both diagnosis and treatment. The standard-of-care surgical treatment of early lung cancer is still minimally invasive lobectomy with systematic lymph node dissection. However, recent research has shown that some GGO lesions may be treated with sublobar resections; these findings may expand the surgical treatment options available in the future.

OBJECTIVES: It remains unknown whether non-electrocardiogram-gated coronary artery calcium (CAC) score in lung cancer screening provides incremental prognostic value. The aim of this study was to evaluate the prognostic value of CAC in the Danish Lung Cancer Screening Trial (DLCST), in addition to conducting a systematic review and meta-analysis including previously published studies regarding CAC in lung cancer screening.DESIGN: In DLCST, we measured Agatston CAC scores in 1,945 current and former smokers. Causes of death were extracted from the Danish National Death Registry. We used Cox proportional hazards model to determine hazard ratios (HRs) of CAC scores. A weighted fixed-effects model was used for the meta-analysis.RESULTS: Median follow-up in DLCST was 7.1 years, and 55% were men. Overall survival rates associated with CAC scores of 0, 1-400, and > 400 were 98%, 96%, and 92% (p < 0.001), respectively. Adjusted HR of cardiovascular death associated with CAC >400 was 3.8 (1.0-15) (p < 0.05). The meta-analysis included 28,045 asymptomatic participants. A high non-gated CAC score was associated with fatal or non-fatal cardiovascular events (p < 0.0001).CONCLUSION: Assessment of non-electrocardiogram-gated CAC in lung cancer screening programs is a robust prognostic measure of fatal or non-fatal cardiovascular events in current and former smokers independent of traditional cardiovascular risk factors.

We present a fast and robust atlas-based algorithm for labeling airway trees, using geodesic distances in a geometric tree-space. Possible branch label configurations for an unlabeled airway tree are evaluated using distances to a training set of labeled airway trees. In tree-space, airway tree topology and geometry change continuously, giving a natural automatic handling of anatomical differences and noise. A hierarchical approach makes the algorithm efficient, assigning labels from the trachea and downwards. Only the airway centerline tree is used, which is relatively unaffected by pathology. The algorithm is evaluated on 80 segmented airway trees from 40 subjects at two time points, labeled by 3 medical experts each, testing accuracy, reproducibility and robustness in patients with Chronic Obstructive Pulmonary Disease (COPD). The accuracy of the algorithm is statistically similar to that of the experts and not significantly correlated with COPD severity. The reproducibility of the algorithm is significantly better than that of the experts, and negatively correlated with COPD severity. Evaluation of the algorithm on a longitudinal set of 8724 trees from a lung cancer screening trial shows that the algorithm can be used in large scale studies with high reproducibility, and that the negative correlation of reproducibility with COPD severity can be explained by missing branches, for instance due to segmentation problems in COPD patients. We conclude that the algorithm is robust to COPD severity given equally complete airway trees, and comparable in performance to that of experts in pulmonary medicine, emphasizing the suitability of the labeling algorithm for clinical use.

Lung cancer is the cancer type that causes the largest number of deaths in Denmark. With advances in medical imaging and widespread use of computed tomography (CT), it is possible to detect even small abnormalities in lung tissue. This has led to a great interest in lung cancer screening with low-dose CT and launching of randomised screening trials worldwide. This paper gives an overview of the current lung cancer screening trials in Denmark and internationally and focuses on main lung cancer findings and mortality results.

Results from the American National Lung Screening Trial (NLST) show a significant reduction in lung cancer and all-cause mortality in a high risk population screened with annual low-dose CT. Handling of pulmonary nodules, false positive tests, overdiagnosis, psychosocial consequences and cost-efficiency etc. are all aspects that require careful consideration. This paper gives an overview of the current knowledge on these issues. Before a recommendation can be made, we need an overall evaluation of both the benefits and harms in CT screening for lung cancer.

Purpose: Assessing airway dimensions and attenuation from CT images is useful in the study of diseases affecting the airways such as Chronic Obstructive Pulmonary Disease (COPD). Measurements can be compared between patients and over time if specific airway segments can be identified. However, manually finding these segments and performing such measurements is very time consuming. The purpose of the developed and validated system is to enable such measurements using automatic segmentations of the airway interior and exterior wall surfaces in three dimensions, anatomical branch labeling of all segmental branches, and longitudinal matching of airway branches in repeated scans of the same subject. Methods and Materials: The segmentation process begins from an automatically detected seed point in the trachea. The airway centerline tree is then constructed by iteratively adding locally optimal paths that most resemble the airway centerlines based on a statistical model derived from a training set. A full segmentation of the wall surfaces is then extracted around the centerline, using a graph based approach, which simultaneously detects both surfaces using image gradients. Deformable image registration is used to match specific airway segments in multiple images of the same subject. The anatomical names of all segmental branches are assigned based on distances to a training set of expert labeled trees. Distances are measured in a geometric tree-space, incorporating both topology and centerline shape differences. Results: The segmentation method has been used on 9711 low dose CT images from the Danish Lung Cancer Screening Trial (DLCST). Manual inspection of thumbnail images revealed gross errors in a total of 44 images. 29 were missing branches at the lobar level and only 15 had obvious false positives. A thorough inspection of 10 randomly selected images, revealed the method extracted 174 branches on average and only 3.79% of the fou

Purpose: Quantitative airway assessment is often performed in specific branches to enable comparison of measurements between patients and over time. Little is known on the accuracy in locating these branches. We determined inter- and intra-observer agreement of manual labeling of segmental bronchi from low-dose chest CT scans. Methods and Materials: We selected 40 participants of the Danish Lung Cancer Screening Trial, 10 of each category: asymptomatic, mild, moderate, and severe COPD. Each subject contributed 2 CT scans with an average interval of 4 years. The airways were segmented automatically using in-house developed software. Three trained observers placed labels L1-L10 and R1-R10 in each of the images, using 3D visualization and reformatted cross-sectional views. Inter-expert agreement for each segmental bronchus for a pair of experts was defined as the percentage of images in which both experts assigned that label to the same branch. Automatic deformable image registration was used to determine corresponding branches in the two scans of the same subject. Intra-expert agreement for a bronchus was then defined as the percentage of image pairs in which the expert assigned the label to the same branch in both scans. Results: Average inter-expert agreement was 73.9% (range 38.8%-100.0%). Agreement was lowest in the lower left lobe (55.0% for L7-L10), and largest in R6 and L6 (95.0% and 99.2%). Average intra-expert agreement was 75.4% (37.5%-100.0%). Conclusion: We found considerable disagreement in expert labeling, possibly reflecting large anatomical heterogeneity and changes with inspiration. Consistent airway measurement cannot be guaranteed based on manual localization.