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Graph refinement, or the task of obtaining subgraphs of interest from over-complete graphs, can have many varied applications. In this work, we extract trees or collection of sub-trees from image data by, first deriving a graph-based representation of the volumetric data and then, posing the tree extraction as a graph refinement task. We present two methods to perform graph refinement. First, we use mean-field approximation (MFA) to approximate the posterior density over the subgraphs from which the optimal subgraph of interest can be estimated. Mean field networks (MFNs) are used for inference based on the interpretation that iterations of MFA can be seen as feed-forward operations in a neural network. This allows us to learn the model parameters using gradient descent. Second, we present a supervised learning approach using graph neural networks (GNNs) which can be seen as generalisations of MFNs. Subgraphs are obtained by training a GNN-based graph refinement model to directly predict edge probabilities. We discuss connections between the two classes of methods and compare them for the task of extracting airways from 3D, low-dose, chest CT data. We show that both the MFN and GNN models show significant improvement when compared to one baseline method, that is similar to a top performing method in the EXACT'09 Challenge, and a 3D U-Net based airway segmentation model, in detecting more branches with fewer false positives., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: Although the descending aortic diameter is larger in smokers, data about thoracic aortic growth is missing. Our aim is to present the distribution of thoracic aortic growth in smokers and to compare it with literature of the general population., Methods: Current and ex-smokers aged 50-70 years from the longitudinal Danish Lung Cancer Screening Trial, were included. Mean and 95th percentile of annual aortic growth of the ascending aortic (AA) and descending aortic (DA) diameters were calculated with the first and last non-contrast computed tomography scans during follow-up. Determinants of change in aortic diameter over time were investigated with linear mixed models., Results: A total of 1987 participants (56% male, mean age 57.4 ± 4.8 years) were included. During a median follow-up of 48 months, mean AA and DA growth rates were comparable between males (AA 0.12 ± 0.31 mm/year and DA 0.10 ± 0.30 mm/year) and females (AA 0.11 ± 0.29 mm/year and DA 0.13 ± 0.27 mm/year). The 95th percentile ranged from 0.42 to 0.47 mm/year, depending on sex and location. Aortic growth was comparable between current and ex-smokers and aortic growth was not associated with pack-years. Our findings are consistent with aortic growth rates of 0.08 to 0.17 mm/years in the general population. Larger aortic growth was associated with lower age, increased height, absence of medication for hypertension or hypercholesterolemia and lower Agatston scores., Conclusions: This longitudinal study of smokers in the age range of 50-70 years shows that ascending and descending aortic growth is approximately 0.1 mm/year and is consistent with growth in the general population., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Objective: The aim of this study was to investigate whether smokers with incidental findings of interstitial lung abnormalities have an increased mortality during long-term follow-up, and review the contributing causes of death., Methods: Baseline CT scans of 1990 participants from the Danish Lung Cancer Screening Trial were qualitatively assessed for predefined interstitial lung abnormalities of any severity. Inclusion criteria for this lung cancer screening trial included current or former smoking, > 20 pack-years, and age 50-70 years. Patients were followed up for up to 12 years., Results: We found interstitial lung abnormalities in 332 participants (16.7%). Interstitial lung abnormalities were associated with increased all-cause mortality in the full cohort (HR: 2.0, 95% CI: 1.4-2.7, P < 0.001) and in lung cancer-free participants (HR: 1.6, 95% CI: 1.1-2.4, P = 0.007). The findings were associated with death from lung cancer (HR: 3.2, 95% CI: 1.7-6.2, P < 0.001) and non-pulmonary malignancies (HR: 2.1, 95% CI: 1.1-4.0, P = 0.02). Participants with fibrotic and non-fibrotic interstitial lung abnormalities had similar survival., Conclusion: Interstitial lung abnormalities were common in this lung cancer screening population of relatively healthy smokers and were associated with mortality regardless of the interstitial morphological phenotype. The increased mortality was partly due to an association with lung cancer and non-pulmonary malignancies., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Lung cancer screening with low dose computed tomography (CT) has not yet been evaluated in randomized clinical trials, although several are underway., Methods: In The Danish Lung Cancer Screening Trial, 4104 smokers and previous smokers from 2004 to 2006 were randomized to either screening with annual low dose CT scans for 5 years or no screening. A history of cigarette smoking of at least 20 pack years was required. All participants have annual lung function tests, and questionnaires regarding health status, psychosocial consequences of screening, smoking habits, and smoking cessation. Baseline CT scans were performed in 2052 participants. Pulmonary nodules were classified according to size and morphology: (1) Nodules smaller than 5 mm and calcified (benign) nodules were tabulated, (2) Noncalcified nodules between 5 and 15 mm were rescanned after 3 months. If the nodule increased in size or was larger than 15 mm the participant was referred for diagnostic workup., Results: At baseline 179 persons showed noncalcified nodules larger than 5 mm, and most were rescanned after 3 months: The rate of false-positive diagnoses was 7.9%, and 17 individuals (0.8%) turned out to have lung cancer. Ten of these had stage I disease. Eleven of 17 lung cancers at baseline were treated surgically, eight of these by video assisted thoracic surgery resection., Conclusions: Screening may facilitate minimal invasive treatment and can be performed with a relatively low rate of false-positive screen results compared with previous studies on lung cancer screening.