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To determine the agreement and reliability of fully automated coronary artery calcium (CAC) scoring in a lung cancer screening population. 1793 low-dose chest CT scans were analyzed (non-contrast-enhanced, non-gated). To establish the reference standard for CAC, first automated calcium scoring was performed using a preliminary version of a method employing coronary calcium atlas and machine learning approach. Thereafter, each scan was inspected by one of four trained raters. When needed, the raters corrected initially automaticity-identified results. In addition, an independent observer subsequently inspected manually corrected results and discarded scans with gross segmentation errors. Subsequently, fully automatic coronary calcium scoring was performed. Agatston score, CAC volume and number of calcifications were computed. Agreement was determined by calculating proportion of agreement and examining Bland-Altman plots. Reliability was determined by calculating linearly weighted kappa (κ) for Agatston strata and intraclass correlation coefficient (ICC) for continuous values. 44 (2.5%) scans were excluded due to metal artifacts or gross segmentation errors. In the remaining 1749 scans, median Agatston score was 39.6 (P25-P75∶0-345.9), median volume score was 60.4 mm3 (P25-P75∶0-361.4) and median number of calcifications was 2 (P25-P75∶0-4) for the automated scores. The κ demonstrated very good reliability (0.85) for Agatston risk categories between the automated and reference scores. The Bland-Altman plots showed underestimation of calcium score values by automated quantification. Median difference was 2.5 (p25-p75∶0.0-53.2) for Agatston score, 7.6 (p25-p75∶0.0-94.4) for CAC volume and 1 (p25-p75∶0-5) for number of calcifications. The ICC was very good for Agatston score (0.90), very good for calcium volume (0.88) and good for number of calcifications (0.64). Fully automated coronary calcium scoring in a lung cancer screening setting is feasible with acceptable reliability and agreement despite an underestimation of the amount of calcium when compared to reference scores.

AI provides tremendous opportunities for improving patient care, but at present there is little evidence of real-world uptake. An important barrier is the lack of well-designed, vendor-neutral and future-proof infrastructures for deployment. Because current AI algorithms are very narrow in scope, it is expected that a typical hospital will deploy many algorithms concurrently. Managing stand-alone point solutions for all of these algorithms will be unmanageable. A solution to this problem is a dedicated platform for deployment of AI. Here we describe a blueprint for such a platform and the high-level design and implementation considerations of such a system that can be used clinically as well as for research and development. Close collaboration between radiologists, data scientists, software developers and experts in hospital IT as well as involvement of patients is crucial in order to successfully bring AI to the clinic.

Volumetric measurements of neonatal brain tissues may be used as a biomarker for later neurodevelopmental outcome. We propose an automatic method for probabilistic brain segmentation in neonatal MRIs. In an IRB-approved study axial T1- and T2-weighted MR images were acquired at term-equivalent age for a preterm cohort of 108 neonates. A method for automatic probabilistic segmentation of the images into eight cerebral tissue classes was developed: cortical and central grey matter, unmyelinated and myelinated white matter, cerebrospinal fluid in the ventricles and in the extra cerebral space, brainstem and cerebellum. Segmentation is based on supervised pixel classification using intensity values and spatial positions of the image voxels. The method was trained and evaluated using leave-one-out experiments on seven images, for which an expert had set a reference standard manually. Subsequently, the method was applied to the remaining 101 scans, and the resulting segmentations were evaluated visually by three experts. Finally, volumes of the eight segmented tissue classes were determined for each patient. The Dice similarity coefficients of the segmented tissue classes, except myelinated white matter, ranged from 0.75 to 0.92. Myelinated white matter was difficult to segment and the achieved Dice coefficient was 0.47. Visual analysis of the results demonstrated accurate segmentations of the eight tissue classes. The probabilistic segmentation method produced volumes that compared favorably with the reference standard. The proposed method provides accurate segmentation of neonatal brain MR images into all given tissue classes, except myelinated white matter. This is the one of the first methods that distinguishes cerebrospinal fluid in the ventricles from cerebrospinal fluid in the extracerebral space. This method might be helpful in predicting neurodevelopmental outcome and useful for evaluating neuroprotective clinical trials in neonates.

Objectives To determine the influence of iterative reconstruction (IR) on quantitative computed tomography (CT) measurements of emphysema, air trapping, and airway wall and lumen dimensions, compared to filtered back-projection (FBP). Methods Inspiratory and expiratory chest CTs of 75 patients (37 male, 38 female; mean age 64.0 ± 5.7 years) were reconstructed using FBP and IR. CT emphysema, CT air trapping and airway dimensions of a segmental bronchus were quantified using several commonly used quantification methods. The two algorithms were compared using the concordance correlation coefficient ( p c ) and Wilcoxon signed rank test. Results Only the E/I-ratio MLD as a measure of CT air trapping and airway dimensions showed no significant differences between the algorithms, whereas all CT emphysema and the other CT air trapping measures were significantly different at IR when compared to FBP ( P  < 0.001). Conclusion The evaluated IR algorithm significantly influences quantitative CT measures in the assessment of emphysema and air trapping. However, the E/I-ratio MLD as a measure of CT air trapping, as well as the airway measurements, is unaffected by this reconstruction method. Quantitative CT of the lungs should be performed with careful attention to the CT protocol, especially when iterative reconstruction is introduced. Key Points • New techniques in CT allow numerous quantitative measurements of lung function . • Iterative reconstruction influences quantitative CT measurements of emphysema and air trapping . • Expiratory-to-inspiratory ratio of mean lung density and airway measurements are unaffected by iterative reconstruction . • Quantitative lung-CT should be performed with careful attention to the CT protocol .

Background  Primary lateral sclerosis (PLS) is a rare motor neuron disease characterized by upper motor neuron degeneration, diagnosed clinically due to the absence of a (neuropathological) gold standard. Post-mortem studies, particularly TDP-43 pathology analysis, are limited. Methods This study reports on 5 cases in which the diagnostic criteria for PLS were met, but in which neuropathology findings showed (partially) conflicting results. These discrepancies prompted us to perform a clinico-pathology study focussing on diagnostic challenges and accuracy in PLS. To this end, all cases were reviewed by an international panel of 11 experts using an e-module and structured questionnaires. Results Autopsy exhibited neuropathological findings consistent with amyotrophic lateral sclerosis (ALS) in one case, while two cases exhibited similar, but more limited lower motor neuron involvement, hinting at PLS or ALS overlap. Another case displayed tau-pathology indicative of progressive supranuclear palsy. The final case displayed extensive myelin loss without a proteinopathy or a clear diagnosis. The expert panel identified 24 different ancillary investigations lacking across cases (e.g. genetic testing, DAT scans, neuropsychological evaluation), listed 28 differential diagnoses, and identified 13 different conditions as the most likely diagnosis. Autopsy results led panel members to change their final diagnosis in 42% of the cases. Conclusions This study underscores the diagnostic challenges posed by diverse underlying pathologies resulting in upper motor neuron phenotypes. Despite adhering to the same diagnostic criteria, consensus amongst experts was limited. Ensuring the diagnostic consistency is crucial for advancing understanding and treatment of PLS. Explicit guidelines for excluding potential mimics along with a neuropathological gold standard are imperative.

PurposeTo estimate airway tapering in control subjects and to assess the usability of tapering as a bronchiectasis biomarker in paediatric populations.MethodsAirway tapering values were semi-automatically quantified in 156 children with control CTs collected in the Normal Chest CT Study Group. Airway tapering as a biomarker for bronchiectasis was assessed on spirometer-guided inspiratory CTs from 12 patients with bronchiectasis and 12 age- and sex-matched controls. Semi-automatic image analysis software was used to quantify intra-branch tapering (reduction in airway diameter along the branch), inter-branch tapering (reduction in airway diameter before and after bifurcation) and airway-artery ratios on chest CTs. Biomarkers were further stratified in small, medium and large airways based on three equal groups of the accompanying vessel size.ResultsControl subjects showed intra-branch tapering of 1% and inter-branch tapering of 24–39%. Subjects with bronchiectasis showed significantly reduced intra-branch of 0.8% and inter-branch tapering of 19–32% and increased airway–artery ratios compared with controls (p < 0.01). Tapering measurements were significantly different between diseased and controls across all airway sizes. Difference in airway–artery ratio was only significant in small airways.ConclusionPaediatric normal values for airway tapering were established in control subjects. Tapering showed to be a promising biomarker for bronchiectasis as subjects with bronchiectasis show significantly less airway tapering across all airway sizes compared with controls. Detecting less tapering in larger airways could potentially lead to earlier diagnosis of bronchiectasis. Additionally, compared with the conventional airway–artery ratio, this novel biomarker has the advantage that it does not require pairing with pulmonary arteries.Key Points• Tapering is a promising objective image biomarker for bronchiectasis that can be extracted semi-automatically and has good correlation with validated visual scoring methods.• Less airway tapering was observed in patients with bronchiectasis and can be observed sensitively throughout the bronchial tree, even in the more central airways.• Tapering values seemed to be less influenced by variety in scanning protocols and lung volume making it a more robust biomarker for bronchiectasis detection.

Objectives To determine inter-observer and inter-examination variability for aortic valve calcification (AVC) and mitral valve and annulus calcification (MC) in low-dose unenhanced ungated lung cancer screening chest computed tomography (CT). Methods We included 578 lung cancer screening trial participants who were examined by CT twice within 3 months to follow indeterminate pulmonary nodules. On these CTs, AVC and MC were measured in cubic millimetres. One hundred CTs were examined by five observers to determine the inter-observer variability. Reliability was assessed by kappa statistics (κ) and intra-class correlation coefficients (ICCs). Variability was expressed as the mean difference ± standard deviation (SD). Results Inter-examination reliability was excellent for AVC (κ = 0.94, ICC = 0.96) and MC (κ = 0.95, ICC = 0.90). Inter-examination variability was 12.7 ± 118.2 mm 3 for AVC and 31.5 ± 219.2 mm 3 for MC. Inter-observer reliability ranged from κ = 0.68 to κ = 0.92 for AVC and from κ = 0.20 to κ = 0.66 for MC. Inter-observer ICC was 0.94 for AVC and ranged from 0.56 to 0.97 for MC. Inter-observer variability ranged from -30.5 ± 252.0 mm 3 to 84.0 ± 240.5 mm 3 for AVC and from -95.2 ± 210.0 mm 3 to 303.7 ± 501.6 mm 3 for MC. Conclusions AVC can be quantified with excellent reliability on ungated unenhanced low-dose chest CT, but manual detection of MC can be subject to substantial inter-observer variability. Lung cancer screening CT may be used for detection and quantification of cardiac valve calcifications. Key points • Low - dose unenhanced ungated chest computed tomography can detect cardiac valve calcifications . • However , calcified cardiac valves are not reported by most radiologists . • Inter - observer and inter - examination variability of aortic valve calcifications is sufficient for longitudinal studies . • Volumetric measurement variability of mitral valve and annulus calcifications is substantial .

Objectives To determine the variation in quantitative computed tomography (CT) measures of air trapping in low-dose chest CTs of heavy smokers. Methods We analysed 45 subjects from a lung cancer screening trial, examined by CT twice within 3 months. Inspiratory and expiratory low-dose CT was obtained using breath hold instructions. CT air trapping was defined as the percentage of voxels in expiratory CT with an attenuation below −856 HU (EXP −856 ) and the expiratory to inspiratory ratio of mean lung density (E/I-ratio MLD ). Variation was determined using limits of agreement, defined as 1.96 times the standard deviation of the mean difference. The effect of both lung volume correction and breath hold reproducibility was determined. Results The limits of agreement for uncorrected CT air trapping measurements were −15.0 to 11.7 % (EXP −856 ) and −9.8 to 8.0 % (E/I-ratio MLD ). Good breath hold reproducibility significantly narrowed the limits for EXP −856 (−10.7 to 7.5 %, P  = 0.002), but not for E/I-ratio MLD (−9.2 to 7.9 %, P  = 0.75). Statistical lung volume correction did not improve the limits for EXP −856 (−12.5 to 8.8 %, P  = 0.12) and E/I-ratio MLD (−7.5 to 5.8 %, P  = 0.17). Conclusions Quantitative air trapping measures on low-dose CT of heavy smokers show considerable variation on repeat CT examinations, regardless of lung volume correction or reproducible breath holds. Key Points • Computed tomography quantitatively measures small airways disease in heavy smokers . • Measurements of air trapping vary considerably on repeat CT examinations . • Variation remains substantial even with reproducible breath holds and lung volume correction .

Objective To determine the agreement and reliability of fully automated coronary artery calcium (CAC) scoring in a lung cancer screening population. Materials and Methods 1793 low-dose chest CT scans were analyzed (non-contrast-enhanced, non-gated). To establish the reference standard for CAC, first automated calcium scoring was performed using a preliminary version of a method employing coronary calcium atlas and machine learning approach. Thereafter, each scan was inspected by one of four trained raters. When needed, the raters corrected initially automaticity-identified results. In addition, an independent observer subsequently inspected manually corrected results and discarded scans with gross segmentation errors. Subsequently, fully automatic coronary calcium scoring was performed. Agatston score, CAC volume and number of calcifications were computed. Agreement was determined by calculating proportion of agreement and examining Bland-Altman plots. Reliability was determined by calculating linearly weighted kappa ( Kappa ) for Agatston strata and intraclass correlation coefficient (ICC) for continuous values. Results 44 (2.5%) scans were excluded due to metal artifacts or gross segmentation errors. In the remaining 1749 scans, median Agatston score was 39.6 (P25-P75:0-345.9), median volume score was 60.4 mm3 (P25-P75:0-361.4) and median number of calcifications was 2 (P25-P75:0-4) for the automated scores. The Kappa demonstrated very good reliability (0.85) for Agatston risk categories between the automated and reference scores. The Bland-Altman plots showed underestimation of calcium score values by automated quantification. Median difference was 2.5 (p25-p75:0.0-53.2) for Agatston score, 7.6 (p25-p75:0.0-94.4) for CAC volume and 1 (p25-p75:0-5) for number of calcifications. The ICC was very good for Agatston score (0.90), very good for calcium volume (0.88) and good for number of calcifications (0.64). Discussion Fully automated coronary calcium scoring in a lung cancer screening setting is feasible with acceptable reliability and agreement despite an underestimation of the amount of calcium when compared to reference scores.

Brown adipose tissue (BAT) combusts high amounts of fatty acids, thereby lowering plasma triglyceride levels and reducing obesity. However, the precise role of BAT in plasma cholesterol metabolism and atherosclerosis development remains unclear. Here we show that BAT activation by β3-adrenergic receptor stimulation protects from atherosclerosis in hyperlipidemic APOE*3-Leiden.CETP mice, a well-established model for human-like lipoprotein metabolism that unlike hyperlipidemic Apoe −/− and Ldlr −/− mice expresses functional apoE and LDLR. BAT activation increases energy expenditure and decreases plasma triglyceride and cholesterol levels. Mechanistically, we demonstrate that BAT activation enhances the selective uptake of fatty acids from triglyceride-rich lipoproteins into BAT, subsequently accelerating the hepatic clearance of the cholesterol-enriched remnants. These effects depend on a functional hepatic apoE-LDLR clearance pathway as BAT activation in Apoe −/− and Ldlr −/− mice does not attenuate hypercholesterolaemia and atherosclerosis. We conclude that activation of BAT is a powerful therapeutic avenue to ameliorate hyperlipidaemia and protect from atherosclerosis. Brown adipose tissue (BAT) produces heat by burning lipid triglycerides. Here, Berbée et al . show that pharmacological BAT activation protects hyperlipidemic mice from atherosclerosis, provided mice retain the metabolic capacity to clear cholesterol-enriched lipoprotein remnants by the liver.