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Background: Data from clinical trials of lumacaftor-ivacaftor (LUM-IVA) demonstrate improvements in lung clearance index (LCI) but not in FEV 1 in children with Cystic Fibrosis (CF) aged 6–11 years and homozygous for the Phe508del mutation. It is not known whether LUM/IVA use in children can impact the progression of structural lung disease. We sought to determine the real-world impact of LUM/IVA on lung structure and function in children aged 6–11 years. Methods: This real-world observational cohort study was conducted across four paediatric sites in Ireland over 24-months using spirometry-controlled CT scores and LCI as primary outcome measures. Children commencing LUM-/IVA as part of routine care were included. CT scans were manually scored with the PRAGMA CF scoring system and analysed using the automated bronchus-artery (BA) method. Secondary outcome measures included rate of change of ppFEV 1, nutritional indices and exacerbations requiring hospitalisation. Results: Seventy-one participants were recruited to the study, 31 of whom had spirometry-controlled CT performed at baseline, and after one year and two years of LUM/IVA treatment. At two years there was a reduction from baseline in trapped air scores (0.13 to 0.07, p = 0.016), but an increase from baseline in the % bronchiectasis score (0.84 to 1.23, p = 0.007). There was no change in overall % disease score (2.78 to 2.25, p = 0.138). Airway lumen to pulmonary artery ratios (A lumenA ratio) were abnormal at baseline and worsened over the course of the study. In 28 participants, the mean annual change from baseline LCI 2.5 (-0.055 (-0.61 to 0.50), p = 0.85) measurements over two years were not significant. Improvements from baseline in weight (0.10 (0.06 to 0.15, p < 0.0001), height (0.05 (0.02 to 0.09), p = 0.002) and BMI (0.09 (0.03 to 0.15) p = 0.005) z-scores were seen with LUM/IVA treatment. The mean annual change from baseline ppFEV 1 (-2.45

Background: SHIP-CT showed that 48-week treatment with inhaled 7% hypertonic saline (HS) reduced airway abnormalities on chest CT using the manual PRAGMA-CF method relative to isotonic saline (IS) in children aged 3-6 years with cystic fibrosis (CF). An algorithm was developed and validated to automatically measure bronchus and artery (BA) dimensions of BA-pairs on chest CT. Aim of the study was to assess the effect of HS on bronchial wall thickening and bronchial widening using the BA-analysis. Methods: The BA-analysis (LungQ, version 2.1.0.1, Thirona, Netherlands) automatically segments the bronchial tree and identifies the segmental bronchi (G0) and distal generations (G1-G10). Dimensions of each BA-pair are measured: diameters of bronchial outer wall (Bout), bronchial inner wall (Bin), bronchial wall thickness (Bwt), and artery (A). BA-ratios are computed: Bout/A and Bin/A to detect bronchial widening and Bwt/A and Bwa/Boa (=bronchial wall area/bronchial outer area) to detect bronchial wall thickening. Results: 113 baseline and 102 48-week scans of 115 SHIP-CT participants were analysed. LungQ measured at baseline and 48-weeks respectively 6,073 and 7,407 BA-pairs in the IS-group and 6,363 and 6,840 BA-pairs in the HS-group. At 48 weeks, Bwt/A (mean difference 0.011; 95%CI, 0.0017 to 0.020) and Bwa/Boa (mean difference 0.030; 95% 0.009 to 0.052) was significantly higher (worse) in the IS-group compared to the HS-group representing more severe bronchial wall thickening in the IS-group (p=0.025 and p=0.019 respectively). Bwt/A and Bwa/Boa decreased and Bin/A remained stable from baseline to 48 weeks in the HS while it declined in the IS-group (all p<0.001). There was no difference in progression of Bout/A between two treatment groups. Conclusion: The au

Background: Newly developed quantitative chest computed tomography (CT) outcomes designed specifically to assess structural abnormalities related to cystic fibrosis (CF) lung disease are now available. CFTR modulators potentially can reduce some structural lung abnormalities. We aimed to investigate the effect of CFTR modulators on structural lung disease progression using different quantitative CT analysis methods specific for people with CF (PwCF). Methods: PwCF with a gating mutation (Ivacaftor) or two Phe508del alleles (lumacaftor-ivacaftor) provided clinical data and underwent chest CT scans. Chest CTs were performed before and after initiation of CFTR modulator treatment. Structural lung abnormalities on CT were assessed using the Perth Rotterdam Annotated Grid Morphometric Analysis for CF (PRAGMA-CF), airway-artery dimensions (AA), and CF-CT methods. Lung disease progression (0–3 years) in exposed and matched unexposed subjects was compared using analysis of covariance. To investigate the effect of treatment in early lung disease, subgroup analyses were performed on data of children and adolescents aged <18 years. Results: We included 16 modulator exposed PwCF and 25 unexposed PwCF. Median (range) age at the baseline visit was 12.55 (4.25–36.49) years and 8.34 (3.47–38.29) years, respectively. The change in PRAGMA-CF %Airway disease (-2.88 (−4.46, −1.30), p = 0.001) and %Bronchiectasis extent (-2.07 (−3.13, −1.02), p < 0.001) improved in exposed PwCF compared to unexposed. Subgroup analysis of paediatric data showed that only PRAGMA-CF %Bronchiectasis (-0.88 (−1.70, −0.07), p = 0.035) improved in exposed PwCF compared to unexposed. Conclusion: In this preliminary real-life retrospective study CFTR modulators improve several quantitative CT outcomes. A follow-up study with a large cohort and standardization of CT scanning is needed to confirm our findings.

INTRODUCTION: Consensus is lacking on the optimal management of asymptomatic congenital pulmonary airway malformation (CPAM). For future studies, the CONNECT consortium (the COllaborative Neonatal Network for the first European CPAM Trial)-an international collaboration of specialised caregivers-has established consensus on a core outcome set of outcome parameters concerning respiratory insufficiency, surgical complications, mass effect and multifocal disease. These outcome parameters have been incorporated in the CONNECT trial, a randomised controlled trial which, in order to develop evidence-based practice, aims to compare conservative and surgical management of patients with an asymptomatic CPAM.METHODS AND ANALYSIS: Children are eligible for inclusion after the CPAM diagnosis has been confirmed on postnatal chest CT scan and they remain asymptomatic. On inclusion, children are randomised to receive either conservative or surgical management. Subsequently, children in both groups are enrolled into a standardised, 5-year follow-up programme with three visits, including a repeat chest CT scan at 2.5 years and a standardised exercise tolerance test at 5 years.The primary outcome is exercise tolerance at age 5 years, measured according to the Bruce treadmill protocol. Secondary outcome measures are molecular genetic diagnostics, validated questionnaires-on parental anxiety, quality of life and healthcare consumption-, repeated imaging and pulmonary morbidity during follow-up, as well as surgical complications and histopathology. This trial aims to end the continuous debate surrounding the optimal management of asymptomatic CPAM. ETHICS AND DISSEMINATION: This study is being conducted in accordance with the Declaration of Helsinki. The Medical Ethics Review Board of Erasmus University Medical Centre Rotterdam, The Netherlands, has approved this protocol (MEC-2022-0441). Results will be disseminated through pee

Respiratory tract exacerbations play a crucial role in progressive lung damage of people with cystic fibrosis, representing a major determinant in the loss of functional lung tissue, quality of life and patient survival. Detection and monitoring of respiratory tract exacerbations are challenging for clinicians, since under- and over-treatment convey several risks for the patient. Although various diagnostic and monitoring tools are available, their implementation is hampered by the current definition of respiratory tract exacerbation, which lacks objective “cut-offs” for clinical and lung function parameters. In particular, the latter shows a large variability, making the current 10% change in spirometry outcomes an unreliable threshold to detect exacerbation. Moreover, spirometry cannot be reliably performed in preschool children and new emerging tools, such as the forced oscillation technique, are still complementary and need more validation. Therefore, lung imaging is a key in providing respiratory tract exacerbation-related structural and functional information. However, imaging encompasses several diagnostic options, each with different advantages and limitations; for instance, conventional chest radiography, the most used radiological technique, may lack sensitivity and specificity in respiratory tract exacerbations diagnosis. Other methods, including computed tomography, positron emission tomography and magnetic resonance imaging, are limited by either radiation safety issues or the need for anesthesia in uncooperative patients. Finally, lung ultrasound has been proposed as a safe bedside option but it is highly operator-dependent and there is no strong evidence of its possible use during respiratory tract exacerbation. This review summarizes the clinical challenges of respiratory tract exacerbations in patients with cystic fibrosis with a special focus on imaging. Firstly, the definition of respiratory tract exacerbation is examined, while diagnostic and

Background: Free-breathing 1H ventilation MRI shows promise but only single-center validation has yet been performed against methods which directly image lung ventilation in patients with cystic fibrosis (CF). Purpose: To investigate the relationship between 129Xe and 1H ventilation images using data acquired at two centers. Study type: Sequence comparison. Population: Center 1; 24 patients with CF (12 female) aged 9–47 years. Center 2; 7 patients with CF (6 female) aged 13–18 years, and 6 healthy controls (6 female) aged 21–31 years. Data were acquired in different patients at each center. Field Strength/Sequence: 1.5 T, 3D steady-state free precession and 2D spoiled gradient echo. Assessment: Subjects were scanned with 129Xe ventilation and 1H free-breathing MRI and performed pulmonary function tests. Ventilation defect percent (VDP) was calculated using linear binning and images were visually assessed by H.M., L.J.S., and G.J.C. (10, 5, and 8 years' experience). Statistical Tests: Correlations and linear regression analyses were performed between 129Xe VDP, 1H VDP, FEV1, and LCI. Bland–Altman analysis of 129Xe VDP and 1H VDP was carried out. Differences in metrics were assessed using one-way ANOVA or Kruskal–Wallis tests. Results: 129Xe VDP and 1H VDP correlated strongly with; each other (r = 0.84), FEV1 z-score (129Xe VDP r = −0.83, 1H VDP r = −0.80), and LCI (129Xe VDP r = 0.91, 1H VDP r = 0.82). Bland–Altman analysis of 129Xe VDP and 1H VDP from both centers had a bias of 0.07% and limits of agreement of −16.1% and 16.2%. Linear regression relationships of VDP with FEV1 were not significantly different between 129Xe and 1H VDP (P = 0.08), while 129Xe VDP had a stronger relationship with LCI than 1H

Imaging plays a pivotal role in the noninvasive assessment of cystic fibrosis (CF)-related lung damage, which remains the main cause of morbidity and mortality in children with CF. The development of new imaging techniques has significantly changed clinical practice, and advances in therapies have posed diagnostic and monitoring challenges. The authors summarise these challenges and offer new perspectives in the use of imaging for children with CF for both clinicians and radiologists. This article focuses on chest radiography and CT, which are the two main radiologic techniques used in most cystic fibrosis centres. Advantages and disadvantages of radiography and CT for imaging in CF are described, with attention to new developments in these techniques, such as the use of artificial intelligence (AI) image analysis strategies to improve the sensitivity of radiography and CT and the introduction of the photon-counting detector CT scanner to increase spatial resolution at no dose expense.

Background: Macrophages are the major resident immune cells in human airways coordinating responses to infection and injury. In cystic fibrosis (CF), neutrophils are recruited to the airways shortly after birth, and actively exocytose damaging enzymes prior to chronic infection, suggesting a potential defect in macrophage immunomodulatory function. Signaling through the exhaustion marker programmed death protein 1 (PD-1) controls macrophage function in cancer, sepsis, and airway infection. Therefore, we sought to identify potential associations between macrophage PD-1 and markers of airway disease in children with CF. Methods: Blood and bronchoalveolar lavage fluid (BALF) were collected from 45 children with CF aged 3 to 62 months and structural lung damage was quantified by computed tomography. The phenotype of airway leukocytes was assessed by flow cytometry, while the release of enzymes and immunomodulatory mediators by molecular assays. Results: Airway macrophage PD-1 expression correlated positively with structural lung damage, neutrophilic inflammation, and infection. Interestingly, even in the absence of detectable infection, macrophage PD-1 expression was elevated and correlated with neutrophilic inflammation. In an in vitro model mimicking leukocyte recruitment into CF airways, soluble mediators derived from recruited neutrophils directly induced PD-1 expression on recruited monocytes/macrophages, suggesting a causal link between neutrophilic inflammation and macrophage PD-1 expression in CF. Finally, blockade of PD-1 in a short-term culture of CF BALF leukocytes resulted in improved pathogen clearance. Conclusion: Taken together, these findings suggest that in early CF lung disease, PD-1 upregulation associates with airway macrophage exhaustion, neutrophil takeover, infection, and structural damage.

The aim of this exploratory study was to evaluate diaphragmatic function across various neuromuscular diseases using spirometry-controlled MRI. We measured motion of the diaphragm relative to that of the thoracic wall (cranial-caudal ratio vs. anterior posterior ratio; CC-AP ratio), and changes in the diaphragmatic curvature (diaphragm height and area ratio) during inspiration in 12 adults with a neuromuscular disease having signs of respiratory muscle weakness, 18 healthy controls, and 35 adult Pompe patients – a group with prominent diaphragmatic weakness. CC-AP ratio was lower in patients with myopathies (n=7, 1.25±0.30) and motor neuron diseases (n=5, 1.30±0.10) than in healthy controls (1.37±0.14; p=0.001 and p=0.008), but not as abnormal as in Pompe patients (1.12±0.18; p=0.011 and p=0.024). The mean diaphragm height ratio was 1.17±0.33 in patients with myopathies, pointing at an insufficient diaphragmatic contraction. This was also seen in patients with Pompe disease (1.28±0.36), but not in healthy controls (0.82±0.33) or patients with motor neuron disease (0.82±0.24). We conclude that spirometry-controlled MRI enables us to investigate respiratory dysfunction across neuromuscular diseases, suggesting that the diaphragm is affected in a different way in myopathies and motor neuron diseases. Whether MRI can also be used to evaluate progression of diaphragmatic dysfunction requires additional studies.

For sensitive diagnosis and monitoring of pulmonary disease, ionizing radiation-free imaging methods are of great importance. A noncontrast and free-breathing proton magnetic resonance imaging (MRI) technique for assessment of pulmonary perfusion is phase-resolved functional lung (PREFUL) MRI. Since there is no validation of PREFUL MRI across different centers and scanners, the purpose of this study was to compare perfusion-weighted PREFUL MRI with the well-established dynamic contrast-enhanced (DCE) MRI across two centers on scanners from two different vendors. Sixteen patients with cystic fibrosis (CF) (Center 1: 10 patients; Center 2: 6 patients) underwent PREFUL and DCE MRI at 1.5T in the same imaging session. Normalized perfusion-weighted values and perfusion defect percentage (QDP) values were calculated for the whole lung and three central slices (dorsal, central, ventral of the carina). Obtained parameters were compared using Pearson correlation, Spearman correlation, Bland–Altman analysis, Wilcoxon signed-rank test, and Wilcoxon rank-sum test. Moderate-to-strong correlations between normalized perfusion-weighted PREFUL and DCE values were found (posterior slice: r = 0.69, p < 0.01). Spatial overlap of PREFUL and DCE QDP maps showed an agreement of 79.4% for the whole lung. Further, spatial overlap values of Center 1 were not significantly different to those of Center 2 for the three central slices (p > 0.07). The feasibility of PREFUL MRI across two different centers and two different vendors was shown in patients with CF and obtained results were in agreement with DCE MRI.

Consensus on the optimal management of asymptomatic congenital pulmonary airway malformation (CPAM) is lacking, and comparison between studies remains difficult due to a large variety in outcome measures. We aimed to define a core outcome set (COS) for pediatric patients with an asymptomatic CPAM. An online, three-round Delphi survey was conducted in two stakeholder groups of specialized caregivers (surgeons and non-surgeons) in various European centers. Proposed outcome parameters were scored according to level of importance, and the final COS was established through consensus. A total of 55 participants (33 surgeons, 22 non-surgeons) from 28 centers in 13 European countries completed the three rounds and rated 43 outcome parameters. The final COS comprises seven outcome parameters: respiratory insufficiency, surgical complications, mass effect/mediastinal shift (at three time-points) and multifocal disease (at two time-points). The seven outcome parameters included in the final COS reflect the diversity in priorities among this large group of European participants. However, we recommend the incorporation of these outcome parameters in the design of future studies, as they describe measurable and validated outcomes as well as the accepted age at measurement.

Background: Risk for infection and potential malignant degeneration are the most common arguments for resecting asymptomatic Congenital Pulmonary Airway Malformations (CPAM). We aimed to investigate if CT- imaging characteristics can be used to predict histopathological features, by using an objective quantitative CT scoring method. Methods: Archival CPAM tissue samples were histologically re-assessed and patients who had a pre-operative volumetric CT-scan were included. Lung disease was quantified using the newly-developed congenital lung abnormality quantification(CLAQ) scoring method and obtained percentages were used to predict histopathological signs of inflammation and presence of mucinous proliferation (MP). Because MP is presumed a precursor for mucinous adenocarcinoma in situ (AIS) this method was also used to compare CT-scans of patients with AIS to those with only CPAM. Results: Thirty-three CPAM patients were included of which 13(39%) had histological signs of inflammation and 8(24%) had a MP. Patients with inflammation had a significantly smaller lesion (14% vs 38%) while those with MP had more extensive disease (54%vs17%). Patients with AIS had a significantly smaller lesion compared to CPAM patients (5%vs29%). Significant predictors for inflammation were smaller lesion size and percentage hypodensity within lesions while a larger lesion size and percentage parenchymal hyperdensity (solid lung tissue components) were predictors for MP as well as AIS. Conclusions: Smaller CPAM lesions may be more susceptible to inflammation while larger lesions may be associated with the presence of MP. Parenchymal hyperdensity is found as a predictor for MP as well as AIS and should therefore elicit more extensive gross sampling. Level of evidence: Level III.

Objectives: To evaluate changes in diaphragmatic function in Pompe disease using MRI over time, both during natural disease course and during treatment with enzyme replacement therapy (ERT). Methods: In this prospective study, 30 adult Pompe patients and 10 healthy controls underwent pulmonary function tests and spirometry-controlled MRI twice, with an interval of 1 year. In the sagittal view of 3D gradient echo breath-hold acquisitions, diaphragmatic motion (cranial-caudal ratio between end-inspiration and end-expiration) and curvature (diaphragm height and area ratio) were calculated using a machine learning algorithm based on convolutional neural networks. Changes in outcomes after 1 year were compared between Pompe patients and healthy controls using the Mann-Whitney test. Results: Pulmonary function outcomes and cranial-caudal ratio in Pompe patients did not change significantly over time compared to healthy controls. Diaphragm height ratio increased by 0.04 (−0.38 to 1.79) in Pompe patients compared to −0.02 (−0.18 to 0.25) in healthy controls (p = 0.02). An increased diaphragmatic curvature over time was observed in particular in untreated Pompe patients (p = 0.03), in those receiving ERT already for over 3 years (p = 0.03), and when severe diaphragmatic weakness was found on the initial MRI (p = 0.01); no progression was observed in Pompe patients who started ERT less than 3 years ago and in Pompe patients with mild diaphragmatic weakness on their initial MRI. Conclusions: MRI enables to detect small changes in diaphragmatic curvature over 1-year time in Pompe patients. It also showed that once severe diaphragmatic weakness has occurred, improvement of diaphragmatic muscle function seems unlikely. Key Points: • Changes in diaphragmatic curvature in Pompe patients over time assessed with 3D MRI may serve as an outcome measure to evaluate the effect of treatment on diaphragmatic function. • Diaphragmatic curvature showed a significant deterioration after 1

Background: Structural lung disease and neutrophil-dominated airway inflammation is present from 3 months of age in children diagnosed with cystic fibrosis after newborn screening. We hypothesised that azithromycin, given three times weekly to infants with cystic fibrosis from diagnosis until age 36 months, would reduce the extent of structural lung disease as captured on chest CT scans. Methods: A phase three, randomised, double-blind, placebo-controlled trial was done at eight paediatric cystic fibrosis centres in Australia and New Zealand. Infants (aged 3–6 months) diagnosed with cystic fibrosis following newborn screening were eligible. Exclusion criteria included prolonged mechanical ventilation in the first 3 months of life, clinically significant medical disease or comorbidities other than cystic fibrosis, or macrolide hypersensitivity. Participants were randomly assigned (1:1) to receive either azithromycin (10 mg/kg bodyweight orally three times per week) or matched placebo until age 36 months. Randomisation was done with a permuted block strategy and an interactive web-based response system, stratified by study site. Unblinding was done once all participants completed the trial. The two primary outcomes were the proportion of children with radiologically defined bronchiectasis, and the percentage of total lung volume affected by disease. Secondary outcomes included clinical outcomes and exploratory outcomes were inflammatory markers. Analyses were done with the intention-to-treat principle. This study is registered at ClinicalTrials.gov (NCT01270074). Findings: Between June 15, 2012, and July 10, 2017, 281 patients were screened, of whom 130 were enrolled, randomly assigned, and received first study dose. 68 participants received azithromycin and 62 received placebo. At 36 months, 88% (n=50) of the azithromycin group and 94% (n=44) of the placebo group had bronchiectasis (odds ratio 0·49, 95% CI 0·12 to 2·00; p=0·32), and total airways disease did not d

Airways segmentation is important for research about pulmonary disease but require a large amount of time by trained specialists. We used an openly available software to improve airways segmentations obtained from an artificial intelligence (AI) tool and retrained the tool to get a better performance. Fifteen initial airway segmentations from low-dose chest computed tomography scans were obtained with a 3D-Unet AI tool previously trained on Danish Lung Cancer Screening Trial and Erasmus-MC Sophia datasets. Segmentations were manually corrected in 3D Slicer. The corrected airway segmentations were used to retrain the 3D-Unet. Airway measurements were automatically obtained and included count, airway length and luminal diameter per generation from the segmentations. Correcting segmentations required 2–4 h per scan. Manually corrected segmentations had more branches (p < 0.001), longer airways (p < 0.001) and smaller luminal diameters (p = 0.004) than initial segmentations. Segmentations from retrained 3D-Unets trended towards more branches and longer airways compared to the initial segmentations. The largest changes were seen in airways from 6th generation onwards. Manual correction results in significantly improved segmentations and is potentially a useful and time-efficient method to improve the AI tool performance on a specific hospital or research dataset.

Measuring airways in chest computed tomography (CT) scans is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine learning algorithms offer an alternative, but need large sets of annotated scans for good performance. We investigate whether crowdsourcing can be used to gather airway annotations. We generate image slices at known locations of airways in 24 subjects and request the crowd workers to outline the airway lumen and airway wall. After combining multiple crowd workers, we compare the measurements to those made by the experts in the original scans. Similar to our preliminary study, a large portion of the annotations were excluded, possibly due to workers misunderstanding the instructions. After excluding such annotations, moderate to strong correlations with the expert can be observed, although these correlations are slightly lower than inter-expert correlations. Furthermore, the results across subjects in this study are quite variable. Although the crowd has potential in annotating airways, further development is needed for it to be robust enough for gathering annotations in practice. For reproducibility, data and code are available online: http://github.com/adriapr/crowdairway.git.

Background: In Pompe disease, an inherited metabolic muscle disorder, severe diaphragmatic weakness often occurs. Enzyme replacement treatment is relatively ineffective for respiratory function, possibly because of irreversible damage to the diaphragm early in the disease course. Mildly impaired diaphragmatic function may not be recognized by spirometry, which is commonly used to study respiratory function. In this cross-sectional study, we aimed to identify early signs of diaphragmatic weakness in Pompe patients using chest MRI. Methods: Pompe patients covering the spectrum of disease severity, and sex and age matched healthy controls were prospectively included and studied using spirometry-controlled sagittal MR images of both mid-hemidiaphragms during forced inspiration. The motions of the diaphragm and thoracic wall were evaluated by measuring thoracic cranial-caudal and anterior–posterior distance ratios between inspiration and expiration. The diaphragm shape was evaluated by measuring the height of the diaphragm curvature. We used multiple linear regression analysis to compare different groups. Results: We included 22 Pompe patients with decreased spirometry results (forced vital capacity in supine position < 80% predicted); 13 Pompe patients with normal spirometry results (forced vital capacity in supine position ≥ 80% predicted) and 18 healthy controls. The mean cranial-caudal ratio was only 1.32 in patients with decreased spirometry results, 1.60 in patients with normal spirometry results and 1.72 in healthy controls (p < 0.001). Anterior–posterior ratios showed no significant differences. The mean height ratios of the diaphragm curvature were 1.41 in patients with decreased spirometry results, 1.08 in patients with normal spirometry results and 0.82 in healthy controls (p = 0.001), indicating an increased curvature of the diaphragm during inspiration in Pompe patients. Conclusions: Even in early-stage Pompe disease, when spirometry results are sti

Airways segmentation is important for research about pulmonary disease but require a large amount of time by trained specialists. We used an openly available software to improve airways segmentations obtained from an artificial intelligence (AI) tool and retrained the tool to get a better performance. Fifteen initial airway segmentations from low-dose chest computed tomography scans were obtained with a 3D-Unet AI tool previously trained on Danish Lung Cancer Screening Trial and Erasmus-MC Sophia datasets. Segmentations were manually corrected in 3D Slicer. The corrected airway segmentations were used to retrain the 3D-Unet. Airway measurements were automatically obtained and included count, airway length and luminal diameter per generation from the segmentations. Correcting segmentations required 2–4 h per scan. Manually corrected segmentations had more branches (p < 0.001), longer airways (p < 0.001) and smaller luminal diameters (p = 0.004) than initial segmentations. Segmentations from retrained 3D-Unets trended towards more branches and longer airways compared to the initial segmentations. The largest changes were seen in airways from 6th generation onwards. Manual correction results in significantly improved segmentations and is potentially a useful and time-efficient method to improve the AI tool performance on a specific hospital or research dataset.

Measuring airways in chest computed tomography (CT) scans is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine learning algorithms offer an alternative, but need large sets of annotated scans for good performance. We investigate whether crowdsourcing can be used to gather airway annotations. We generate image slices at known locations of airways in 24 subjects and request the crowd workers to outline the airway lumen and airway wall. After combining multiple crowd workers, we compare the measurements to those made by the experts in the original scans. Similar to our preliminary study, a large portion of the annotations were excluded, possibly due to workers misunderstanding the instructions. After excluding such annotations, moderate to strong correlations with the expert can be observed, although these correlations are slightly lower than inter-expert correlations. Furthermore, the results across subjects in this study are quite variable. Although the crowd has potential in annotating airways, further development is needed for it to be robust enough for gathering annotations in practice. For reproducibility, data and code are available online: http://github.com/adriapr/crowdairway.git.

In people with cystic fibrosis (PwCF), viscous sputum and dysfunction of the mucociliary escalator leads to early and chronic infections. The prevalence of Aspergillus fumigatus in sputum is high in PwCF and the contribution of A. fumigatus to the progression of structural lung disease has been reported. However, overall, relatively little is known about the contribution of A. fumigatus to CF lung disease. More knowledge is needed to aid clinical decisions on whether to start antifungal treatment. In this review, we give an overview of A. fumigatus colonisation and infection in PwCF and the different types of pulmonary disease caused by it. Furthermore, we discuss the current evidence for structural lung damage associated with A. fumigatus in PwCF on chest computed tomography and magnetic resonance imaging. We conclude that radiological outcomes to identify disease caused by A. fumigatus can be important for clinical studies and management.

Airways segmentation is important for research about pulmonary disease but require a large amount of time by trained specialists. We used an openly available software to improve airways segmentations obtained from an artificial intelligence (AI) tool and retrained the tool to get a better performance. Fifteen initial airway segmentations from low-dose chest computed tomography scans were obtained with a 3D-Unet AI tool previously trained on Danish Lung Cancer Screening Trial and Erasmus-MC Sophia datasets. Segmentations were manually corrected in 3D Slicer. The corrected airway segmentations were used to retrain the 3D-Unet. Airway measurements were automatically obtained and included count, airway length and luminal diameter per generation from the segmentations. Correcting segmentations required 2–4 h per scan. Manually corrected segmentations had more branches (p < 0.001), longer airways (p < 0.001) and smaller luminal diameters (p = 0.004) than initial segmentations. Segmentations from retrained 3D-Unets trended towards more branches and longer airways compared to the initial segmentations. The largest changes were seen in airways from 6th generation onwards. Manual correction results in significantly improved segmentations and is potentially a useful and time-efficient method to improve the AI tool performance on a specific hospital or research dataset.

Objectives/Hypothesis: Dysphonia is a common problem at long-term follow-up after airway surgery for laryngotracheal stenosis (LTS) with major impact on quality of life. Dysphonia after LTS can be caused by scar tissue from initial stenosis along with anatomical alterations after surgery. There is need for a modality to noninvasively image structure and function of the reconstructed upper airways including the vocal cords to assess voice outcome and possible treatment after LTS. Our objective was to correlate vocal cord structure and function of patients after airway reconstruction for LTS on static and dynamic magnetic resonance imaging (MRI) to voice outcome. Study Design: Prospective cohort study. Methods: Voice outcome was assessed by voice questionnaires ((pediatric) Voice Handicap Index (p)VHI)) and the Dysphonia Severity Index (DSI). Postsurgical anatomy, airway lumen, and vocal cord thickness and movement on multiplanar static high-resolution MRI and dynamic acquisitions during phonation was correlated to voice outcome. Results: Forty-eight patients (age 14.4 (range 7.5–30.7) years) and 11 healthy volunteers (15.9 (8.2–28.8) years) were included. Static MRI demonstrated vocal cord thickening in 80.9% of patients, correlated to a decrease in DSI (expected odds 0.75 [C.I. 0.58–0.96] P =.02). Dynamic MRI showed impaired vocal cord adduction during phonation in 61.7% of patients, associated with a lower DSI score (0.65 [C.I. 0.48–0.88] P =.006). Conclusions: In LTS patients, after airway reconstruction MRI can safely provide excellent structural and functional detail of the vocal cords correlating to DSI, with further usefulness expected from technical refinements. We therefore suggest MRI as a tool for extensive imaging during LTS follow-up. Level of evidence: 3 Laryngoscope, 131:E2402–E2408, 2021.

This paper presents a fully automatic and end-to-end optimised airway segmentation method for thoracic computed tomography, based on the U-Net architecture. We use a simple and low-memory 3D U-Net as backbone, which allows the method to process large 3D image patches, often comprising full lungs, in a single pass through the network. This makes the method simple, robust and efficient. We validated the proposed method on three datasets with very different characteristics and various airway abnormalities: (1) a dataset of pediatric patients including subjects with cystic fibrosis, (2) a subset of the Danish Lung Cancer Screening Trial, including subjects with chronic obstructive pulmonary disease, and (3) the EXACT’09 public dataset. We compared our method with other state-of-the-art airway segmentation methods, including relevant learning-based methods in the literature evaluated on the EXACT’09 data. We show that our method can extract highly complete airway trees with few false positive errors, on scans from both healthy and diseased subjects, and also that the method generalizes well across different datasets. On the EXACT’09 test set, our method achieved the second highest sensitivity score among all methods that reported good specificity.

Measuring airways in chest computed tomography (CT) scans is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine learning algorithms offer an alternative, but need large sets of annotated scans for good performance. We investigate whether crowdsourcing can be used to gather airway annotations. We generate image slices at known locations of airways in 24 subjects and request the crowd workers to outline the airway lumen and airway wall. After combining multiple crowd workers, we compare the measurements to those made by the experts in the original scans. Similar to our preliminary study, a large portion of the annotations were excluded, possibly due to workers misunderstanding the instructions. After excluding such annotations, moderate to strong correlations with the expert can be observed, although these correlations are slightly lower than inter-expert correlations. Furthermore, the results across subjects in this study are quite variable. Although the crowd has potential in annotating airways, further development is needed for it to be robust enough for gathering annotations in practice. For reproducibility, data and code are available online: http://github.com/adriapr/crowdairway.git.

Background: In Pompe disease, an inherited metabolic muscle disorder, severe diaphragmatic weakness often occurs. Enzyme replacement treatment is relatively ineffective for respiratory function, possibly because of irreversible damage to the diaphragm early in the disease course. Mildly impaired diaphragmatic function may not be recognized by spirometry, which is commonly used to study respiratory function. In this cross-sectional study, we aimed to identify early signs of diaphragmatic weakness in Pompe patients using chest MRI. Methods: Pompe patients covering the spectrum of disease severity, and sex and age matched healthy controls were prospectively included and studied using spirometry-controlled sagittal MR images of both mid-hemidiaphragms during forced inspiration. The motions of the diaphragm and thoracic wall were evaluated by measuring thoracic cranial-caudal and anterior–posterior distance ratios between inspiration and expiration. The diaphragm shape was evaluated by measuring the height of the diaphragm curvature. We used multiple linear regression analysis to compare different groups. Results: We included 22 Pompe patients with decreased spirometry results (forced vital capacity in supine position < 80% predicted); 13 Pompe patients with normal spirometry results (forced vital capacity in supine position ≥ 80% predicted) and 18 healthy controls. The mean cranial-caudal ratio was only 1.32 in patients with decreased spirometry results, 1.60 in patients with normal spirometry results and 1.72 in healthy controls (p < 0.001). Anterior–posterior ratios showed no significant differences. The mean height ratios of the diaphragm curvature were 1.41 in patients with decreased spirometry results, 1.08 in patients with normal spirometry results and 0.82 in healthy controls (p = 0.001), indicating an increased curvature of the diaphragm during inspiration in Pompe patients. Conclusions: Even in early-stage Pompe disease, when spirometry results are sti

Chest computed tomography (CT) is the gold standard for detecting structural abnormalities in patients with primary ciliary dyskinesia (PCD) such as bronchiectasis, bronchial wall thickening and mucus plugging. There are no studies on quantitative assessment of airway and artery abnormalities in children with PCD. The objectives of the present study were to quantify airway and artery dimensions on chest CT in a cohort of children with PCD and compare these with control children to analyse the influence of covariates on airway and artery dimensions. Chest CTs of 13 children with PCD (14 CT scans) and 12 control children were collected retrospectively. The bronchial tree was segmented semi-automatically and reconstructed in a threedimensional view. All visible airway–artery (AA) pairs were measured perpendicular to the airway centre line, annotating per branch inner and outer airway and adjacent artery diameter and computing inner airway diameter/artery ratio (AinA ratio), outer airway diameter/artery ratio (AoutA ratio), wall thickness (WT), WT/outer airway diameter ratio (Awt ratio) and WT/artery ratio. In the children with PCD (38.5% male, mean age 13.5 years, range 9.8–15.3) 1526 AA pairs were measured versus 1516 in controls (58.3% male, mean age 13.5 years, range 8–14.8). AinA ratio and AoutA ratio were significantly higher in children with PCD than in control children (both p<0.001). Awt ratio was significantly higher in control children than in children with PCD (p<0.001). Our study showed that in children with PCD airways are more dilated than in controls and do not show airway wall thickening.

Data augmentation is of paramount importance in biomedical image processing tasks, characterized by inadequate amounts of labelled data, to best use all of the data that is present. In-use techniques range from intensity transformations and elastic deformations, to linearly combining existing data points to make new ones. In this work, we propose the use of spectral techniques for data augmentation, using the discrete cosine and wavelet transforms. We empirically evaluate our approaches on a CT texture analysis task to detect abnormal lung-tissue in patients with cystic fibrosis. Empirical experiments show that the proposed spectral methods perform favourably as compared to the existing methods. When used in combination with existing methods, our proposed approach can increase the relative minor class segmentation performance by 44.1% over a simple replication baseline.

Data augmentation is of paramount importance in biomedical image processing tasks, characterized by inadequate amounts of labelled data, to best use all of the data that is present. In-use techniques range from intensity transformations and elastic deformations, to linearly combining existing data points to make new ones. In this work, we propose the use of spectral techniques for data augmentation, using the discrete cosine and wavelet transforms. We empirically evaluate our approaches on a CT texture analysis task to detect abnormal lung-tissue in patients with cystic fibrosis. Empirical experiments show that the proposed spectral methods perform favourably as compared to the existing methods. When used in combination with existing methods, our proposed approach can increase the relative minor class segmentation performance by 44.1% over a simple replication baseline.

RATIONALE: Chest computed tomography (CT) is the gold standard for demonstrating cystic fibrosis (CF) airways disease. However, there are no standardised outcome measures appropriate for children under 6 years.OBJECTIVES: We developed the Perth-Rotterdam Annotated Grid Morphometric Analysis for CF (PRAGMA-CF), a quantitative measure of airways disease, and compared it to the commonly used CF-CT scoring method.METHODS: CT scans from the Australian Respiratory Early Surveillance Team for CF (AREST CF) cohort in Western Australia were included. PRAGMA-CF was performed by annotating a grid overlaid on ten axial slices for the presence of bronchiectasis, mucous plugging or other airway abnormalities (inspiratory scans) and trapped air (expiratory scans). The separate proportions of total disease (%Dis), bronchiectasis (%Bx) and trapped air (%TA) were determined. Thirty scans were used for observer reliability, and thirty paired scans obtained at 1 and 3-years old were used for comparison with a validated standard and biological plausibility.MEASUREMENTS AND MAIN RESULTS: Intraobserver, intraclass correlation coefficients (95% confidence interval) for %Dis, %Bx and %TA were 0.93 (0.86 - 0.97), 0.93 (0.85 - 0.96) and 0.96 (0.91 - 0.98), respectively. The change in %Dis (p = 0.004) and %Bx (p = 0.001) with PRAGMA-CF was related to neutrophil elastase (NE) presence at age 3, whereas only the change in bronchiectasis score was related to NE (p < 0.001) with CF-CT. Sample size calculations for various effect sizes are presented.CONCLUSIONS: PRAGMA-CF is a sensitive and reproducible outcome measure for assessing the extent of lung disease in very young children with CF.

PURPOSE: To investigate changes in trapped air volume and distribution over time and compare computed tomography (CT) with pulmonary function tests for determining trapped air.METHODS: Thirty children contributed two CTs and pulmonary function tests over 2 years. Localized changes in trapped air on CT were assessed using image analysis software, by deforming the CT at timepoint 2 to match timepoint 1, and measuring the volume of stable (TAstable), disappeared (TAdisappeared) and new (TAnew) trapped air as a proportion of total lung volume. We used the difference between total lung capacity measured by plethysmography and helium dilution, residual volume to total lung capacity ratio, forced expiratory flow at 75% of vital capacity, and maximum mid-expiratory flow as pulmonary function test markers of trapped air. Statistical analysis included Wilcoxon's signed rank test and Spearman correlation coefficients.RESULTS: Median (range) age at baseline was 11.9 (5-17) years. Median (range) of trapped air was 9.5 (2-33)% at timepoint 1 and 9.0 (0-25)% at timepoint 2 (p=0.49). Median (range) TAstable, TAdisappeared and TAnew were respectively 3.0 (0-12)%, 5.0 (1-22)% and 7.0 (0-20)%. Trapped air on CT correlated statistically significantly with all pulmonary function measures (p<0.01), other than residual volume to total lung capacity ratio (p=0.37).CONCLUSION: Trapped air on CT did not significantly progress over 2 years, may have a substantial stable component, and is significantly correlated with pulmonary function markers.