Spectral Data Augmentation Techniques to quantify Lung Pathology from CT-images

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.Comment: 5 pages including references, accepted as Oral presentation at IEEE ISBI 202

Diffusion weighted imaging in cystic fibrosis disease: beyond morphological imaging

To explore the feasibility of diffusion-weighted imaging (DWI) to assess inflammatory lung changes in patients with Cystic Fibrosis (CF) METHODS: CF patients referred for their annual check-up had spirometry, chest-CT and MRI on the same day. MRI was performed in a 1.5 T scanner with BLADE and EPI-DWI sequences (b = 0-600 s/mm(2)). End-inspiratory and end-expiratory scans were acquired in multi-row scanners. DWI was scored with an established semi-quantitative scoring system. DWI score was correlated to CT sub-scores for bronchiectasis (CF-CTBE), mucus (CF-CTmucus), total score (CF-CTtotal-score), FEV1, and BMI. T-test was used to assess differences between patients with and without DWI-hotspots

Crowdsourcing Airway Annotations in Chest Computed Tomography Images

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: \url{http://github.com/adriapr/crowdairway.git}

Creating a training set for artificial intelligence from initial segmentations of airways

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

Diagnosis of bronchiectasis and airway wall thickening in children with cystic fibrosis: Objective airway-artery quantification

Objectives: To quantify airway and artery (AA)-dimensions in cystic fibrosis (CF) and control patients for objective CT diagnosis of bronchiectasis and airway wall thickness (AWT). Methods: Spirometer-guided inspiratory and expiratory CTs of 11 CF and 12 control patients were collected retrospectively. Airway pathways were annotated semi-automatically to reconstruct three-dimensional bronchial trees. All visible AA-pairs were measured perpendicular to the airway axis. Inner, outer and AWT (outer−inner) diameter were divided by the adjacent artery diameter to compute AinA-, AoutA- and AWTA-ratios. AA-ratios were predicted using mixed-effects models including disease status, lung volume, gender, height and age as covariates. Results: Demographics did not differ significantly between cohorts. Mean AA-pairs CF: 299 inspiratory; 82 expiratory. Controls: 131 inspiratory; 58 expiratory. All ratios were significantly larger in inspiratory compared to expiratory CTs for both groups (p<0.001). AoutA- and AWTA-ratios were larger in CF than in controls, independent of lung volume (p<0.01). Difference of AoutA- and AWTA-ratios between patients with CF and controls increased significantly for every following airway generation (p<0.001). Conclusion: Diagnosis of bronchiectasis is highly dependent on lung volume and more reliably diagnosed using outer airway diameter. Difference in bronchiectasis and AWT severity between the two cohorts increased with each airway generation. Key points: • More peripheral airways are visible in CF patients compared to controls.• Structural lung changes in CF patients are greater with each airway generation.• Number of airways visualized on CT could quantify CF lung disease.• For objective airway disease quantification on CT, lung volume standardization is required

Management of respiratory tract exacerbations in people with cystic fibrosis: Focus on imaging

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 monitoring tools are briefly described to set the scene. This is followed by advantages and disadvantages of each imaging technique, concluding with a diagnostic imaging algorithm for disease monitoring during respiratory tract exacerbation in the cystic fibrosis patient

Дискретно-континуальные системы: подходы, модели, программно-модельные комплексы

<div><p>Background</p><p>Diaphragm weakness is the main reason for respiratory dysfunction in patients with Pompe disease, a progressive metabolic myopathy affecting respiratory and limb-girdle muscles. Since respiratory failure is the major cause of death among adult patients, early identification of respiratory muscle involvement is necessary to initiate treatment in time and possibly prevent irreversible damage. In this paper we investigate the suitability of dynamic MR imaging in combination with state-of-the-art image analysis methods to assess respiratory muscle weakness.</p><p>Methods</p><p>The proposed methodology relies on image registration and lung surface extraction to quantify lung kinematics during breathing. This allows for the extraction of geometry and motion features of the lung that characterize the independent contribution of the diaphragm and the thoracic muscles to the respiratory cycle.</p><p>Results</p><p>Results in 16 3D+t MRI scans (10 Pompe patients and 6 controls) of a slow expiratory maneuver show that kinematic analysis from dynamic 3D images reveals important additional information about diaphragm mechanics and respiratory muscle involvement when compared to conventional pulmonary function tests. Pompe patients with severely reduced pulmonary function showed severe diaphragm weakness presented by minimal motion of the diaphragm. In patients with moderately reduced pulmonary function, cranial displacement of posterior diaphragm parts was reduced and the diaphragm dome was oriented more horizontally at full inspiration compared to healthy controls.</p><p>Conclusion</p><p>Dynamic 3D MRI provides data for analyzing the contribution of both diaphragm and thoracic muscles independently. The proposed image analysis method has the potential to detect less severe diaphragm weakness and could thus be used to determine the optimal start of treatment in adult patients with Pompe disease in prospect of increased treatment response.</p></div

Sediment Hydraulical Studies on the Control of Sediments. XI : Application of Vortex Tube Sand Trap to Storage Dams

The hydraulic problems of vortex tube sand trap with a jet flow gate and with a double-opened slit inlet are examined for its application to a storage dam. The behaviour of spiral flow in a vortex flow tube, inlet velocity to slit, and the efficiency of a linear sand trap in a modelled dam reservoir are tested more than 300 times using vortex flow tube with double-cylinder slit inlet. The grading at sediment terrace in a modelled reservoir is also examined after flushing sand

Maximum inspiratory pressure as a clinically meaningful trial endpoint for neuromuscular diseases: a comprehensive review of the literature

Respiratory muscle strength is a proven predictor of long-term outcome of neuromuscular disease (NMD), including amyotrophic lateral sclerosis, Duchenne muscular dystrophy, and spinal muscular atrophy. Maximal inspiratory pressure (MIP), a sensitive measure of respiratory muscle strength, one of several useful tests of respiratory muscle strength, is gaining interest as a therapeutic clinical trial endpoint for NMD. In this comprehensive review we investigate the use of MIP as a measure of respiratory muscle strength in clinical trials of therapeutics targeting respiratory muscle, examine the correlation of MIP with survival, quality of life, and other measures of pulmonary function, and outline the role of MIP as a clinically significantly meaningful outcome measure. Our analysis supports the utility of MIP for the early evaluation of respiratory muscle strength, especially of the diaphragm, in patients with NMD and as a surrogate endpoint in clinical trials of therapies for NMD