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}

The development of bronchiectasis on chest computed tomography in children with cystic fibrosis: can pre-stages be identified?

Objective: Bronchiectasis is an important component of cystic fibrosis (CF) lung disease but little is known about its development. We aimed to study the development of bronchiectasis and identify determinants for rapid progression of bronchiectasis on chest CT. Methods: Forty-three patients with CF with at least four consecutive biennial volumetric CTs were included. Areas with bronchiectasis on the most recent CT were marked as regions of interest (ROIs). These ROIs were generated on all preceding CTs using deformable image registration. Observers indicated whether: bronchiectasis, mucus plugging, airway wall thickening, atelectasis/consolidation or normal airways were present in the ROIs. Results: We identified 362 ROIs on the most recent CT. In 187 (51.7 %) ROIs bronchiectasis was present on all preceding CTs, while 175 ROIs showed development of bronchiectasis. In 139/175 (79.4 %) no pre-stages of bronchiectasis were identified. In 36/175 (20.6 %) bronchiectatic airways the following pre-stages were identified: mucus plugging (17.7 %), airway wall thickening (1.7 %) or atelectasis/consolidation (1.1 %). Pancreatic insufficiency was more prevalent in the rapid progressors compared to the slow progressors (p = 0.05). Conclusion: Most bronchiectatic airways developed within 2 years without visible pre-stages, underlining the treacherous nature of CF lung disease. Mucus plugging was the most frequent pre-stage. Key Points: • Development of bronchiectasis in cystic fibrosis lung disease on CT.• Most bronchiectatic airways developed within 2 years without pre-stages.• The most frequently identified pre-stage was mucus plugging.• This study underlines the treacherous nature of CF lung disease

Diet-Induced Swine Model with Obesity/Leptin Resistance for the Study of Metabolic Syndrome and Type 2 Diabetes

The objective of the present study was to determine the suitability of a swine breed with leptin resistance and predisposition to obesity (the Iberian pig) as model for studies on metabolic syndrome and type 2 diabetes. Thus, six Iberian sows had ad libitum access to food enriched with saturated fat (SFAD group; food consumption was estimated to be 4.5 kg/animal/day) whilst four females acted as controls and were fed with 2 kg/animal/day of a commercial maintenance diet. After three months of differential feeding, SFAD animals developed central obesity, dyslipidemia, insulin resistance and impaired glucose tolerance, and elevated blood pressure; the five parameters associated with the metabolic syndrome. Thus, the current study characterizes the Iberian pig as a robust, amenable, and reliable translational model for studies on nutrition-associated diseases

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

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

Automatic detection of crop rows in maize fields with high weeds pressure

This paper proposes a new method, oriented to crop row detection in images from maize fields with high weed pressure. The vision system is designed to be installed onboard a mobile agricultural vehicle, i.e. submitted to gyros, vibrations and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of three main processes: image segmentation, double thresholding, based on the Otsu’s method, and crop row detection. Image segmentation is based on the application of a vegetation index, the double thresholding achieves the separation between weeds and crops and the crop row detection applies least squares linear regression for line adjustment. Crop and weed separation becomes effective and the crop row detection can be favorably compared against the classical approach based on the Hough transform. Both gain effectiveness and accuracy thanks to the double thresholding that makes the main finding of the paper

Beaming into the Rat World: Enabling Real-Time Interaction between Rat and Human Each at Their Own Scale

Immersive virtual reality (IVR) typically generates the illusion in participants that they are in the displayed virtual scene where they can experience and interact in events as if they were really happening. Teleoperator (TO) systems place people at a remote physical destination embodied as a robotic device, and where typically participants have the sensation of being at the destination, with the ability to interact with entities there. In this paper, we show how to combine IVR and TO to allow a new class of application. The participant in the IVR is represented in the destination by a physical robot (TO) and simultaneously the remote place and entities within it are represented to the participant in the IVR. Hence, the IVR participant has a normal virtual reality experience, but where his or her actions and behaviour control the remote robot and can therefore have physical consequences. Here, we show how such a system can be deployed to allow a human and a rat to operate together, but the human interacting with the rat on a human scale, and the rat interacting with the human on the rat scale. The human is represented in a rat arena by a small robot that is slaved to the human’s movements, whereas the tracked rat is represented to the human in the virtual reality by a humanoid avatar. We describe the system and also a study that was designed to test whether humans can successfully play a game with the rat. The results show that the system functioned well and that the humans were able to interact with the rat to fulfil the tasks of the game. This system opens up the possibility of new applications in the life sciences involving participant observation of and interaction with animals but at human scale