Using in vivo imaging for asthma

Prediction of Aerosol Deposition in the Human Respiratory Tract via Computational Models: A Review with Recent Updates

The measurement of deposited aerosol particles in the respiratory tract via in vivo and in vitro approaches is difficult due to those approaches’ many limitations. In order to overcome these obstacles, different computational models have been developed to predict the deposition of aerosol particles inside the lung. Recently, some remarkable models have been developed based on conventional semi-empirical models, one-dimensional whole-lung models, three-dimensional computational fluid dynamics models, and artificial neural networks for the prediction of aerosol-particle deposition with a high accuracy relative to experimental data. However, these models still have some disadvantages that should be overcome shortly. In this paper, we take a closer look at the current research trends as well as the future directions of this research area.

Detailed computational analysis of flow dynamics in an extended respiratory airway model

BACKGROUND

Understanding respiratory physiology can aid clinicians in diagnosing the cause of respiratory symptoms or shed light on drug delivery inhaler device optimisation. However, the sheer complexity of the human lung prohibits a full-scale study.

METHODS

In this study, a realistic respiratory airway model including large-to-small conducting airways was built. This airway model consists of subject-specific upper and lower airways, extending from nasal and oral openings to terminal bronchioles (up to the 15th generation). Based on the subject-specific airway model, topological information was extracted and a digital reference model that exhibits strong asymmetry and multi-fractal properties was provided. Inhalation flow rates 18 L/min and 50 L/min were adopted to understand inspiratory conditions subjecting to resting and light exercise inhalation modes. Regional airflow in terms of axial velocity and secondary flow vortices along the lung airway model was extracted.

FINDINGS

Obvious secondary flow currents were seen in the larynx-trachea segment and left main bronchus, while for the terminal conducting airway in the right lower lobe, the airflow tends to be much smoother with no secondary flow currents.

INTERPRETATION

This paper provides insights on respiratory physiology, especially in the lower lung airways, and will be potentially useful for diagnosis of lower airway diseases.

Synchrotron-based dynamic computed tomography of tissue motion for regional lung function measurement

During breathing, lung inflation is a dynamic process involving a balance of mechanical factors, including trans-pulmonary pressure gradients, tissue compliance and airway resistance. Current techniques lack the capacity for dynamic measurement of ventilation in vivo at sufficient spatial and temporal resolution to allow the spatio-temporal patterns of ventilation to be precisely defined. As a result, little is known of the regional dynamics of lung inflation, in either health or disease. Using fast synchrotron-based imaging (up to 60 frames s(-1)), we have combined dynamic computed tomography (CT) with cross-correlation velocimetry to measure regional time constants and expansion within the mammalian lung in vivo. Additionally, our new technique provides estimation of the airflow distribution throughout the bronchial tree during the ventilation cycle. Measurements of lung expansion and airflow in mice and rabbit pups are shown to agree with independent measures. The ability to measure lung function at a regional level will provide invaluable information for studies into normal and pathological lung dynamics, and may provide new pathways for diagnosis of regional lung diseases. Although proof-of-concept data were acquired on a synchrotron, the methodology developed potentially lends itself to clinical CT scanning and therefore offers translational research opportunities.