CFD Modeling and Image Analysis of Exhaled Aerosols due to a Growing Bronchial Tumor: towards Non-Invasive Diagnosis and Treatment of Respiratory Obstructive Diseases

Abstract

Diagnosis and prognosis of tumorigenesis are generally performed with CT, PET, or biopsy. Such methods are accurate, but have the limitations of high cost and posing additional health risks to patients. In this study, we introduce an alternative computer aided diagnostic tool that can locate malignant sites caused by tumorigenesis in a non-invasive and low-cost way. Our hypothesis is that exhaled aerosol distribution is unique to lung structure and is sensitive to airway structure variations. With appropriate approaches, it is possible to locate the disease site, determine the disease severity, and subsequently formulate a targeted drug delivery plan to treat the disease. This study numerically evaluated the feasibility of the proposed breath test in an image-based lung model with varying pathological stages of a bronchial squamous tumor. Large eddy simulations and a Lagrangian tracking approach were used to model respiratory airflows and aerosol dynamics. Respirations of tracer aerosols of 1 µm at a flow rate of 20 L/min were simulated, with the distributions of exhaled aerosols recorded on a filter at the mouth exit. Aerosol patterns were quantified with multiple analytical techniques such as concentration disparity, spatial scanning and fractal analysis. We demonstrated that a growing bronchial tumor induced notable variations in both the airflow and exhaled aerosol distribution. These variations became more apparent with increasing tumor severity. The exhaled aerosols exhibited distinctive pattern parameters such as spatial probability, fractal dimension, and multifractal spectrum. Results of this study show that morphometric measures of the exhaled aerosol pattern can be used to detect and monitor the pathological states of respiratory diseases in the upper airway. The proposed breath test also has the potential to locate the site of the disease, which is critical in developing a personalized, site-specific drug delivery protocol.

Anatomical Details of the Rabbit Nasal Passages and Their Implications in Breathing, Air Conditioning, and Olfaction

“…b. The lateral recess (pink color) is fitted compactly between the MT and ET, in contrast to the outwardly protruding recess in deer (Ranslow et al, ), Marmosets (Smith et al, ), and humans (Xi et al, c). The nasal septum ends at the NM region and the two nasal passages merge at the anterior point (approximately 43.0 mm from the naris) of the ET region.…”

“…Compared to the nasal airways of a human or monkey, the nasal airway architecture of the NZW rabbit is much more complex and bears more similarities to other macrosmatic animals such as dogs, rats, and deer (Craven et al, ; Corley et al, ; Richter et al, ; Ranslow et al, ; Xi et al, a). However, appreciable disparities also exist among these non‐primate species.…”

Correlating exhaled aerosol images to small airway obstructive diseases: A study with dynamic mode decomposition and machine learning

“…The distance from the origin to the dynamic mode signifies the temporal behavior of the corresponding mode, growing with time (disease progression in this study) if the distance is larger than one while decaying if smaller than one. The unit circle pattern of λ i suggests that most modes are stable [6], which is reasonable for the present sequentially converging flow during exhalation, while those dynamic modes fallen on or close to the unit circle might result from the recursive usage of a selective group of flow rates and particle sizes. Eigenvalues in the interior of the unit circle are corresponding to strong damping, which leads to a stable system.…”

Magnetic aerosol drug targeting in lung cancer therapy using permanent magnet

“…In some lung cancers (e.g. squamous cell lung cancer), the tumor starts growing from lung epithelium and extends in some cases until it blocks a portion of the airway (Xi et al., 2015). While some works have modeled the trajectory of particles moving within the branches and their passive deposition on the tumor site (Kleinstreuer & Zhang, 2003; Xi et al., 2015), the active manipulation of particles toward the tumor site has not been investigated.…”