(193ae) Noninvasive Diagnostics for the Early Detection of Lower Respiratory Diseases?an in silico Study

According to the National Vital Statistic Report in 2012, chronic lower respiratory diseases is the 3rd leading cause of death in the US. Specifically, firefighters and soldiers are regularly exposed to lung irritants through ambient particulate matter present in their operational environment. The occupational exposure results in the inflammation and contraction of the airways and the obstruction of airflow in the deeper lung, which significantly increase the risks of developing respiratory diseases, such as chronic obstructive pulmonary disease (COPD), asthma, and constrictive bronchiolitis. To achieve better treatment outcomes, the diagnosis is necessary to detect the disease at earlier stages. However, there is strong evidence to suggest that the majority of patients are not aware of their condition, limited by the imaging resolution or the invasive nature of conventional diagnostic methods. Specifically, conventional methods to diagnose pulmonary diseases involve costly and invasive procures such as X-ray screening and bronchoscope. In this study, we developed a new noninvasive diagnostic methodology, i.e., “the exhaled aerosol-based analysis,” to identify pulmonary diseases in the deeper lung by the measurable exhaled aerosol concentration pattern changes in human upper airways, combining the state-of-art technologies in both medical imaging analysis and computational fluid dynamics (CFD) simulations. The central hypothesis of the proposed “exhaled aerosol-based diagnosis” is that the changing of deeper lung structure will cause pattern shift of exhaled aerosols at upper airways. Mono-dispersed fludeoxyglucose (FDG) were employed as the biomarker aerosols in this study. CFD intersubject variability studies ascertained the validity, sensitivity, and robustness of the proposed diagnostic method. We simulated the inhalation and exhalation of FDG in three representative human respiratory system configurations (from mouth to Generation 17). Numerical results confirmed that the FDG concentration and size distribution exhaled is sensitive to the structural abnormality in lower airways caused by pulmonary diseases. The framework of the novel noninvasive pulmonary diagnostics is also developed to potentially improve the aerosol delivery protocol for future clinical trials. To achieve the detection at a subject-specific level, the individual normal lung morphology will be scanned for all firefighters and soldiers before the start of their services. CFD simulations will be performed to obtain the biomarker vapor concentration and size distribution of the healthy lung and artificially diseased lung as the subject-specific baseline as a priori. Using the baseline to compare with the vapor concentration measurement taken annually, clinical doctors will be able to detect any regional specific deeper lung diseases at their early stages.