Brittany Barton

Mucus is viscous fluidic biological tissue that is used for protecting airways by trapping and clearing pollutants and protecting from other viruses. In respiratory diseases such as Cystic Fibrosis and COPD, mucus becomes dehydrated resulting in breathing difficulty and increased infection. By quantifying mucus density, we are both better able to investigate respiratory diseases and evaluate the severity of the disease in patients. Optical Coherence Tomography, a laser based cross-sectional imaging technique with cell-scale resolution, has been used to spatially resolve nanoparticle diffusion throughout mucus in order to non-invasively quantify mucus density. Platforms such as LabVIEW and MATLAB are used to control the DI-OCT system and analyze data. This research includes development of Deep-Imaging Optical Coherence Tomography (DI-OCT) that can image twice as deep as traditionally OCT systems, which would enable doctors to image both mucus and epithelial layers of the respiratory tract, making the technique more clinically relevant. The alignment of the system is complete, which was determined by the output profile of the expected light spectrum. In tandem with DI-OCT development, we have developed new metrics to characterize mucus measured using traditional OCT, which will be later translated to DI-OCT. Spatial mapping of mucus density throughout mucus samples is presented, which could be used to identify local diseased tissue in real-time for targeted respiratory treatment. The combination of DI-OCT with more robust mucus characterization techniques brings this research one step closer to personalized respiratory disease treatment.