Project description

Cystic fibrosis (CF) is a genetic disorder caused by mutations in a gene called CFTR. This gene produces a protein (also called CFTR) that is an ion channel in the epithelial cells that line all the tubes in the body other than blood vessels. While lots of organs are affected, it is the airway disease that causes poor quality of life and early death. The CFTR ion channel defect results in dehydration of the airway surface liquid (ASL) and the inability to clear mucus via the normal clearance mechanism called mucociliary clearance (MCC). This creates the perfect environment for inhaled bacteria to grow in, causing a cycle of infection and inflammation that destroys lung tissue. We have run a long X-ray imaging program of work at the SPring-8 synchrotron in Japan to develop non-invasive techniques to quantify ASL depth and MCC. The MCC assessments are made by depositing micron-sized marker particles onto the airway surface and then tracking their motion over time, with high spatial and temporal resolution. More recently we have translated this technique to the Munich Compact Light Source, a smaller synchrotron-like facility in Germany. We have data collected from live anaesthetised mice that assessed the effects of airway-rehydrating treatments on MCC. The aim of this project is to apply novel image processing and/or machine learning approaches to automate the detection and tracking of the marker particles as they move through the airways.

Assumed knowledge

Matlab and basic image processing knowledge

Supervisors research focus

The Cystic Fibrosis Airway Research Group (CFARG) and Respiratory X-ray Imaging Laboratory (ReXIL) are located in Respiratory Medicine in the Gilbert Building at the Women’s and Children’s Hospital. We are dedicated to developing gene-based therapies for CF lung disease, as well as novel imaging-based methods for assessing the effectiveness of therapies.

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