Developing CT Imaging Biomarkers of Disease Progression and Treatment Response in COPD through Application of Computational Modelling

Lead Research Organisation: University College London
Department Name: Medical Physics and Biomedical Eng

Abstract

Position Description: Using existing tools to characterise lung features, manifold learning and disease progression modelling will be applied to CT scans of COPD patients. Robustness and accuracy of these tools will be evaluated and an integrated processing pipeline for proposing and qualifying novel biomarkers of disease progression and therapeutic response developed. Separate clusters may distinguish functional changes associated with increased likelihood of exacerbations and exacerbations that accelerate lung deterioration. Using data from GSK and others the ability of this pipeline to identify those most at risk of structural lung disease progression as a result of early exacerbations, and who may therefore benefit from future disease-modifying interventions, will be tested personalised medicine in COPD.

Publications

10 25 50
publication icon
Young AL (2020) Disease Progression Modeling in Chronic Obstructive Pulmonary Disease. in American journal of respiratory and critical care medicine

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R512400/1 01/10/2017 30/09/2021
1921662 Studentship EP/R512400/1 25/09/2017 01/10/2021 Bojidar Rangelov
 
Description The PhD project so far has formulated a an imaging diagnosis of exacerbations of Chronic Obstructive Pulmonary Disease (COPD), through an extensive Systematic Review (publication pending). I has also developed essential image processing tools and laid the foundations for novel machine learning modelling of disease progression.
Exploitation Route The outcomes of the project can have significant impact on the way exacerbations of Chronic Obstructive Pulmonary Disease (COPD) are managed in the clinic, as well as quantified in drug trials. Furthermore, the project may add fundamental understanding of the pathophysiology of COPD through the use of imaging and novel machine learning modelling tools.
Sectors Digital/Communication/Information Technologies (including Software),Healthcare,Pharmaceuticals and Medical Biotechnology