Pulmonary fibrosis is a respiratory disease in which scar tissue is formed in the lung that may lead to functional lung volume loss, breathlessness and eventually potentially death. Radiation-induced fibrosis can occur within the lungs as a result of radiotherapy (RT) for lung, throat and breast cancer treatment. Despite >210,000 people being diagnosed with lung cancer (including trachea and bronchus) each year in the EU, nowadays, there exist very few interdisciplinary tools that could be used to characterise the prognosis of radiation-induced fibrosis (RIF) and suggest optimal ways to manage the side-effects of RT on a personalised setting. To address this, we are developing models of RIF progression that combining novel multiscale in silico approaches, together with novel image processing techniques, to simulate the development of such lung pathologies in response to treatment. Our plan is to utilised the in silico tech towards elucidating complex interactions between lung tissue and interstitium changes, drug delivery, RT and relevant clinical indices, towards improving the prognosis of pulmonary fibrosis using pertinent clinical data. This project has been financially supported by UCY internal grant, while the clinical work is been supported by Drs Papageorgiou, Vomvas, Symeonidou and Peraticou from the Bank of Cyprus Oncology Centre (Cyprus).
Relevant work:
Ioannou et al. 2021. Society of Biomechanics, Milan, Italy.
