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ARTIFICIAL INTELLIGENCE & DIGITAL PATHOLOGY

Our group has been exploring the role of AI, Machine Learning and Deep Learning with collaborators over the last 4-5 years. We are interested in using these cutting edge technologies as diagnostic and prognostic aids to help patient treatment and stratification and application to pathology as well as radiology. AI has the potential to remove subjectivity, improve efficiency and provide objective quatifiable outputs which can facilitate clinical decision making. We are also interested in digital pathology implementation and its use as an educational tool.

 

ROLE OF TUMOUR MICROENVIRONMENT IN HEAD & NECK CANCER PROGRESSION

This work involves mechanism of H&N cancer invasion and metastasis, in particular the role of tumour microenvironment and stroma in cancer invasion, metastasis and extranodal extension. The stroma in head and neck includes numerous cells (e.g. fibroblasts, endothelial cells, pericytes, immune cells etc) all of which have been shown to play a key role in cancer progression. In addition, we have also been working on the role of chemokines and their receptors and their correlation to cancer behaviour.

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SALIVARY GLAND TUMOUR PATHOLOGY & BIOMARKERS

Salivary gland tumours are a group of rare and diverse neoplasms affectign the head and neck region. There are over 30 different salivary gland tumours with overlapping histological features making diagnosis challenging even for experienced pathologists. Correct diagnosis requires a wide range of immunohistochemical and molecular investigations which are not widely available. We are interested in validation and discovery of novel and existing biomarkers for these complex tumours to aid patient treatment including their digital footprint. 

EARLY DETECTION OF HEAD & NECK CANCERS & PRE-CANCERS

Pre-cancer (dysplasia) precedes the majority of H&N cancers meaning that early detection/diagnosis can prevent a significant proportion of these. The current diagnosis and grading systems for pre-cancer/dysplasia are subjective with wide inter- and intra-observer variability and can not reliably predict the future behaviour. We are working on novel digital and molecular tissue and salivary biomarkers for early detection of these lesions and to predict malignant transformation. This work has a huge potential to benefit patients by reducing the number of cancers developing and informing their treatment.

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