Scheme: University Research Fellowship
Organisation: Imperial College London
Dates: Jan 2016-Dec 2020
Summary: With recent advances in medical imaging and surgical robotics, surgical oncology is entering a new era that is set to bring major healthcare and socio-economic benefits. The main goal of surgical oncology is to achieve complete resection of cancerous tissue with minimal iatrogenic injury to surrounding tissue. In practice, this often presents a formidable challenge to surgeons. Surgery on tumours residing within the brain is particularly demanding, and the prognosis for patients afflicted with such tumours remains very poor. Intrinsic brain tumours are highly infiltrative making it difficult to distinguish tumour tissue from surrounding tissue. Moreover, it is imperative to preserve unaffected brain tissue, which is delicate, often eloquent, and has little capacity for regeneration. Current state-of-the-art technologies used to facilitate brain tumour identification such as neuronavigation, iMRI and fluorescence imaging have significant limitations intraoperatively or can not provide complete tumour identification. The aim of my research is to integrate multi-modal intra-operative imaging and navigation technologies into a cognitive robotic platform. This will enable accurate and highly personalised in vivo tissue characterisation with the aim of improving both the efficacy and safety of tumour resection. Based on my recent developments of reliable soft tissue tracking, retargeting of optical biopsy sites and deformable 3D reconstruction, my research focuses on the intra-operative surgical navigation, the anatomy-specific tissue scanning with imaging probes and the tissue characterisation with on-line diagnosis support.