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Details of Grant 

EPSRC Reference: EP/N022750/1
Title: Dynamic Peri-operative Cerenkov Luminescence Imaging for Robotic Assisted Surgery (EDCLIRS)
Principal Investigator: Arridge, Professor SR
Other Investigators:
Stoyanov, Dr D
Researcher Co-Investigators:
Project Partners:
Lightpoint Medical Ltd
Department: Computer Science
Organisation: UCL
Scheme: Standard Research - NR1
Starts: 01 June 2016 Ends: 30 November 2018 Value (£): 242,828
EPSRC Research Topic Classifications:
Image & Vision Computing Medical Imaging
Robotics & Autonomy
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
20 Oct 2015 TAPs Pitch Panel Announced
Summary on Grant Application Form
Prostate cancer occurs in about one in seven of the male population and is fatal in about 20% of those cases, being the second most common cancer after lung cancer. Surgical intervention seeks to remove sufficient malignant tissue without leaving residuals that can lead to recurrence. At the same time new surgical techniques are emerging to minimise the impact on healthy tissue and preserve nerves and the quality of life. However, currently, the assessment of the success in removing all cancerous tissue depends on evaluation in a pathology lab and means that the surgery will not be curative or needs to be revisited. It is therefore crucial to develop technology that can allow the surgeon to make decisions during surgery that can reduce the chances of recurring disease. One well established indicator of cancerous tissue is the injection of a radioactively labelled tracer that differentiates between malignancy and normal tissue. This tracer can be imaged using positron emission tomography, but this is not a technology that can be utilized within a surgical setting. Recently a new methodology has been developed which allows the radioactive tracer to be imaged using ordinary cameras, by exploiting the emission by radioactive particles of Cerenkov light, in the visible spectrum. This phenomenon opens the possibility to place cameras on endoscopes and combine them with existing methods for robotic assisted surgery. In this project, we will pursue this idea, and make use of techniques for tracking movement of the cameras and the patient, including them in a model of light emission and detection, and realizing a real-time dynamic imaging system assisting the surgeon to excise all cancerous tissue while preserving as much healthy tissue as possible.
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