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Skills and Knowledge Transfer grant

Implementation of a 3D Computational Mouse Atlas for Detection of Pancreatic Tumours in Transgenic Mice

Headshot of Dr Algernon Bloom

At a glance

Completed
Award date
October 2019 - March 2021
Grant amount
£75,593
Principal investigator
Dr Algernon Bloom
Institute
Queen Mary University of London

R

  • Reduction
  • Refinement
Read the abstract
View the grant profile on GtR

Contents

Overview

Why did we fund this project?

This award aims to implement an autosegmentation tool in magnetic resonance imaging (MRI) to reduce the number of KPC mice, the most common pancreatic cancer mouse model, needed in orthotopic pancreatic cancer studies.

Research on pancreatic cancer and the development of treatments predominantly uses mice, including genetically altered animals where tumours spontaneously develop. Longitudinal studies are performed to analyse the tumour, which typically requires mice to be culled at each time point. The use of MRI would allow tumour development to be studied in the same animals, however, the interpretation of images can be challenging as the mouse pancreas is soft and diffuse making it difficult to define from surrounding tissues. Through an NC3Rs PhD Studentship, awarded to Professor Jane Sosabowski (Co-Investigator) Algernon Bloom has used machine learning to develop an autosegmentation tool (3D CAMMP) that can automatically identify a tumour-positive pancreas in an MRI image with 95% accuracy compared to veterinary radiologists and image analysis experts, allowing easier analysis of MRI imaging. Mice can be entered into a study based on tumour size (rather than animal age) enabling a more accurate tumour assessment and a subsequent reduction in tumour variability. Using MRI imaging, the Barts Cancer Institute has reduced the number of KPC mice per pancreatic cancer study from 12 to eight animals.

Algernon will now collaborate with researchers at the Francis Crick Institute, the Beatson Institute of Cancer (University of Glasgow), and the University of Cambridge to implement 3D CAMMP in their laboratories. Algernon will also develop a user-friendly interface to enable uptake by non-imaging experts, in collaboration with Invicro, a Boston-based image analysis and software development company. 3D CAMMP is available to users through the Invicro Whole Body Atlas.

This award was made in collaboration with Cancer Research UK.