Preclinical Radiomics: A novel approach linking imaging with biological outcomes in mouse models

Lead Research Organisation: Queen's University of Belfast
Department Name: Centre for Cancer Res and Cell Biology

Abstract

Imaging is an essential tool in animal studies that allows investigators to look inside the bodies of mice to assess the size, shape and location of different tissues. Imaging can be used to monitor how different disease progress and to show how different tissues such as tumours respond to experimental treatments. In humans, new techniques are being developed to analyse routinely collected computed tomography (CT) scans. These images are then analysed by a computer to extract hundreds of features, termed 'radiomics features', which have the potential to uncover different disease characteristics that cannot be detected by the naked eye. This technique can complement traditional diagnosis methods and may help clinicians to make more informed personalised treatment choices and could replace the need for traditional invasive biopsies.

In this project, we will develop a similar approach for radiomics in mouse tissues. We will adapt existing methods used in the patients, to analyse CT scans from different mouse tissues and tumours, and setup a standard procedure for this process. Using this method, we will determine the relationship between the imaging features of different mouse tissues with the particular biological characteristics to develop a new way to monitor disease progression and response to treatment. This approach will deliver extra data from CT scans on the features of tissues, reducing the need for large animal numbers and invasive procedures.

Technical Summary

Small animal imaging is an essential tool in animal studies that enables the non-invasive visualisation of tissues within the body. Radiomics is an emerging field that translates medical images into quantitative data to enable phenotypic profiling of tumours to support clinical decision making and to improve diagnosis and predictive accuracy. Whilst radiomics has been associated with several clinical endpoints, the complex relationships between radiomics, clinical factors, and tumour biology are largely unknown. We hypothesize that the development of a standardized workflow for routine radiomics analysis in small animal CT imaging can be used to define causal relationships between tissue characteristics, phenotype and image features. The overall aim of this project is to establish radiomics as a non-invasive tool that can be widely implemented in all biomedical research laboratories using preclinical CT imaging. This approach can be used to maximise the quantitative assessment of mouse tissues and importantly reduce animal numbers during longitudinal sampling to monitor the effects of disease progression and experimental interventions.

Publications

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