Radiomics of PET Hypoxia Tracer Image Data
Research type
Research Study
Full title
Radiomic Analysis of PET Hypoxia Markers
IRAS ID
288608
Contact name
Andy Welch
Contact email
Duration of Study in the UK
0 years, 2 months, 30 days
Research summary
Hypoxia in tumours triggers genetic changes to improve their survival in an environment with reduced oxygen. These make tumours resistant to treatments such as radiation and chemotherapy. Hypoxia is also associated with a high chance of cancer recurrence post-treatment. The procedures currently available to diagnose hypoxia are invasive and operator dependent. PET scanning, a non-invasive procedure that produces three-dimensional images of the disease, may resolve these issues.
18F-FDG is the commonest radiotracer used in PET imaging and reflects glucose accumulation within cells. It has been assumed that 18F-FDG could be used to image hypoxia since this will boost the transmission of glucose molecules through cell membranes. However, previous studies have reported conflict or no clear correlation between 18F-FDG accumulation and hypoxia.
18F-FAZA has been introduced as a more targeted tracer for hypoxia imaging as it traps in cells when oxygen levels drop. However, it has been found to be successful in some tumours but to fail in others, for reasons that remain unclear. Further analysing these images might enhance current understanding.
The PET images consist of a range of intensities that represents the radiotracer uptake. The physiological changes induced by hypoxia are hypothesised to contribute to image heterogeneity undetectable by the human eye. This research aims to conduct further analysis using radiomics to extract image features which might allow prediction of treatment outcomes.
This study’s subjects are patients with colorectal cancer that have had PET scans done with 18F-FDG and 18F-FAZA. Along with clinical data, histopathology or post-treatment evaluation will be included in our study to find their correlation towards image features.
The goal of radiomics is to produce reliable models to predict outcomes. Thus significant features will undergo further assessment. Together with clinical data, individual radiomic features will be tested as predictors.REC name
South West - Cornwall & Plymouth Research Ethics Committee
REC reference
21/SW/0141
Date of REC Opinion
20 Oct 2021
REC opinion
Further Information Favourable Opinion