MSc projects 2122 004

Whole-body PET imaging methods to understand glucose metabolism as a biomarker in bones of head and neck cancer patients

Abstract:
  • Introduction: Worldwide, there are approx. 400,000 new head and neck cancers reported each year with the majority of these cancers being head and neck squamous cell carcinomas (HNSCC) and primarily affecting the epithelium lining of the sino-nasal tract, oral cavity, pharynx and larynx. The aim of this study is to analyse human whole-body 18F-FDG PET/CT images to understand if glucose metabolism in bones of HNSCC patients can reveal biomarker information to help explain the complex interactions between bone regulation of glucose metabolism in head and neck cancers patients.
  • Methods and Materials: A retrospective, observational study design using the 18F-FDG PET/CT data from 51 head and neck cancer patients and 13 healthy volunteers. Standardised uptake values (SUVs) and Hounsfield Units (HUs) were used as outcome measures for PET and CT data respectively. Network analysis and standard statistical analysis tests were performed across age, gender, pathological T-stage and primary tumour location for both PET and CT outcome measures.
  • Results: Significant differences exist for glucose metabolism between HN cancer patients and healthy volunteers specifically for the skull, sternum, forearm and humerus. Gender differences were observed for PET and CT datasets collected using healthy subjects and cancer patients. The femur shows a significantly different 18F-FDG uptake between gender with females showing a higher SUV for both cancer patients and healthy volunteers. There is no correlation observed between SUV and age, blood glucose levels.
  • Discussion: Statistical analysis of head and neck cancer patients 18F-FDG PET/CT images has provided additional evidence that glucose metabolism in bones can act as a biomarker which can help our understanding of the complex interaction between bones, hormones, gender in cancer patients and possibly genetic differences between primary tumour locations.
Project type:
  • Analysis of existing data
Imaging keywords:
Application / disease keywords:
  • 18F-FDG
  • Head and neck
  • Squamous cell carcinoma (SCC)
  • Cancer
  • Network analysis
Supervisor(s):
Programme:
Year:
  • 21-22