Quantitative Accuracy of Iterative Reconstruction Algorithms in Positron Emission Tomography

UoM administered thesis: Phd

  • Authors:
  • Ian Armstrong


Positron Emission Tomography (PET) plays an essential role in the management of patients with cancer. It is used to detect and characterise malignancy as well as monitor response to therapy. PET is a quantitative imaging tool, producing images that quantify the uptake of a radiotracer that has been administered to the patient. The most common measure of uptake derived from the image is known as a Standardised Uptake Value (SUV). Data acquired on the scanner is processed to produce images that are reported by clinicians. This task is known as image reconstruction and uses computational algorithms to process the scan data. The last decade has seen substantial development of these algorithms, which have become commercially available: modelling of the scanner spatial resolution (resolution modelling) and time of flight (TOF). The Biograph mCT was the first scanner from Siemens Healthcare to feature these two algorithms and the scanner at Central Manchester University Hospitals was the first Biograph mCT to go live in the UK. This PhD project, sponsored by Siemens Healthcare, aims to evaluate the effect of these algorithms on SUV in routine oncology imaging through a combination of phantom and patient studies.Resolution modelling improved visualisation of small objects and resulted in significant increases of uptake measurements. This may pose a challenge to clinicians when interpreting established uptake metrics that are used as an indication of disease status. Resolution modelling reduced the variability of SUV. This improved precision is particularly beneficial when assessing SUV changes during therapy monitoring.TOF was shown to reduce image noise with a conservation of FDG uptake measurements, relative to non-TOF algorithms. As a result of this work, TOF has been used routinely since mid-2014 at the CMUH department. This has facilitated a reduction of patient and staff radiation dose and an increase of 100 scans performed each year in the department.


Original languageEnglish
Awarding Institution
Award date1 Aug 2017