Quantification of functional imaging biomarkers in medicine:technical validation and simplification

This thesis describes various technical aspects of validation of quantitative imaging biomarkers derived from different imaging studies (PET, PET-CT, MRI) for various targets (perfusion, diffusion, cell metabolism). For the quantification of each of these biomarkers a combination of system modelling, signal processing and parameter estimation is required. Several aspects hereof (such as model selection, fitting routines and signal extraction methods) have been investigated in this PhD project. A recurring theme in these studies is the accuracy and precision of a quantitative imaging biomarker. Precision or repeatability can be assessed using test-retest studies. With poor precision, the clinical value of a biomarker is limited. Moreover, clinical applicability of a method is important for implementation in routine care. The research described in this thesis therefore focused on optimization as well as simplification of quantification methods. The study in chapter two investigated the possibility of simplifying the clinical protocol in tracer kinetic modelling of brain perfusion with [15O]H2O PET. The study looked into the possibility of calculating perfusion without knowing the arterial input function. The study confirmed that without the AIF relative quantification is still possible. Although none of the methods was able to provide an accurate estimate of absolute perfusion, one method provided a reasonable precision and could therefore be used to study longitudinal changes. The aim of the study in chapter three was, firstly, to derive the optimal plasma input kinetic model for dynamic O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) PET studies and, secondly, to use that model as a reference to evaluate simplified methods. [18F]FET is a PET tracer used in cancer imaging, in particular for brain tumours. The tracer has been shown to be very sensitive in detecting neoplasia in the brain and is therefore useful in determining the tumour extent in glioma. The optimal model was the reversible two-tissue compartment ...