Error reduction strategies for quantitative PET with focus on hybrid PET/MRI

Abstract: Positron Emission Tomography (PET) is an important tool for detection, staging and follow-up in a wide range of diseases, including cancer and neurological disorders. As a functional imaging tool, PET can visualize biological processes, where positron emitting radioactive isotopes are connected to molecules with different functions in the body. While PET-images can be visually interpreted, they can also be used for quantitative measurements, where functions such as glucose metabolism, dopamine receptor function, and blood-flow can be quantified. Measurements can be performed in static imaging, or in dynamic imaging where graphical methods can be used for analysis.PET images benefit from fusion with anatomical images which facilitates the interpretation. The combination of PET with computed tomography (CT) as in PET/CT hybrid equipment is a well-established imaging method. Magnetic Resonance Imaging (MRI) has some advantages over CT such as the high soft tissue contrast, but the combination with PET in a fully integrated system is far more technically challenging. Most of the technical concerns have been solved, and PET/MRI modalities are now commercially available.Among the remaining challenges, the attenuation correction is still not yet completely solved, where the attenuation maps on the PET/MRI modalities are approximate and bone is not accounted for in all parts of the body. There are also challenges with quantitative PET in general, where for example low spatial resolution and presence of noise can lead to quantitative errors. The purpose of this thesis was to investigate and develop strategies to reduce quantitative errors in PET imaging with special focus on PET/MRI.In study I, we studied the limits for quantification of size and uptake in small lesions in PET images reconstructed with a resolution modelling algorithm. We constructed a phantom of small balloons and reconstructed images with three different algorithms and measured volume and activity concentration in the images. The measured activity concentration in the lesions was corrected for the low resolution that yields partial-volume effects (PVE). We found that resolution modelling improved quantification of all lesions, and that in combination with correction factors, lesions larger than ~9 mm diameter could be correctly quantified.Study II is focused on the effect of frame time length on the graphical Logan-analysis for dynamic studies with 11C-raclopride. Logan analysis is reported to be sensitive to noise, and image noise is heavily dependent on the frame time length. Noise can also generate bias when using iterative reconstruction methods. Weivconcluded that with region-based analyses, a bias of approximately 10% in the non-displaceable binding potential was found when using the shortest time frames, and that the bias was mainly caused by the reconstruction algorithm. Long time frames generated stable parameters.The last two studies focused on the attenuation correction in PET/MRI hybrid equipment. In study III, a method for attenuation correction in PET/MRI was implemented and evaluated. The method is developed for the pelvic region and is based on statistical decomposition of T2-weighted images. We found that the new method improved quantification, especially in regions in vicinity of bone. In study IV, we proposed a concept for patient-specific quality assurance of attenuation maps, based on measurements of the MRI B0-field. The method shows potential to find errors in the attenuation map related to metallic implants, air, and patient contour.The work in this thesis has contributed to increased knowledge about the effect of resolution and noise for quantification in PET images. It has also introduced a new method for attenuation correction in PET/MRI, and a concept for quality assurance of PET/MRI attenuation maps.