Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

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A. Martinez-Möller
Challenges in multimodality imaging using positron emission tomography
PhD Thesis, TU München 2009. (bib)

The combination of Positron Emission Tomography (PET) and Computed Tomography (CT) has resulted in improved diagnostic accuracy and enhanced clinical workflows, demonstrating the potential of multimodality imaging and raising the interest for the combination of PET with Magnetic Resonance Imaging (MRI). This thesis focuses on the problems of patient motion and photon attenuation, relevant to PET imaging and its combination with CT and MRI. Three specific applications are addressed. Respiratory motion results in image blurring and does not allow full exploitation of the spatial resolution offered by state-of-the-art PET scanners (below 5 mm). In order to implement respiratory gating, different respiratory sensors were compared for assessing the optimum way to determine the respiratory phase at each point in time. Furthermore, the feasibility of simultaneous cardiac-respiratory gating was shown, providing images of the heart with virtually no motion. Patient motion does not only affect the acquired PET data, but also jeopardizes the diagnostic accuracy of PET/CT scanners, in which perfect spatial co-registration between both modalities is assumed. In the course of this work, a relevant issue for cardiac imaging was found concerning the CT-based photon attenuation correction, which was biased when misregistration between PET and CT data occurred. Analysis of clinical examinations demonstrated severe artifacts taking place in nearly 30% of the cases and resulting in false positive defects, indicating that realignment of the images was necessary. As an alternative to manual registration, an automatic emission-driven correction was proposed which was able to eliminate the artifacts. Finally, attenuation correction poses additional problems for combined MRI/PET imaging, which require the development of novel techniques to generate an attenuation map from the MRI data. A method based on the segmentation of MRI images in four different attenuation classes (air, lung, fat and soft tissue) was developed. Application of the segmented attenuation map to PET/CT oncological data was found to result only in a slight decrease of the observed uptake, particularly for osseous lesions (avg. 8%), and this change did not result in any differences in the clinical interpretation. Furthermore, it was shown with PET/CT and MRI data of the same subjects that such tissue segmentation could be robustly obtained from one single MRI acquisition. Multimodality imaging has profoundly changed the practice of clinical PET despite being less than one decade old. This thesis is a step forward by investigating three relevant issues and proposing solutions which are being adopted by major PET manufacturers and contribute to provide improved diagnosis.
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