E. Rota Kops

Multimodal Fingerprints of Resting State Networks as assessed by Simultaneous Trimodal MR-PET-EEG Imaging

Simultaneous MR-PET-EEG (magnetic resonance imaging - positron emission tomography – electroencephalography), a new tool for the investigation of neuronal networks in the human brain, is presented here for the first time. It enables the assessment of molecular metabolic information with high spatial and temporal resolution in a given brain simultaneously. Here, we characterize the brain’s default mode network (DMN) in healthy male subjects using multimodal fingerprinting by quantifying energy metabolism via 2- [18F]fluoro-2-desoxy-D-glucose PET (FDG-PET), the inhibition – excitation balance of neuronal activation via magnetic resonance spectroscopy (MRS), its functional connectivity via fMRI and its electrophysiological signature via EEG. The trimodal approach reveals a complementary fingerprint. Neuronal activation within the DMN as assessed with fMRI is positively correlated with the mean standard uptake value of FDG. Electrical source localization of EEG signals shows a significant difference between the dorsal DMN and sensorimotor network in the frequency range of δ, θ, α and β–1, but not with β–2 and β–3. In addition to basic neuroscience questions addressing neurovascular-metabolic coupling, this new methodology lays the foundation for individual physiological and pathological fingerprints for a wide research field addressing healthy aging, gender effects, plasticity and different psychiatric and neurological diseases.

High resolution PET image reconstruction for the Siemens MR/PET-hybrid BrainPET scanner in LOR space

The Siemens MR/PET-hybrid BrainPET scanner allows the simultaneous acquisition of PET listmode data and MR sequences. The full benefit of the 3D listmode data in terms of image quality is realised with a novel LOR space reconstruction based on PRESTO (PET REconstruction Software TOolkit). A pre-calculated, memory-resident system matrix has been applied for the iterative MLEM/OSEM reconstruction taking all 250 million physical LORs without rebinning into account. Several images are presented documenting the achieved high image quality.

PET motion correction in LOR space using scanner-independent, adaptive projection data for image reconstruction with PRESTO

Figure 2 shows reconstructed images of a two-chamber phantom (filled with two activity concentrations) which was measured in 7 different positions. The applied motion of the phantom induces a significant image degradation (left). Motion parameters were extracted from EPI volumes to correct the emission data before the reconstruction with PRESTO. The blurring due to motion completely vanishes (right).

Reconstruction of attenuation maps for a PET/MR scanner based on the LSO background activity

The majority of all modern PET cameras use LSO and LYSO crystals which contain a small proportion of the radioactive isotope of Lutetium. The aim of this study is to obtain attenuation maps for dedicated head PET/MR scanners based on the background activity of the LSO scintillator. In particular, attenuation maps for the Tx/Rx coils in the PET Field of View have to be provided. Before reconstructing such an attenuation map, the scanners stability with respect to detector temperature and background count rate was examined. First image reconstructions of the 8-channel Tx/Rx head coil and a 3-rod phantom obtained with LSO background prove that the method is feasible as long as the overall scan time is sufficiently long.

Ultra fast 3-D PET image reconstruction using highly compressed, memory-resident system matrices with optimised SIMD access patterns

Fully 3D PET image reconstruction for large detector systems still remains a challenging computational task due to the tremendous number of Lines-of-Response. The reconstruction software PRESTO (PET REconstruction Software TOolkit) allows to use accurate geometrical weighting schemes for the forward/backward projection, e.g. Volume-of-Intersection, while using all measured LORs separately. PRESTO exploits matrix redundancies to realise a strongly compressed, memory-resident system matrix. In this way, the needed time to calculate matrix weights no longer influences the reconstruction time. Nevertheless, in the first implementation the addressing of matrix weights, projection values and voxel values in disfavoured memory access patterns caused severe computational inefficiencies due to the limited memory bandwidth. In this work, the image data and projection data in memory as well as the order of mathematical operations have been re-organised to provide an optimal merit for the Single Instruction Multiple Data (SIMD) approach. A global speedup factor of 15 for has been achieved while obtaining identical results.