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Journal Article

Diffusion Tensor Imaging in a Human PET/MR Hybrid System

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Hofmann,  M
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Boss, A., Kolb, A., Hofmann, M., Bisdas, S., Nägele, T., Ernemann, U., et al. (2010). Diffusion Tensor Imaging in a Human PET/MR Hybrid System. Investigative Radiology, 45(5), 270-274. doi:10.1097/RLI.0b013e3181dc3671.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-C016-6
Abstract
Purpose: The aim of this study was to test and demonstrate the feasibility of diffusion tensor imaging (DTI) with a hybrid positron emission tomography (PET)/magnetic resonance imaging system for simultaneous PET and magnetic resonance (MR) data acquisition. Materials and Methods: All measurements were performed with a prototype hybrid PET/MR scanner dedicated for brain and head imaging. The PET scanner, which is inserted into a conventional 3.0-Tesla high field MR imager equipped with a transmit/receive birdcage head coil, consists of 192 block detectors with a matrix of 12 × 12 lutetium oxyorthosilicate scintillation crystals combined with MR-compatible 3 × 3 avalanche photodiode arrays. In 7 volunteers and 4 patients with brain tumors, DTI was performed during simultaneous PET data readout applying a diffusion weighted echo planar sequence (12 noncollinear directions, echo time (TE)/repetition time (TR) 98 ms/5300 ms, b-value 800 s/mm2). Image quality and accuracy of DTI were assessed in comparison with DTI images acquired after removal of the PET insert. Results: The diffusion images showed good image quality in all volunteers regardless of simultaneous PET data readout or after removal of the PET scanner; however, significantly (P < 0.01) stronger rim artifacts were found in fractional anisotropy images computed from DTI images recorded during simultaneous PET acquisition, demonstrating higher eddy-current effects. In region of interest analysis, no notable differences were found in the computation of the direction of the principal eigenvector (P > 0.05) and fractional anisotropy values (P > 0.05). In the assessment of pathologies, in all 4 patients PET and DTI provided important clinical information in addition to conventional magnetic resonance imaging. Conclusion: Diffusion tensor imaging may be combined with simultaneous PET data acquisition, offering additional important morphologic and functional information for treatment planning in patients with brain tumors.