Diffusion Tensor Imaging in a Human PET/MR Hybrid System


    loading  Checking for direct PDF access through Ovid

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.

    loading  Loading Related Articles