Preparing data for multiparametric PET/MR imaging: Influence of PET point spread function modelling and EPI distortion correction on the spatial correlation of [18F]FDG-PET and diffusion-weighted MRI in head and neck cancer

Purpose: Multiparametric imaging holds great potential for characterization of disease heterogeneity. For integrated PET/MR imaging, the combination of F-18-flourodeoxyglucose (FDG) PET and diffusion weighted imaging (DWI) has been suggested for the assessment of tumor heterogeneity. However, PET image resolution is limited and DWI is prone to image distortions. The aim of this study was to assess the influence of PET point spread function (PSF) modelling and DWI distortion correction on the voxelwise correlation between FDG-PET and DWI. Methods: Data were collected from 11 patients with head and neck cancer, each undergoing PET/MR imaging twice. PET reconstructions with and without PSF modelling and DWI with and without distortion correction were derived. Tumor SUV was compared between PET reconstructions by linear regression. Geometric distortions of DWI with and without distortion correction were quantified by voxelwise correlation coefficients to an undistorted anatomical reference. The influence of PSF modelling and DWI distortion correction on a multiparametric analysis was assessed as a change of the voxelwise correlation coefficient between FDG-PET and DWI measured in tumors. Results: The inclusion of PSF modelling in the PET reconstruction affected tumor quantification by a 10-20% increase in SUV. Distortion correction reduced DWI geometric distortions significantly. The impact of PET PSF modelling on the spatial correlation with DWI was insignificant. However, distortion correction of DWI had a significant effect on the spatial correlation with PET. Conclusions: Proper preparation of the imaging modalities is important for a correct analysis and interpretation of multiparametric PET/MR imaging of head and neck cancer.