2019
DOI: 10.1016/j.ejmp.2019.04.006
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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

Abstract: Multiparametric imaging holds great potential for characterization of disease heterogeneity. For integrated PET/MR imaging, the combination of 18 F-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 betwe… Show more

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Cited by 9 publications
(7 citation statements)
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References 31 publications
(57 reference statements)
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“…The voxel-by-voxel analysis of parameter maps revealed weak correlations between RGD and FDG uptake, which varied strongly within the patient cohort, indicating that they provide different and potentially complementary information about the tumor. Our results demonstrated an average correlation coe cient of -0.7 between FDG uptake and ADC values, in line with earlier studies (26,43,44), while the correlation between ADC and RGD uptake was weaker.…”
Section: Discussionsupporting
confidence: 92%
“…The voxel-by-voxel analysis of parameter maps revealed weak correlations between RGD and FDG uptake, which varied strongly within the patient cohort, indicating that they provide different and potentially complementary information about the tumor. Our results demonstrated an average correlation coe cient of -0.7 between FDG uptake and ADC values, in line with earlier studies (26,43,44), while the correlation between ADC and RGD uptake was weaker.…”
Section: Discussionsupporting
confidence: 92%
“…Other sequences, such as those for diffusion weighted MRI, are more prone to geometric distortions, but these can potentially also be corrected for. 43 One benefit of the presented deep learning network is that its input relies solely on the fast (19-second) Dixon sequence, which is acquired as a standard in all routine PET/MRI examinations, regardless of the anatomic site.…”
Section: Discussionmentioning
confidence: 99%
“…Thanks to the information provided by PET, the improved TOF and the PFS, fewer MRI sequences are necessary in PET/MRI, therefore shortening the exploration time. Nevertheless, the examinations are still significantly longer and more uncomfortable than those of PET/CT [ 18 ]. This fact, added to the few PET/MRI pieces of equipment available, and their high cost, are its main drawbacks.…”
Section: Discussionmentioning
confidence: 99%