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Aim/Introduction: Quantification in PET/MRI is of importance, and its accuracy is currently limited by the MR based attenuation correction estimate. A common method for attenuation correction of the pelvic region is based on a 2-echo Dixon MRI sequence for segmentation of fat and water and does not account for bone. In this work, we evaluate a new method for attenuation correction using an algorithm based on statistical decomposition of a T2 weighted MRI scan.

Materials and Methods: Substitute CT images (sCTs) were calculated from T2 weighted MRI scans with a statistical decomposition algorithm, originally developed for MRI-based radiotherapy dose-planning [1]. These sCTs benefits from having bone density information included, in addition to fat and water information. Prostate cancer patients from the PARAPLY study [2] were retrospectivelyselected, scanned with PET/MRI 11C-Acatate and CT the same day. The stand-alone CT images were transformed to the same geometry as the PET and MR images, using a non-rigid registration. CT images, generated sCT images, and the Dixonbased attenuation maps (MRAC), all in the same geometry, were together with the PET raw data used to reconstruct attenuation-corrected PET images using the PETrecon toolbox [GE Healthcare]. The two MR-based attenuation corrections were compared to the CT-based attenuation correction with root mean squared error (RMSE). Lesion analysis will also be reported. PET/MRI images were acquired on a Signa PET/MRI (GE Healthcare), and the CT images on a Brilliance Big Bore (Phillips Healthcare). The study will include 12 patients and a subset of 6 patients has been analyzed so far and is presented here.

Results: Soft tissue in-between pelvic bone structures were overestimated with 13% in MRAC-PET, and the error was reduced to 5% with sCT attenuation corrected PET (sCT-PET). For the whole patient volume, an average underestimation of 6% was found in the MRAC-PET, compared to 1% for sCTPET. RMSE within the body was reduced with a factor 2.5 with sCT-PET (RMSE=3.6%), compared to MRAC-PET (RMSE=8.8%).

Conclusion: Applying sCT from statistical decomposition as a base for calculation of attenuation maps reduces quantification errors in PET-images of the pelvic region compared to the common Dixon based method.