Fakultät Informatik und Mathematik
Regensburg Center for Artificial Intelligence
Regensburg Center of Biomedical Engineering
Regensburg Center of Health Sciences and Technology

Prof. Dr. rer nat. Christoph Palm

Thomas Beyer, Markus Weigert, Harald H. Quick, Uwe Pietrzyk, Florian Vogt, Christoph Palm, Gerald Antoch, Stefan P. Müller, Andreas Bockisch

MR-based attenuation correction (AC) will become an integral part of combined PET/MR systems. Here, we propose a toolbox to validate MR-AC of clinical PET/MRI data sets.
Torso scans of ten patients were acquired on a combined PET/CT and on a 1.5-T MRI system. MR-based attenuation data were derived from the CT following MR–CT image co-registration and subsequent histogram matching. PET images were reconstructed after CT- (PET/CT) and MR-based AC (PET/MRI). Lesion-to-background (L/B) ratios were estimated on PET/CT and PET/MRI.
MR–CT histogram matching leads to a mean voxel intensity difference in the CT- and MR-based attenuation images of 12% (max). Mean differences between PET/MRI and PET/CT were 19% (max). L/B ratios were similar except for the lung where local misregistration and intensity transformation leads to a biased PET/MRI.
Our toolbox can be used to study pitfalls in MR-AC. We found that co-registration accuracy and pixel value transformation determine the accuracy of PET/MRI.

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