Impact of incorrect tissue classification in Dixon-based MR-AC: fat-water tissue inversion

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Background: The current MR-based attenuation correction (AC) used in combined PET/MR systems computes a Dixon attenuation map (MR-ACDixon) based on fat and water images derived from in- and opposed-phase MRI. We observed an occasional fat/water inversion in MR-ACDixon. The aim of our study was to estimate the prevalence of this phenomenon in a large patient cohort and assess the possible bias on PET data. Methods: PET/MRI was performed on a Siemens Biograph mMR (Siemens AG, Erlangen, Germany). We visually inspected attenuation maps of 283 brain or head/neck (H/N) patients, classified them as non-inverted or inverted, and calculated the fat/water tissue fraction. We selected ten FDG-PET brain patients with non-inverted attenuation maps for further analysis. Tissue inversion was simulated, and PET images were reconstructed using both original and inverted attenuation maps. The FDG-PET images of the ten brain patients were analyzed using 11 concentric annulus regions of 5 mm width placed over a central transaxial image plane traversing PETDixon. Results: Out of the 283 patients, a fat/water inversion in 23 patients (8.1%) was observed. The average fraction of fat in the correct MR-ACDixon was 13% for brain and 17% for H/N patients. In the inverted cases, we found an average fat fraction of 56% for the brain patients and 41% for the H/N patients. The effect of the simulated tissue inversion in the brain studies was clearly seen on AC-PET images. The percent-difference image revealed a radial error where the largest difference was at the ventricles (30% ± 3%) and smallest at the cortical region (10% ± 2%). Conclusions: Tissue inversion in Dixon MRI is well known and can occur when there is an error in the off-resonance correction method. Tissue inversion needs to be considered if, based on Dixon-AC, the construction of normal PET databases is performed or any quantitative physiological parameters are fitted. Visual inspection is needed if Dixon-AC is to be used in clinical routine.




Ladefoged, C. N., Hansen, A. E., Keller, S. H., Holm, S., Law, I., Beyer, T., … Andersen, F. L. (2014). Impact of incorrect tissue classification in Dixon-based MR-AC: fat-water tissue inversion. EJNMMI Physics, 1(1), 1–9.

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