The Feasibility of Maximum Likelihood Estimation of Activity and Attenuation (MLAA) Algorithm for Reduction of Truncation Artifact in the Breast PET/MRI

In integrated positron emission tomography (PET)/magnetic resonance imaging (MRI) systems, the field of view (FOV) in MRI is smaller than in PET, the difference of FOV between PET and MRI can cause geometric distortion and truncation artifacts at off-center positions. Especially, breast PET/MRI can easily lead to off-center positions around the back of the body by prone patient on the breast radiofrequency (RF) coil, it leads to truncation artifact in MRI, the PET imaging requires the attenuation correction within PET FOV using an attenuation map by acquiring MRI data. However, MRI-based attenuation maps containing truncation artifacts result in errors in visibility and quantification for PET imaging due to the limitations of MRI FOV. The maximum likelihood estimation of activity and attenuation (MLAA)-based algorithm can estimate the truncated part of an attenuation map from PET emission data. This study aimed to reduce truncation artifacts using MLAA-based attenuation correction (AC) in breast PET/MRI. A uniform phantom and national electrical manufacturers’ association international electro-technical commission body PET phantom, simulated using a Siemens Biograph PET/MRI scanner with a breast RF coil, was evaluated. PET images were evaluated between the conventional Dixon volume interpolated breath-hold examination (VIBE) of the MRI-based attenuation map and MLAA-based attenuation map by predicting the missing body contour. In this study, the MLAA algorithm was joint estimation based attenuation map composed of Dixon VIBE with a PET emission data. PET images with Dixon VIBE AC showed truncation artifacts along the horizontal axis of patient at the off-center of the FOV. The contours of the phantoms were recovered using the MLAA algorithm. The PET activity concentration with Dixon VIBE in truncated regions was 15–17% of the non-truncated regions; however, this increased to 91–97% when using the MLAA algorithm. The MLAA algorithm in breast PET/MRI reduces truncation artifacts and improves the visibility and quantification.