Whole-Body PET/MR Imaging: Quantitative Evaluation of a Novel Model-Based MR Attenuation Correction Method Including Bone

Attenuation correction (AC) of PET is an essential step in obtaining accurate and quantitative PET images. With the successful introduction of whole-body hybrid imaging systems combining PET with CT (1) or MR imaging (2), it has become possible to perform AC using methods other than rod-source transmission scans. In PET/CT systems, CT images can be directly transformed to linear attenuation coefficients (LACs) at 511 keV, the PET photon energy, using a bilinear conversion (3). In PET/MR systems, PET AC is a technical challenge (4,5) because MR images, providing mainly proton densities, cannot be directly converted to attenuation coefficient maps (μ-maps) at 511 keV. In routine PET/MR imaging, segmentation methods based on a fast 3-dimensional MR Dixon sequence are used to generate μ-maps. These methods provide up to 4 tissue classes, including air, fat, lung, and soft tissue (6,7). This method is in wide use for clinical PET/MR studies because of its short acquisition time and easy implementation (8-10), but it has certain limitations compared with CT-based AC. The limited MR imaging field of view, for example, truncates the MR-based μ-map (11,12), and the lack of signal in common MR acquisition techniques results in an ambiguity between bone and air on the generated image. Four-compartment segmentation sets the LAC of bone to that of soft tissue, leading to a systematic underestimation in PET standardized uptake values (SUVs) because of the cutoff at 0.1 cm−1. For whole-body PET/MR imaging, several groups have quantitatively evaluated the effect of replacing the LACs of bones with an LAC of soft tissue in PET AC. All studies are based on PET/CT datasets, and the CT images have been modified by thresholding to simulate a segmentation-based MR μ-map before being transformed to LACs at 511 keV. Martinez-Moller et al. (6) calculated a bias of −8% in bone lesions with a segmentation-based μ-map, Schulz et al. (7) evaluated an underestimation of −6.5%, and Samarin et al. (13) reported a bias of −11.2% in osseous lesions. Hofmann et al. (14) evaluated a bias of −14.1% in normal tissue and −7.5% in lesions. For head imaging, several approaches have been proposed to include cortical bone as an attenuation class using either a combination of atlas registration and pattern recognition (15) or pseudo CTs generated with an ultrashort echo time MR sequence (16). Because of the limited field of view and rather long acquisition time of the ultrashort echo time sequence, this method has not yet been assigned to whole-body PET/MR imaging (16). The atlas- and pattern-recognition–based method was introduced for whole-body imaging (15) but was tested only on PET/CT data in combination with an MR-only acquisition that had been transferred to the PET/CT dataset. With this method, the bias was reduced to −8% and −6% for normal tissue and lesions, respectively. Thus, the aim of this study was to evaluate a prototype model-based AC method in hybrid PET/MR imaging that considers major bones in addition to the head on whole-body PET/MR to improve PET/MR AC and specifically the PET quantification in bone lesions and lesions close to bone. The method was tested on 20 patients and compared with routine Dixon-based AC and a CT-based AC generated for each patient individually. All patient data were reconstructed only from the raw PET data of the PET/MR system, using identical scanner hardware and identical reconstruction settings. Thus, unlike previously published quantitative comparisons of PET/MR and PET/CT data, all influences other than the μ-maps were eliminated.