MR-based field-of-view extension in MR/PET: B0 homogenization using gradient enhancement (HUGE).

In whole-body MR/PET, the human attenuation correction can be based on the MR data. However, an MR-based field-of-view (FoV) is limited due to physical restrictions such as B0 inhomogeneities and gradient nonlinearities. Therefore, for large patients, the MR image and the attenuation map might be truncated and the attenuation correction might be biased. The aim of this work is to explore extending the MR FoV through B0 homogenization using gradient enhancement in which an optimal readout gradient field is determined to locally compensate B0 inhomogeneities and gradient nonlinearities. A spin-echo-based sequence was developed that computes an optimal gradient for certain regions of interest, for example, the patient's arms. A significant distortion reduction was achieved outside the normal MR-based FoV. This FoV extension was achieved without any hardware modifications. In-plane distortions in a transaxially extended FoV of up to 600 mm were analyzed in phantom studies. In vivo measurements of the patient's arms lying outside the normal specified FoV were compared with and without the use of B0 homogenization using gradient enhancement. In summary, we designed a sequence that provides data for reducing the image distortions due to B0 inhomogeneities and gradient nonlinearities and used the data to extend the MR FoV.

MR-based truncation and attenuation correction in integrated PET/MR hybrid imaging using HUGE with continuous table motion.

PURPOSE: The objective of this study was to introduce and evaluate a method for MR-based attenuation and truncation correction in phantom and patient measurements to improve PET quantification in PET/MR hybrid imaging. METHODS: The fully MR-based method HUGE (B0 Homogenization using gradient enhancement) provides field-of-view extension in MR imaging, which can be used for truncation correction and improved PET quantification in PET/MR hybrid imaging. The HUGE method in this recent implementation is combined with continuously moving table data acquisition to provide a seamless nontruncated whole-body data set of the outer patient contours to complete the established standard MR-based Dixon-VIBE data for attenuation correction. The method was systematically evaluated in NEMA standard phantom experiments to investigate the impact of HUGE truncation correction on PET quantification. The method was then applied to 24 oncologic patients in whole-body PET/MR hybrid imaging. The impact of MR-based truncation correction with HUGE on PET data was compared to the impact of the established PET-based MLAA algorithm for contour detection. RESULTS: In phantom and in all patient measurements, the standard Dixon-VIBE attenuation correction data show geometric distortions and signal truncations at the edges of the MR imaging field-of-view. In contrast, the Dixon-VIBE-based attenuation correction data additionally extended by applying HUGE shows significantly less distortion and truncations and due to the continuously moving table acquisition robustly provides smooth outer contours of the patient arms. In the investigated patient cases, MLAA frequently showed an overestimation of arm volume and associated artifacts limiting contour detection. When applying HUGE, an average relative increase in SUVmean in patients' lesion of 4.2% and for MLAA of 4.6% were measured, when compared to standard Dixon-VIBE only. In specific lesions maximal differences in SUVmean up to 13% for HUGE and 14% for MLAA were measured. Quantification in truncated regions showed maximal differences up to 40% for both, MLAA and HUGE. Average differences in those regions in SUVmean for HUGE are 13.3% and 14.6% for MLAA. In a patient with I-124 radiotracer PET-based MLAA contour detection completely failed in this specific case, whereas HUGE as MR-based approach provided accurate truncation correction. CONCLUSIONS: The HUGE method for truncation correction combined with continuous table movement extends the lateral MR field-of-view and effectively reduces truncations along the outer contours of the patient's arms in whole-body PET/MR imaging. HUGE as a fully MR-based approach is independent of the choice of radiotracer, thus also offering robust truncation correction in patients that are not injected with Fluordesoxyglucose (FDG) as radiotracer. Therefore, this method improves the standard Dixon MR-based attenuation correction and PET image quantification in whole-body PET/MR imaging applications.

Field of view extension and truncation correction for MR-based human attenuation correction in simultaneous MR/PET imaging.

PURPOSE: In quantitative PET imaging, it is critical to accurately measure and compensate for the attenuation of the photons absorbed in the tissue. While in PET/CT the linear attenuation coefficients can be easily determined from a low-dose CT-based transmission scan, in whole-body MR/PET the computation of the linear attenuation coefficients is based on the MR data. However, a constraint of the MR-based attenuation correction (AC) is the MR-inherent field-of-view (FoV) limitation due to static magnetic field (B0) inhomogeneities and gradient nonlinearities. Therefore, the MR-based human AC map may be truncated or geometrically distorted toward the edges of the FoV and, consequently, the PET reconstruction with MR-based AC may be biased. This is especially of impact laterally where the patient arms rest beside the body and are not fully considered. METHODS: A method is proposed to extend the MR FoV by determining an optimal readout gradient field which locally compensates B0 inhomogeneities and gradient nonlinearities. This technique was used to reduce truncation in AC maps of 12 patients, and the impact on the PET quantification was analyzed and compared to truncated data without applying the FoV extension and additionally to an established approach of PET-based FoV extension. RESULTS: The truncation artifacts in the MR-based AC maps were successfully reduced in all patients, and the mean body volume was thereby increased by 5.4%. In some cases large patient-dependent changes in SUV of up to 30% were observed in individual lesions when compared to the standard truncated attenuation map. CONCLUSIONS: The proposed technique successfully extends the MR FoV in MR-based attenuation correction and shows an improvement of PET quantification in whole-body MR/PET hybrid imaging. In comparison to the PET-based completion of the truncated body contour, the proposed method is also applicable to specialized PET tracers with little uptake in the arms and might reduce the computation time by obviating the need for iterative calculations of the PET emission data beyond those required for reconstructing images.