title: PET attenuation correction using synthetic CT from ultrashort echo-time MR imaging.
abstract: Integrated PET/MR systems are becoming increasingly popular in clinical and research applications. Quantitative PET reconstruction requires correction for γ-photon attenuations using an attenuation coefficient map (μ map) that is a measure of the electron density. One challenge of PET/MR, in contrast to PET/CT, lies in the accurate computation of μ maps. Unlike CT, MR imaging measures physical properties not directly related to electron density. Previous approaches have computed the attenuation coefficients using a segmentation of MR images or using deformable registration of atlas CT images to the space of the subject MR images.
  
  
  METHODS
  In this work, we propose a patch-based method to generate whole-head μ maps from ultrashort echo-time (UTE) MR imaging sequences. UTE images are preferred to other MR sequences because of the increased signal from bone. To generate a synthetic CT image, we use patches from a reference dataset, which consists of dual-echo UTE images and a coregistered CT scan from the same subject. Matching of patches between the reference and target images allows corresponding patches from the reference CT scan to be combined via a Bayesian framework. No registration or segmentation is required.
  
  
  RESULTS
  For evaluation, UTE, CT, and PET data acquired from 5 patients under an institutional review board-approved protocol were used. Another patient (with UTE and CT data only) was selected to be the reference to generate synthetic CT images for these 5 patients. PET reconstructions were attenuation-corrected using the original CT, our synthetic CT, Siemens Dixon-based μ maps, Siemens UTE-based μ maps, and deformable registration-based CT. Our synthetic CT-based PET reconstruction showed higher correlation (average ρ = 0.996, R(2) = 0.991) to the original CT-based PET, as compared with the segmentation- and registration-based methods. Synthetic CT-based reconstruction had minimal bias (regression slope, 0.990), as compared with the segmentation-based methods (regression slope, 0.905). A peak signal-to-noise ratio of 35.98 dB in the reconstructed PET activity was observed, compared with 29.767, 29.34, and 27.43 dB for the Siemens Dixon-, UTE-, and registration-based μ maps.
  
  
  CONCLUSIONS
  A patch-matching approach to synthesize CT images from dual-echo UTE images leads to significantly improved accuracy of PET reconstruction as compared with actual CT scans. The PET reconstruction is improved over segmentation- (Dixon and Siemens UTE) and registration-based methods, even in subjects with pathologic findings.
authors.affiliation: Center for Neuroscience and Regenerative Medicine, Henry Jackson Foundation, Bethesda, Maryland snehashis.roy@gmail.com.
authors.forename: Snehashis
authors.initials: S
authors.lastname: Roy
authors.affiliation: Center for Neuroscience and Regenerative Medicine, Henry Jackson Foundation, Bethesda, Maryland.
authors.forename: Wen-Tung
authors.initials: WT
authors.lastname: Wang
authors.affiliation: Image Analysis and Communications Laboratory, Johns Hopkins University, Baltimore, Maryland; and.
authors.forename: Aaron
authors.initials: A
authors.lastname: Carass
authors.affiliation: Image Analysis and Communications Laboratory, Johns Hopkins University, Baltimore, Maryland; and.
authors.forename: Jerry L
authors.initials: JL
authors.lastname: Prince
authors.affiliation: Department of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, Maryland.
authors.forename: John A
authors.initials: JA
authors.lastname: Butman
authors.affiliation: Center for Neuroscience and Regenerative Medicine, Henry Jackson Foundation, Bethesda, Maryland.
authors.forename: Dzung L
authors.initials: DL
authors.lastname: Pham
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology / Q000000981:diagnostic imaging / Q000473:pathology; D003198:Computer Simulation; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D064847:Multimodal Imaging / Q000379:methods*; D049268:Positron-Emission Tomography / Q000379:methods*; D019275:Radiopharmaceuticals; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
keywords: CT; PET/CT; PET/MRI; UTE; attenuation correction