title: Improved UTE-based attenuation correction for cranial PET-MR using dynamic magnetic field monitoring.
abstract: OBJECTIVE
  Ultrashort echo time (UTE) MRI has been proposed as a way to produce segmented attenuation maps for PET, as it provides contrast between bone, air, and soft tissue. However, UTE sequences require samples to be acquired during rapidly changing gradient fields, which makes the resulting images prone to eddy current artifacts. In this work it is demonstrated that this can lead to misclassification of tissues in segmented attenuation maps (AC maps) and that these effects can be corrected for by measuring the true k-space trajectories using a magnetic field camera.
  
  
  METHODS
  The k-space trajectories during a dual echo UTE sequence were measured using a dynamic magnetic field camera. UTE images were reconstructed using nominal trajectories and again using the measured trajectories. A numerical phantom was used to demonstrate the effect of reconstructing with incorrect trajectories. Images of an ovine leg phantom were reconstructed and segmented and the resulting attenuation maps were compared to a segmented map derived from a CT scan of the same phantom, using the Dice similarity measure. The feasibility of the proposed method was demonstrated in in vivo cranial imaging in five healthy volunteers. Simulated PET data were generated for one volunteer to show the impact of misclassifications on the PET reconstruction.
  
  
  RESULTS
  Images of the numerical phantom exhibited blurring and edge artifacts on the bone-tissue and air-tissue interfaces when nominal k-space trajectories were used, leading to misclassification of soft tissue as bone and misclassification of bone as air. Images of the tissue phantom and the in vivo cranial images exhibited the same artifacts. The artifacts were greatly reduced when the measured trajectories were used. For the tissue phantom, the Dice coefficient for bone in MR relative to CT was 0.616 using the nominal trajectories and 0.814 using the measured trajectories. The Dice coefficients for soft tissue were 0.933 and 0.934 for the nominal and measured cases, respectively. For air the corresponding figures were 0.991 and 0.993. Compared to an unattenuated reference image, the mean error in simulated PET uptake in the brain was 9.16% when AC maps derived from nominal trajectories was used, with errors in the SUV max for simulated lesions in the range of 7.17%-12.19%. Corresponding figures when AC maps derived from measured trajectories were used were 0.34% (mean error) and -0.21% to +1.81% (lesions).
  
  
  CONCLUSIONS
  Eddy current artifacts in UTE imaging can be corrected for by measuring the true k-space trajectories during a calibration scan and using them in subsequent image reconstructions. This improves the accuracy of segmented PET attenuation maps derived from UTE sequences and subsequent PET reconstruction.
authors.affiliation: Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas Hospital, London SE1 7EH, United Kingdom.
authors.forename: A P
authors.initials: AP
authors.lastname: Aitken
authors.affiliation: Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas Hospital, London SE1 7EH, United Kingdom.
authors.forename: D
authors.initials: D
authors.lastname: Giese
authors.affiliation: Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas Hospital, London SE1 7EH, United Kingdom.
authors.forename: C
authors.initials: C
authors.lastname: Tsoumpas
authors.affiliation: Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas Hospital, London SE1 7EH, United Kingdom.
authors.forename: P
authors.initials: P
authors.lastname: Schleyer
authors.affiliation: Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas Hospital, London SE1 7EH, United Kingdom.
authors.forename: S
authors.initials: S
authors.lastname: Kozerke
authors.affiliation: Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas Hospital, London SE1 7EH, United Kingdom.
authors.forename: C
authors.initials: C
authors.lastname: Prieto
authors.affiliation: Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas Hospital, London SE1 7EH, United Kingdom.
authors.forename: T
authors.initials: T
authors.lastname: Schaeffter
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D060526:Magnetic Fields; D008279:Magnetic Resonance Imaging; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography; D012886:Skull / Q000000981:diagnostic imaging*; D013997:Time Factors