title: Multi-Atlas-Based Attenuation Correction for Brain 18F-FDG PET Imaging Using a Time-of-Flight PET/MR Scanner: Comparison with Clinical Single-Atlas- and CT-Based Attenuation Correction.
abstract: In this work, we assessed the feasibility of attenuation correction (AC) based on a multi-atlas-based method (m-Atlas) by comparing it with a clinical AC method (single-atlas-based method [s-Atlas]), on a time-of-flight (TOF) PET/MRI scanner.
  
  
  METHODS
  We enrolled 15 patients. The median patient age was 59 y (age range, 31-80). All patients underwent clinically indicated whole-body (18)F-FDG PET/CT for staging, restaging, or follow-up of malignant disease. All patients volunteered for an additional PET/MRI scan of the head (no additional tracer being injected). For each patient, 3 AC maps were generated. Both s-Atlas and m-Atlas AC maps were generated from the same patient-specific LAVA-Flex T1-weighted images being acquired by default on the PET/MRI scanner during the first 18 s of the PET scan. An s-Atlas AC map was extracted by the PET/MRI scanner, and an m-Atlas AC map was created using a Web service tool that automatically generates m-Atlas pseudo-CT images. For comparison, the AC map generated by PET/CT was registered and used as a gold standard. PET images were reconstructed from raw data on the TOF PET/MRI scanner using each AC map. All PET images were normalized to the SPM5 PET template, and (18)F-FDG accumulation was quantified in 67 volumes of interest (VOIs; automated anatomic labeling atlas). Relative (%diff) and absolute differences (|%diff|) between images based on each atlas AC and CT-AC were calculated. (18)F-FDG uptake in all VOIs and generalized merged VOIs were compared using the paired t test and Bland-Altman test.
  
  
  RESULTS
  The range of error on m-Atlas in all 1,005 VOIs was -4.99% to 4.09%. The |%diff| on the m-Atlas was improved by about 20% compared with s-Atlas (s-Atlas vs. m-Atlas: 1.49% ± 1.06% vs. 1.21% ± 0.89%, P < 0.01). In generalized VOIs, %diff on m-Atlas in the temporal lobe and cerebellum was significantly smaller (s-Atlas vs. m-Atlas: temporal lobe, 1.49% ± 1.37% vs. -0.37% ± 1.41%, P < 0.01; cerebellum, 1.55% ± 1.97% vs. -1.15% ± 1.72%, P < 0.01).
  
  
  CONCLUSIONS
  The errors introduced using either s-Atlas or m-Atlas did not exceed 5% in any brain region investigated. When compared with the clinical s-Atlas, m-Atlas is more accurate, especially in regions close to the skull base.
authors.affiliation: Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland Department of Radiology, Nippon Medical School, Tokyo, Japan tetsuro.sekine@gmail.com.
authors.forename: Tetsuro
authors.initials: T
authors.lastname: Sekine
authors.affiliation: Translational Imaging Group, Centre for Medical Image Computing, University College London, NW1 2HE, London, United Kingdom.
authors.forename: Ninon
authors.initials: N
authors.lastname: Burgos
authors.affiliation: Institute of Pharmacology & Toxicology, University of Zurich, Zurich, Switzerland PMOD Technologies Ltd., Zurich, Switzerland.
authors.forename: Geoffrey
authors.initials: G
authors.lastname: Warnock
authors.affiliation: Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland.
authors.forename: Martin
authors.initials: M
authors.lastname: Huellner
authors.affiliation: Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland.
authors.forename: Alfred
authors.initials: A
authors.lastname: Buck
authors.affiliation: Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland.
authors.forename: Edwin E G W
authors.initials: EE
authors.lastname: Ter Voert
authors.affiliation: Translational Imaging Group, Centre for Medical Image Computing, University College London, NW1 2HE, London, United Kingdom Dementia Research Centre, Institute of Neurology, University College London, WC1N 3AR London, United Kingdom.
authors.forename: M Jorge
authors.initials: MJ
authors.lastname: Cardoso
authors.affiliation: Institute of Nuclear Medicine, University College London, NW1 2BU London, United Kingdom Centre for Medical Radiation Physics, University of Wollongong, NSW 2522 Wollongong, Australia.
authors.forename: Brian F
authors.initials: BF
authors.lastname: Hutton
authors.affiliation: Translational Imaging Group, Centre for Medical Image Computing, University College London, NW1 2HE, London, United Kingdom Dementia Research Centre, Institute of Neurology, University College London, WC1N 3AR London, United Kingdom.
authors.forename: Sebastien
authors.initials: S
authors.lastname: Ourselin
authors.affiliation: Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland Division of Diagnostic and Interventional Radiology, Department of Medical Radiology, University Hospital Zurich, Zurich, Switzerland; and.
authors.forename: Patrick
authors.initials: P
authors.lastname: Veit-Haibach
authors.affiliation: GE Healthcare, Waukesha, Wisconsin.
authors.forename: Gaspar
authors.initials: G
authors.lastname: Delso
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000000981:diagnostic imaging; D001932:Brain Neoplasms / Q000000981:diagnostic imaging*; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D064847:Multimodal Imaging / Q000379:methods*; D049268:Positron-Emission Tomography / Q000379:methods*; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
keywords: 18F-FDG; PET/MR; atlas-based; attenuation correction; brain