Estimation of regional bone metabolism from whole-body F-18-fluoride PET static images

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We evaluate a new quantitative method of acquiring and analysing 18F positron emission tomography (PET) studies that enables regional bone plasma clearance (K i ) to be estimated from static scans acquired at multiple sites in the skeleton following a single injection of tracer.

Dynamic lumbar spine 18F PET data from two clinical trials were used to simulate a series of static scans acquired 30–60 min after injection. Venous blood samples were taken at 30, 40, 50 and 60 min and K i evaluated by Patlak analysis and the static scan method. The data were used to evaluate the precision errors of the Patlak and static scan methods expressed as the percentage coefficient of variation (%CV) and compare their response to 6 months of treatment with the bone anabolic agent teriparatide.

Static scan K i measurements 30–60 min after injection were highly correlated with the Patlak results (r > 0.99). The %CV for the static scan method was 17.5% 30 min after injection, decreasing to 14.5% at 60 min, compared with 13.0% for Patlak analysis. Response to teriparatide treatment was +25.2% for the static scan method compared with +24.3% for Patlak analysis. The mean ratio (SD) of the static scan and Patlak K i results was 1.006 (0.015) at 30 min after injection decreasing to 0.965 (0.015) at 60 min.

18F-Fluoride bone plasma clearance can be estimated from a static scan and venous blood samples acquired 30–60 min after injection. The method enables K i to be estimated at multiple skeletal sites with a single injection of tracer.
Original languageEnglish
Pages (from-to)337 - 343
Number of pages7
JournalEuropean Journal of Nuclear Medicine and Molecular Imaging
Issue number2
Publication statusPublished - Feb 2012


  • Bone and Bones
  • Positron-Emission Tomography
  • Teriparatide
  • Fluorodeoxyglucose F18
  • Humans
  • Whole Body Imaging
  • Aged
  • Models, Statistical
  • Kinetics
  • Fluorine Radioisotopes
  • Osteoporosis, Postmenopausal
  • Middle Aged
  • Time Factors
  • Image Processing, Computer-Assisted
  • Female


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