Image-derived input function in PET brain studies: Blood-based methods are resistant to motion artifacts

Paolo Zanotti-Fregonara, Jeih San Liow, Claude Comtat, Sami S. Zoghbi, Yi Zhang, Victor W. Pike, Masahiro Fujita, Robert B. Innis

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


BACKGROUND: Image-derived input function (IDIF) from carotid arteries is an elegant alternative to full arterial blood sampling for brain PET studies. However, a recent study using blood-free IDIFs found that this method is particularly vulnerable to patient motion. The present study used both simulated and clinical [C](R)-rolipram data to assess the robustness of a blood-based IDIF method (a method that is ultimately normalized with blood samples) with regard to motion artifacts. METHODS: The impact of motion on the accuracy of IDIF was first assessed with an analytical simulation of a high-resolution research tomograph using a numerical phantom of the human brain, equipped with internal carotids. Different degrees of translational (from 1 to 20 mm) and rotational (from 1 to 15°) motions were tested. The impact of motion was then tested on the high-resolution research tomograph dynamic scans of three healthy volunteers, reconstructed with and without an online motion correction system. IDIFs and Logan-distribution volume (VT) values derived from simulated and clinical scans with motion were compared with those obtained from the scans with motion correction. RESULTS: In the phantom scans, the difference in the area under the curve (AUC) for the carotid time-activity curves was up to 19% for rotations and up to 66% for translations compared with the motionless simulation. However, for the final IDIFs, which were fitted to blood samples, the AUC difference was 11% for rotations and 8% for translations. Logan-VT errors were always less than 10%, except for the maximum translation of 20 mm, in which the error was 18%. Errors in the clinical scans without motion correction appeared to be minor, with differences in AUC and Logan-VT always less than 10% compared with scans with motion correction. CONCLUSION: When a blood-based IDIF method is used for neurological PET studies, the motion of the patient affects IDIF estimation and kinetic modeling only minimally.

Original languageEnglish (US)
Pages (from-to)982-989
Number of pages8
JournalNuclear medicine communications
Issue number9
StatePublished - Sep 2012


  • PET
  • image-derived input function
  • neuroreceptor tracers

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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