Fully automated calculation of image-derived input function in simultaneous 
PET/MRI in a sheep model

Jochimsen, Thies H.; Zeisig, Vilia; Schulz, Jessica; Werner, Peter; Patt, Marianne; Patt, Jörg; Dreyer, Antje Y.; Boltze, Johannes; Barthel, Henryk; Sabri, Osama; Sattler, Bernhard

doi:10.1186/s40658-016-0139-2

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Fully automated calculation of image-derived input function in simultaneous PET/MRI in a sheep model

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Schulz, Jessica
Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Jochimsen, T. H., Zeisig, V., Schulz, J., Werner, P., Patt, M., Patt, J., et al. (2016). Fully automated calculation of image-derived input function in simultaneous PET/MRI in a sheep model. EJNMMI Physics, 3: 2. doi:10.1186/s40658-016-0139-2.

Cite as: https://hdl.handle.net/11858/00-001M-0000-002B-2DD1-0

Abstract

Background

Obtaining the arterial input function (AIF) from image data in dynamic positron emission tomography (PET) examinations is a non-invasive alternative to arterial blood sampling. In simultaneous PET/magnetic resonance imaging (PET/MRI), high-resolution MRI angiographies can be used to define major arteries for correction of partial-volume effects (PVE) and point spread function (PSF) response in the PET data. The present study describes a fully automated method to obtain the image-derived input function (IDIF) in PET/MRI. Results are compared to those obtained by arterial blood sampling.
Methods

To segment the trunk of the major arteries in the neck, a high-resolution time-of-flight MRI angiography was postprocessed by a vessel-enhancement filter based on the inertia tensor. Together with the measured PSF of the PET subsystem, the arterial mask was used for geometrical deconvolution, yielding the time-resolved activity concentration averaged over a major artery. The method was compared to manual arterial blood sampling at the hind leg of 21 sheep (animal stroke model) during measurement of blood flow with O15-water. Absolute quantification of activity concentration was compared after bolus passage during steady state, i.e., between 2.5- and 5-min post injection. Cerebral blood flow (CBF) values from blood sampling and IDIF were also compared.
Results

The cross-calibration factor obtained by comparing activity concentrations in blood samples and IDIF during steady state is 0.98 ± 0.10. In all examinations, the IDIF provided a much earlier and sharper bolus peak than in the time course of activity concentration obtained by arterial blood sampling. CBF using the IDIF was 22 % higher than CBF obtained by using the AIF yielded by blood sampling.
Conclusions

The small deviation between arterial blood sampling and IDIF during steady state indicates that correction of PVE and PSF is possible with the method presented. The differences in bolus dynamics and, hence, CBF values can be explained by the different sampling locations (hind leg vs. major neck arteries) with differences in delay/dispersion. It will be the topic of further work to test the method on humans with the perspective of replacing invasive blood sampling by an IDIF using simultaneous PET/MRI.