Image-derived input functions from dynamic (15)O–water PET scans using penalised reconstruction

BACKGROUND: Quantitative positron emission tomography (PET) scans of the brain typically require arterial blood sampling but this is complicated and logistically challenging. One solution to remove the need for arterial blood sampling is the use of image-derived input functions (IDIFs). Obtaining accurate IDIFs, however, has proved to be challenging, mainly due to the limited resolution of PET. Here, we employ penalised reconstruction alongside iterative thresholding methods and simple partial volume correction methods to produce IDIFs from a single PET scan, and subsequently, compare these to blood-sampled input curves (BSIFs) as ground truth. Retrospectively we used data from sixteen subjects with two dynamic (15)O-labelled water PET scans and continuous arterial blood sampling: one baseline scan and another post-administration of acetazolamide. RESULTS: IDIFs and BSIFs agreed well in terms of the area under the curve of input curves when comparing peaks, tails and peak-to-tail ratios with R(2) values of 0.95, 0.70 and 0.76, respectively. Grey matter cerebral blood flow (CBF) values showed good agreement with an average difference between the BSIF and IDIF CBF values of 2% ± and a coefficient of variation (CoV) of 7.3%. CONCLUSION: Our results show promising results that a robust IDIF can be produced for dynamic (15)O–water PET scans using only the dynamic PET scan images with no need for a corresponding MRI or complex analytical techniques and thereby making routine clinical use of quantitative CBF measurements with (15)O–water feasible. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-023-00535-w.