Task-evoked simultaneous FDG-PET and fMRI data for measurement of neural metabolism in the human visual cortex

Abstract

Understanding how the living human brain functions requires sophisticated in vivo neuroimaging technologies to characterise the complexity of neuroanatomy, neural function, and brain metabolism. Fluorodeoxyglucose positron emission tomography (FDG-PET) studies of human brain function have historically been limited in their capacity to measure dynamic neural activity. Simultaneous [18 F]-FDG-PET and functional magnetic resonance imaging (fMRI) with FDG infusion protocols enable examination of dynamic changes in cerebral glucose metabolism simultaneously with dynamic changes in blood oxygenation. The Monash vis-fPET-fMRI dataset is a simultaneously acquired FDG-fPET/BOLD-fMRI dataset acquired from n = 10 healthy adults (18–49 yrs) whilst they viewed a flickering checkerboard task. The dataset contains both raw (unprocessed) images and source data organized according to the BIDS specification. The source data includes PET listmode, normalization, sinogram and physiology data. Here, the technical feasibility of using opensource frameworks to reconstruct the PET listmode data is demonstrated. The dataset has significant re-use value for the development of new processing pipelines, signal optimisation methods, and to formulate new hypotheses concerning the relationship between neuronal glucose uptake and cerebral haemodynamics.

Monash DaCRA fPET-fMRI: A dataset for comparison of radiotracer administration for high temporal resolution functional FDG-PET

“…To prepare the BIDS dataset, the open source conversion tool Heudiconv [ 20 ] was used to organize the imaging data into structured directory layouts, and the dcm2niix converter [ 21 ] was used to convert image data from dicom to NIfTI format. Following the approach in our previous article [ 28 ], we applied scripts to (i) remove personal identifiable information from the raw PET dicom header, (ii) add custom json sidecar files to the PET raw data and reconstructed image data, and (iii) generate plasma radioactivity files. Refer to [ 19 ] for these scripts.…”

“…Simultaneous MR-PET is a nascent technique, opening up many opportunities for scientific discovery, methods development, and signal optimization of dual-modality data. Although few imaging facilities worldwide currently possess the infrastructure and technical skill to acquire fPET-fMRI data, the rapid increase in publication (e.g., [ 5–7 , 10–12 , 15 , 28 , 40 ]) and reuse metrics of publicly available datasets [ 41 , 42 ] attests to the value that the international neuroscience community places on this novel data type. The Monash DaCRA fPET-fMRI dataset is the only publicly available dataset that allows comparison of radiotracer administration protocols for fPET-fMRI.…”

“…With listmode and reconstructed data, examples of reuse include the development of new processing pipelines and signal optimization methods that take into account variability in radiotracer dynamics related to differences in administration method. Release of listmode PET data is notable; to our knowledge only 1 other open source dataset includes listmode PET data: the Monash visfPET-fMRI dataset [ 28 ]. These data releases are very novel, occurring prior to the formalization of the PET BIDS standard (BEP009) [ 43 , 44 ].…”

“…These data releases are very novel, occurring prior to the formalization of the PET BIDS standard (BEP009) [ 43 , 44 ]. The draft PET BIDS standard does not yet extend to listmode data [ 44 ], so we applied our BIDS-like standard [ 28 ] to ensure that it is consistent with the interoperability principle of the FAIR philosophy. We [ 28 ] have previously demonstrated that listmode fPET data can be accurately reconstructed using open source methods STIR [ 45 ] and SIRF [ 46 ], confirming that the Monash DaCRA fPET-fMRI dataset is also consistent with the reusability principle of the FAIR philosophy.…”

“…The draft PET BIDS standard does not yet extend to listmode data [ 44 ], so we applied our BIDS-like standard [ 28 ] to ensure that it is consistent with the interoperability principle of the FAIR philosophy. We [ 28 ] have previously demonstrated that listmode fPET data can be accurately reconstructed using open source methods STIR [ 45 ] and SIRF [ 46 ], confirming that the Monash DaCRA fPET-fMRI dataset is also consistent with the reusability principle of the FAIR philosophy. One caveat for the listmode data is that it is not possible to release the proprietary point-spread function (PSF) data for partial volume error (PVE) correction during reconstruction.…”