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

  1. Sharna D Jamadar
  2. Emma X Liang
  3. Shenjun Zhong
  4. Phillip G D Ward
  5. Alexandra Carey
  6. Richard McIntyre
  7. Zhaolin Chen
  8. Gary F Egan

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

“Functional” [18F]-fluorodeoxyglucose positron emission tomography (FDG-fPET) is a new approach for measuring glucose uptake in the human brain. The goal of FDG-fPET is to maintain a constant plasma supply of radioactive FDG in order to track, with high temporal resolution, the dynamic uptake of glucose during neuronal activity that occurs in response to a task or at rest. FDG-fPET has most often been applied in simultaneous BOLD-fMRI/FDG-fPET (blood oxygenation level–dependent functional MRI fluorodeoxyglucose functional positron emission tomography) imaging. BOLD-fMRI/FDG-fPET provides the capability to image the 2 primary sources of energetic dynamics in the brain, the cerebrovascular haemodynamic response and cerebral glucose uptake.

Findings

In this Data Note, we describe an open access dataset, Monash DaCRA fPET-fMRI, which contrasts 3 radiotracer administration protocols for FDG-fPET: bolus, constant infusion, and hybrid bolus/infusion. Participants (n = 5 in each group) were randomly assigned to each radiotracer administration protocol and underwent simultaneous BOLD-fMRI/FDG-fPET scanning while viewing a flickering checkerboard. The bolus group received the full FDG dose in a standard bolus administration, the infusion group received the full FDG dose as a slow infusion over the duration of the scan, and the bolus-infusion group received 50% of the FDG dose as bolus and 50% as constant infusion. We validate the dataset by contrasting plasma radioactivity, grey matter mean uptake, and task-related activity in the visual cortex.

Conclusions

The Monash DaCRA fPET-fMRI dataset provides significant reuse value for researchers interested in the comparison of signal dynamics in fPET, and its relationship with fMRI task-evoked activity.

Article activity feed

  1. GigaScience

    Functional

    Reviewer 3: Chris Armit

    This Data Note describes an Open CC0 neuroimaging dataset of 15 subjects (young adults) who underwent simultaneous BOLD-fMRI and FDG-fPET imaging. FDG-fPET ([18]-fluorodeoxyglucose positron emission tomography) measures glucose uptake in the human brain, whereas BOLD-fMRI (blood oxygenation level dependent functional magnetic resonance imaging) captures the cerebrovascular haemodynamic response. FDG-PET data was acquired using three different radiotracer administration protocols - bolus, constant infusion, and 50% bolus + 50% infusion - and each administration protocol was applied to 5 subjects. BOLD-fMRI and FDG-PET was acquired while participants viewed a checkerboard stimulation, which was used to trigger dynamic changes in brain glucose metabolism.

    This neuroimaging dataset allows researchers to explore the complexity of energetic dynamics in the brain using multimodal imaging data analysis. In addition, this neuroimaging dataset includes structural MRI data for each of the subject, including T1 and T2 FLAIR, enabling neuroanatomical correlations to be explored. The neuroimaging data are available from OpenNeuro [http://doi.org/10.18112/openneuro.ds003397.v1.1.1] and the authors are to be commended for ascribing a CC0 Public Domain Dedication to this dataset. Importantly, the authors highlight that consent was obtained from participants to release de-identified data. I downloaded a small number of image files from this dataset and I confirm that the de-identified NIfTI (Neuroimaging Informatics Technology Initiative) format files can be opened using Fiji / ImageJ.

    This neuroimaging dataset has immense reuse potential and I recommend this Data Note for publication in GigaScience.

  2. GigaScience

    Background

    Reviewer 2: Nicolas Costes

    Jadamar et al present a database of limited size, but of a rarity which amply justifies its interest. This is a combined dynamic FDG PET (fTEP) and fMRI study performed in three groups of 5 subjects for whom 3 different modes of FDG administration were used: bolus, infusion and bolus + infusion. The statistical analysis resulting from this study is also of limited scope due to the low residual degree of freedom of the design, but nevertheless makes it possible to confirm the expected characteristics of the shape of PET kinetics; It confirms the superiority of the bolus + infusion protocol ensuring maximum sensitivity to highlighting the neural circuits involved in the visual flickering task performed during acquisition. The interest of the study lies in the free provision of the whole data that can be used, as it is argued, as a demonstrator for the development of methods for correcting, processing and analyzing data. A multivariate analysis combing PET and fMRI taking advantage of the simultaneous recording is not accired out: a simple GLM voxel-to-voxel analysis makes it possible to expose notable differences between the 3 methods of administration of FDG. However, the provision of data opens the field for future exploitation. The fact that raw data before PET reconstruction is provided is relatively new and opens up the possibility of extending the field of their exploitation to methods of correction and reconstruction. Respecting the BIDS description format as much as possible is also a plus. These data are of undeniable interest to the community and therefore the description of their content and the exhaustive provision of all the demographic and physical parameters of their realization deserve their publication. Some following remarks should be considered before publication. p7. [18F]-FDG 18 should be in upper script p9: raw PE data are in the original format exported from the siemens console: is there a distinction between list-mode file exceeding 4 Gb, as it is the case on the Siemens console? In which format the raw data will be provided? Results: Figure 2: A. Please specify if plasma curves are corrected for 18F radioactivity decay at the time of injection. Figure 3. Why was the correction applied for Zcorr? FWE? FDR? Figure 4. How exactly « percent final change » is computed: is it an average of the active periods compared to rest period? Is it computed from the beta regressor or directly on signal change? In the later case, on which interval? Figure 5. A well the average accros all protocols is provided in Fig3.D to serve as a reference, could you also provide the average accros References Please review references: check for incomplete references (2., 8., 21. for example), uniformity of format and provide DOI as it is already done for the majority of your them.

  3. GigaScience

    Abstract

    **Reviewer 1: Antoine Verger **

    Review on "Data Note: Monash DaCRA fPET-fMRI: A DAtaset for Comparison of Radiotracer Administration for high temporal resolution functional FDG-PET" This article is an important contribution in its field. This study is an open access dataset, Monash DaCRA fPET-fMRI, which contrasts three radiotracer administration protocols for FDG-fPET: bolus, constant infusion and hybrid bolus/infusion. The Monash DaCRA fPET-fMRI dataset is the only publicly available dataset that allows comparison of radiotracer administration protocols for fPET-fMRI. Even if the provided dataset is useful for the scientific community, the validation part needs some explanations.

    Comments:

    • Shame that this dataset is not available also for rest fPET-fMRI images. Indeed, most of the studies are also performed at rest (connectivity of neurodegenerative disorders for example) and should need some controls. Please discuss the opportunity to provide such databases.
    • Was the administered FDG dose unique for all patients or adapted to the body weight? Please detail.
    • The authors should discuss the gender variability across the 3 groups. Metabolism and radiotracer uptake is dependent of gender. The authors should at least include this covariate in their group analyses.
    • Of course, raw data are available. I have nonetheless one question: what is the interest of using PSF and after a Gaussian filter in reconstructed images? Why using PSF in dynamic PET (noisy) images? Please, can the authors justify the 16sec of frames for reconstruction of their images? Was it justified by any optimization?
    • The authors further applied a filter of FWHM 12 mm after having previously reconstructed their images with a Gaussian filter? They should choose one of these two filters. If not, smoothing of PET images is too important.
    • For the validation set at the group level, is the PET intensity normalization based on proportional scaling? It is particularly important to understand how the authors have obtained the grey matter mean signal.
    • How was the grey matter mean signal obtained? From a grey matter MRI mask?
    • Could the authors develop the way to have access to open access reconstructions algorithms? Particularly if images have been obtained with Biograph Siemens. They mention STIR and SIRF: please develop: is it able for anyone who has no access to a Siemens reconstruction algorithm? Is a specific PSF reconstruction for Siemens is implemented?
    • "there has not yet is not yet agreement in the best way to manage" : please rephrase.
    • Figure 1: Please include the conventional MRI sequences at the beginning of the acquisition.
    • Figure 2: Please provide units for signal intensity? It would be also more comfortable to provide elements to distinguish the tasks from the rest periods.
    • Figure 2: is the grey matter signal obtained for all the grey matter or only for the occipital cortex? Should the authors discuss the higher variability observed between patients for methods with bolus? Is it linked to the different sex ratio between the protocols? Discuss Why one patient in the infusion protocol has a truncated time-activity curve?
    • Figure 3: the authors should explain the variability of fMRI patterns in GLM albeit the same protocol was performed. Is there an influence of the coupled glycolytic metabolism?
    • Figure 3: how the authors explain the absence of correlation with task in the infusion protocol? (this was not observed in the 3 phases of the protocols for infusion in Figure 5).
    • Figure 4: define how the increase in signal percentage was calculated? How was the grey-matter normalized at the group level? Proportional scaling can be source of false positive abnormalities.
    • Figure 5: Can the authors display the changes in connectivity of the occipital area between the 3 phases for each protocol? (by adding a supplemental part at the bottom of the Figure).
  4. Version published to 10.1093/gigascience/giac031
  5. Version published to 10.1101/2021.08.02.454708v1 on bioRxiv