Guidelines for the content and format of PET brain data in publications and archives: A consensus paper

Knudsen, Gitte M.; Ganz, Melanie; Appelhoff, Stefan; Boellaard, Ronald; Bormans, Guy; Carson, Richard E.; Catana, Ciprian; Doudet, Doris J.; Gee, Antony D.; Greve, Douglas N.; Gunn, Roger N.; Halldin, Christer; Herscovitch, Peter; Huang, Henry; Keller, Sune H.; Lammertsma, Adriaan A.; Lanzenberger, Rupert; Liow, Jeih San; Lohith, Talakad; Lubberink, Mark; Lyoo, Chul Hyoung; Mann, J. John; Matheson, Granville J.; Nichols, Thomas E.; Nørgaard, Martin Agge; Ogden, Todd; Parsey, Ramin V.; Pike, Victor W.; Price, Julie C.; Rizzo, Gaia; Rosa‐Neto, Pedro; Schain, Martin; Scott, Peter; Searle, Graham; Slifstein, Mark; Suhara, Tetsuya; Talbot, Peter S.; Thomas, Adam G.; Veronese, Mattia; Wong, Dean F.; Yaqub, Maqsood; Zanderigo, Francesca; Zoghbi, Sami S.; Innis, Robert B.

doi:10.1177/0271678x20905433

Cited by 60 publications

(54 citation statements)

References 25 publications

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“…change in amyloid signal in Alzheimer's disease [1]), so that data from multiple centres need to be combined to form the large datasets needed to obtain statistically significant conclusions. The growing need for multi-centre collaborations and (raw) data sharing in clinical brain research [2,3] further highlights the need for image comparability between PET systems across multiple clinical centres.…”

Section: Introductionmentioning

confidence: 99%

Harmonisation of PET/CT contrast recovery performance for brain studies

Verwer

Golla

Kaalep

et al. 2021

Eur J Nucl Med Mol Imaging

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Purpose In order to achieve comparability of image quality, harmonisation of PET system performance is imperative. In this study, prototype harmonisation criteria for PET brain studies were developed. Methods Twelve clinical PET/CT systems (4 GE, 4 Philips, 4 Siemens, including SiPM-based “digital” systems) were used to acquire 30-min PET scans of a Hoffman 3D Brain phantom filled with ~ 33 kBq·mL−1 [18F]FDG. Scan data were reconstructed using various reconstruction settings. The images were rigidly coregistered to a template (voxel size 1.17 × 1.17 × 2.00 mm3) onto which several volumes of interest (VOIs) were defined. Recovery coefficients (RC) and grey matter to white matter ratios (GMWMr) were derived for eroded (denoted in the text by subscript e) and non-eroded grey (GM) and white (WM) matter VOIs as well as a mid-phantom cold spot (VOIcold) and VOIs from the Hammers atlas. In addition, left-right hemisphere differences and voxel-by-voxel differences compared to a reference image were assessed. Results Systematic differences were observed for reconstructions with and without point-spread-function modelling (PSFON and PSFOFF, respectively). Normalising to image-derived activity, upper and lower limits ensuring image comparability were as follows: for PSFON, RCGMe = [0.97–1.01] and GMWMre = [3.51–3.91] for eroded VOI and RCGM = [0.78–0.83] and GMWMr = [1.77–2.06] for non-eroded VOI, and for PSFOFF, RCGMe = [0.92–0.99] and GMWMre = [3.14–3.68] for eroded VOI and RCGM = [0.75–0.81] and GMWMr = [1.72–1.95] for non-eroded VOI. Conclusions To achieve inter-scanner comparability, we propose selecting reconstruction settings based on RCGMe and GMWMre as specified in “Results”. These proposed standards should be tested prospectively to validate and/or refine the harmonisation criteria.

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Section: Introductionmentioning

confidence: 99%

Harmonisation of PET/CT contrast recovery performance for brain studies

Verwer

Golla

Kaalep

et al. 2021

Eur J Nucl Med Mol Imaging

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“…Consensus guidelines for standardized and complete reporting of PET imaging study results have recently been published [141]. These represent best practices for data reporting and sharing and are aimed at maximizing reproducibility, transparency, and the potential for data pooling.…”

Section: Standardized Reporting Of Pet Imaging Resultsmentioning

confidence: 99%

The Use, Standardization, and Interpretation of Brain Imaging Data in Clinical Trials of Neurodegenerative Disorders

Schwarz

2021

Neurotherapeutics

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Imaging biomarkers play a wide-ranging role in clinical trials for neurological disorders. This includes selecting the appropriate trial participants, establishing target engagement and mechanism-related pharmacodynamic effect, monitoring safety, and providing evidence of disease modification. In the early stages of clinical drug development, evidence of target engagement and/or downstream pharmacodynamic effect—especially with a clear relationship to dose—can provide confidence that the therapeutic candidate should be advanced to larger and more expensive trials, and can inform the selection of the dose(s) to be further tested, i.e., to “de-risk” the drug development program. In these later-phase trials, evidence that the therapeutic candidate is altering disease-related biomarkers can provide important evidence that the clinical benefit of the compound (if observed) is grounded in meaningful biological changes. The interpretation of disease-related imaging markers, and comparability across different trials and imaging tools, is greatly improved when standardized outcome measures are defined. This standardization should not impinge on scientific advances in the imaging tools per se but provides a common language in which the results generated by these tools are expressed. PET markers of pathological protein aggregates and structural imaging of brain atrophy are common disease-related elements across many neurological disorders. However, PET tracers for pathologies beyond amyloid β and tau are needed, and the interpretability of structural imaging can be enhanced by some simple considerations to guard against the possible confound of pseudo-atrophy. Learnings from much-studied conditions such as Alzheimer’s disease and multiple sclerosis will be beneficial as the field embraces rarer diseases.

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“…It should by now be clear to the reader that a set of critical decisions needs to be made before applying sequential BF testing in a clinical PET study. For this reason, we recommend all researchers to pre-register their analysis before data collection starts 9 (van ‘t Veer and Giner-Sorolla 2016; Poldrack et al 2017; Knudsen et al 2020). A pre-registration can be thought of as a safety net for the researcher.…”

Section: Discussionmentioning

confidence: 99%

Early stopping in clinical PET studies: how to reduce expense and exposure

Svensson

Schain

Knudsen

et al. 2020

Preprint

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Clinical positron emission tomography (PET) research is costly and entails exposing participants to radioactivity. Researchers should therefor aim to include just the number of subjects needed to fulfill the purpose of the study, no more, no less. In this tutorial we show how to apply sequential Bayes Factor testing in order to stop the recruitment of subjects in a clinical PET study as soon as enough data have been collected to make a conclusion. We evaluate this framework in two common PET study designs: a cross-sectional (e.g., patient-control comparison) and a paired-sample design (e.g., pre-intervention-post scan comparison). By using simulations, we show that it is possible to stop a clinical PET study early, both when there is an effect and when there is no effect, while keeping the number of erroneous conclusions at acceptable levels. Based on the results we recommend settings for a sequential design that are appropriate for commonly seen sample sizes in clinical PET-studies. Finally, we apply sequential Bayes Factor testing to a real PET data set and show that it is possible to obtain support in favor of an effect while simultaneously reducing the sample size with 30%. Using this procedure allows researchers to reduce expense and radioactivity exposure for a range of effect sizes relevant for PET research.

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Guidelines for the content and format of PET brain data in publications and archives: A consensus paper

Cited by 60 publications

References 25 publications

Harmonisation of PET/CT contrast recovery performance for brain studies

Harmonisation of PET/CT contrast recovery performance for brain studies

The Use, Standardization, and Interpretation of Brain Imaging Data in Clinical Trials of Neurodegenerative Disorders

Early stopping in clinical PET studies: how to reduce expense and exposure

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