Evidence map›Paper›PMID 33423088›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2021

Validation of FDG-PET datasets of normal controls for the extraction of SPM-based brain metabolism maps.

Silvia Paola Caminiti, Arianna Sala, Luca Presotto, Andrea Chincarini, Stelvio Sestini, Daniela Perani, Alzheimer’s Disease Neuroimaging Initiative (ADNI), for the Associazione Italiana Medicina Nucleare (AIMN) datasets, The AIMN Neurology Study-Group collaborators:, Orazio Schillaci, Valentina Berti, Maria Lucia Calcagni and 6 more

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In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
4.6field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 42 citations in OpenAlex.

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  7. Altered brain glucose metabolism and connectivity in young adults with obstructive sleep apnea.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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  13. Alzheimer's research & therapy · 2024
    Observational
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  18. FDG-PET markers of heterogeneity and different risk of progression in amnestic MCI.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 3 institutions in 1 country.

Silvia Paola Caminiti *Vita-Salute San Raffaele University, Milan, Italy.
Arianna Sala *Vita-Salute San Raffaele University, Milan, Italy.
Luca Presotto *Nuclear Medicine Unit, San Raffaele Hospital, Via Olgettina 60, 20132, Milan, Italy.
Andrea ChincariniIstituto Nazionale di Fisica Nucleare, Genoa, Italy.
Stelvio SestiniOspedale di Prato (NOP) S. Stefano, Prato, Italy.
Daniela PeraniVita-Salute San Raffaele University, Milan, Italy. perani.daniela@hsr.it.ORCID http://orcid.org/0000-0002-9784-292X
Alzheimer’s Disease Neuroimaging Initiative (ADNI), for the Associazione Italiana Medicina Nucleare (AIMN) datasets, The AIMN Neurology Study-Group collaborators:
Orazio Schillaci
Valentina Berti
Maria Lucia Calcagni
Angelina Cistaro
Silvia Morbelli
Flavio Nobili
Sabina Pappatà
Duccio Volterrani
Clara Luigia Gobbo
Vita-Salute San Raffaele University · ITIstituto Nazionale di Fisica Nucleare · ITOspedale di Prato Santo Stefano · IT

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Ministero della Salute NET- 2011-02346784NIA NIH HHS U01 AG024904U.S. Department of Defense W81XWH-12-2-0012
6 · The paper itself

Abstract

purposeAn appropriate healthy control dataset is mandatory to achieve good performance in voxel-wise analyses. We aimed at evaluating [18F]FDG PET brain datasets of healthy controls (HC), based on publicly available data, for the extraction of voxel-based brain metabolism maps at the single-subject level.

methodsSelection of HC images was based on visual rating, after Cook's distance and jack-knife analyses, to exclude artefacts and/or outliers. The performance of these HC datasets (ADNI-HC and AIMN-HC) to extract hypometabolism patterns in single patients was tested in comparison with the standard reference HC dataset (HSR-HC) by means of Dice score analysis. We evaluated the performance and comparability of the different HC datasets in the assessment of single-subject SPM-based hypometabolism in three independent cohorts of patients, namely, ADD, bvFTD and DLB.

resultsTwo-step Cook's distance analysis and the subsequent jack-knife analysis resulted in the selection of n = 125 subjects from the AIMN-HC dataset and n = 75 subjects from the ADNI-HC dataset. The average concordance between SPM hypometabolism t-maps in the three patient cohorts, as obtained with the new datasets and compared to the HSR-HC standard reference dataset, was 0.87 for the AIMN-HC dataset and 0.83 for the ADNI-HC dataset. Pattern expression analysis revealed high overall accuracy (> 80%) of the SPM t-map classification according to different statistical thresholds and sample sizes.

conclusionsThe applied procedures ensure validity of these HC datasets for the single-subject estimation of brain metabolism using voxel-wise comparisons. These well-selected HC datasets are ready-to-use in research and clinical settings.

Indexed as

Fluorodeoxyglucose F18Positron-Emission TomographyBrainBrain MappingHumansFluorodeoxyglucose F18Brain hypometabolismDementiaFluorodeoxyglucoseHealthy control datasetNeurodegenerationPETSPMVoxel-wise analysis

Identifiers

PMID33423088
OpenAlexW3119304774

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.