Evidence map›Paper›PMID 34611766›Full record

ArticleMolecular imaging and biology2022

Amyloid-β PET Classification on Cognitive Aging Stages Using the Centiloid Scale.

Giordana Salvi de Souza, Michele Alberton Andrade, Wyllians Vendramini Borelli, Lucas Porcello Schilling, Cristina Sebastião Matushita, Mirna Wetters Portuguez, Jaderson Costa da Costa, Ana Maria Marques da Silva

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In one paragraph

Article in Molecular imaging and biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. The clinical Alzheimer's disease spectrum classified in the A/T/N framework withEuropean journal of nuclear medicine and molecular imaging · 2026
    Observational
  3. A harmonized framework for studying exceptional cognitive aging in Latin America.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Predicting cognitive stage transition using p-tau181, Centiloid, and other measures.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023
    Article
  8. Biomarkers for dementia in Latin American countries: Gaps and opportunities.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023
    Article
  9. Article
  10. Article
  11. Article
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

8 authors.

Giordana Salvi de SouzaSchool of Medicine, PUCRS, Porto Alegre, Brazil. giordana.souza@edu.pucrs.br.
Michele Alberton AndradeSchool of Medicine, PUCRS, Porto Alegre, Brazil.
Wyllians Vendramini BorelliBrain Institute of Rio Grande Do Sul (BraIns), PUCRS, Porto Alegre, Brazil.
Lucas Porcello SchillingBrain Institute of Rio Grande Do Sul (BraIns), PUCRS, Porto Alegre, Brazil.
Cristina Sebastião MatushitaBrain Institute of Rio Grande Do Sul (BraIns), PUCRS, Porto Alegre, Brazil.
Mirna Wetters PortuguezSchool of Medicine, PUCRS, Porto Alegre, Brazil.
Jaderson Costa da CostaSchool of Medicine, PUCRS, Porto Alegre, Brazil.
Ana Maria Marques da SilvaSchool of Medicine, PUCRS, Porto Alegre, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

proposeThis study aims to explore the use of the Centiloid (CL) method in amyloid-β PET quantification to evaluate distinct cognitive aging stages, investigating subjects' mismatch classification using different cut-points for amyloid-β positivity. PROCEDURES: The CL equation was applied in four groups of individuals: SuperAgers (SA), healthy age-matched controls (AC), healthy middle-aged controls (MC), and Alzheimer's disease (AD). The amyloid-β burden was calculated and compared between groups and quantitative variables. Three different cut-points (Jack CR, Wiste HJ, Weigand SD, et al., Alzheimer's Dement 13:205-216, 2017; Salvadó G, Molinuevo JL, Brugulat-Serrat A, et al., Alzheimer's Res Ther 11:27, 2019; and Amadoru S, Doré V, McLean CA, et al., Alzheimer's Res Ther 12:22, 2020) were applied in CL values to differentiate the earliest abnormal pathophysiological accumulation of Aβ and the established Aβ pathology.

resultsThe AD group exhibited a significantly increased Aβ burden compared to the MC, but not AC groups. Both healthy control (MC and AC) groups were not significantly different. Visually, the SA group showed a diverse distribution of CL values compared with MC; however, the difference was not significant. The CL values have a moderate and significant relationship between Aβ visual read, RAVLT DR and MMSE. Depending on the cut-point used, 10 CL, 19 CL, or 30 CL, 7.5% of our individuals had a different classification in the Aβ positivity. For the AC group, we obtained about 40 to 60% of the individuals classified as positive.

conclusionSuperAgers exhibited a similar Aβ load to AC and MC, differing in cognitive performance. Independently of cut-point used (10 CL, 19 CL, or 30 CL), three SA individuals were classified as Aβ positive, showing the duality between the individual's clinics and the biological definition of Alzheimer's. Different cut-points lead to Aβ positivity classification mismatch in individuals, and an extra care is needed for individuals who have a CL value between 10 and 30 CL.

Indexed as

Alzheimer DiseaseCognitive AgingAmyloid beta-PeptidesAniline CompoundsHumansMiddle AgedPositron-Emission TomographyAmyloid beta-PeptidesAniline Compounds11C-PiBDiagnostic imagingHealthy agingPositron emission tomographySuperAgers

Identifiers

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Registered trials

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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.