Evidence map›Paper›PMID 38553802›Full record

ArticleAnnals of clinical and translational neurology2024

The diagnostic and prognostic value of tau-PET in amnestic MCI with different FDG-PET subtypes.

Cecilia Boccalini, Silvia Paola Caminiti, Arturo Chiti, Giovanni B Frisoni, Valentina Garibotto, Daniela Perani, Alzheimer's Disease Neuroimaging Initiative

Open access · goldAbstract read
In one paragraph

Article in Annals of clinical and translational neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Alzheimer's disease biological domain sub-stratification enhances the precision of functional analyses.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  2. Article
  3. Clinical and molecular correlates of limbic age-related TDP-43 encephalopathy (LATE)European journal of nuclear medicine and molecular imaging · 2025
    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

7 authors at 3 institutions in 3 countries.

Cecilia BoccaliniVita-Salute San Raffaele University, Milan, Italy.ORCID https://orcid.org/0000-0002-3518-436X
Silvia Paola CaminitiVita-Salute San Raffaele University, Milan, Italy.ORCID https://orcid.org/0000-0003-4568-1738
Arturo ChitiVita-Salute San Raffaele University, Milan, Italy.
Giovanni B FrisoniLaboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.
Valentina GaribottoLaboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Daniela PeraniVita-Salute San Raffaele University, Milan, Italy.ORCID https://orcid.org/0000-0002-3421-204X
Alzheimer's Disease Neuroimaging Initiative
University of Geneva · CHVita-Salute San Raffaele University · ITAlzheimer’s Disease Neuroimaging Initiative · US

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
NIA NIH HHS U01 AG024904Swiss National Science Foundation 320030_169876Swiss National Science Foundation 320030_182772Swiss National Science Foundation 320030_185028Swiss National Science Foundation IZSEZ0_188355
6 · The paper itself

Abstract

objectivesMild cognitive impairment presenting with an amnestic syndrome (aMCI) and amyloid positivity is considered due to AD. Many subjects, however, can show an overall very slow progression relevant for differential diagnosis, prognosis, and treatment. This study assessed PET biomarkers, including brain glucose metabolism, tau, and amyloid load, in a series of comparable aMCI at baseline, clinically evaluated at follow-up.

methodsWe included 72 aMCI subjects from Geneva Memory Center (N = 31) and ADNI cohorts (N = 41), selected based on available FDG-PET, tau-PET, amyloid-PET, and clinical follow-up (2.3 years ± 1.2). A data-driven algorithm classified brain metabolic patterns into subtypes that were then compared for clinical and PET biomarker measures and cognitive decline. Voxel-wise comparisons were performed both with FDG-PET and tau-PET data.

resultsThe algorithm classified three metabolic subtypes, namely "Hippocampal-sparing with cortical hypometabolism" (Type1; N = 27), "Hippocampal and cortical hypometabolism" (Type 2; N = 23), and "Medial temporal hypometabolism" (Type 3; N = 22). Amyloid positivity and tau accumulation in the medial temporal and neocortical regions characterized Type 1 and Type 2, whereas Type 3 showed no significant tau pathology, variable amyloid positivity, and stability at follow-up. All tau-positive patients, independently of the FDG-based subtype, showed faster cognitive decline.

interpretationaMCI subjects can differ in metabolic patterns, tau and amyloid pathology, and clinical progression. Here, we complemented with PET tau biomarker the specific brain hypometabolic patterns at the individual level in the prodromal phase, contributing to the patient's classification. Tau PET is the most accurate biomarker in supporting or excluding the AD diagnosis in aMCI across metabolic subtypes and also predicting the risk of decline.

Indexed as

AmnesiaCognitive DysfunctionFluorodeoxyglucose F18Positron-Emission Tomographytau ProteinsAgedAged, 80 and overAlzheimer DiseaseBiomarkersBrainDisease ProgressionFemaleFollow-Up StudiesHumansMaleMiddle AgedBiomarkersFluorodeoxyglucose F18tau Proteins

Identifiers

PMID38553802
PMCPMC11093253
OpenAlexW4393344827

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.