Evidence map›Paper›PMID 40720133›Full record

ArticleJAMA neurology2025

Concordance Between Amyloid-PET Quantification and Real-World Visual Reads.

Ehud Zeltzer, Daniel R Schonhaut, Nidhi S Mundada, Ganna Blazhenets, David N Soleimani-Meigooni, Hanna Cho, Kamalini G Ranasinghe, Charles Windon, Golnaz Yadollahikhales, Charles Apgar and 13 more

Abstract read
In one paragraph

Article in JAMA neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–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

19 citing papers in PubMed.

  1. Trial
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  13. Review
  14. Calibration of multisite raters for prospective visual reads of amyloid PET scans.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Visual read performance ofAlzheimer's & dementia (Amsterdam, Netherlands)
    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

23 authors.

Ehud ZeltzerAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.
Daniel R SchonhautAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.
Nidhi S MundadaAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.
Ganna BlazhenetsAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.
David N Soleimani-MeigooniAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.
Hanna ChoAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.
Kamalini G RanasingheAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.
Charles WindonAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.
Golnaz YadollahikhalesJona Goldrich Center for Alzheimer's and Memory disorders, Department of Neurology, Cedars Sinai Medical Center, Los Angeles, California.
Charles ApgarCenter for Research and Innovation, American College of Radiology, Reston, Virginia.
Constantine GatsonisDepartment of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island.
Maria C CarrilloAlzheimer's Association, Chicago, Illinois.
Lucy HannaDepartment of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island.
Justin RomanoffDepartment of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island.
Bruce E HillnerDepartment of Medicine, Virginia Commonwealth University, Richmond.
Robert A KoeppeDepartment of Radiology, University of Michigan, Ann Arbor.
Andrew MarchCenter for Research and Innovation, American College of Radiology, Reston, Virginia.
Barry A SiegelEdward Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri.
Karen SmithAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.
Rachel A WhitmerDepartment of Public Health Sciences, Department of Neurology, Alzheimer's Disease Research Center, University of California Davis.
Leonardo IaccarinoAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.
Gil D RabinoviciAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.
Renaud La JoieAlzheimer's Disease Research Center, Memory and Aging Center, Department of Neurology, University of California, San Francisco.

Funding

Research Education ComponentP30AG062422 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Gil Dan Rabinovici · 2019 to 2026
$36.9M
Reimagining Precision Medicine Approaches to AD DiagnosisR35AG072362 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI POSSIN, KATHERINE LAUREL, RABINOVICI, GIL DAN · 2021 to 2025
$4.8M
Development of Emergent PET Tracers in Frontotemporal Lobar DegenerationK23AG076960 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI David Nima Soleimani-Meigooni · 2022 to 2026
$951k
NIA NIH HHS K23 AG076960NIA NIH HHS P30 AG062422NIA NIH HHS R35 AG072362
6 · The paper itself

Abstract

Importance: With increased payer coverage and the advent of antiamyloid therapies, clinical use of amyloid positron emission tomography (PET) is likely to increase to help guide the diagnosis and treatment of patients with cognitive impairment. However, unlike most previous research studies, in clinical practice, scan acquisition is less standardized, interpretation typically relies purely on visual reads rather than scan quantification, and patients have more frequent comorbidities, all of which might compromise test accuracy. Objective: To compare visual interpretation of amyloid-PET in real-world clinical settings to scan interpretation based on central quantification, in order to assess the accuracy of clinical reads. Design, Setting, and Participants: This cross-sectional quality improvement study used data from the Imaging Dementia-Evidence for Amyloid Scanning study, collected between February 2016 and January 2018 and analyzed between December 2021 and April 2023. The setting included 294 imaging facilities in the US. Medicare beneficiaries 65 years or older with cognitive decline for whom Alzheimer disease was a diagnostic consideration were recruited by dementia specialists from their clinical practices. Exposures: Amyloid-PET with [18F]florbetapir, [18F]florbetaben, or [18F]flutemetamol. Main Outcomes and Measures: PET scans were visually interpreted as positive or negative by local radiologists or nuclear medicine physicians following approved guidelines. Independently, scans were centrally processed and quantified using the standardized Centiloid (CL) scale. We applied an a priori autopsy-based threshold of 24.4 CL to quantitatively define scan positivity. Results: Of 18 293 participants included in the parent study, scan images were available for 10 774 (59%), of which Centiloids were successfully calculated for 10 361 (96%). Median (IQR) patient age was 75 (71-80) years; 5245 patients (51%) were female, 6500 (63%) had mild cognitive impairment, and 3861 (37%) had dementia). Participants self-reported the following races and ethnicities: 1 Alaska Native (0%), 23 American Indian (0.2%), 188 Asian (1.8%), 316 Black (3.1%), 449 Hispanic or Latino (4.3%), 8 Native Hawaiian or Other Pacific Islander (0.1%), and 9125 White (88.2%). A total of 6332 scans (61%) were visually read as positive, and 6121 (59%) were quantitatively positive. Agreement between visual reads and quantitative classification was 86.3% (95% CI, 85.7%-87.0%; Cohen κ = 0.72; 95% CI, 0.70-0.73). A total of 5519 (53%) scans were positive visually and quantitatively (V+/Q+), 3416 (33%) were negative by both (V-/Q-), 813 (8%) were V+/Q-, and 602 (6%) were V-/Q+. Female sex (female: 4581/5241 [87.4%]; male: 4354/5109 [85.2%]; P =.001), White race (White race: 7900/9125 [86.6%]; non-White race: 1035/1225 [84.5%]; P =.046), and use of [18F]flutemetamol and [18F]florbetaben ([18F]flutemetamol: 559/628 [89.0%]; [18F]florbetaben: 2664/3032 [87.9%]; [18F]florbetapir: 5712/6690 [85.4%]; P <.001), compared with [18F]florbetapir, were associated with higher visual-quantitative concordance. Scans within a 10- to 40-CL borderline positivity zone were more likely to be discordant. Conclusions and Relevance: This cross-sectional study found high concordance between local visual reads and central quantification of clinical amyloid-PET scans, supporting the validity of amyloid-PET visual reads in real-world clinical practice.

Indexed as

Alzheimer DiseaseBrainCognitive DysfunctionPositron-Emission TomographyAgedAged, 80 and overAniline CompoundsCross-Sectional StudiesFemaleHumansMaleRadiopharmaceuticalsAniline CompoundsRadiopharmaceuticals

Identifiers

PMID40720133
PMCPMC12305444

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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.