Evidence map›Paper›PMID 28574875›Full record

ArticleClinical nuclear medicine2017

Augmenting Amyloid PET Interpretations With Quantitative Information Improves Consistency of Early Amyloid Detection.

Nicholas R Harn, Suzanne L Hunt, Jacqueline Hill, Eric Vidoni, Mark Perry, Jeffrey M Burns

Open access · greenAbstract read
In one paragraph

Article in Clinical nuclear medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

35 citing papers in PubMed, 49 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Slowed Driving Reaction Time in Preclinical Alzheimer's Disease.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2025
    Article
  5. Article
  6. Comparison of Amyloid-PET Analysis Software UsingDiagnostics (Basel, Switzerland) · 2025
    Article
  7. Machine learning based on event-related oscillations of working memory differentiates between preclinical Alzheimer's disease and normal aging.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025
    Article
  8. Frontiers in global women's health · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Visual reading for [Frontiers in neuroscience · 2023
    Article
  15. Quantification of amyloid PET for future clinical use: a state-of-the-art review.European journal of nuclear medicine and molecular imaging · 2022
    Review
  16. Decreased imaging time of amyloid PET using [Radiological physics and technology · 2022
    Article
  17. Article
  18. Article
  19. Article
  20. 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

6 authors at 2 institutions in 2 countries.

Nicholas R HarnFrom the Departments of *Radiology, †Biostatistics, and ‡Neurology, University of Kansas Medical Center, Kansas City, KS.
Suzanne L Hunt
Jacqueline Hill
Eric Vidoni
Mark Perry
Jeffrey M Burns
Rainbow Medical (Israel) · ILUniversity of Kansas Medical Center · US

Funding

University of Kansas Alzheimer's Disease Core CentersP30AG035982 · NIA · UNIVERSITY OF KANSAS MEDICAL CENTER · PI BROOKS, WILLIAM M. · 2011 to 2020
$16.6M
Heartland Institute for Clinical and Translational ResearchUL1TR000001 · NCATS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI BAROHN, RICHARD J. · 2012 to 2015
$13.0M
Effect of Aerobic Exercise on Alzheimer's Pathophysiology in Preclinical ADR01AG043962 · NIA · UNIVERSITY OF KANSAS MEDICAL CENTER · PI BURNS, JEFFREY MURRAY · 2013 to 2018
$3.0M
NCATS NIH HHS UL1 TR000001NIA NIH HHS P30 AG035982NIA NIH HHS R01 AG043962
6 · The paper itself

Abstract

purposeEstablishing reliable methods for interpreting elevated cerebral amyloid-β plaque on PET scans is increasingly important for radiologists, as availability of PET imaging in clinical practice increases. We examined a 3-step method to detect plaque in cognitively normal older adults, focusing on the additive value of quantitative information during the PET scan interpretation process.

methodsFifty-five F-florbetapir PET scans were evaluated by 3 experienced raters. Scans were first visually interpreted as having "elevated" or "nonelevated" plaque burden ("Visual Read"). Images were then processed using a standardized quantitative analysis software (MIMneuro) to generate whole brain and region of interest SUV ratios. This "Quantitative Read" was considered elevated if at least 2 of 6 regions of interest had an SUV ratio of more than 1.1. The final interpretation combined both visual and quantitative data together ("VisQ Read"). Cohen kappa values were assessed as a measure of interpretation agreement.

resultsPlaque was elevated in 25.5% to 29.1% of the 165 total Visual Reads. Interrater agreement was strong (kappa = 0.73-0.82) and consistent with reported values. Quantitative Reads were elevated in 45.5% of participants. Final VisQ Reads changed from initial Visual Reads in 16 interpretations (9.7%), with most changing from "nonelevated" Visual Reads to "elevated." These changed interpretations demonstrated lower plaque quantification than those initially read as "elevated" that remained unchanged. Interrater variability improved for VisQ Reads with the addition of quantitative information (kappa = 0.88-0.96).

conclusionsInclusion of quantitative information increases consistency of PET scan interpretations for early detection of cerebral amyloid-β plaque accumulation.

Indexed as

Positron-Emission TomographyAdolescentAdultAmyloidBrainEarly DiagnosisFemaleHumansImage Interpretation, Computer-AssistedMaleMiddle AgedPlaque, AmyloidSoftwareYoung AdultAmyloid

Identifiers

PMID28574875
PMCPMC5491352
OpenAlexW2621211284

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.