Evidence map›Paper›PMID 34993096›Full record

ArticleQuantitative imaging in medicine and surgery2022

Evaluation of semi-quantitative measures of

Ebba Gløersen Müller, Caroline Stokke, Henning Langen Stokmo, Trine Holt Edwin, Anne-Brita Knapskog, Mona-Elisabeth Revheim

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

14 citing papers in PubMed, 15 citations in OpenAlex.

  1. Quantitative agreement between AMYclz and CortexID forJapanese journal of radiology · 2026
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  3. The clinical Alzheimer's disease spectrum classified in the A/T/N framework withEuropean journal of nuclear medicine and molecular imaging · 2026
    Observational
  4. Radiomics-enhancedEuropean radiology experimental · 2026
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  7. Screening of [ACS pharmacology & translational science · 2024
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  9. Article
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  11. Article
  12. Article
  13. A comparison of advanced semi-quantitative amyloid PET analysis methods.European journal of nuclear medicine and molecular imaging · 2022
    Article
  14. Observational
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 1 country.

Ebba Gløersen MüllerDivision of Radiology and Nuclear Medicine, Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
Caroline StokkeDivision of Radiology and Nuclear Medicine, Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway.
Henning Langen StokmoDivision of Radiology and Nuclear Medicine, Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
Trine Holt EdwinInstitute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway.
Anne-Brita KnapskogDepartment of Geriatric Medicine, The memory clinic, Oslo University Hospital, Oslo, Norway.
Mona-Elisabeth RevheimDivision of Radiology and Nuclear Medicine, Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
Oslo University Hospital · NOUniversity of Oslo · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background

methodsThis observational study included 195 patients with cognitive impairment who underwent

resultsPET images from 191 patients were semi-quantified with SyngoVia and CortexID and 86 PET-magnetic resonance imaging pairs with PMOD. All receiver operating characteristics curves showed a high area under the curve (>0.98). Thresholds for a visually positive PET was for SUVRcer: 1.87 (SyngoVia) and 1.64 (CortexID) and for SUVRpons: 0.54 (SyngoVia) and 0.55 (CortexID). The threshold on the Centiloid scale was 39.6 Centiloids. All semi-quantitative measures showed a very high correlation between different software and normalization methods. Composite SUVRcer was significantly different between SyngoVia and PMOD, SyngoVia and CortexID but not between PMOD and CortexID. Composite SUVRpons were significantly different between all three software. There were significant differences in the mean rank of SUVRpons, SUVRcer, and Centiloid between Alzheimer's disease-group and non-Alzheimer's disease-group.

conclusionsSUVR from different software performed equally well in discriminating visually positive and negative

Indexed as

amyloid-betaCentiloidFlutemetamolpositron emission tomography (PET)quantification

Identifiers

PMID34993096
PMCPMC8666793
OpenAlexW3191911351

What OpenQuestion holds

Textmetadata
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.