Evidence map›Paper›PMID 42313223›Full record

ArticleEuropean radiology experimental2026

Radiomics-enhanced

Zengbei Yuan, Jianzhou Zhang, Zirong Zhou, Xing Chen, Na Qi, Weilun Wang, Xinwei Cheng, Yingkang Lin, Jun Zhao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European radiology experimental, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Zengbei Yuan *Department of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Jianzhou Zhang *Department of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Zirong Zhou *Department of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Xing ChenDepartment of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Na QiDepartment of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Weilun WangDepartment of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Xinwei ChengDepartment of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Yingkang LinDepartment of Rehabilitation, Guangdong Work Injury Rehabilitation Hospital, Guangzhou, China. 3411485403@qq.com.
Jun ZhaoDepartment of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China. petcenter@126.com.ORCID http://orcid.org/0000-0002-9887-5512

Funding

Key Discipline Construction Project of Shanghai Pudong New Area Health Commission PWZxk2022-12National Key Research and Development Program of China 2022YFC2406900
6 · The paper itself

Abstract

objectiveReliable assessment of cerebral amyloid-β (Aβ) deposition is essential for the diagnosis and management of Alzheimer's disease (AD). This study aimed to evaluate the feasibility of integrating radiomics-enhanced MATERIALS AND

methodsNinety-four subjects who underwent (

resultsThe combined feature achieved the best performance with the LR model, with area under the receiver operating characteristic curve = 0.9373, accuracy = 0.8723, F1-score = 0.898). SHAP analysis identified biologically meaningful features derived from both radiomics and PET modalities, showing clear inter-group separation. In Centiloid regression, the ExtraTrees model achieved strong agreement with measured values.

conclusionThis framework provides an interpretable and quantitative solution for amyloid evaluation, enabling both categorical Aβ status discrimination and continuous Centiloid estimation from routine PET/MRI data. This approach represents a proof-of-concept for supporting RELEVANCE STATEMENT: This study demonstrates that radiomics-enhanced PET/MR features can reliably predict both Aβ status and Centiloid values without specialized processing platforms, offering a clinically deployable, standardized, and interpretable approach to improve AD diagnosis and monitoring. KEY POINTS: Radiomics-enhanced

Indexed as

Alzheimer DiseaseAmyloid beta-PeptidesAniline CompoundsEthylene GlycolsMagnetic Resonance ImagingPositron-Emission TomographyAgedAged, 80 and overFemaleHumansMaleMultimodal ImagingRadiomicsRadiopharmaceuticalsRetrospective StudiesAmyloid beta-PeptidesAniline CompoundsEthylene GlycolsflorbetapirRadiopharmaceuticalsAlzheimer diseaseFlorbetapirMachine learningPositron emission tomographyRadiomics.

Identifiers

PMID42313223
PMCPMC13280297

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.