Evidence map›Paper›PMID 42767949›Full record

ArticleAnnals of family medicine2026

AI-Enhanced Super-Resolution Handheld Ultrasound for Carotid Plaque Detection in Community Screening.

Jie Lan, Shun Liu, Haoming Chen, Tingyu Zhang, Penghui Zeng, Jun Li, Linyuan Jin, Tao Tan, Meng Du, Zhiyi Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of family medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Jie LanKey Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, Hengyang Medical School, The Affiliated Changsha Central Hospital, University of South China, Changsha, Hunan, China.
Shun LiuKey Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, Hengyang Medical School, The Affiliated Changsha Central Hospital, University of South China, Changsha, Hunan, China.
Haoming ChenFaculty of Applied Sciences, Macao Polytechnic University, Sé, Macau, China.
Tingyu ZhangKey Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, Hengyang Medical School, The Affiliated Changsha Central Hospital, University of South China, Changsha, Hunan, China.
Penghui ZengKey Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, Hengyang Medical School, The Affiliated Changsha Central Hospital, University of South China, Changsha, Hunan, China.
Jun LiKey Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, Hengyang Medical School, The Affiliated Changsha Central Hospital, University of South China, Changsha, Hunan, China.
Linyuan JinDepartment of Medical Imaging, Hengyang Medical School, The Affiliated Changsha Central Hospital, University of South China, Changsha, Hunan, China.
Tao TanFaculty of Applied Sciences, Macao Polytechnic University, Sé, Macau, China.
Meng DuKey Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, Hengyang Medical School, The Affiliated Changsha Central Hospital, University of South China, Changsha, Hunan, China.
Zhiyi ChenKey Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, Hengyang Medical School, The Affiliated Changsha Central Hospital, University of South China, Changsha, Hunan, China zhiyi_chen@usc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIschemic stroke is a leading cause of disability and death, and early identification of carotid atherosclerotic plaques is critical for stroke prevention in primary care and community settings. We examined whether artificial intelligence (AI)-enhanced handheld ultrasound (HHUS) could improve carotid plaque detection and stenosis assessment in community-based primary care screening.

methodsWe developed a super-resolution reconstruction model (Hyper-CycleGAN) and validated it in a clinical cohort of 127 patients with 198 plaques. The validated model was then applied in a community screening setting with 117 participants and 153 plaques, using portable ultrasound as the reference standard. We evaluated agreement with the reference standard (Bland-Altman, intraclass correlation coefficient) and community diagnostic performance (detection rates, quadratic-weighted Cohen κ, confusion matrices, and standard metrics).

resultsIn community screening, AI-enhanced HHUS identified 94.8% of carotid plaques compared with 87.6% using standard HHUS. Agreement in stenosis grading with the reference standard improved, with weighted κ increasing from 0.492 to 0.836. Sensitivity for identifying ultrasound-defined vulnerable plaques increased from 47.4% to 63.2%, and specificity remained high.

conclusionsAI-enhanced HHUS improved carotid plaque detection and stenosis assessment in community screening, supporting more accurate risk stratification and referral decisions in primary care. This approach could expand access to low-cost stroke prevention strategies in underserved communities.Abstract available in: يبرع (Arabic); (Chinese); Francais (French); Deutsch (German); हिन्दी (Hindi); Indonesian (Indonesian); (Japanese); Portugues (Portuguese); Español (Spanish).

Indexed as

Artificial IntelligenceCarotid StenosisMass ScreeningPlaque, AtheroscleroticUltrasonography, Carotid ArteriesAgedFemaleHumansMaleMiddle AgedPrimary Health CareSensitivity and SpecificityUltrasonographyartificial intelligencecarotid plaquecommunity screeninghandheld ultrasoundprimary caresuper resolution

Identifiers

PMID42767949
PMCPMC13592921

What Socratic 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 Socratic graph.