Evidence map›Paper›PMID 42069625›Full record

ArticleJournal of ovarian research2026

Abnormal adnexal uptake in

Qixin Wang, Rui Sun, Canran Xiao, Xiaoliang Chen

Abstract read
In one paragraph

Article in Journal of ovarian research, 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
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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

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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

4 authors.

Qixin WangDepartment of Nuclear Medicine, Chongqing University Cancer Hospital, No 181 HanYu St, Shapingba District, Chongqing, 400030, PR China.
Rui SunDepartment of Nuclear Medicine, Chongqing University Cancer Hospital, No 181 HanYu St, Shapingba District, Chongqing, 400030, PR China.
Canran XiaoDepartment of Nuclear Medicine, Chongqing University Cancer Hospital, No 181 HanYu St, Shapingba District, Chongqing, 400030, PR China.
Xiaoliang ChenDepartment of Nuclear Medicine, Chongqing University Cancer Hospital, No 181 HanYu St, Shapingba District, Chongqing, 400030, PR China. chenxiaoliangcquch@163.com.ORCID http://orcid.org/0000-0002-3505-5314

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe adnexal region in females presents complex imaging due to the menstrual cycle. Accurate diagnosis is crucial for effective tumor treatment. This study aims to assess the clinical utility of abnormal adnexal uptake on

methodsThis study retrospectively analyzed all female patients with abnormal adnexal uptake on

resultsThe study included 121 female patients with a mean age of 53.8 ± 12.2 years (18-80 years). A total of 184 adnexal lesions with abnormal uptake were identified. Pathology/follow-up confirmed 82.6% as malignancies, comprising 84 primary and 16 metastatic cases. Additionally, 2 borderline tumors and 19 benign lesions were detected. The positive predictive value was 83.5%. SUVmax differed significantly among primary malignant, metastatic, and benign lesions (12.52 ± 5.41 vs. 9.78 ± 3.39 vs. 5.52 ± 4.17). In the subset of patients with available pathological specimens, SUVmax showed weak to moderate positive correlations with Ki-67 (r = 0.361, p < 0.001) and p53 (r = 0.419, p < 0.001). Notably, the mean SUVmax in the Ki67 > 20% group was significantly higher than in the Ki67 ≤ 20% group (p < 0.001). ROC analysis showed an AUC of 0.85 of SUVmax alone for diagnosing malignant adnexal lesions, increasing to 0.89 when combined with tumor markers. DISCUSSION:

Indexed as

Adnexal DiseasesGallium RadioisotopesPositron Emission Tomography Computed TomographyAdnexa UteriAdolescentAdultAgedAged, 80 and overFemaleFibroblast Activation Protein AlphaHumansMiddle AgedQuinolinesRetrospective StudiesYoung Adult68Ga-FAPIFibroblast Activation Protein AlphaGallium RadioisotopesQuinolinesAdnexal lesionsDiagnostic performancePET/CT

Identifiers

PMID42069625
PMCPMC13281325

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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.