Evidence map›Paper›PMID 41278494›Full record

ArticleOrthopedic research and reviews2025

Opportunistic Screening with Radiomics Model Based on CT Imaging of Adrenal Adenoma to Assess Bone Mass Change.

Cheng Jia, Ling Jiang, Yue Zhang, Tiantian Yang, Datian Su, Mingxin Song, Heqi Yang, Jian Qin, Changqin Li, Hui Yang

Abstract read
In one paragraph

Article in Orthopedic research and reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
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.

Cheng Jia *Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China.
Ling Jiang *Department of Medical Engineering, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China.
Yue ZhangDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China.
Tiantian YangDepartment of Radiology, Central Hospital Affiliated to Shandong First Medical University University, Ji'nan, Shandong, People's Republic of China.
Datian SuDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China.
Mingxin SongDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China.
Heqi YangDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China.
Jian QinDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China.
Changqin LiDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China.
Hui YangDepartment of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: There was a strong correlation between adrenal adenoma and osteoporosis, the primary objective of this research was to establish and authenticate a radiomics nomogram using CT scan of adrenal adenoma to screen abnormal bone mineral density (BMD) opportunistically. Methods and Materials: A total of 161 patients with adrenal adenomas who underwent thoracoabdominal CT and quantitative CT (QCT) were enrolled retrospectively. The radiomics features were chosen from the cross-sectional CT images of adrenal adenomas and the nomogram models that including patient's clinical and radiomics features were then established. The receiver operating characteristic (ROC) curve was performed to evaluate the performance of the model and the decision curve analysis (DCA) was used to assess the clinical usefulness. Results: To build a radiomics model, 11 radiomics features based on CT scans of adrenal adenomas were selected and showed good performance in distinguishing abnormal BMD from normal BMD. Moreover, the radiomics nomogram model demonstrated excellent ability to identify abnormal BMD of adrenal adenoma patients with area under the curve (AUC) of 0.87 (95% CI, 0.80-0.93) in training cohort and 0.85 (95% CI, 0.74-0.96) in validation cohort. The accuracy, sensitivity, specificity of the nomogram model were 79.7%, 78.3%, 81.1% in training cohort, and 72.9%, 67.7%, 82.4% in validation cohort respectively. Conclusion: The radiomics nomogram based on clinical and radiomics features of adrenal adenoma CT images had a satisfying predictive ability and can be an opportunistic effective tool for identifying bone mass change.

Indexed as

adrenal adenomanomogramosteoporosisQCTradiomics

Identifiers

PMID41278494
PMCPMC12630013

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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.