Evidence map›Paper›PMID 40950303›Full record

ArticleAmerican journal of translational research2025

Assessment of mammographic and ultrasonic signatures for differentiating benign and malignant breast structural distortions.

Lijing Zhang, Kai Yang, Cong Chen, Xi Wu, Guang Yang

Abstract read
In one paragraph

Article in American journal of translational research, 2025. 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. Review
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

5 authors.

Lijing ZhangDepartment of Medical Imaging, Shijiazhuang Maternal and Child Health Hospital (Shijiazhuang Children's Hospital) Shijiangzhuang 050000, Hebei, China.
Kai YangDepartment of Radiology, Fourth Hospital of Hebei Medical University Shijiangzhuang 050011, Hebei, China.
Cong ChenDepartment of Medicine Imaging, Shijiazhuang Great Wall Hospital of Integrated Traditional Chinese and Western Shijiangzhuang 050000, Hebei, China.
Xi WuDepartment of Radiology, Affiliated Hospital of Bachelor's School, Army Medical University Shijiangzhuang 050000, Hebei, China.
Guang YangDepartment of Radiology, Fourth Hospital of Hebei Medical University Shijiangzhuang 050011, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the diagnostic performance of mammography and ultrasonography in distinguishing benign from malignant breast structural distortions and to develop an integrated predictive model combining radiomic features and molecular markers for improved risk stratification.

methodsThis retrospective study included 260 patients with histopathologically confirmed breast structural distortions (156 malignant, 104 benign). Lesions were characterized using Breast Imaging Reporting and Data System (BI-RADS) criteria. Radiomic features were extracted with PyRadiomics, harmonized via ComBat, and selected using Least Absolute Shrinkage and Selection Operator (LASSO) regression. A predictive model incorporated imaging features, molecular markers (vascular endothelial growth factor [VEGF], transforming growth factor-β1 [TGF-β1]), and clinical variables. Diagnostic accuracy was assessed by sensitivity, specificity, AUC, and decision curve analysis, with subgroup analyses by age, menopausal status, and breast density.

resultsMalignant distortions showed higher rates of spiculated margins (82.1% vs. 16.3%, P<0.001) and hypoechoic irregular masses (78.2% vs. 27.9%, P<0.001). Combined mammography-ultrasound assessment improved diagnostic performance (AUC 0.91) versus single modalities (mammography 0.79; ultrasound 0.82). The radiomic-molecular model further enhanced accuracy (AUC 0.94) and reduced unnecessary biopsies by 32%. Spiculation complexity and VEGF overexpression were independent predictors of lymphovascular invasion and lower 5-year disease-free survival (68% vs. 89%, P=0.01).

conclusionIntegrating mammography, ultrasonography, and radiomic-pathologic markers significantly improves differentiation of malignant breast distortions and supports personalized prognosis.

Indexed as

Breast structural distortionsdisease-free survivalpredictive modelingradiomicsvascular endothelial growth factor

Identifiers

PMID40950303
PMCPMC12432718

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.