Evidence map›Paper›PMID 42157122›Full record

ArticleBMC medical imaging2026

Enhancing mixed solid and cystic breast lesions diagnosis: a simplified scoring system integrating ultrasound features and clinical factors.

Yingying Jia, Qiong Lan, Ting Liu, Yangyang Zhu, Cui Cao, Xinyue Hu, Fang Nie

Abstract readMulticenter Study
In one paragraph

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

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yingying Jia *Lanzhou University Second Hospital, Lanzhou, Gansu, China.
Qiong Lan *Gansu Provincial Maternity and Child-Care Hospital (Gansu Provincial Central Hospital), Lanzhou, Gansu, China.
Ting LiuLanzhou University Second Hospital, Lanzhou, Gansu, China.
Yangyang ZhuLanzhou University Second Hospital, Lanzhou, Gansu, China.
Cui CaoXigu District People's Hospital, Lanzhou, Gansu, China.
Xinyue HuLanzhou University Second Hospital, Lanzhou, Gansu, China.
Fang NieLanzhou University Second Hospital, Lanzhou, Gansu, China. ery_nief@lzu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) 6th Edition's updated definition of mixed solid and cystic breast lesions (MSCBLs) reflects the diagnostic challenges in assessing these lesions. This study aimed to develop and validate a scoring system based on ultrasound (US) features and clinical factors to differentiate benign from malignant MSCBLs.

methodsThis retrospective multicenter study included 499 MSCBLs from three medical centers, which were divided into a training cohort (n = 396, 79.4%) and an external validation cohort (n = 103, 20.6%). Ultrasound features and clinical characteristics were analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of malignancy, on the basis of which a nomogram was constructed. This nomogram was subsequently simplified into a practical scoring system. The performance of the scoring system was validated in the independent external cohort. Furthermore, its added diagnostic value was assessed across radiologists with different levels of experience.

resultsMultivariate logistic analysis identified age, lesion type, shape, vascularity, and lesion size as independent predictors of malignancy. The simplified scoring system demonstrated high diagnostic efficacy in the training cohort (area under the curve, AUC = 0.853, 95% CI: 0.813-0.892), with internal validation using bootstrap resampling confirming robust performance (optimism-corrected AUC = 0.834). In the external validation cohort, the scoring system demonstrated good diagnostic performance (AUC = 0.801, 95% CI: 0.710-0.893) and high interobserver agreement (weighted κ=0.78, 95% CI: 0.72-0.84). It also improved diagnostic performance for junior and intermediate radiologists, improving AUC from 0.66 to 0.74 for junior radiologists (p < 0.001) and increasing specificity for intermediate radiologists.

conclusionThe MSCBLs scoring system provides a reliable tool for risk stratification, enhancing the diagnostic performance of junior radiologists and ensuring high interobserver consistency, while serving as a valuable complement to existing risk stratification systems.

Indexed as

Breast NeoplasmsUltrasonography, MammaryAdultAgedDiagnosis, DifferentialFemaleHumansMiddle AgedNomogramsReproducibility of ResultsRetrospective StudiesSensitivity and SpecificityDiagnosisMixed solid and cystic breast lesionsNomogramScoring systemUltrasound

Identifiers

PMID42157122
PMCPMC13361560

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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.