Evidence map›Paper›PMID 42564513›Full record

ArticleEuropean journal of radiology open2026

DCE-MRI kinetic heterogeneity facilitates the discrimination of benignity and malignancy of breast in combination with the DWI and morphological features.

Ruobing Wang, Yanhong Chen, Chen Luo, Lijun Wang, Ran Luo, Ling Zhan, Zhengwei Zhang, Minmin Wang, Qiufeng Yin, Zhongyang Zhang and 4 more

Abstract read
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Article in European journal of radiology open, 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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4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Ruobing WangDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yanhong ChenDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Chen LuoDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Lijun WangDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ran LuoDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ling ZhanDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhengwei ZhangDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Minmin WangDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Qiufeng YinDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhongyang ZhangDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Lijun YanSchool of Software and Microelectronics, Peking University, Beijing, China.
Yuzhen ZhangDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Dengbin WangDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Huanhuan LiuDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to validate the diagnostic value of kinetic heterogeneity (KH) across multiple cohorts and to develop a nomogram integrating KH, apparent diffusion coefficient (ADC), and key morphological and clinical features for preoperative discrimination between benign and malignant breast masses. Methods: This retrospective study included 501 female patients with 541 confirmed breast mass lesions. Training (n = 280) and internal validation (n = 119) cohorts were collected (2018-2019). Temporal validation (n = 101, 2024) and independent test cohorts (n = 41, 2025-2026), from a different scanner system) were also included. KH was computed using voxel-wise time-intensity curve analysis. Independent predictors were identified using logistic regression to construct a nomogram. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis, and compared with KH-, ADC-, and combined models. Results: Age, lesion margin, ADC, and KH were independent predictors. The nomogram achieved AUCs of 0.897 (95% confidence interval [CI]: 0.838-0.955) and 0.909 (95% CI: 0.811-1.000) in the temporal validation and independent test cohorts, outperforming the ADC + KH (0.855, 0.890), ADC (0.829, 0.848), and KH (0.803, 0.757) models. Sensitivities were 93.8% and 94.1%, with negative predictive values (NPVs) of 92.7% and 95.2%, respectively. Calibration and decision curve analysis demonstrated good agreement and positive net benefit across a wide range of threshold probabilities. Conclusion: The nomogram integrating KH, ADC, margin, and age demonstrated superior diagnostic performance in preoperatively discriminating between benign and malignant breast mass lesions.

Indexed as

Apparent diffusion coefficientBreast cancerDCE-MRIKinetic heterogeneityNomogram

Identifiers

PMID42564513
PMCPMC13445188

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