Evidence map›Paper›PMID 41231330›Full record

ArticleLa Radiologia medica2026

Whole-lesion histogram analysis of multi-model diffusion-weighted imaging for characterization and molecular classification of breast lesions.

Yuan Yuan, Manhua Huang, Jie Peng, Xiulan Zhang, Xiaofang Lin, Xiang Li, Dewei Zeng

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Article in La Radiologia medica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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7 authors.

Yuan YuanDepartment of Radiology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Manhua HuangDepartment of Radiology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Jie PengDepartment of Radiology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Xiulan ZhangDepartment of Radiology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Xiaofang LinDepartment of Pathology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Xiang LiDepartment of Clinical Laboratory, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Dewei ZengDepartment of Radiology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China. hbzengdw@163.com.ORCID http://orcid.org/0009-0003-5137-5881

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No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate the value of whole-lesion histogram analysis derived from mono-exponential, bi-exponential, and stretched-exponential DWI models in differentiating benign from malignant breast lesions and exploring molecular subtypes. MATERIAL AND

methodsThis retrospective study included 112 patients with 90 malignant lesions (17 Luminal A, 39 Luminal B, 18 HER2-positive, 10 triple-negative, and 6 undetermined) and 22 benign lesions, all examined with 1.5 T MRI. Histogram parameters-apparent diffusion coefficient (ADC), true diffusion (Dt), pseudo-diffusion (Dp), perfusion fraction (f), distributed diffusion coefficient (DDC), and heterogeneity index (alpha)-were analyzed using the Mann-Whitney U test, Kruskal-Wallis test, logistic regression, ROC analysis, the DeLong test, and the chi-square test.

resultsHistogram parameters from all models showed significant differences between benign and malignant lesions, with high diagnostic performance (AUC range: 0.898-0.938). However, combining the models did not significantly improve the AUC (p > 0.05). In molecular subtype analyses, DDC_75% differed significantly between Luminal A and triple-negative subtypes (p = 0.035); Dt_50%, Dt_75%, and DDC_75% distinguished Luminal B from triple-negative subtypes (p = 0.016, 0.021, and 0.041, respectively); and ADC_kurtosis and DDC_kurtosis showed significant differences between HER2-positive and triple-negative subtypes (p = 0.021 and 0.029, respectively). ROC analysis indicated variable diagnostic efficacy among parameters across molecular subtypes, and model combinations did not enhance AUC values.

conclusionWhole-lesion histogram analysis based on multi-model DWI shows potential for characterizing breast lesions. These exploratory findings, derived from an imbalanced single-center cohort, require further validation in larger prospective studies before clinical application.

Indexed as

Breast NeoplasmsDiffusion Magnetic Resonance ImagingAdultAgedDiagnosis, DifferentialFemaleHumansMiddle AgedRetrospective StudiesBreast cancerDWIHistogram analysisMalignant statusMolecular subtypesMulti-model

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