ArticleCancer management and research2019
Added value of histogram analysis of apparent diffusion coefficient maps for differentiating triple-negative breast cancer from other subtypes of breast cancer on standard MRI.
Article in Cancer management and research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 13 citations in OpenAlex.
- Exploiting machine-learning models with DCE-MRI radiomics for breast cancer molecular subtyping.Frontiers in oncology · 2026Article
- The use of ADC histogram analysis in the diagnosis and determination of aggressiveness of peripheral zone prostate cancer.Polish journal of radiology · 2025Article
- A Machine-Learning Model for the Prediction of Triple-Negative Breast Cancer Based on Multiparameter MRI.Breast cancer (Dove Medical Press) · 2025Article
- A multiparametric approach to predict triple-negative breast cancer including parameters derived from ultrafast dynamic contrast-enhanced MRI.European radiology · 2023Article
- Identification of triple-negative breast cancer and androgen receptor expression based on histogram and texture analysis of dynamic contrast-enhanced MRI.BMC medical imaging · 2023Article
- Whole-Tumor ADC Texture Analysis Is Able to Predict Breast Cancer Receptor Status.Diagnostics (Basel, Switzerland) · 2023Article
- The utility of diffusion-weighted imaging for differentiation of phyllodes tumor from fibroadenoma and breast cancer.Frontiers in oncology · 2023Article
- Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer.World journal of gastroenterology · 2022Article
- Optimal Selection of Imaging Examination for Lymph Node Detection of Breast Cancer With Different Molecular Subtypes.Frontiers in oncology · 2022Article
- Whole-Lesion Histogram Analysis of the Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker for Assessing the Level of Tumor-Infiltrating Lymphocytes: Value in Molecular Subtypes of Breast Cancer.Frontiers in oncology · 2020Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundTriple-negative breast cancers generally occur in young women with remarkable potential to be aggressive. It will be of great help to detect this subtype of tumor early. To retrospectively evaluate the performance of histogram analysis of apparent diffusion coefficient (ADC) maps in distinguishing triple-negative breast cancer (TNBC) from other subtypes of breast cancer (non-TNBC), when combined with magnetic resonance imaging (MRI) features. MATERIALS AND
methodsFrom February 2014 to December 2018, 192 patients were included in this study taking preoperative standard MRI (s-MRI) and DWI. Seventy-six of them were pathologically confirmed with TNBC and rest 116 with other subtypes. First, their clinical-pathological features and morphological characteristics on MRI were assessed, including tumor size, foci quantity, tumor shape, margin, internal enhancement, and time-signal intensity curve types, in addition to the signal intensity on T2-weighted images. Second, whole-lesion apparent diffusion coefficient (ADC) histogram analysis was executed. Finally, both univariate and multivariate regression analyses were applied to identify the most useful variables in separating TNBCs from non-TNBCs, and then their effects were evaluated following receiver operating characteristic curve analysis.
resultMultivariate regression analysis indicated that circumscribed margin, rim enhancement, and ADC
conclusionCircumscribed margin and rim enhancement on s-MRI and ADC
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