ArticleBMC medical imaging2023
Identification of triple-negative breast cancer and androgen receptor expression based on histogram and texture analysis of dynamic contrast-enhanced MRI.
Article in BMC medical imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Preliminary exploration of radiomic mammographic analysis in triple negative breast cancer related to BRCA profile.Scientific reports · 2026Article
- Impact of androgen receptor on triple negative breast cancer: a systematic review and meta-analytic study.BMJ public health · 2026Article
- Development and validation of an interpretable ensemble model for predicting androgen receptor status in triple-negative breast cancer: a multi-center study.Frontiers in oncology · 2026Article
- Advancements and challenges in triple-negative breast cancer: a comprehensive review of therapeutic and diagnostic strategies.Frontiers in oncology · 2024Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTriple-negative breast cancer (TNBC) is highly malignant and has a poor prognosis due to the lack of effective therapeutic targets. Androgen receptor (AR) has been investigated as a possible therapeutic target. This study quantitatively assessed intratumor heterogeneity by histogram analysis of pharmacokinetic parameters and texture analysis on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to discriminate TNBC from non-triple-negative breast cancer (non-TNBC) and to identify AR expression in TNBC.
methodsThis retrospective study included 99 patients with histopathologically proven breast cancer (TNBC: 36, non-TNBC: 63) who underwent breast DCE-MRI before surgery. The pharmacokinetic parameters of DCE-MRI (K
resultsThe binary logistic regression analysis revealed that K
conclusionHistogram and texture analysis of breast lesions on DCE-MRI showed potential to identify TNBC, and the specific features can be possible predictors of AR expression, enhancing the ability to individualize the treatment of patients with TNBC.
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Registered trials
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