ArticleDiagnostics (Basel, Switzerland)2022
Multiregional Radiomic Signatures Based on Functional Parametric Maps from DCE-MRI for Preoperative Identification of Estrogen Receptor and Progesterone Receptor Status in Breast Cancer.
Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 7 citations in OpenAlex.
- Development and validation of an MRI-based deep learning system for triple-class ER expression classification in breast cancer: a large-scale multicenter study.BMC medicine · 2026Article
- Radiomics Integration of Mammography and DCE-MRI for Predicting Molecular Subtypes in Breast Cancer Patients.Breast cancer (Dove Medical Press) · 2025Article
- Development of a nomogram-based model combining intra- and peritumoral ultrasound radiomics with clinical features for differentiating benign from malignant in Breast Imaging Reporting and Data System category 3-5 nodules.Quantitative imaging in medicine and surgery · 2023Article
- Dynamic contrast-enhanced magnetic resonance imaging radiomics analysis based on intratumoral subregions for predicting luminal and nonluminal breast cancer.Quantitative imaging in medicine and surgery · 2023Article
- Breast Cancer Surrogate Subtype Classification Using Pretreatment Multi-Phase Dynamic Contrast-Enhanced Magnetic Resonance Imaging Radiomics: A Retrospective Single-Center Study.Journal of personalized medicine · 2023Article
- Characterization of Breast Tumors from MR Images Using Radiomics and Machine Learning Approaches.Journal of personalized medicine · 2023Article
- Whole-Tumor ADC Texture Analysis Is Able to Predict Breast Cancer Receptor Status.Diagnostics (Basel, Switzerland) · 2023Article
- A Two-Step Feature Selection Radiomic Approach to Predict Molecular Outcomes in Breast Cancer.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Radiomics based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been used for breast estrogen receptor (ER) and progesterone receptor (PR) status evaluation. However, the radiomic features of peritumoral regions were not thoroughly analyzed. This study aimed to establish and validate the multiregional radiomic signatures (RSs) for the preoperative identification of the ER and PR status in breast cancer. A total of 443 patients with breast cancer were divided into training (
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Registered trials
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