Application of DCE-MRI radiomics signature analysis in differentiating molecular subtypes of luminal and non-luminal breast cancer
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Medicine"
DOI: 10.3389/fmed.2023.1140514
Abstract: Background The goal of this study was to develop and validate a radiomics signature based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) preoperatively differentiating luminal and non-luminal molecular subtypes in patients with invasive breast cancer.… read more here.
Keywords: molecular subtypes; radiomics signature; breast cancer; non luminal ... See more keywords
Hormonal Receptor Immunochemistry Heterogeneity and 18F-FDG Metabolic Heterogeneity: Preliminary Results of Their Relationship and Prognostic Value in Luminal Non-Metastatic Breast Cancers
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in Oncology"
DOI: 10.3389/fonc.2020.599050
Abstract: Introduction We aimed to investigate whether 18F-FDG PET metabolic heterogeneity reflects the heterogeneity of estrogen receptor (ER) and progesterone receptor (PR) expressions within luminal non-metastatic breast tumors and if it could help in identifying patients… read more here.
Keywords: breast; heterogeneity; luminal non; metastatic breast ... See more keywords
Development and validation of an ultrasound-based radiomics nomogram for predicting the luminal from non-luminal type in patients with breast carcinoma
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Oncology"
DOI: 10.3389/fonc.2022.993466
Abstract: Introduction The molecular subtype plays a significant role in breast carcinoma (BC), which is the main indicator to guide treatment and is closely associated with prognosis. The aim of this study was to investigate the… read more here.
Keywords: luminal non; rad score; non luminal; luminal type ... See more keywords
Cross-attention multi-branch CNN using DCE-MRI to classify breast cancer molecular subtypes
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DOI: 10.3389/fonc.2023.1107850
Abstract: Purpose The aim of this study is to improve the accuracy of classifying luminal or non-luminal subtypes of breast cancer by using computer algorithms based on DCE-MRI, and to validate the diagnostic efficacy of the… read more here.
Keywords: breast; dce mri; breast cancer; non luminal ... See more keywords