Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Magnetic Resonance Imaging Phenotypes of Breast Cancer Molecular Subtypes: A Systematic Review.

Academic radiology - 1 Jan 2022

Ab Mumin Nazimah, Ramli Hamid Marlina Tanty, Wong Jeannie Hsiu Ding, Rahmat Kartini, Ng Kwan Hoong

Abstract excerpt

OBJECTIVE: Magnetic resonance imaging (MRI) is the most sensitive imaging modality in detecting breast cancer. The purpose of this systematic review is to investigate the role of human extracted MRI phenotypes in classifying molecular subtypes of breast cancer. METHODS: We performed a literature search of published articles on the application of MRI phenotypic features in invasive breast cancer molecular subtype...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Artificial Intelligence
Share to Breast Neoplasms

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Diffusion Magnetic Resonance Imaging

Share to Phenotype

Source

Identifiers

PMID: 34481705
DOI: 10.1016/j.acra.2021.07.017

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Magnetic Resonance Imaging Phenotypes of Breast Cancer Molecular Subtypes: A Systematic Review.PMID 34481705Read ↗

Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data setSemantic proximity Read ↗

Identifying relations between imaging phenotypes and molecular subtypes of breast cancer: Model discovery and external validation.Semantic proximity Read ↗

Radiogenomic analysis of breast cancer: luminal B molecular subtype is associated with enhancement dynamics at MR imaging.Semantic proximity Read ↗

Molecular Subtypes Recognition of Breast Cancer in Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging Phenotypes from Radiomics Data.Semantic proximity Read ↗

Unsupervised Clustering of Quantitative Image Phenotypes Reveals Breast Cancer Subtypes with Distinct Prognoses and Molecular PathwaysSemantic proximity Read ↗

MRI phenotypes associated with breast cancer predisposing genetic variants, a multisite review.Semantic proximity Read ↗

Computational approach to radiogenomics of breast cancer: Luminal A and luminal B molecular subtypes are associated with imaging features on routine breast MRI extracted using computer vision algorithms.Semantic proximity Read ↗

Synthetic MRI, dynamic contrast-enhanced MRI combined with diffusion-weighted imaging for identifying molecular subtypes of breast cancer using machine learning modelsSemantic proximity Read ↗

Ultrasound Characteristics in Predicting Molecular Subtypes of Breast Cancer: A Retrospective AnalysisSemantic proximity Read ↗

Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma.Semantic proximity Read ↗

Multiparametric MRI-based radiomics combined with machine learning for preoperative differentiation of luminal A and luminal B breast cancer: a multicenter studySemantic proximity Read ↗

MRI-based Prognostic Model in Early-Stage HR+/HER2- Breast CancerSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.