Online citations, reference lists, and bibliographies.
← Back to Search

Breast Cancer Radiogenomics: Current Status And Future Directions.

L. Grimm, M. Mazurowski
Published 2020 · Medicine

Cite This
Download PDF
Analyze on Scholarcy
Radiogenomics is an area of research that aims to identify associations between imaging phenotypes ("radio-") and tumor genome ("-genomics"). Breast cancer radiogenomics research in particular has been an especially prolific area of investigation in recent years as evidenced by the wide number and variety of publications and conferences presentations. To date, research has primarily been focused on dynamic contrast enhanced pre-operative breast MRI and breast cancer molecular subtypes, but investigations have extended to all breast imaging modalities as well as multiple additional genetic markers including those that are commercially available. Furthermore, both human and computer-extracted features as well as deep learning techniques have been explored. This review will summarize the specific imaging modalities used in radiogenomics analysis, describe the methods of extracting imaging features, and present the types of genomics, molecular, and related information used for analysis. Finally, the limitations and future directions of breast cancer radiogenomics research will be discussed.
This paper references
The SUVmax for 18F-FDG Correlates With Molecular Subtype and Survival of Previously Untreated Metastatic Breast Cancer
J. Zhang (2013)
70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer.
F. Cardoso (2016)
MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays.
H. Li (2016)
Differentiation of triple-negative breast cancer from other subtypes through whole-tumor histogram analysis on multiparametric MR imaging
T. Xie (2018)
Interobserver Variability Between Breast Imagers Using the Fifth Edition of the BI-RADS MRI Lexicon.
L. Grimm (2015)
Inter-reader Variability in the Use of BI-RADS Descriptors for Suspicious Findings on Diagnostic Mammography: A Multi-institution Study of 10 Academic Radiologists.
Amie Y. Lee (2017)
Identification of a correlation between the sonographic appearance and molecular subtype of invasive breast cancer: A review of 311 cases.
T. Wu (2019)
Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer
Jose-Gerardo Tamez-Peña (2018)
Breast cancer MRI radiomics: An overview of algorithmic features and impact of inter‐reader variability in annotating tumors
Ashirbani Saha (2018)
Textural Features for Image Classification
R. Haralick (1973)
Breast imaging reporting and data system (BI-RADS).
L. Liberman (2002)
Magnetic resonance imaging texture analysis classification of primary breast cancer
S. Waugh (2015)
Breast cancer molecular subtype as a predictor of the utility of preoperative MRI.
R. Ha (2015)
The role of ultrasonographic findings to predict molecular subtype, histologic grade, and hormone receptor status of breast cancer.
Filiz Çelebi (2015)
Factors Associated with Preoperative Magnetic Resonance Imaging Use among Medicare Beneficiaries with Nonmetastatic Breast Cancer
L. M. Henderson (2016)
Identification of intrinsic imaging phenotypes for breast cancer tumors: preliminary associations with gene expression profiles.
A. Ashraf (2014)
Prediction of biological characteristics of breast cancer using dual-phase FDG PET/CT
S. Sasada (2019)
Screening Mammography and Digital Breast Tomosynthesis: Utilization Updates.
Gilda Boroumand (2018)
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
L. Grimm (2015)
Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma
Y. Zhu (2015)
Tumor metabolism and perfusion ratio assessed by 18F-FDG PET/CT and DCE-MRI in breast cancer patients: Correlation with tumor subtype and histologic prognostic factors.
Young-Sil An (2015)
Breast Cancer: Radiogenomic Biomarker Reveals Associations among Dynamic Contrast-enhanced MR Imaging, Long Noncoding RNA, and Metastasis.
S. Yamamoto (2015)
Prognostic value of PAM50 and risk of recurrence score in patients with early-stage breast cancer with long-term follow-up
H. Ohnstad (2017)
Multiparametric MRI of the breast: A review
M. A. Marino (2018)
Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013
A. Goldhirsch (2013)
The maximum standardized uptake value of metastatic site in 18 F-FDG PET/CT predicts molecular subtypes and survival in metastatic breast cancer: An Izmir Oncology Group study.
S. Çokmert (2016)
The role of diffusion weighted imaging as supplement to dynamic contrast enhanced breast MRI: Can it help predict malignancy, histologic grade and recurrence?
Shima Roknsharifi (2019)
Histogram analysis of apparent diffusion coefficient at 3.0t: Correlation with prognostic factors and subtypes of invasive ductal carcinoma
Eun Jeong Kim (2015)
Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors
G. Cho (2015)
Breast Cancer Treatment: A Review
Adrienne G Waks (2019)
Identifying ultrasound and clinical features of breast cancer molecular subtypes by ensemble decision
L. Zhang (2015)
Breast MRI in the Diagnostic and Preoperative Workup Among Medicare Beneficiaries With Breast Cancer
T. Onega (2016)
A Multichannel Markov Random Field Framework for Tumor Segmentation With an Application to Classification of Gene Expression-Based Breast Cancer Recurrence Risk
A. Ashraf (2013)
Intratumoral heterogeneity of the distribution of kinetic parameters in breast cancer: comparison based on the molecular subtypes of invasive breast cancer
K. Yamaguchi (2014)
Microcalcification-associated breast cancer: HER2-enriched molecular subtype is associated with mammographic features.
Zhong Nie (2018)
Correlation of Molecular Subtypes of Invasive Ductal Carcinoma of Breast with Glucose Metabolism in FDG PET/CT: Based on the Recommendations of the St. Gallen Consensus Meeting 2013
S. Lee (2016)
Breast cancer subtype intertumor heterogeneity: MRI‐based features predict results of a genomic assay
E. Sutton (2015)
A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features
Ashirbani Saha (2018)
Can breast cancer molecular subtype help to select patients for preoperative MR imaging?
L. Grimm (2015)
A study of association of Oncotype DX recurrence score with DCE-MRI characteristics using multivariate machine learning models
Ashirbani Saha (2018)
BI-RADS 3–5 microcalcifications can preoperatively predict breast cancer HER2 and Luminal a molecular subtype
D. Cen (2017)
Molecular subclasses of breast cancer: how do we define them? The IMPAKT 2012 Working Group Statement.
S. Guiu (2012)
Is there a correlation between 3T multiparametric MRI and molecular subtypes of breast cancer?
S. Montemezzi (2018)
Imaging features of breast cancers on digital breast tomosynthesis according to molecular subtype: association with breast cancer detection.
S. H. Lee (2017)
Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score
R. Ha (2019)
MaZda - A software package for image texture analysis
P. Szczypinski (2009)
18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Features in Locally Advanced Breast Cancer and Their Correlation with Molecular Subtypes
Siddhant Khare (2018)
The Association of Mammographic Density and Molecular Breast Cancer Subtype
B. Edwards (2017)
Role of 18F-FDG PET/CT in evaluating molecular subtypes and clinicopathological features of primary breast cancer
E. Arslan (2018)
Is There a Correlation Between Breast Cancer Molecular Subtype Using Receptors as Surrogates and Mammographic Appearance?
Brigid K. Killelea (2013)
Apparent diffusion coefficient in estrogen receptor‐positive and lymph node‐negative invasive breast cancers at 3.0T DW‐MRI: A potential predictor for an oncotype Dx test recurrence score
S. Thakur (2018)
Correlations between diffusion-weighted imaging and breast cancer biomarkers
L. Martincich (2012)
Diffusion‐weighted MRI characteristics associated with prognostic pathological factors and recurrence risk in invasive ER+/HER2– breast cancers
Nita Amornsiripanitch (2018)
Association between 18F-FDG uptake and molecular subtype of breast cancer
K. Kitajima (2015)
MRI phenotype of breast cancer: Kinetic assessment for molecular subtypes
Eric M Blaschke (2015)
Correlations between apparent diffusion coefficient values of invasive ductal carcinoma and pathologic factors on diffusion‐weighted MRI at 3.0 Tesla
S. H. Park (2015)
Qualitative Radiogenomics: Association between Oncotype DX Test Recurrence Score and BI-RADS Mammographic and Breast MR Imaging Features.
Genevieve A Woodard (2018)
Identifying relations between imaging phenotypes and molecular subtypes of breast cancer: Model discovery and external validation
J. Wu (2017)
Breast cancer classification by proteomic technologies: current state of knowledge.
S. W. Lam (2014)
Prospective Validation of a 21-Gene Expression Assay in Breast Cancer.
J. Sparano (2015)
Preoperative Breast MRI: Surgeons' Patient Selection Patterns and Potential Bias in Outcomes Analyses.
J. Lee (2017)
The Triple Negative Paradox: Primary Tumor Chemosensitivity of Breast Cancer Subtypes
L. Carey (2007)
Quantitative assessment of metabolic tumor burden in molecular subtypes of primary breast cancer with FDG PET/CT.
W. Chen (2018)
Radiogenomic analysis of breast cancer using MRI: a preliminary study to define the landscape.
S. Yamamoto (2012)
Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study.
L. Carey (2006)
Molecular portraits of human breast tumours
C. Perou (2000)
Radiomics Analysis on Ultrasound for Prediction of Biologic Behavior in Breast Invasive Ductal Carcinoma
Yi Guo (2018)
[18F]FDG PET/CT features for the molecular characterization of primary breast tumors
L. Antunovic (2017)
Estrogen receptor, progesterone receptor, HER-2, and response to postmastectomy radiotherapy in high-risk breast cancer: the Danish Breast Cancer Cooperative Group.
M. Kyndi (2008)
Radiogenomic analysis of breast cancer: luminal B molecular subtype is associated with enhancement dynamics at MR imaging.
M. Mazurowski (2014)
The Role of the 21-Gene Recurrence Score in Breast Cancer Treatment
J. Ethier (2016)
Imaging features of automated breast volume scanner: Correlation with molecular subtypes of breast cancer.
Feng-yang Zheng (2017)
Effects of MRI scanner parameters on breast cancer radiomics
Ashirbani Saha (2017)
Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI
M. Mazurowski (2019)

This paper is referenced by
Semantic Scholar Logo Some data provided by SemanticScholar