Personalized Medicine, Biomarkers of Risk and Breast MRI

[1]  Ruijiang Li,et al.  Intratumor partitioning and texture analysis of dynamic contrast‐enhanced (DCE)‐MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy , 2016, Journal of magnetic resonance imaging : JMRI.

[2]  Eralda Mema,et al.  Three-Dimensional Quantitative Validation of Breast Magnetic Resonance Imaging Background Parenchymal Enhancement Assessments. , 2016, Current problems in diagnostic radiology.

[3]  Harini Veeraraghavan,et al.  Breast cancer molecular subtype classifier that incorporates MRI features , 2016, Journal of magnetic resonance imaging : JMRI.

[4]  Lars J. Grimm,et al.  Breast MRI radiogenomics: Current status and research implications , 2016, Journal of magnetic resonance imaging : JMRI.

[5]  Erich P Huang,et al.  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. , 2016, Radiology.

[6]  F. Couch,et al.  Genomic Biomarkers for Breast Cancer Risk. , 2016, Advances in experimental medicine and biology.

[7]  Lei Wang,et al.  Principles and methods for automatic and semi-automatic tissue segmentation in MRI data , 2016, Magnetic Resonance Materials in Physics, Biology and Medicine.

[8]  M. Giger,et al.  Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma , 2015, Scientific Reports.

[9]  Joseph O. Deasy,et al.  Breast cancer subtype intertumor heterogeneity: MRI‐based features predict results of a genomic assay , 2015, Journal of magnetic resonance imaging : JMRI.

[10]  Lars J. Grimm,et al.  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 , 2015, Journal of magnetic resonance imaging : JMRI.

[11]  Hon J. Yu,et al.  Background Parenchymal Enhancement of the Contralateral Normal Breast: Association with Tumor Response in Breast Cancer Patients Receiving Neoadjuvant Chemotherapy1 , 2015, Translational oncology.

[12]  Ivan Dmitriev,et al.  Association between Parenchymal Enhancement of the Contralateral Breast in Dynamic Contrast-enhanced MR Imaging and Outcome of Patients with Unilateral Invasive Breast Cancer. , 2015, Radiology.

[13]  E. Mamounas Impact of Neoadjuvant Chemotherapy on Locoregional Surgical Treatment of Breast Cancer , 2015, Annals of surgical oncology.

[14]  Vandana Dialani,et al.  Role of Imaging in Neoadjuvant Therapy for Breast Cancer , 2015, Annals of Surgical Oncology.

[15]  K. Hunt,et al.  Tumor Biology Correlates With Rates of Breast-Conserving Surgery and Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer: Findings From the ACOSOG Z1071 (Alliance) Prospective Multicenter Clinical Trial , 2014, Annals of surgery.

[16]  T. Helbich,et al.  Improved Diagnostic Accuracy With Multiparametric Magnetic Resonance Imaging of the Breast Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging, Diffusion-Weighted Imaging, and 3-Dimensional Proton Magnetic Resonance Spectroscopic Imaging , 2014, Investigative radiology.

[17]  Woo Kyung Moon,et al.  Early Prediction of Response to Neoadjuvant Chemotherapy Using Parametric Response , 2015 .

[18]  M. Leach,et al.  MRI breast screening in high-risk women: cancer detection and survival analysis , 2014, Breast Cancer Research and Treatment.

[19]  A. Nishioka,et al.  Early prediction of response to neoadjuvant chemotherapy in patients with breast cancer using diffusion-weighted imaging and gray-scale ultrasonography , 2014, Oncology reports.

[20]  H. Bonnefoi,et al.  Correlation between imaging and molecular classification of breast cancers. , 2013, Diagnostic and interventional imaging.

[21]  Stephen M. Moore,et al.  The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository , 2013, Journal of Digital Imaging.

[22]  J. Wildberger,et al.  The role of magnetic resonance imaging in assessing residual disease and pathologic complete response in breast cancer patients receiving neoadjuvant chemotherapy: a systematic review , 2013, Insights into Imaging.

[23]  Karla Kerlikowske,et al.  Relationship between mammographic density and breast cancer death in the Breast Cancer Surveillance Consortium. , 2012, Journal of the National Cancer Institute.

[24]  T. Uematsu,et al.  Should breast MRI be performed with adjustment for the phase in patients' menstrual cycle? Correlation between mammographic density, age, and background enhancement on breast MRI without adjusting for the phase in patients' menstrual cycle. , 2012, European journal of radiology.

[25]  A. Tutt,et al.  Recommendations from an International Consensus Conference on the Current Status and Future of Neoadjuvant Systemic Therapy in Primary Breast Cancer , 2012, Annals of Surgical Oncology.

[26]  Janet Waters,et al.  MRI for breast cancer screening, diagnosis, and treatment , 2011, The Lancet.

[27]  Jennifer D. Brooks,et al.  Background parenchymal enhancement at breast MR imaging and breast cancer risk. , 2011, Radiology.

[28]  N. Hylton,et al.  Quantification of background enhancement in breast magnetic resonance imaging , 2011, Journal of magnetic resonance imaging : JMRI.

[29]  Maryellen L. Giger,et al.  Normal parenchymal enhancement patterns in women undergoing MR screening of the breast , 2011, European Radiology.

[30]  Roberto Orecchia,et al.  Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group. , 2010, European journal of cancer.

[31]  M. Giger,et al.  Cancerous breast lesions on dynamic contrast-enhanced MR images: computerized characterization for image-based prognostic markers. , 2010, Radiology.

[32]  Barbara L. Smith,et al.  Breast cancer subtype approximated by estrogen receptor, progesterone receptor, and HER-2 is associated with local and distant recurrence after breast-conserving therapy. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[33]  S. Paik,et al.  Preoperative chemotherapy: updates of National Surgical Adjuvant Breast and Bowel Project Protocols B-18 and B-27. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[34]  R. Bast,et al.  American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. , 2007, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[35]  E. Morris Diagnostic breast MR imaging: current status and future directions. , 2007, Radiologic clinics of North America.

[36]  M. Yaffe,et al.  American Cancer Society Guidelines for Breast Screening with MRI as an Adjunct to Mammography , 2007, CA: a cancer journal for clinicians.

[37]  Peter Gibbs,et al.  Diffusion changes precede size reduction in neoadjuvant treatment of breast cancer. , 2006, Magnetic resonance imaging.

[38]  Norman Wolmark,et al.  Sequential preoperative or postoperative docetaxel added to preoperative doxorubicin plus cyclophosphamide for operable breast cancer:National Surgical Adjuvant Breast and Bowel Project Protocol B-27. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[39]  M. Cronin,et al.  A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. , 2004, The New England journal of medicine.

[40]  Christian A. Rees,et al.  Molecular portraits of human breast tumours , 2000, Nature.

[41]  H Rusinek,et al.  Fatty and fibroglandular tissue volumes in the breasts of women 20-83 years old: comparison of X-ray mammography and computer-assisted MR imaging. , 1997, AJR. American journal of roentgenology.

[42]  P. Tofts Modeling tracer kinetics in dynamic Gd‐DTPA MR imaging , 1997, Journal of magnetic resonance imaging : JMRI.