Sequential [ 18 F ] FDG-[ 18 F ] FMISO PET and Multiparametric MRI at 3 T for Insights into Breast Cancer Heterogeneity and Correlation with Patient Outcomes : First Clinical Experience

Department of Radiation Oncology, Medical University of Vienna, Austria Christian Doppler Laboratory for Medical Radiation Research for Radiation Oncology, Medical University Vienna, Austria Department of Biomedical Imaging and Image-guided erapy, Molecular and Gender Imaging Medical University of Vienna, Austria Department of Biomedical Imaging and Image-guided erapy, Division of Nuclear Medicine, Medical University of Vienna, Austria Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA

[1]  T. Hasebe,et al.  Intracellular hypoxia measured by 18F-fluoromisonidazole positron emission tomography has prognostic impact in patients with estrogen receptor-positive breast cancer , 2018, Breast Cancer Research.

[2]  I. Brčić,et al.  Correlation of MRI features and pathohistological prognostic factors in invasive ductal breast carcinoma , 2017, Acta clinica Belgica.

[3]  M. Shekhar,et al.  Breast cancer complexity: implications of intratumoral heterogeneity in clinical management , 2017, Cancer and Metastasis Reviews.

[4]  D. Rubin,et al.  Heterogeneous Enhancement Patterns of Tumor-adjacent Parenchyma at MR Imaging Are Associated with Dysregulated Signaling Pathways and Poor Survival in Breast Cancer. , 2017, Radiology.

[5]  Richard Pötter,et al.  Changes in Tumor Biology During Chemoradiation of Cervix Cancer Assessed by Multiparametric MRI and Hypoxia PET , 2017, Molecular Imaging and Biology.

[6]  W. Kaiser,et al.  Prognostic Value of "Prepectoral Edema" in MR-mammography. , 2017, Anticancer research.

[7]  Giuseppe Guglielmi,et al.  Can Diffusion-Weighted Imaging and Related Apparent Diffusion Coefficient be a Prognostic Value in Women With Breast Cancer? , 2017, Cancer investigation.

[8]  J. Deasy,et al.  Quantitative apparent diffusion coefficient measurement obtained by 3.0Tesla MRI as a potential noninvasive marker of tumor aggressiveness in breast cancer. , 2016, European journal of radiology.

[9]  E. Sigmund,et al.  Assessment of Aggressiveness of Breast Cancer Using Simultaneous 18F-FDG-PET and DCE-MRI: Preliminary Observation , 2016, Clinical nuclear medicine.

[10]  D. Noh,et al.  Pretreatment MR Imaging Features of Triple-Negative Breast Cancer: Association with Response to Neoadjuvant Chemotherapy and Recurrence-Free Survival. , 2016, Radiology.

[11]  E. Öztürk,et al.  Diffusion Weighted MR Imaging of Breast and Correlation of Prognostic Factors in Breast Cancer. , 2016, Balkan medical journal.

[12]  T. Helbich,et al.  Breast MRI: EUSOBI recommendations for women’s information , 2015, European Radiology.

[13]  Anthony Rhodes,et al.  Estrogen and progesterone receptors in breast cancer. , 2014, Future oncology.

[14]  S. Masuda,et al.  Prognostic significance of the Ki67 scoring categories in breast cancer subgroups. , 2014, Clinical breast cancer.

[15]  Wolfgang Bogner,et al.  Improved Differentiation of Benign and Malignant Breast Tumors with Multiparametric 18Fluorodeoxyglucose Positron Emission Tomography Magnetic Resonance Imaging: A Feasibility Study , 2014, Clinical Cancer Research.

[16]  Salvatore Piscuoglio,et al.  Breast cancer intra-tumor heterogeneity , 2014, Breast Cancer Research.

[17]  Guangyu Liu,et al.  18F-Fluoromisonidazole PET/CT: A Potential Tool for Predicting Primary Endocrine Therapy Resistance in Breast Cancer , 2013, The Journal of Nuclear Medicine.

[18]  Michael Baumann,et al.  Exploratory prospective trial of hypoxia-specific PET imaging during radiochemotherapy in patients with locally advanced head-and-neck cancer. , 2012, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[19]  Helmar Bergmann,et al.  PET based volume segmentation with emphasis on the iterative TrueX algorithm. , 2012, Zeitschrift fur medizinische Physik.

[20]  Matthias Dietzel,et al.  Application of breast MRI for prediction of lymph node metastases – systematic approach using 17 individual descriptors and a dedicated decision tree , 2010, Acta radiologica.

[21]  K Thielemans,et al.  Image-based point spread function implementation in a fully 3D OSEM reconstruction algorithm for PET , 2010, Physics in medicine and biology.

[22]  G. Song,et al.  Role of hypoxia in the hallmarks of human cancer , 2009, Journal of cellular biochemistry.

[23]  C. Sotiriou,et al.  Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures , 2007, Breast Cancer Research.

[24]  C. Perou,et al.  Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. , 2006, JAMA.

[25]  H. Hoekstra,et al.  Positron emission tomography in patients with breast cancer using (18)F-3'-deoxy-3'-fluoro-l-thymidine ((18)F-FLT)-a pilot study. , 2006, European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology.

[26]  James L Tatum,et al.  Hypoxia: Importance in tumor biology, noninvasive measurement by imaging, and value of its measurement in the management of cancer therapy , 2006, International journal of radiation biology.

[27]  P. Okunieff,et al.  Evidence for and against hypoxia as the primary cause of tumor aggressiveness. , 2003, Advances in experimental medicine and biology.

[28]  T W Griffin,et al.  Imaging of hypoxia in human tumors with [F-18]fluoromisonidazole. , 1992, International journal of radiation oncology, biology, physics.