Prediction of malignancy by a radiomic signature from contrast agent‐free diffusion MRI in suspicious breast lesions found on screening mammography.
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Michael Götz | Manuel Wiesenfarth | Sebastian Bickelhaupt | Daniel Paech | David Bonekamp | Franziska Steudle | Diana Tichy | Heinz-Peter Schlemmer | Philipp Kickingereder | Frederik B Laun | Heidi Daniel | M. Götz | F. Laun | H. Schlemmer | D. Bonekamp | Klaus Maier-Hein | M. Wiesenfarth | P. Kickingereder | S. Bickelhaupt | D. Paech | F. Steudle | W. Lederer | H. Daniel | Nils Gählert | D. Tichy | Wolfgang Lederer | Nils Gählert | Klaus H Maier-Hein
[1] Guido Gerig,et al. User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.
[2] Michael Golatta,et al. Evaluation of Virtual Touch Tissue Imaging Quantification, a New Shear Wave Velocity Imaging Method, for Breast Lesion Assessment by Ultrasound , 2014, BioMed research international.
[3] Elastographie als Zusatzmodalität der Mammasonographie , 2014, Der Radiologe.
[4] M. Götz,et al. Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models. , 2016, Radiology.
[5] G. Angelelli,et al. Unenhanced breast MRI (STIR, T2-weighted TSE, DWIBS): An accurate and alternative strategy for detecting and differentiating breast lesions. , 2015, Magnetic resonance imaging.
[6] Matthias Benndorf,et al. Sensitivity and specificity of unenhanced MR mammography (DWI combined with T2-weighted TSE imaging, ueMRM) for the differentiation of mass lesions , 2010, European Radiology.
[7] D. Clevert,et al. [Elastography as an additional tool in breast sonography. Technical principles and clinical applications]. , 2014, Der Radiologe.
[8] Neema Jamshidi,et al. Breast Cancer: Radiogenomic Biomarker Reveals Associations among Dynamic Contrast-enhanced MR Imaging, Long Noncoding RNA, and Metastasis. , 2015, Radiology.
[9] K. Straif,et al. Breast-cancer screening--viewpoint of the IARC Working Group. , 2015, The New England journal of medicine.
[10] Harald Binder,et al. Adapting Prediction Error Estimates for Biased Complexity Selection in High-Dimensional Bootstrap Samples , 2008, Statistical applications in genetics and molecular biology.
[11] Anant Madabhushi,et al. A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores , 2016, Scientific Reports.
[12] Wendy B DeMartini,et al. Differential diagnosis of mammographically and clinically occult breast lesions on diffusion‐weighted MRI , 2010, Journal of magnetic resonance imaging : JMRI.
[13] The Burden of False-Positive Results in Analog and Digital Screening Mammography: Experience of the Nova Scotia Breast Screening Program , 2014, Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes.
[14] David F Kallmes,et al. Intracranial Gadolinium Deposition after Contrast-enhanced MR Imaging. , 2015, Radiology.
[15] 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.
[16] F. Laun,et al. Fast and Noninvasive Characterization of Suspicious Lesions Detected at Breast Cancer X-Ray Screening: Capability of Diffusion-weighted MR Imaging with MIPs. , 2016, Radiology.
[17] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[18] Noam Nissan,et al. Diffusion‐weighted breast MRI: Clinical applications and emerging techniques , 2017, Journal of magnetic resonance imaging : JMRI.
[19] R. Tibshirani,et al. Improvements on Cross-Validation: The 632+ Bootstrap Method , 1997 .
[20] Alexander Radbruch,et al. High-Signal Intensity in the Dentate Nucleus and Globus Pallidus on Unenhanced T1-Weighted Images: Evaluation of the Macrocyclic Gadolinium-Based Contrast Agent Gadobutrol , 2015, Investigative radiology.
[21] K. Bock,et al. Mammographiescreening in Deutschland , 2014, Der Radiologe.
[22] Alfonso Frigerio,et al. False-Positive Results in Mammographic Screening for Breast Cancer in Europe: A Literature Review and Survey of Service Screening Programmes , 2012, Journal of medical screening.
[23] T. Helbich,et al. Diffusion-weighted MR for differentiation of breast lesions at 3.0 T: how does selection of diffusion protocols affect diagnosis? , 2009, Radiology.
[24] P. Lambin,et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach , 2014, Nature Communications.
[25] Hiroshi Honda,et al. Detection of non-palpable breast cancer in asymptomatic women by using unenhanced diffusion-weighted and T2-weighted MR imaging: comparison with mammography and dynamic contrast-enhanced MR imaging , 2010, European Radiology.
[26] M. Giger,et al. Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma , 2015, Scientific Reports.
[27] Bin Zheng,et al. Applying a new quantitative global breast MRI feature analysis scheme to assess tumor response to chemotherapy , 2016, Journal of magnetic resonance imaging : JMRI.
[28] Liang Hu,et al. Image manifold revealing for breast lesion segmentation in DCE-MRI. , 2015, Bio-medical materials and engineering.
[29] S. Heywang-Köbrunner,et al. [Mammography screening in Germany. Current results and future challenges]. , 2014, Der Radiologe.
[30] M Nolden,et al. MITK Diffusion Imaging , 2012, Methods of Information in Medicine.
[31] R. A. Lerski,et al. Magnetic resonance imaging texture analysis classification of primary breast cancer , 2016, European Radiology.
[32] Peng Zhao,et al. On Model Selection Consistency of Lasso , 2006, J. Mach. Learn. Res..
[33] Sebastian Bickelhaupt,et al. Independent value of image fusion in unenhanced breast MRI using diffusion-weighted and morphological T2-weighted images for lesion characterization in patients with recently detected BI-RADS 4/5 x-ray mammography findings , 2017, European Radiology.
[34] H. Aerts,et al. Applications and limitations of radiomics , 2016, Physics in medicine and biology.
[35] L. Philpotts,et al. The patient burden of screening mammography recall. , 2014, Journal of women's health.
[36] Maciej A Mazurowski,et al. Radiogenomic analysis of breast cancer: luminal B molecular subtype is associated with enhancement dynamics at MR imaging. , 2014, Radiology.
[37] P. Lambin,et al. Machine Learning methods for Quantitative Radiomic Biomarkers , 2015, Scientific Reports.
[38] Klaus H. Maier-Hein,et al. The Medical Imaging Interaction Toolkit: challenges and advances , 2013, International Journal of Computer Assisted Radiology and Surgery.
[39] Mario Sansone,et al. Integration of DCE-MRI and DW-MRI Quantitative Parameters for Breast Lesion Classification , 2015, BioMed research international.