Diagnostic value of diffusion-weighted imaging with synthetic b-values in breast tumors: comparison with dynamic contrast-enhanced and multiparametric MRI

[1]  Samuel J. Magny,et al.  Breast Imaging Reporting and Data System , 2020, Definitions.

[2]  E. Sigmund,et al.  Diffusion MRI of the breast: Current status and future directions , 2020, Journal of magnetic resonance imaging : JMRI.

[3]  Danny F. Martinez,et al.  Limited role of DWI with apparent diffusion coefficient mapping in breast lesions presenting as non-mass enhancement on dynamic contrast-enhanced MRI , 2019, Breast Cancer Research.

[4]  D. Le Bihan,et al.  Diffusion-weighted imaging of the breast—a consensus and mission statement from the EUSOBI International Breast Diffusion-Weighted Imaging working group , 2019, European Radiology.

[5]  S. Partridge,et al.  Diffusion-weighted MRI for Unenhanced Breast Cancer Screening. , 2019, Radiology.

[6]  Quantitative evaluation of computed and voxelwise computed diffusion-weighted imaging in breast cancer. , 2019, The British journal of radiology.

[7]  T. Helbich,et al.  Diffusion‐Weighted MRI of Breast Cancer: Improved Lesion Visibility and Image Quality Using Synthetic b‐Values , 2019, Journal of magnetic resonance imaging : JMRI.

[8]  N. Hylton,et al.  Diffusion-weighted MRI in Multicenter Trials of Breast Cancer. , 2019, Radiology.

[9]  C. Kuhl,et al.  Contrast‐enhanced MRI for breast cancer screening , 2019, Journal of magnetic resonance imaging : JMRI.

[10]  M. Su,et al.  Feasibility and Diagnostic Performance of Voxelwise Computed Diffusion‐Weighted Imaging in Breast Cancer , 2018, Journal of magnetic resonance imaging : JMRI.

[11]  S. Y. Park,et al.  Comparison of the Diagnostic Performance of Synthetic Versus Acquired High b‐Value (1500 s/mm2) Diffusion‐Weighted MRI in Women With Breast Cancers , 2018, Journal of Magnetic Resonance Imaging.

[12]  Y. Akiyama,et al.  How to Improve the Conspicuity of Breast Tumors on Computed High b-value Diffusion-weighted Imaging , 2018, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[13]  S. Kul,et al.  Assessment of breast mass morphology with diffusion‐weighted MRI: Beyond apparent diffusion coefficient , 2018, Journal of magnetic resonance imaging : JMRI.

[14]  T. Helbich,et al.  Diffusion-Weighted Imaging With Apparent Diffusion Coefficient Mapping for Breast Cancer Detection as a Stand-Alone Parameter: Comparison With Dynamic Contrast-Enhanced and Multiparametric Magnetic Resonance Imaging , 2018, Investigative radiology.

[15]  T. Helbich,et al.  Potential of Noncontrast Magnetic Resonance Imaging With Diffusion-Weighted Imaging in Characterization of Breast Lesions: Intraindividual Comparison With Dynamic Contrast-Enhanced Magnetic Resonance Imaging , 2017, Investigative radiology.

[16]  I. Dekkers,et al.  Gadolinium retention after administration of contrast agents based on linear chelators and the recommendations of the European Medicines Agency , 2018, European Radiology.

[17]  T. Yoshiura,et al.  Computed diffusion-weighted MR imaging for visualization of pancreatic adenocarcinoma: Comparison with acquired diffusion-weighted imaging. , 2017, European Journal of Radiology.

[18]  Fernando Calamante,et al.  Gadolinium deposition in the brain: summary of evidence and recommendations , 2017, The Lancet Neurology.

[19]  V. Runge Critical Questions Regarding Gadolinium Deposition in the Brain and Body After Injections of the Gadolinium-Based Contrast Agents, Safety, and Clinical Recommendations in Consideration of the EMA's Pharmacovigilance and Risk Assessment Committee Recommendation for Suspension of the Marketing Authori , 2017, Investigative radiology.

[20]  Junfeng Li,et al.  Comparison and Optimization of 3.0 T Breast Images Quality of Diffusion-Weighted Imaging with Multiple B-Values. , 2017, Academic radiology.

[21]  Noam Nissan,et al.  Diffusion‐weighted breast MRI: Clinical applications and emerging techniques , 2017, Journal of magnetic resonance imaging : JMRI.

[22]  Feasibility of Computed Diffusion Weighted Imaging and Optimization of b-value in Cervical Cancer , 2016, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[23]  Matthew Blackledge,et al.  Evaluating the diagnostic sensitivity of computed diffusion‐weighted MR imaging in the detection of breast cancer , 2016, Journal of magnetic resonance imaging : JMRI.

[24]  Christoph I. Lee,et al.  Performance of DWI as a Rapid Unenhanced Technique for Detecting Mammographically Occult Breast Cancer in Elevated-Risk Women With Dense Breasts. , 2016, AJR. American journal of roentgenology.

[25]  H. Kim,et al.  Diagnostic Performance of Fused Diffusion-Weighted Imaging Using Unenhanced or Postcontrast T1-Weighted MR Imaging in Patients With Breast Cancer , 2016, Medicine.

[26]  N. Schwenzer,et al.  Apparent diffusion coefficient‐dependent voxelwise computed diffusion‐weighted imaging: An approach for improving SNR and reducing T2 shine‐through effects , 2016, Journal of magnetic resonance imaging : JMRI.

[27]  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.

[28]  M. Dietzel,et al.  Combined reading of Contrast Enhanced and Diffusion Weighted Magnetic Resonance Imaging by using a simple sum score , 2016, European Radiology.

[29]  F. Sardanelli,et al.  Breast cancer detection using double reading of unenhanced MRI including T1-weighted, T2-weighted STIR, and diffusion-weighted imaging: a proof of concept study. , 2014, AJR. American journal of roentgenology.

[30]  M. Oudkerk,et al.  Effect of b value and pre-admission of contrast on diagnostic accuracy of 1.5-T breast DWI: a systematic review and meta-analysis , 2014, European Radiology.

[31]  Tamaki Yamada,et al.  Investigation of the optimal b-value to detect breast tumors with diffusion weighted imaging by 1.5-T MRI , 2014, Cancer Imaging.

[32]  T. Scheenen,et al.  Quantitative Evaluation of Computed High b Value Diffusion-Weighted Magnetic Resonance Imaging of the Prostate , 2013, Investigative radiology.

[33]  S. Ramadan,et al.  Diffusion-weighted imaging of the breast: comparison of b-values 1000 s/mm² and 1500 s/mm². , 2013, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[34]  J. Babb,et al.  Diffusion‐weighted imaging of the prostate: Comparison of b1000 and b2000 image sets for index lesion detection , 2013, Journal of magnetic resonance imaging : JMRI.

[35]  C. Marsault,et al.  Diffusion-weighted MR imaging of the breast: advantages and pitfalls. , 2013, European journal of radiology.

[36]  S. Ramadan,et al.  DiŠusion-weighted Imaging of the Breast : Comparison of B-values 1000 s / mm 2 and 1500 s / mm 2 , 2013 .

[37]  Conspicuity of breast lesions at different b values on diffusion-weighted imaging , 2012, BMC Cancer.

[38]  D. Collins,et al.  Computed diffusion-weighted MR imaging may improve tumor detection. , 2011, Radiology.

[39]  Xiao-Hua Zhou,et al.  Comprar Statistical Methods In Diagnostic Medicine | Xiao-Hua Zhou | 9780470183144 | Wiley , 2011 .

[40]  Qian Wu,et al.  Meta-analysis of quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesions , 2010, BMC Cancer.

[41]  Katarzyna J Macura,et al.  Diffusion-weighted imaging improves the diagnostic accuracy of conventional 3.0-T breast MR imaging. , 2010, Radiology.

[42]  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.

[43]  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.

[44]  Wendy B DeMartini,et al.  Quantitative diffusion-weighted imaging as an adjunct to conventional breast MRI for improved positive predictive value. , 2009, AJR. American journal of roentgenology.

[45]  Caroline Reinhold,et al.  Early invasive cervical cancer: CT and MR imaging in preoperative evaluation - ACRIN/GOG comparative study of diagnostic performance and interobserver variability. , 2007, Radiology.

[46]  Mithat Gonen,et al.  Analyzing Receiver Operating Characteristic Curves with SAS , 2007 .

[47]  Xiao-Hua Zhou,et al.  Statistical Methods in Diagnostic Medicine , 2002 .

[48]  Jonathan H Burdette,et al.  Diffusion-Weighted Imaging of Cerebral Infarctions: Are Higher b Values Better? , 2002, Journal of computer assisted tomography.

[49]  L. Liberman,et al.  Breast imaging reporting and data system (BI-RADS). , 2002, Radiologic clinics of North America.

[50]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.