Diffusion-weighted imaging of the breast—a consensus and mission statement from the EUSOBI International Breast Diffusion-Weighted Imaging working group
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D. Le Bihan | F. Gilbert | A. Patterson | S. Partridge | E. Sigmund | M. Iima | R. Mann | P. Clauser | K. Pinker | P. Baltzer | J. Camps-Herrero | F. Thibault | L. Martincich
[1] Samuel J. Magny,et al. Breast Imaging Reporting and Data System , 2020, Definitions.
[2] Danny F. Martinez,et al. Radiomic Signatures Derived from Diffusion-Weighted Imaging for the Assessment of Breast Cancer Receptor Status and Molecular Subtypes , 2019, Molecular Imaging and Biology.
[3] F. Gilbert,et al. A Meta-analysis of the Diagnostic Performance of Diffusion MRI for Breast Lesion Characterization. , 2019, Radiology.
[4] Colleen H. Neal,et al. Utility of Diffusion-weighted Imaging to Decrease Unnecessary Biopsies Prompted by Breast MRI: A Trial of the ECOG-ACRIN Cancer Research Group (A6702) , 2019, Clinical Cancer Research.
[5] L. Esserman,et al. Test–retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial , 2018, Journal of magnetic resonance imaging : JMRI.
[6] Lihua Li,et al. Differentiation of triple-negative breast cancer from other subtypes through whole-tumor histogram analysis on multiparametric MR imaging , 2018, European Radiology.
[7] Zheng Zhang,et al. Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial. , 2018, Radiology.
[8] R. Grimm,et al. Risk stratification of ductal carcinoma in situ using whole-lesion histogram analysis of the apparent diffusion coefficient , 2018, European Radiology.
[9] H. Degani,et al. Quantitative evaluation of breast cancer response to neoadjuvant chemotherapy by diffusion tensor imaging: Initial results , 2018, Journal of magnetic resonance imaging : JMRI.
[10] Effects of diffusion time on non-Gaussian diffusion and intravoxel incoherent motion (IVIM) MRI parameters in breast cancer and hepatocellular carcinoma xenograft models , 2018, Acta radiologica open.
[11] C. Jack,et al. Quantitative magnetic resonance imaging phantoms: A review and the need for a system phantom , 2018, Magnetic resonance in medicine.
[12] Stuart A. Taylor,et al. UK quantitative WB-DWI technical workgroup: consensus meeting recommendations on optimisation, quality control, processing and analysis of quantitative whole-body diffusion-weighted imaging for cancer , 2017, The British journal of radiology.
[13] Kaori Togashi,et al. Intravoxel Incoherent Motion and Quantitative Non-Gaussian Diffusion MR Imaging: Evaluation of the Diagnostic and Prognostic Value of Several Markers of Malignant and Benign Breast Lesions. , 2017, Radiology.
[14] Thomas E. Yankeelov,et al. Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network , 2017, Journal of medical imaging.
[15] Qiu-ying Yao,et al. Breast Lesions: Diagnosis Using Diffusion Weighted Imaging at 1.5T and 3.0T—Systematic Review and Meta‐analysis , 2017, Clinical breast cancer.
[16] S. Suo,et al. Multiparametric diffusion‐weighted imaging in breast lesions: Association with pathologic diagnosis and prognostic factors , 2017, Journal of magnetic resonance imaging : JMRI.
[17] R. Grimm,et al. Intravoxel incoherent motion (IVIM)‐derived parameters in diffusion‐weighted MRI: Associations with prognostic factors in invasive ductal carcinoma , 2017, Journal of magnetic resonance imaging : JMRI.
[18] D. Collins,et al. Extracranial Soft-Tissue Tumors: Repeatability of Apparent Diffusion Coefficient Estimates from Diffusion-weighted MR Imaging. , 2017, Radiology.
[19] M. Uğurlu,et al. Diagnostic performance of diffusion tensor imaging parameters in breast cancer and correlation with the prognostic factors , 2017, Journal of magnetic resonance imaging : JMRI.
[20] Noam Nissan,et al. Diffusion‐weighted breast MRI: Clinical applications and emerging techniques , 2017, Journal of magnetic resonance imaging : JMRI.
[21] Wolfgang Bogner,et al. Diffusion-weighted imaging of breast lesions: Region-of-interest placement and different ADC parameters influence apparent diffusion coefficient values , 2017, European Radiology.
[22] Maria Bernathova,et al. Diffusion‐weighted MRI of breast lesions: a prospective clinical investigation of the quantitative imaging biomarker characteristics of reproducibility, repeatability, and diagnostic accuracy , 2016, NMR in biomedicine.
[23] Geoffrey S. Payne,et al. DCE-MRI, DW-MRI, and MRS in Cancer: Challenges and Advantages of Implementing Qualitative and Quantitative Multi-parametric Imaging in the Clinic , 2016, Topics in magnetic resonance imaging : TMRI.
[24] N. Hylton,et al. Design of a breast phantom for quantitative MRI , 2016, Journal of magnetic resonance imaging : JMRI.
[25] Li Zhang,et al. Accuracy of combined dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging for breast cancer detection: a meta-analysis , 2016, Acta radiologica.
[26] N. Toschi,et al. On the use of trace-weighted images in body diffusional kurtosis imaging. , 2016, Magnetic resonance imaging.
[27] Jin You Kim,et al. Apparent diffusion coefficient of breast cancer and normal fibroglandular tissue in diffusion-weighted imaging: the effects of menstrual cycle and menopausal status , 2016, Breast Cancer Research and Treatment.
[28] Jian-Rong Ding,et al. Apparent diffusion coefficient value of diffusion-weighted imaging for differential diagnosis of ductal carcinoma in situ and infiltrating ductal carcinoma. , 2016, Journal of cancer research and therapeutics.
[29] M. Esposito,et al. Quality assurance multicenter comparison of different MR scanners for quantitative diffusion‐weighted imaging , 2016, Journal of magnetic resonance imaging : JMRI.
[30] D. Margolis,et al. PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. , 2016, European urology.
[31] D. Sodickson,et al. Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors , 2016, European Radiology.
[32] M. Dietzel,et al. Combined reading of Contrast Enhanced and Diffusion Weighted Magnetic Resonance Imaging by using a simple sum score , 2016, European Radiology.
[33] H. Moshonov,et al. Evaluation of Apparent Diffusion Coefficient to Predict Grade, Microinvasion, and Invasion in Ductal Carcinoma In Situ of the Breast. , 2015, Academic radiology.
[34] Amro Masarwah,et al. Diffusion-Weighted Imaging in 3.0 Tesla Breast MRI: Diagnostic Performance and Tumor Characterization Using Small Subregions vs. Whole Tumor Regions of Interest , 2015, PloS one.
[35] Dominic Holland,et al. Inhomogeneous static magnetic field‐induced distortion correction applied to diffusion weighted MRI of the breast at 3T , 2015, Magnetic resonance in medicine.
[36] Daniel K Sodickson,et al. Comparison of fitting methods and b‐value sampling strategies for intravoxel incoherent motion in breast cancer , 2015, Magnetic resonance in medicine.
[37] John Kornak,et al. Gradient nonlinearity correction to improve apparent diffusion coefficient accuracy and standardization in the american college of radiology imaging network 6698 breast cancer trial , 2015, Journal of magnetic resonance imaging : JMRI.
[38] E Crowe,et al. Assessment and quantification of sources of variability in breast apparent diffusion coefficient (ADC) measurements at diffusion weighted imaging. , 2015, European journal of radiology.
[39] Saadallah Ramadan,et al. Utilisation of MR spectroscopy and diffusion weighted imaging in predicting and monitoring of breast cancer response to chemotherapy , 2015, Journal of medical imaging and radiation oncology.
[40] Kunwei Shen,et al. Breast Cancer: Diffusion Kurtosis MR Imaging-Diagnostic Accuracy and Correlation with Clinical-Pathologic Factors. , 2015, Radiology.
[41] Thomas E Yankeelov,et al. Multiparametric Magnetic Resonance Imaging for Predicting Pathological Response After the First Cycle of Neoadjuvant Chemotherapy in Breast Cancer , 2015, Investigative radiology.
[42] D. Le Bihan,et al. Quantitative Non-Gaussian Diffusion and Intravoxel Incoherent Motion Magnetic Resonance Imaging: Differentiation of Malignant and Benign Breast Lesions , 2015, Investigative radiology.
[43] Bing Ma,et al. Multi-Site Clinical Evaluation of DW-MRI as a Treatment Response Metric for Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy , 2015, PloS one.
[44] Hugo Alexandre Ferreira,et al. Breast DWI at 3 T: influence of the fat-suppression technique on image quality and diagnostic performance. , 2015, Clinical radiology.
[45] R. Nunes,et al. Region of interest demarcation for quantification of the apparent diffusion coefficient in breast lesions and its interobserver variability. , 2015, Diagnostic and interventional radiology.
[46] H. Barnhart,et al. The emerging science of quantitative imaging biomarkers terminology and definitions for scientific studies and regulatory submissions , 2015, Statistical methods in medical research.
[47] T. Helbich,et al. Quantitative Apparent Diffusion Coefficient as a Noninvasive Imaging Biomarker for the Differentiation of Invasive Breast Cancer and Ductal Carcinoma In Situ , 2015, Investigative radiology.
[48] Dongmei Wu,et al. Characterization of Breast Tumors Using Diffusion Kurtosis Imaging (DKI) , 2014, PloS one.
[49] Louisa Bokacheva,et al. Intravoxel incoherent motion diffusion‐weighted MRI at 3.0 T differentiates malignant breast lesions from benign lesions and breast parenchyma , 2014, Journal of magnetic resonance imaging : JMRI.
[50] 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.
[51] T. Helbich,et al. MRI-only lesions: application of diffusion-weighted imaging obviates unnecessary MR-guided breast biopsies , 2014, European Radiology.
[52] R. Nunes,et al. Diffusion-weighted breast imaging at 3 T: preliminary experience. , 2014, Clinical radiology.
[53] H. Degani,et al. Diffusion-tensor MR imaging of the breast: hormonal regulation. , 2014, Radiology.
[54] John Kornak,et al. Repeatability of quantitative MRI measurements in normal breast tissue. , 2014, Translational oncology.
[55] Mauro Iori,et al. MR Scanner Systems Should Be Adequately Characterized in Diffusion-MRI of the Breast , 2014, PloS one.
[56] Shuixing Zhang,et al. Intravoxel incoherent motion (IVIM) in evaluation of breast lesions: comparison with conventional DWI. , 2013, European journal of radiology.
[57] Ozgur Cakir,et al. Comparison of the diagnostic performances of diffusion parameters in diffusion weighted imaging and diffusion tensor imaging of breast lesions. , 2013, European journal of radiology.
[58] D. Bihan. Apparent Diffusion Coefficient and Beyond: What Diffusion MR Imaging Can Tell Us about Tissue Structure , 2013 .
[59] Christopher J. Hardy,et al. Improved correction for gradient nonlinearity effects in diffusion‐weighted imaging , 2013, Journal of magnetic resonance imaging : JMRI.
[60] Isabelle Thomassin,et al. Diffusion-weighted MRI in pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer , 2013, European Radiology.
[61] Timothy D Johnson,et al. Multi‐system repeatability and reproducibility of apparent diffusion coefficient measurement using an ice‐water phantom , 2013, Journal of magnetic resonance imaging : JMRI.
[62] K. Pinker,et al. Combined contrast-enhanced magnetic resonance and diffusion-weighted imaging reading adapted to the “Breast Imaging Reporting and Data System” for multiparametric 3-T imaging of breast lesions , 2013, European Radiology.
[63] D. Le Bihan. Apparent diffusion coefficient and beyond: what diffusion MR imaging can tell us about tissue structure. , 2013, Radiology.
[64] Diffusion weighted imaging of liver lesions suspect for metastases: Apparent diffusion coefficient (ADC) values and lesion contrast are independent from Gd-EOB-DTPA administration. , 2012, European journal of radiology.
[65] Erez Eyal,et al. Parametric Diffusion Tensor Imaging of the Breast , 2012, Investigative radiology.
[66] Eun-Kyung Kim,et al. Triple-negative invasive breast cancer on dynamic contrast-enhanced and diffusion-weighted MR imaging: comparison with other breast cancer subtypes , 2012, European Radiology.
[67] N. deSouza,et al. Diffusion weighted imaging of the normal breast: reproducibility of apparent diffusion coefficient measurements and variation with menstrual cycle and menopausal status , 2012, European Radiology.
[68] C. Meyer,et al. Diffusion coefficient measurement using a temperature‐controlled fluid for quality control in multicenter studies , 2011, Journal of magnetic resonance imaging : JMRI.
[69] Kaori Togashi,et al. Apparent diffusion coefficient as an MR imaging biomarker of low-risk ductal carcinoma in situ: a pilot study. , 2011, Radiology.
[70] Wendy B DeMartini,et al. Characterization of ductal carcinoma in situ on diffusion weighted breast MRI , 2011, European Radiology.
[71] D. Sodickson,et al. Intravoxel incoherent motion imaging of tumor microenvironment in locally advanced breast cancer , 2011, Magnetic resonance in medicine.
[72] Thomas E Yankeelov,et al. Motion correction in diffusion‐weighted MRI of the breast at 3T , 2011, Journal of magnetic resonance imaging : JMRI.
[73] Qian Wu,et al. Meta-analysis of quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesions , 2010, BMC Cancer.
[74] Wendy B DeMartini,et al. Apparent diffusion coefficient values for discriminating benign and malignant breast MRI lesions: effects of lesion type and size. , 2010, AJR. American journal of roentgenology.
[75] M. Oudkerk,et al. Diffusion‐weighted imaging of normal fibroglandular breast tissue: influence of microperfusion and fat suppression technique on the apparent diffusion coefficient , 2010, NMR in biomedicine.
[76] Roberto Orecchia,et al. Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group. , 2010, European journal of cancer.
[77] Wendy B DeMartini,et al. Diffusion tensor MRI: Preliminary anisotropy measures and mapping of breast tumors , 2010, Journal of magnetic resonance imaging : JMRI.
[78] Matthias Dietzel,et al. Diffusion tensor magnetic resonance imaging of the breast: a pilot study , 2010, European Radiology.
[79] 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.
[80] Robin M Heidemann,et al. High resolution diffusion‐weighted imaging using readout‐segmented echo‐planar imaging, parallel imaging and a two‐dimensional navigator‐based reacquisition , 2009, Magnetic resonance in medicine.
[81] H. Hatabu,et al. Diffusion-weighted imaging of mucinous carcinoma of the breast: evaluation of apparent diffusion coefficient and signal intensity in correlation with histologic findings. , 2009, AJR. American journal of roentgenology.
[82] J. R. Reichenbach,et al. Diffusion-weighted imaging (DWI) in MR mammography (MRM): clinical comparison of echo planar imaging (EPI) and half-Fourier single-shot turbo spin echo (HASTE) diffusion techniques , 2009, European Radiology.
[83] C. Boetes,et al. Breast MRI: guidelines from the European Society of Breast Imaging , 2008, European Radiology.
[84] Evelyn Wenkel,et al. Diffusion weighted imaging in breast MRI: comparison of two different pulse sequences. , 2007, Academic radiology.
[85] Peter Gibbs,et al. Diffusion changes precede size reduction in neoadjuvant treatment of breast cancer. , 2006, Magnetic resonance imaging.
[86] Thierry Metens,et al. Quantitative diffusion imaging in breast cancer: A clinical prospective study , 2006, Journal of magnetic resonance imaging : JMRI.
[87] H. Thomsen,et al. ESUR guidelines on contrast media , 2006, Abdominal Imaging.
[88] Peter Kellman,et al. Image reconstruction in SNR units: A general method for SNR measurement † , 2005, Magnetic resonance in medicine.
[89] S. Schoenberg,et al. Practical approaches to the evaluation of signal‐to‐noise ratio performance with parallel imaging: Application with cardiac imaging and a 32‐channel cardiac coil , 2005, Magnetic resonance in medicine.
[90] Masahiko Watanabe,et al. Diffusion-Weighted Imaging of Malignant Breast Tumors: The Usefulness of Apparent Diffusion Coefficient (ADC) Value and ADC Map for the Detection of Malignant Breast Tumors and Evaluation of Cancer Extension , 2005, Journal of computer assisted tomography.
[91] Masanori Ozaki,et al. ADC mapping of benign and malignant breast tumors. , 2005, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.
[92] M. Leach,et al. Developing a quality control protocol for diffusion imaging on a clinical MRI system. , 2004, Physics in medicine and biology.
[93] L. Liberman,et al. Breast imaging reporting and data system (BI-RADS). , 2002, Radiologic clinics of North America.
[94] T. A. Carpenter,et al. Optimised diffusion-weighting for measurement of apparent diffusion coefficient (ADC) in human brain. , 1997, Magnetic resonance imaging.