Multiparametric MRI of the breast: A review

During their development, cancers acquire several functional capabilities, which are defined as the hallmarks of cancer. For a deeper understanding of the hallmarks of cancer, and, consequently, improved personalized patient care, diagnostic tests must be multilayered and complex to identify the relevant underlying processes of cancer development and progression. In this context, magnetic resonance imaging (MRI) has emerged as an exceptionally powerful, versatile, and precise imaging technique. MRI of the breast is an essential tool in breast imaging, with multiple indications. Dynamic contrast‐enhanced MRI (CE‐MRI) is the most sensitive test for breast cancer detection, with a good specificity. CE‐MRI provides mainly morphological, and, to some extent, functional information about tumor perfusion and vascularity. Recently, several functional imaging techniques in MRI, such as diffusion‐weighted imaging and spectroscopy, have been assessed for breast imaging and this combined application is defined as multiparametric imaging. Furthermore, the application of higher field strengths (≥3T) has demonstrated improved sensitivity and specificity of breast cancer detection. Multiparametric imaging with different functional MRI parameters (mpMRI) visualizes and quantifies the functional processes of cancer development and progression at multiple levels, and provides specific information about the hallmarks of cancer. MpMRI of the breast improves diagnostic accuracy in breast cancer, obviates unnecessary breast biopsies, and enables an improved assessment and prediction of response to neoadjuvant therapy. This review will provide a comprehensive overview of the current possibilities and emerging techniques for mpMRI of the breast.

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

[2]  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.

[3]  Bin Wang,et al.  Intravoxel incoherent motion diffusion-weighted imaging as an adjunct to dynamic contrast-enhanced MRI to improve accuracy of the differential diagnosis of benign and malignant breast lesions. , 2017, Magnetic resonance imaging.

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

[5]  Thomas E Yankeelov,et al.  Three-dimensional Image-based Mechanical Modeling for Predicting the Response of Breast Cancer to Neoadjuvant Therapy. , 2017, Computer methods in applied mechanics and engineering.

[6]  P. Luijten,et al.  Proton and phosphorus magnetic resonance spectroscopy of the healthy human breast at 7 T , 2016, NMR in biomedicine.

[7]  T. Noguchi,et al.  Diagnostic Performance of Diffusion Tensor Imaging with Readout-segmented Echo-planar Imaging for Invasive Breast Cancer: Correlation of ADC and FA with Pathological Prognostic Markers , 2016, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[8]  Xiao Li,et al.  Diffusion tensor imaging of breast lesions: evaluation of apparent diffusion coefficient and fractional anisotropy and tissue cellularity. , 2016, The British journal of radiology.

[9]  J. Joo,et al.  Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer: association with histopathological features and subtypes. , 2016, The British journal of radiology.

[10]  E. Morris,et al.  Diffusion tensor imaging in the normal breast: influences of fibroglandular tissue composition and background parenchymal enhancement. , 2016, Clinical imaging.

[11]  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.

[12]  Glycerophosphocholine and Glycerophosphoethanolamine Are Not the Main Sources of the In Vivo 31P MRS Phosphodiester Signals from Healthy Fibroglandular Breast Tissue at 7 T , 2016, Front. Oncol..

[13]  S. Partridge,et al.  Multiparametric MR Imaging of Breast Cancer. , 2016, Magnetic resonance imaging clinics of North America.

[14]  Wolfgang Bogner,et al.  Quantitative Sodium MR Imaging at 7 T: Initial Results and Comparison with Diffusion-weighted Imaging in Patients with Breast Tumors. , 2016, Radiology.

[15]  Martin J. Graves,et al.  A comparison of quantitative methods for clinical imaging with hyperpolarized 13C‐pyruvate , 2016, NMR in biomedicine.

[16]  M. A. van den Bosch,et al.  Dynamic contrast-enhanced breast MRI at 7T and 3T: an intra-individual comparison study , 2016, SpringerPlus.

[17]  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.

[18]  T. Helbich,et al.  A simple scoring system for breast MRI interpretation: does it compensate for reader experience? , 2016, European Radiology.

[19]  D. Georg,et al.  Multiparametric MRI of the prostate at 3 T: limited value of 3D 1H-MR spectroscopy as a fourth parameter , 2016, World Journal of Urology.

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

[21]  P. Westenend,et al.  Multiparametric MRI With Dynamic Contrast Enhancement, Diffusion-Weighted Imaging, and 31-Phosphorus Spectroscopy at 7 T for Characterization of Breast Cancer , 2015, Investigative radiology.

[22]  Sylvain Favelier,et al.  Current role of multiparametric magnetic resonance imaging for prostate cancer. , 2015, Quantitative imaging in medicine and surgery.

[23]  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.

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

[25]  Kunwei Shen,et al.  Breast Cancer: Diffusion Kurtosis MR Imaging-Diagnostic Accuracy and Correlation with Clinical-Pathologic Factors. , 2015, Radiology.

[26]  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.

[27]  T. Helbich,et al.  Multiparametric MR Imaging with High-Resolution Dynamic Contrast-enhanced and Diffusion-weighted Imaging at 7 T Improves the Assessment of Breast Tumors: A Feasibility Study. , 2015, Radiology.

[28]  C. Mountford,et al.  Lipid and Metabolite Deregulation in the Breast Tissue of Women Carrying BRCA1 and BRCA2 Genetic Mutations. , 2015, Radiology.

[29]  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.

[30]  Lin Li,et al.  Parameters of Dynamic Contrast-Enhanced MRI as Imaging Markers for Angiogenesis and Proliferation in Human Breast Cancer , 2015, Medical science monitor : international medical journal of experimental and clinical research.

[31]  O. Paulson,et al.  Monitoring mammary tumor progression and effect of tamoxifen treatment in MMTV‐PymT using MRI and magnetic resonance spectroscopy with hyperpolarized [1‐13C]pyruvate , 2015, Magnetic resonance in medicine.

[32]  T. Helbich,et al.  Bilateral diffusion-weighted MR imaging of breast tumors with submillimeter resolution using readout-segmented echo-planar imaging at 7 T. , 2015, Radiology.

[33]  S. Choi,et al.  Prognosis Prediction of Measurable Enhancing Lesion after Completion of Standard Concomitant Chemoradiotherapy and Adjuvant Temozolomide in Glioblastoma Patients: Application of Dynamic Susceptibility Contrast Perfusion and Diffusion-Weighted Imaging , 2014, PloS one.

[34]  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.

[35]  Nico Karssemeijer,et al.  A Novel Approach to Contrast-Enhanced Breast Magnetic Resonance Imaging for Screening: High-Resolution Ultrafast Dynamic Imaging , 2014, Investigative radiology.

[36]  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.

[37]  H. Hricak,et al.  Multiparametric 3T MRI for the prediction of pathological downgrading after radical prostatectomy in patients with biopsy-proven Gleason score 3 + 4 prostate cancer , 2014, European Radiology.

[38]  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.

[39]  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.

[40]  T. Helbich,et al.  Molecular imaging for the characterization of breast tumors , 2014, Expert review of anticancer therapy.

[41]  Wolfgang Bogner,et al.  Dynamic Contrast-Enhanced Magnetic Resonance Imaging of Breast Tumors at 3 and 7 T: A Comparison , 2014, Investigative radiology.

[42]  Kimberly L Desmond,et al.  Mapping of amide, amine, and aliphatic peaks in the CEST spectra of murine xenografts at 7 T , 2014, Magnetic resonance in medicine.

[43]  T. Helbich,et al.  MRI-only lesions: application of diffusion-weighted imaging obviates unnecessary MR-guided breast biopsies , 2014, European Radiology.

[44]  H. Khalil,et al.  Improving outcomes of screening breast MRI with practice evolution: Initial clinical experience with 3T compared to 1.5T , 2014, Journal of magnetic resonance imaging : JMRI.

[45]  He N. Xu,et al.  Is higher lactate an indicator of tumor metastatic risk? A pilot MRS study using hyperpolarized (13)C-pyruvate. , 2014, Academic radiology.

[46]  S. Gruber,et al.  Clinical application of bilateral high temporal and spatial resolution dynamic contrast-enhanced magnetic resonance imaging of the breast at 7 T , 2014, European Radiology.

[47]  Gil Navon,et al.  Molecular imaging of tumors and metastases using chemical exchange saturation transfer (CEST) MRI , 2013, Scientific Reports.

[48]  J. Gore,et al.  Amide proton transfer imaging of the human breast at 7T: development and reproducibility , 2013, NMR in biomedicine.

[49]  Xavier Golay,et al.  Imaging Brain Deoxyglucose Uptake and Metabolism by Glucocest MRI , 2013, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[50]  P. Bolan Magnetic resonance spectroscopy of the breast: current status. , 2013, Magnetic resonance imaging clinics of North America.

[51]  Baris Turkbey,et al.  Prostate cancer: can multiparametric MR imaging help identify patients who are candidates for active surveillance? , 2013, Radiology.

[52]  J. Kurhanewicz,et al.  Hyperpolarized [1-13C]Dehydroascorbate MR Spectroscopy in a Murine Model of Prostate Cancer: Comparison with 18F-FDG PET , 2013, The Journal of Nuclear Medicine.

[53]  Matthias Dietzel,et al.  Breast lesions: diagnosis by using proton MR spectroscopy at 1.5 and 3.0 T--systematic review and meta-analysis. , 2013, Radiology.

[54]  D. Parente,et al.  Multiparametric magnetic resonance imaging of the prostate. , 2013, Magnetic resonance imaging clinics of North America.

[55]  D. Klomp,et al.  Ultra high spatial and temporal resolution breast imaging at 7T , 2013, NMR in biomedicine.

[56]  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.

[57]  Les Irwig,et al.  Meta-analysis of magnetic resonance imaging in detecting residual breast cancer after neoadjuvant therapy. , 2013, Journal of the National Cancer Institute.

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

[59]  H. Schlemmer,et al.  CEST-imaging: A new contrast in MR-mammography by means of chemical exchange saturation transfer. , 2012, European journal of radiology.

[60]  Peter R Luijten,et al.  Quantitative 31P magnetic resonance spectroscopy of the human breast at 7 T , 2012, Magnetic resonance in medicine.

[61]  Jie Chen,et al.  Can diffusion-weighted MR imaging and contrast-enhanced MR imaging precisely evaluate and predict pathological response to neoadjuvant chemotherapy in patients with breast cancer? , 2012, Breast Cancer Research and Treatment.

[62]  R. Ponzone,et al.  Correlations between diffusion-weighted imaging and breast cancer biomarkers , 2012, European Radiology.

[63]  T. Helbich,et al.  Molecular imaging of cancer: MR spectroscopy and beyond. , 2012, European journal of radiology.

[64]  Jia Huajie,et al.  Can diffusion-weighted MR imaging and contrast-enhanced MR imaging precisely evaluate and predict pathological response to neoadjuvant chemotherapy in patients with breast cancer? , 2012 .

[65]  S. Duffy,et al.  High resolution MRI of the breast at 3 T: which BI-RADS® descriptors are most strongly associated with the diagnosis of breast cancer? , 2012, European Radiology.

[66]  Cecilia Possanzini,et al.  31P MRSI and 1H MRS at 7 T: initial results in human breast cancer , 2011, NMR in biomedicine.

[67]  T. Helbich,et al.  Three-dimensional proton MR spectroscopic imaging at 3 T for the differentiation of benign and malignant breast lesions. , 2011, Radiology.

[68]  Z. Bhujwalla,et al.  Choline metabolism in malignant transformation , 2011, Nature Reviews Cancer.

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

[70]  Wei Huang,et al.  Discrimination of benign and malignant breast lesions by using shutter-speed dynamic contrast-enhanced MR imaging. , 2011, Radiology.

[71]  H. Schlemmer,et al.  A new contrast in MR mammography by means of chemical exchange saturation transfer (CEST) imaging at 3 Tesla: preliminary results. , 2011, RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin.

[72]  F. Gallagher,et al.  Tumor imaging using hyperpolarized 13C magnetic resonance spectroscopy , 2011, Magnetic resonance in medicine.

[73]  Thomas E Yankeelov,et al.  Magnetic resonance in the era of molecular imaging of cancer. , 2011, Magnetic resonance imaging.

[74]  Wendy B DeMartini,et al.  Improved diagnostic accuracy of breast MRI through combined apparent diffusion coefficients and dynamic contrast‐enhanced kinetics , 2011, Magnetic resonance in medicine.

[75]  D. Hanahan,et al.  Hallmarks of Cancer: The Next Generation , 2011, Cell.

[76]  N. deSouza,et al.  Functional magnetic resonance: biomarkers of response in breast cancer , 2011, Breast Cancer Research.

[77]  Sibel Kul,et al.  Contribution of diffusion-weighted imaging to dynamic contrast-enhanced MRI in the characterization of breast tumors. , 2011, AJR. American journal of roentgenology.

[78]  Ronald Ouwerkerk,et al.  Sodium MRI. , 2011, Methods in molecular biology.

[79]  D. Collins,et al.  Primary human breast adenocarcinoma: imaging and histologic correlates of intrinsic susceptibility-weighted MR imaging before and during chemotherapy. , 2010, Radiology.

[80]  D. Bluemke,et al.  Multiparametric magnetic resonance imaging, spectroscopy and multinuclear (²³Na) imaging monitoring of preoperative chemotherapy for locally advanced breast cancer. , 2010, Academic radiology.

[81]  Woo Kyung Moon,et al.  Diffusion-weighted MR imaging: pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer. , 2010, Radiology.

[82]  Thomas E. Yankeelov,et al.  Current and Future Trends in Magnetic Resonance Imaging Assessments of the Response of Breast Tumors to Neoadjuvant Chemotherapy , 2010, Journal of oncology.

[83]  Bruce Daniel,et al.  Detecting blood oxygen level‐dependent (BOLD) contrast in the breast , 2010, Journal of magnetic resonance imaging : JMRI.

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

[85]  Savannah C Partridge,et al.  Diffusion tensor magnetic resonance imaging of the normal breast. , 2010, Magnetic resonance imaging.

[86]  Wendy B DeMartini,et al.  Diffusion tensor MRI: Preliminary anisotropy measures and mapping of breast tumors , 2010, Journal of magnetic resonance imaging : JMRI.

[87]  David A. Bluemke,et al.  Diffusion-weighted Imaging Improves the Diagnostic Accuracy of Conventional 3.0-T , 2010 .

[88]  Matthias Dietzel,et al.  Diffusion tensor magnetic resonance imaging of the breast: a pilot study , 2010, European Radiology.

[89]  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.

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

[91]  Wilma van der Riet,et al.  Diffusion-weighted MR imaging with background body signal suppression (DWIBS) for the diagnosis of malignant and benign breast lesions , 2009, European Radiology.

[92]  Hiroshi Honda,et al.  Enhanced mass on contrast‐enhanced breast MR imaging: Lesion characterization using combination of dynamic contrast‐enhanced and diffusion‐weighted MR images , 2008, Journal of magnetic resonance imaging : JMRI.

[93]  John V Frangioni,et al.  New technologies for human cancer imaging. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[94]  Peter Vaupel,et al.  Hypoxia and aggressive tumor phenotype: implications for therapy and prognosis. , 2008, The oncologist.

[95]  Daniel B. Vigneron,et al.  Current and Potential Applications of Clinical 13C MR Spectroscopy , 2008, Journal of Nuclear Medicine.

[96]  Evelyn Wenkel,et al.  Diffusion weighted imaging in breast MRI: comparison of two different pulse sequences. , 2007, Academic radiology.

[97]  C. Kuhl The current status of breast MR imaging. Part I. Choice of technique, image interpretation, diagnostic accuracy, and transfer to clinical practice. , 2007, Radiology.

[98]  Thomas E Yankeelov,et al.  Integration of quantitative DCE-MRI and ADC mapping to monitor treatment response in human breast cancer: initial results. , 2007, Magnetic resonance imaging.

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

[100]  R. Brasch,et al.  Magnetic resonance characterization of tumor microvessels in experimental breast tumors using a slow clearance blood pool contrast agent (carboxymethyldextran-A2-Gd-DOTA) with histopathological correlation , 2005, European Radiology.

[101]  J. Helpern,et al.  Diffusional kurtosis imaging: The quantification of non‐gaussian water diffusion by means of magnetic resonance imaging , 2005, Magnetic resonance in medicine.

[102]  D. Yee,et al.  Neoadjuvant chemotherapy of locally advanced breast cancer: predicting response with in vivo (1)H MR spectroscopy--a pilot study at 4 T. , 2004, Radiology.

[103]  Ning-Yu An,et al.  Differentiation of clinically benign and malignant breast lesions using diffusion‐weighted imaging , 2002, Journal of magnetic resonance imaging : JMRI.

[104]  D. Le Bihan,et al.  Diffusion tensor imaging: Concepts and applications , 2001, Journal of magnetic resonance imaging : JMRI.

[105]  T. Helbich,et al.  Quantitative gadopentetate‐enhanced MRI of breast tumors: Testing of different analytic methods , 2000, Magnetic resonance in medicine.

[106]  F. Podo Tumour phospholipid metabolism , 1999, NMR in biomedicine.

[107]  P Vaupel,et al.  Association between tumor hypoxia and malignant progression in advanced cancer of the uterine cervix. , 1996, Cancer research.

[108]  J. Folkman Clinical Applications of Research on Angiogenesis , 1995 .

[109]  P S Tofts,et al.  Quantitative Analysis of Dynamic Gd‐DTPA Enhancement in Breast Tumors Using a Permeability Model , 1995, Magnetic resonance in medicine.

[110]  J. Folkman Seminars in Medicine of the Beth Israel Hospital, Boston. Clinical applications of research on angiogenesis. , 1995, The New England journal of medicine.

[111]  Sh. Heywang Kobrunner Contrast-enhanced magnetic resonance imaging of the breast , 1994 .

[112]  O. Linton [The American College of Radiology]. , 1992, Journal de radiologie.

[113]  P. Tofts,et al.  Measurement of the blood‐brain barrier permeability and leakage space using dynamic MR imaging. 1. Fundamental concepts , 1991, Magnetic resonance in medicine.