Maximum intensity breast diffusion MRI for BI-RADS 4 lesions detected on X-ray mammography.

AIM To investigate an abbreviated, contrast-agent free diffusion-weighted (DW) breast magnetic resonance imaging (MRI) protocol that provides a single image for the radiologist to read in order to non-invasively examine Breast Imaging-Reporting and Data System (BI-RADS) 4 lesions detected using breast cancer screening X-ray mammography. MATERIALS AND METHODS This retrospective evaluation within a institutional review board-approved, prospective study included 115 women (mean 57 years, range 50-69 years) with BI-RADS 4 findings on X-ray mammography and indication for biopsy over a period of 15 months. Full diagnostic breast MRI (FDP) was performed prior to biopsy (1.5 T). Maximum intensity breast diffusion (MIBD) images were generated from DW images (b = 1,500 mm/s2, 3 mm section thickness) of the breast. MIBD and T2-weighted (T2W) images were read by two radiologists and compared to the diagnostic accuracy of an expert reading of the FDP with histopathology as the reference standard. The acquisition time of MIBD and T2W MRI was about 7 minutes. RESULTS MIBD MRI provided a diagnostic accuracy of 87.93% (95% confidence interval [CI]: 80.58-93.24%) for R1 and 89.66% (95% CI: 82.63-94.54%) for R2. Expert reading of the FDP revealed a similar accuracy of 86.2% (95% CI: 78.67-91.43%). The positive predictive value (PPV) could be increased from 36.2% (95% CI: 28.02-45.28; X-ray mammography alone) to a mean PPV of 80.89% (R1 79.17%, R2 82.16%) using MIBD MRI. Mean reading time was 30 seconds (25%/75 percentile 24.5-41.25). CONCLUSIONS MIBD MRI might be of supplemental value if added to the work-up of BI-RADS 4 X-ray mammography screening findings. MIBD MRI might help reduce the false-positive rate prior to biopsy for reference lesions at only limited expense of measurement and reading time.

[1]  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.

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

[3]  David F Kallmes,et al.  Intracranial Gadolinium Deposition after Contrast-enhanced MR Imaging. , 2015, Radiology.

[4]  Eveline A M Heijnsdijk,et al.  Nation-wide data on screening performance during the transition to digital mammography: observations in 6 million screens. , 2013, European journal of cancer.

[5]  N Houssami,et al.  Application of breast tomosynthesis in screening: incremental effect on mammography acquisition and reading time. , 2012, The British journal of radiology.

[6]  K. Straif,et al.  Breast-cancer screening--viewpoint of the IARC Working Group. , 2015, The New England journal of medicine.

[7]  T. Kuder,et al.  Applicability and discriminative value of a semiautomatic three-dimensional spherical volume for the assessment of the apparent diffusion coefficient in suspicious breast lesions-feasibility study. , 2016, Clinical imaging.

[8]  Pascal J. Kieslich,et al.  Gadolinium retention in the dentate nucleus and globus pallidus is dependent on the class of contrast agent. , 2015, Radiology.

[9]  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.

[10]  T. Takahara,et al.  Diffusion weighted whole body imaging with background body signal suppression (DWIBS): technical improvement using free breathing, STIR and high resolution 3D display. , 2004, Radiation medicine.

[11]  C. Kuhl,et al.  Assessment of BI-RADS category 4 lesions detected with screening mammography and screening US: utility of MR imaging. , 2015, Radiology.

[12]  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.

[13]  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.

[14]  C. Kuhl MR imaging for surveillance of women at high familial risk for breast cancer. , 2006, Magnetic resonance imaging clinics of North America.

[15]  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.

[16]  Daisuke Takenaka,et al.  High signal intensity in the dentate nucleus and globus pallidus on unenhanced T1-weighted MR images: relationship with increasing cumulative dose of a gadolinium-based contrast material. , 2014, Radiology.

[17]  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.

[18]  S. Kul,et al.  Can unenhanced breast MRI be used to decrease negative biopsy rates? , 2015, Diagnostic and interventional radiology.

[19]  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.

[20]  Ralf-Dieter Hilgers,et al.  Abbreviated breast magnetic resonance imaging (MRI): first postcontrast subtracted images and maximum-intensity projection-a novel approach to breast cancer screening with MRI. , 2014, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[21]  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.

[22]  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.

[23]  Vincenzo Di Lazzaro,et al.  Progressive Increase of T1 Signal Intensity of the Dentate Nucleus on Unenhanced Magnetic Resonance Images Is Associated With Cumulative Doses of Intravenously Administered Gadodiamide in Patients With Normal Renal Function, Suggesting Dechelation , 2014, Investigative radiology.

[24]  Michael Götz,et al.  Prediction of malignancy by a radiomic signature from contrast agent‐free diffusion MRI in suspicious breast lesions found on screening mammography. , 2017, Journal of magnetic resonance imaging : JMRI.

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

[26]  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.

[27]  Jacqueline R. Halladay,et al.  Positive predictive value of mammography: comparison of interpretations of screening and diagnostic images by the same radiologist and by different radiologists. , 2010, AJR. American journal of roentgenology.