Literature DB >> 24706105

MRI-only lesions: application of diffusion-weighted imaging obviates unnecessary MR-guided breast biopsies.

Claudio Spick1, Katja Pinker-Domenig, Margaretha Rudas, Thomas H Helbich, Pascal A Baltzer.   

Abstract

OBJECTIVE: To assess if the application of diffusion-weighted imaging (DWI) obviates unnecessary MR-guided biopsies in suspicious breast lesions visible only on contrast-enhanced MRI (CE-MRI).
METHODS: This institutional review board (IRB)-approved, retrospective, single-centre study included 101 patients (mean age, 49.5; SD 13.9 years) who underwent additional DWI at 1.5 T prior to MRI-guided biopsy of 104 lesions classified as suspicious for malignancy and visible on CE-MRI only. An experienced radiologist, blinded to histopathologic and follow-up results, measured apparent diffusion coefficient (ADC) values obtained from DWI. Diagnostic accuracy was investigated using receiver operating characteristics (ROC) analysis.
RESULTS: Histopathology revealed 20 malignant and 84 benign lesions. Lesions were masses in 61 (15 malignant, 24.6 %) and non-masses in 43 cases (five malignant, 11.6 %). Mean ADC values were 1.53 ± 0.38 × 10(-3) mm(2)/s in benign lesions and 1.06 ± 0.27 × 10(-3) mm(2)/s in malignant lesions. ROC analysis revealed exclusively benign lesions if ADC values were greater than 1.58 × 10(-3) mm(2)/s. As a consequence, 29 false-positive biopsies (34.5 %) could have been avoided without any false-negative findings. Both in mass and in non-mass lesions, rule-in and rule-out criteria were identified using flexible ADC thresholds based on ROC analysis.
CONCLUSION: Additional application of DWI in breast lesions visible only on MRI can avoid false-positive, MR-guided biopsies. Thus, DWI should be an integral part of breast MRI protocols. KEY POINTS: DWI measurements are a fast and helpful technique for improved breast lesion diagnosis. DWI application in breast lesions visible only on MRI obviates false-positive, MR-guided biopsies. Flexible ADC thresholds provide rule-in and rule-out criteria for breast lesion malignancy.

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Year:  2014        PMID: 24706105     DOI: 10.1007/s00330-014-3153-6

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  32 in total

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Authors:  Shantanu Sinha; Flora Anne Lucas-Quesada; Usha Sinha; Nanette DeBruhl; Lawrence W Bassett
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2.  Contribution of diffusion-weighted imaging to dynamic contrast-enhanced MRI in the characterization of breast tumors.

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3.  Quantitative diffusion imaging in breast cancer: a clinical prospective study.

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4.  1H MR spectroscopy and diffusion-weighted imaging of the breast: are they useful tools for characterizing breast lesions before biopsy?

Authors:  Mitsuhiro Tozaki; Eisuke Fukuma
Journal:  AJR Am J Roentgenol       Date:  2009-09       Impact factor: 3.959

5.  Quantitative diffusion-weighted imaging as an adjunct to conventional breast MRI for improved positive predictive value.

Authors:  Savannah C Partridge; Wendy B DeMartini; Brenda F Kurland; Peter R Eby; Steven W White; Constance D Lehman
Journal:  AJR Am J Roentgenol       Date:  2009-12       Impact factor: 3.959

Review 6.  Diffusion-weighted magnetic resonance imaging and its application to cancer.

Authors:  Elizabeth M Charles-Edwards; Nandita M deSouza
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7.  Readout-segmented echo-planar imaging improves the diagnostic performance of diffusion-weighted MR breast examinations at 3.0 T.

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Review 9.  Systematic review: using magnetic resonance imaging to screen women at high risk for breast cancer.

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10.  Quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesion.

Authors:  C Marini; C Iacconi; M Giannelli; A Cilotti; M Moretti; C Bartolozzi
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  35 in total

1.  Diffusion-weighted imaging of breast tumours at 3 Tesla and 7 Tesla: a comparison.

Authors:  S Gruber; L Minarikova; K Pinker; O Zaric; M Chmelik; B Strasser; P Baltzer; T Helbich; S Trattnig; W Bogner
Journal:  Eur Radiol       Date:  2015-08-27       Impact factor: 5.315

2.  Evaluation of Kinetic Entropy of Breast Masses Initially Found on MRI using Whole-lesion Curve Distribution Data: Comparison with the Standard Kinetic Analysis.

Authors:  Akiko Shimauchi; Hiroyuki Abe; David V Schacht; Jian Yulei; Federico D Pineda; Sanaz A Jansen; Rajiv Ganesh; Gillian M Newstead
Journal:  Eur Radiol       Date:  2015-02-20       Impact factor: 5.315

3.  [Researcher of the month].

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4.  Incidentally detected enhancing lesions found in breast MRI: analysis of apparent diffusion coefficient and T2 signal intensity significantly improves specificity.

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5.  Monitoring In-Vivo the Mammary Gland Microstructure during Morphogenesis from Lactation to Post-Weaning Using Diffusion Tensor MRI.

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Review 6.  Clinical role of breast MRI now and going forward.

Authors:  D Leithner; G J Wengert; T H Helbich; S Thakur; R E Ochoa-Albiztegui; E A Morris; K Pinker
Journal:  Clin Radiol       Date:  2017-12-09       Impact factor: 2.350

7.  Additional value of diffusion-weighted imaging to evaluate multifocal and multicentric breast cancer detected using pre-operative breast MRI.

Authors:  Sung Eun Song; Eun Kyung Park; Kyu Ran Cho; Bo Kyoung Seo; Ok Hee Woo; Seung Pil Jung; Sung Bum Cho
Journal:  Eur Radiol       Date:  2017-06-07       Impact factor: 5.315

8.  Combined reading of Contrast Enhanced and Diffusion Weighted Magnetic Resonance Imaging by using a simple sum score.

Authors:  Anja Baltzer; Matthias Dietzel; Clemens G Kaiser; Pascal A Baltzer
Journal:  Eur Radiol       Date:  2015-06-27       Impact factor: 5.315

9.  Diffusion-weighted imaging of breast lesions: Region-of-interest placement and different ADC parameters influence apparent diffusion coefficient values.

Authors:  Hubert Bickel; Katja Pinker; Stephan Polanec; Heinrich Magometschnigg; Georg Wengert; Claudio Spick; Wolfgang Bogner; Zsuzsanna Bago-Horvath; Thomas H Helbich; Pascal Baltzer
Journal:  Eur Radiol       Date:  2016-08-30       Impact factor: 5.315

10.  Utility of Diffusion-weighted Imaging to Decrease Unnecessary Biopsies Prompted by Breast MRI: A Trial of the ECOG-ACRIN Cancer Research Group (A6702).

Authors:  Habib Rahbar; Zheng Zhang; Thomas L Chenevert; Justin Romanoff; Averi E Kitsch; Lucy G Hanna; Sara M Harvey; Linda Moy; Wendy B DeMartini; Basak Dogan; Wei T Yang; Lilian C Wang; Bonnie N Joe; Karen Y Oh; Colleen H Neal; Elizabeth S McDonald; Mitchell D Schnall; Constance D Lehman; Christopher E Comstock; Savannah C Partridge
Journal:  Clin Cancer Res       Date:  2019-01-15       Impact factor: 12.531

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