Literature DB >> 19703869

Diffusion-weighted MR for differentiation of breast lesions at 3.0 T: how does selection of diffusion protocols affect diagnosis?

Wolfgang Bogner1, Stephan Gruber, Katja Pinker, Günther Grabner, Andreas Stadlbauer, Michael Weber, Ewald Moser, Thomas H Helbich, Siegfried Trattnig.   

Abstract

PURPOSE: To compare the diagnostic quality of diffusion-weighted (DW) imaging schemes with regard to apparent diffusion coefficient (ADC) accuracy, ADC precision, and DW imaging contrast-to-noise ratio (CNR) for different types of lesions and breast tissue.
MATERIALS AND METHODS: Institutional review board approval and written, informed consent were obtained. Fifty-one patients with histopathologic correlation or follow-up performed with a 3.0-T MR imager were included in this study. There were 112 regions of interest drawn in 24 malignant, 17 benign, 20 cystic, and 51 normal tissue regions. ADC maps were calculated for combinations of 10 b values (range, 0-1250 sec/mm(2)). Differences in ADC among tissue types were evaluated. The CNRs of lesions at DW imaging were compared for all b values. A repeated-measures analysis of variance was used to assess lesion differentiation.
RESULTS: ADCs calculated from b values of 50 and 850 sec/mm(2) were 0.99 x 10(-3) mm(2)/sec +/- 0.18 (standard deviation), 1.47 x 10(-3) mm(2)/sec +/- 0.21, 1.85 x 10(-3) mm(2)/sec +/- 0.22, and 2.64 x 10(-3) mm(2)/sec +/- 0.30 for malignant, benign, normal, and cystic tissues, respectively. An ADC threshold level of 1.25 x 10(-3) mm(2)/sec allowed discrimination between malignant and benign lesions with a diagnostic accuracy of 95% (P < .001). ADC calculations performed with multiple b values were not significantly more precise than those performed with only two. We found an overestimation of ADC for maximum b values of up to 1000 sec/mm(2). The best CNR for tumors was identified at 850 sec/mm(2).
CONCLUSION: Optimum ADC determination and DW imaging quality at 3.0 T was found with a combined b value protocol of 50 and 850 sec/mm(2). This provided a high accuracy for differentiation of benign and malignant breast tumors. (c) RSNA, 2009.

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Year:  2009        PMID: 19703869     DOI: 10.1148/radiol.2532081718

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  96 in total

Review 1.  Triple-negative breast cancer: present challenges and new perspectives.

Authors:  Franca Podo; Lutgarde M C Buydens; Hadassa Degani; Riet Hilhorst; Edda Klipp; Ingrid S Gribbestad; Sabine Van Huffel; Hanneke W M van Laarhoven; Jan Luts; Daniel Monleon; Geert J Postma; Nicole Schneiderhan-Marra; Filippo Santoro; Hans Wouters; Hege G Russnes; Therese Sørlie; Elda Tagliabue; Anne-Lise Børresen-Dale
Journal:  Mol Oncol       Date:  2010-04-24       Impact factor: 6.603

2.  [Functional and molecular imaging of breast tumors].

Authors:  K Pinker; P Brader; G Karanikas; K El-Rabadi; W Bogner; S Gruber; M Reisegger; S Trattnig; T H Helbich
Journal:  Radiologe       Date:  2010-11       Impact factor: 0.635

3.  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

4.  Intravoxel incoherent motion imaging of tumor microenvironment in locally advanced breast cancer.

Authors:  E E Sigmund; G Y Cho; S Kim; M Finn; M Moccaldi; J H Jensen; D K Sodickson; J D Goldberg; S Formenti; L Moy
Journal:  Magn Reson Med       Date:  2011-02-01       Impact factor: 4.668

5.  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.

Authors:  Katja Pinker; Linda Moy; Elizabeth J Sutton; Ritse M Mann; Michael Weber; Sunitha B Thakur; Maxine S Jochelson; Zsuzsanna Bago-Horvath; Elizabeth A Morris; Pascal At Baltzer; Thomas H Helbich
Journal:  Invest Radiol       Date:  2018-10       Impact factor: 6.016

6.  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

7.  [Therapy monitoring of neoadjuvant therapy with MRI. RECIST and functional imaging].

Authors:  S Grandl; M Ingrisch; K Hellerhoff
Journal:  Radiologe       Date:  2014-03       Impact factor: 0.635

8.  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

9.  High-resolution diffusion-weighted imaging for the separation of benign from malignant BI-RADS 4/5 lesions found on breast MRI at 3T.

Authors:  Dorota J Wisner; Nathan Rogers; Vibhas S Deshpande; David N Newitt; Gerhard A Laub; David A Porter; John Kornak; Bonnie N Joe; Nola M Hylton
Journal:  J Magn Reson Imaging       Date:  2013-11-08       Impact factor: 4.813

Review 10.  Diffusion-weighted breast MRI: Clinical applications and emerging techniques.

Authors:  Savannah C Partridge; Noam Nissan; Habib Rahbar; Averi E Kitsch; Eric E Sigmund
Journal:  J Magn Reson Imaging       Date:  2016-09-30       Impact factor: 4.813

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