Literature DB >> 21633054

Apparent diffusion coefficient as an MR imaging biomarker of low-risk ductal carcinoma in situ: a pilot study.

Mami Iima1, Denis Le Bihan, Ryosuke Okumura, Tomohisa Okada, Koji Fujimoto, Shotaro Kanao, Shiro Tanaka, Masakazu Fujimoto, Hiromi Sakashita, Kaori Togashi.   

Abstract

PURPOSE: To evaluate the potential of apparent diffusion coefficients (ADCs) obtained at quantitative diffusion-weighted magnetic resonance (MR) imaging of the breast as a biomarker of low-grade ductal carcinoma in situ (DCIS).
MATERIALS AND METHODS: This retrospective study was approved by an institutional review board, and the requirement to obtain informed consent was waived. Twenty-two women (age range, 36-75 years; mean age, 56.4 years) with pure DCIS (seven with low-grade DCIS, five with intermediate-grade DCIS, and seven with high-grade DCIS) and three with microinvasion underwent breast MR imaging at 1.5 T between January 2008 and November 2010. MR examinations included contrast material-enhanced (gadoteridol) T1-weighted imaging and diffusion-weighted MR imaging with b values of 0 and 1000 sec/mm(2). ADC maps were generated. The distributions of the ADCs in regions of interest covering the lesions were compared among the three grades by using linear mixed-model analysis, and the discriminatory power of the lesion minimum ADC was determined with receiver operating characteristic analysis.
RESULTS: The mean ADC was 1.42 × 10(-3) mm(2)/sec (95% confidence interval [CI]: 1.31 × 10(-3) mm(2)/sec, 1.54 × 10(-3) mm(2)/sec) for low-grade DCIS, 1.23 × 10(-3) mm(2)/sec (95% CI: 1.10 × 10(-3) mm(2)/sec, 1.36 × 10(-3) mm(2)/sec) for intermediate-grade DCIS, 1.19 × 10(-3) mm(2)/sec (95% CI: 1.08 × 10(-3) mm(2)/sec, 1.30 × 10(-3) mm(2)/sec) for high-grade DCIS, and 2.06 × 10(-3) mm(2)/sec (95% CI: 1.94 × 10(-3) mm(2)/sec, 2.18 × 10(-3) mm(2)/sec) for normal breast tissue. The mean ADCs for high- and intermediate-grade DCIS were significantly lower than that for low-grade DCIS (P < .01 and P = .03, respectively), and the mean ADC for low-grade DCIS was significantly lower than that for normal tissue (P < .001). The lesion minimum ADC for low-grade DCIS was also significantly higher than that for high- and intermediate-grade DCIS (P < .01). A threshold of 1.30 × 10(-3) mm(2)/sec for the minimum ADC in the diagnosis of low-grade DCIS had a specificity of 100% (12 of 12 patients; 95% CI: 73.5%, 100%) and a positive predictive value of 100% (four of four patients; 95% CI: 39.8%, 100%).
CONCLUSION: These preliminary results suggest that quantitative diffusion-weighted MR imaging could be used to identify patients with low-grade DCIS with very high specificity. If the results of this study are confirmed, this approach could potentially spare those patients from invasive approaches such as mastectomy or axillary lymph node excision. © RSNA, 2011.

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Year:  2011        PMID: 21633054     DOI: 10.1148/radiol.11101892

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


  32 in total

1.  Diagnostic performance of ADCs in different ROIs for breast lesions.

Authors:  Wei Zhang; Guan-Qiao Jin; Jun-Jie Liu; Dan-Ke Su; Ning-Bin Luo; Dong Xie; Shao-Lv Lai; Xiang-Yang Huang; Wei-Li Huang
Journal:  Int J Clin Exp Med       Date:  2015-08-15

2.  Detection of invasive components in cases of breast ductal carcinoma in situ on biopsy by using apparent diffusion coefficient MR parameters.

Authors:  Naoko Mori; Hideki Ota; Shunji Mugikura; Chiaki Takasawa; Junya Tominaga; Takanori Ishida; Mika Watanabe; Kei Takase; Shoki Takahashi
Journal:  Eur Radiol       Date:  2013-06-04       Impact factor: 5.315

3.  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

4.  Fat suppression techniques (STIR vs. SPAIR) on diffusion-weighted imaging of breast lesions at 3.0 T: preliminary experience.

Authors:  Sofia Brandão; Luísa Nogueira; Eduarda Matos; Rita Gouveia Nunes; Hugo Alexandre Ferreira; Joana Loureiro; Isabel Ramos
Journal:  Radiol Med       Date:  2015-02-10       Impact factor: 3.469

5.  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.

Authors:  K Pinker; H Bickel; T H Helbich; S Gruber; P Dubsky; U Pluschnig; M Rudas; Z Bago-Horvath; M Weber; S Trattnig; W Bogner
Journal:  Eur Radiol       Date:  2013-03-16       Impact factor: 5.315

6.  Investigation of the diffusion abnormality index as a new imaging biomarker for early assessment of brain tumor response to radiation therapy.

Authors:  Reza Farjam; Christina I Tsien; Felix Y Feng; Diana Gomez-Hassan; James A Hayman; Theodore S Lawrence; Yue Cao
Journal:  Neuro Oncol       Date:  2013-12-09       Impact factor: 12.300

7.  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

8.  Risk stratification of ductal carcinoma in situ using whole-lesion histogram analysis of the apparent diffusion coefficient.

Authors:  Jin You Kim; Jin Joo Kim; Ji Won Lee; Nam Kyung Lee; Geewon Lee; Taewoo Kang; Heesung Park; Yo Han Son; Robert Grimm
Journal:  Eur Radiol       Date:  2018-08-02       Impact factor: 5.315

Review 9.  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

10.  Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors.

Authors:  Gene Young Cho; Linda Moy; Sungheon G Kim; Steven H Baete; Melanie Moccaldi; James S Babb; Daniel K Sodickson; Eric E Sigmund
Journal:  Eur Radiol       Date:  2015-11-28       Impact factor: 5.315

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