Literature DB >> 27501902

Quantitative apparent diffusion coefficient measurement obtained by 3.0Tesla MRI as a potential noninvasive marker of tumor aggressiveness in breast cancer.

Manuela Durando1, Lucas Gennaro2, Gene Y Cho3, Dilip D Giri4, Merlin M Gnanasigamani5, Sujata Patil6, Elizabeth J Sutton7, Joseph O Deasy8, Elizabeth A Morris9, Sunitha B Thakur10.   

Abstract

PURPOSE: To assess the association between apparent diffusion coefficient (ADC), and histological prognostic parameters in malignant breast lesions. The ability of ADC to identify lesions with the presence of Lymphovascular invasion (LVI) in breast carcinoma was also examined.
MATERIALS AND METHODS: This HIPAA-compliant retrospective study consisted of 212 consecutive patients with known cancers who underwent 3.0T MRI between January 2011 and 2013. In this study, a total of 126 malignant lesions in 114 women, who had undergone DWI (b-values of 0 and 1000s/mm(2)) in addition to diagnostic MRI, were included. Patients with less than 0.8cm lesions, or those who underwent neoadjuvant chemotherapy or suboptimal DW images were excluded. Classical prognostic factors [lesion size, histopathological type and grade, lymph node (LN) status and lymphovascular invasion (LVI)], molecular prognostic markers [estrogen receptor (ER), progesterone receptor (PR) and human epidermal grow factor receptor 2 (HER2)] were reviewed and recorded. A region of interest (ROI) was drawn within the lesions to measure ADC values. Statistical analyses were performed by the Wilcoxon rank sum test (statistical significance at P<0.05). Adjusted p values from multiple comparison analysis were also calculated.
RESULTS: This study demonstrates an inverse correlation between ADC and LVI in malignant lesions and the ability of ADC to identify aggressiveness in lesions with positive LVI. Tumor size, grade, ER, PR, HER2 and lymph node status did not impact tumor ADC value. However, tumors with LVI showed significantly lower ADC values when compared to tumors without LVI, regardless of the enhancement type, histological grade, histological type, and LN status.
CONCLUSION: Our study shows that ADC could be a potential clinical adjunct in the evaluation of prognostic factors related to malignant lesion aggressiveness such as LVI.
Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Breast cancer; DW-MRI at 3.0T; Lymph nodes; Lymphovascular invasion; Prognostic factors

Mesh:

Substances:

Year:  2016        PMID: 27501902      PMCID: PMC5505563          DOI: 10.1016/j.ejrad.2016.06.019

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  32 in total

1.  Diffusion-weighted imaging in breast cancer: relationship between apparent diffusion coefficient and tumour aggressiveness.

Authors:  M Costantini; P Belli; P Rinaldi; E Bufi; G Giardina; G Franceschini; G Petrone; L Bonomo
Journal:  Clin Radiol       Date:  2010-09-24       Impact factor: 2.350

2.  Prognostic value of lymphovascular invasion in women with lymph node negative invasive breast carcinoma.

Authors:  A H S Lee; S E Pinder; R D Macmillan; M Mitchell; I O Ellis; C W Elston; R W Blamey
Journal:  Eur J Cancer       Date:  2005-12-27       Impact factor: 9.162

3.  Apparent diffusion coefficient values for discriminating benign and malignant breast MRI lesions: effects of lesion type and size.

Authors:  Savannah C Partridge; Christiane D Mullins; Brenda F Kurland; Michael D Allain; Wendy B DeMartini; Peter R Eby; Constance D Lehman
Journal:  AJR Am J Roentgenol       Date:  2010-06       Impact factor: 3.959

4.  Diffusion-weighted imaging improves the diagnostic accuracy of conventional 3.0-T breast MR imaging.

Authors:  Riham H Ei Khouli; Michael A Jacobs; Sarah D Mezban; Peng Huang; Ihab R Kamel; Katarzyna J Macura; David A Bluemke
Journal:  Radiology       Date:  2010-07       Impact factor: 11.105

Review 5.  Diffusion-weighted imaging in cancer: physical foundations and applications of restriction spectrum imaging.

Authors:  Nathan S White; Carrie McDonald; Carrie R McDonald; Niky Farid; Josh Kuperman; David Karow; Natalie M Schenker-Ahmed; Hauke Bartsch; Rebecca Rakow-Penner; Dominic Holland; Ahmed Shabaik; Atle Bjørnerud; Tuva Hope; Jona Hattangadi-Gluth; Michael Liss; J Kellogg Parsons; Clark C Chen; Steve Raman; Daniel Margolis; Robert E Reiter; Leonard Marks; Santosh Kesari; Arno J Mundt; Christopher J Kane; Christopher J Kaine; Bob S Carter; William G Bradley; Anders M Dale
Journal:  Cancer Res       Date:  2014-09-01       Impact factor: 12.701

6.  Quantitative apparent diffusion coefficient as a noninvasive imaging biomarker for the differentiation of invasive breast cancer and ductal carcinoma in situ.

Authors:  Hubert Bickel; Katja Pinker-Domenig; Wolfgang Bogner; Claudio Spick; Zsuzsanna Bagó-Horváth; Michael Weber; Thomas Helbich; Pascal Baltzer
Journal:  Invest Radiol       Date:  2015-02       Impact factor: 6.016

7.  Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer.

Authors:  Naoko Mori; Shunji Mugikura; Chiaki Takasawa; Minoru Miyashita; Akiko Shimauchi; Hideki Ota; Takanori Ishida; Atsuko kasajima; Kei Takase; Tetsuya Kodama; Shoki Takahashi
Journal:  Eur Radiol       Date:  2015-05-30       Impact factor: 5.315

8.  Apparent Diffusion Coefficient in Invasive Ductal Breast Carcinoma: Correlation with Detailed Histologic Features and the Enhancement Ratio on Dynamic Contrast-Enhanced MR Images.

Authors:  Roka Namoto Matsubayashi; Teruhiko Fujii; Kotaro Yasumori; Toru Muranaka; Seiya Momosaki
Journal:  J Oncol       Date:  2010-09-02       Impact factor: 4.375

9.  Prognostic value of lymphangiogenesis and lymphovascular invasion in invasive breast cancer.

Authors:  Sebastian F Schoppmann; Guenther Bayer; Klaus Aumayr; Susanne Taucher; Silvana Geleff; Margaretha Rudas; Ernst Kubista; Hubert Hausmaninger; Hellmut Samonigg; Michael Gnant; Raimund Jakesz; Reinhard Horvat
Journal:  Ann Surg       Date:  2004-08       Impact factor: 12.969

10.  Diffusion-weighted imaging of breast cancer: correlation of the apparent diffusion coefficient value with prognostic factors.

Authors:  Sung Hun Kim; Eun Suk Cha; Hyeon Sook Kim; Bong Joo Kang; Jae Jeong Choi; Ji Han Jung; Yong Gyu Park; Young Jin Suh
Journal:  J Magn Reson Imaging       Date:  2009-09       Impact factor: 4.813

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  17 in total

1.  Correlation between minimum apparent diffusion coefficient values and the histological grade of breast invasive ductal carcinoma.

Authors:  Suhong Zhao; Weihua Guo; Ru Tan; Peipei Chen; Zhaohua Li; Fengguo Sun; Guangrui Shao
Journal:  Oncol Lett       Date:  2018-03-23       Impact factor: 2.967

2.  Is there any relationship between adc values of diffusion-weighted imaging and the histopathological prognostic factors of invasive ductal carcinoma?

Authors:  Hale Aydin; Bahar Guner; Isil Esen Bostanci; Zarife Melda Bulut; Bilgin Kadri Aribas; Lutfi Dogan; Mehmet Ali Gulcelik
Journal:  Br J Radiol       Date:  2018-01-12       Impact factor: 3.039

Review 3.  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

4.  Is the necrosis/wall ADC ratio useful for the differentiation of benign and malignant breast lesions?

Authors:  Irmak Durur-Subasi; Afak Durur-Karakaya; Adem Karaman; Mehmet Seker; Elif Demirci; Fatih Alper
Journal:  Br J Radiol       Date:  2017-03-24       Impact factor: 3.039

5.  Apparent diffusion coefficient in estrogen receptor-positive and lymph node-negative invasive breast cancers at 3.0T DW-MRI: A potential predictor for an oncotype Dx test recurrence score.

Authors:  Sunitha B Thakur; Manuela Durando; Soledad Milans; Gene Y Cho; Lucas Gennaro; Elizabeth J Sutton; Dilip Giri; Elizabeth A Morris
Journal:  J Magn Reson Imaging       Date:  2017-06-22       Impact factor: 4.813

6.  Diffusion-Weighted Imaging of Different Breast Cancer Molecular Subtypes: A Systematic Review and Meta-Analysis.

Authors:  Hans-Jonas Meyer; Andreas Wienke; Alexey Surov
Journal:  Breast Care (Basel)       Date:  2021-02-23       Impact factor: 2.860

7.  Predictive Models in Differentiating Vertebral Lesions Using Multiparametric MRI.

Authors:  R Rathore; A Parihar; D K Dwivedi; A K Dwivedi; N Kohli; R K Garg; A Chandra
Journal:  AJNR Am J Neuroradiol       Date:  2017-10-12       Impact factor: 3.825

8.  Added value of histogram analysis of apparent diffusion coefficient maps for differentiating triple-negative breast cancer from other subtypes of breast cancer on standard MRI.

Authors:  Hong-Li Liu; Min Zong; Han Wei; Cong Wang; Jian-Juan Lou; Si-Qi Wang; Qi-Gui Zou; Yan-Ni Jiang
Journal:  Cancer Manag Res       Date:  2019-09-06       Impact factor: 3.989

9.  Can apparent diffusion coefficient (ADC) distinguish breast cancer from benign breast findings? A meta-analysis based on 13 847 lesions.

Authors:  Alexey Surov; Hans Jonas Meyer; Andreas Wienke
Journal:  BMC Cancer       Date:  2019-10-15       Impact factor: 4.430

10.  Sequential [18F]FDG-[18F]FMISO PET and Multiparametric MRI at 3T for Insights into Breast Cancer Heterogeneity and Correlation with Patient Outcomes: First Clinical Experience.

Authors:  Piotr Andrzejewski; Georg Wengert; Thomas H Helbich; Heinrich Magometschnigg; Dietmar Georg; Marcus Hacker; Pascal Baltzer; Paola Clauser; Panagiotis Kapetas; Petra Georg; Wolfgang Wadsak; Katja Pinker
Journal:  Contrast Media Mol Imaging       Date:  2019-01-08       Impact factor: 3.161

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