Literature DB >> 29330631

Apparent diffusion coefficient mapping using diffusion-weighted MRI: impact of background parenchymal enhancement, amount of fibroglandular tissue and menopausal status on breast cancer diagnosis.

Joao V Horvat1, Manuela Durando1,2, Soledad Milans1,3, Sujata Patil4, Jessica Massler1,5, Girard Gibbons1, Dilip Giri6, Katja Pinker1,7, Elizabeth A Morris1, Sunitha B Thakur8,9.   

Abstract

OBJECTIVES: To investigate the impact of background parenchymal enhancement (BPE), amount of fibroglandular tissue (FGT) and menopausal status on apparent diffusion coefficient (ADC) values in differentiation between malignant and benign lesions.
METHODS: In this HIPAA-compliant study, mean ADC values of 218 malignant and 130 benign lesions from 288 patients were retrospectively evaluated. The differences in mean ADC values between benign and malignant lesions were calculated within groups stratified by BPE level (high/low), amount of FGT (dense/non-dense) and menopausal status (premenopausal/postmenopausal). Sensitivities and specificities for distinguishing malignant from benign lesions within different groups were compared for statistical significance.
RESULTS: The mean ADC value for malignant lesions was significantly lower compared to that for benign lesions (1.07±0.21 x 10-3 mm2/s vs. 1.53±0.26 x 10-3 mm2/s) (p<0.0001). Using the optimal cut-off point of 1.30 x 10-3 mm2/s, an area under the curve of 0.918 was obtained, with sensitivity and specificity both of 87 %. There was no statistically significant difference in sensitivities and specificities of ADC values between different groups stratified by BPE level, amount of FGT or menopausal status.
CONCLUSIONS: Differentiation between benign and malignant lesions on ADC values is not significantly affected by BPE level, amount of FGT or menopausal status. KEY POINTS: • ADC allows differentiation between benign and malignant lesions. • ADC is useful for breast cancer diagnosis despite different patient characteristics. • BPE, FGT or menopause do not significantly affect sensitivity and specificity.

Entities:  

Keywords:  Breast density; Breast neoplasms; Diagnostic imaging; Diffusion magnetic resonance imaging; Menopause

Mesh:

Year:  2018        PMID: 29330631      PMCID: PMC6089248          DOI: 10.1007/s00330-017-5202-4

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


  30 in total

1.  Comparison of contrast enhancement and diffusion-weighted magnetic resonance imaging in healthy and cancerous breast tissue.

Authors:  Gene Young Cho; Linda Moy; Sungheon G Kim; Ana Paula Klautau Leite; Steven H Baete; James S Babb; Daniel K Sodickson; Eric E Sigmund
Journal:  Eur J Radiol       Date:  2015-07-02       Impact factor: 3.528

2.  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

3.  Diffusion-weighted MRI: association between patient characteristics and apparent diffusion coefficients of normal breast fibroglandular tissue at 3 T.

Authors:  Elizabeth S McDonald; Jennifer G Schopp; Sue Peacock; Wendy B DeMartini; Wendy D DeMartini; Habib Rahbar; Constance D Lehman; Savannah C Partridge
Journal:  AJR Am J Roentgenol       Date:  2014-05       Impact factor: 3.959

4.  Impact of fibroglandular tissue and background parenchymal enhancement on diffusion weighted imaging of breast lesions.

Authors:  Chiara Iacconi; Sunitha B Thakur; David D Dershaw; Jennifer Brooks; Charles W Fry; Elizabeth A Morris
Journal:  Eur J Radiol       Date:  2014-12       Impact factor: 3.528

5.  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

6.  Diagnostic efficacy of the diffusion weighted imaging in the characterization of different types of breast lesions.

Authors:  Sibel Kul; Ilker Eyuboglu; Aysegul Cansu; Etem Alhan
Journal:  J Magn Reson Imaging       Date:  2013-11-08       Impact factor: 4.813

7.  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

8.  Apparent diffusion coefficient of breast cancer and normal fibroglandular tissue in diffusion-weighted imaging: the effects of menstrual cycle and menopausal status.

Authors:  Jin You Kim; Hie Bum Suh; Hyun Jung Kang; Jong Ki Shin; Ki Seok Choo; Kyung Jin Nam; Seok Won Lee; Young Lae Jung; Young Tae Bae
Journal:  Breast Cancer Res Treat       Date:  2016-04-18       Impact factor: 4.872

9.  White paper on imaging biomarkers.

Authors: 
Journal:  Insights Imaging       Date:  2010-05-27

Review 10.  Breast MRI: EUSOBI recommendations for women's information.

Authors:  Ritse M Mann; Corinne Balleyguier; Pascal A Baltzer; Ulrich Bick; Catherine Colin; Eleanor Cornford; Andrew Evans; Eva Fallenberg; Gabor Forrai; Michael H Fuchsjäger; Fiona J Gilbert; Thomas H Helbich; Sylvia H Heywang-Köbrunner; Julia Camps-Herrero; Christiane K Kuhl; Laura Martincich; Federica Pediconi; Pietro Panizza; Luis J Pina; Ruud M Pijnappel; Katja Pinker-Domenig; Per Skaane; Francesco Sardanelli
Journal:  Eur Radiol       Date:  2015-05-23       Impact factor: 5.315

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  8 in total

1.  Diffusion-weighted MRI for Unenhanced Breast Cancer Screening.

Authors:  Nita Amornsiripanitch; Sebastian Bickelhaupt; Hee Jung Shin; Madeline Dang; Habib Rahbar; Katja Pinker; Savannah C Partridge
Journal:  Radiology       Date:  2019-10-08       Impact factor: 11.105

2.  Multiparametric 18F-FDG PET/MRI of the Breast: Are There Differences in Imaging Biomarkers of Contralateral Healthy Tissue Between Patients With and Without Breast Cancer?

Authors:  Doris Leithner; Thomas H Helbich; Blanca Bernard-Davila; Maria Adele Marino; Daly Avendano; Danny F Martinez; Maxine S Jochelson; Panagiotis Kapetas; Pascal A T Baltzer; Alexander Haug; Marcus Hacker; Yasemin Tanyildizi; Elizabeth A Morris; Katja Pinker
Journal:  J Nucl Med       Date:  2019-06-28       Impact factor: 10.057

3.  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

4.  A multiparametric [18F]FDG PET/MRI diagnostic model including imaging biomarkers of the tumor and contralateral healthy breast tissue aids breast cancer diagnosis.

Authors:  Doris Leithner; Joao V Horvat; Blanca Bernard-Davila; Thomas H Helbich; R Elena Ochoa-Albiztegui; Danny F Martinez; Michelle Zhang; Sunitha B Thakur; Georg J Wengert; Anton Staudenherz; Maxine S Jochelson; Elizabeth A Morris; Pascal A T Baltzer; Paola Clauser; Panagiotis Kapetas; Katja Pinker
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-06-13       Impact factor: 9.236

5.  Radiomic Signatures Derived from Diffusion-Weighted Imaging for the Assessment of Breast Cancer Receptor Status and Molecular Subtypes.

Authors:  Doris Leithner; Blanca Bernard-Davila; Danny F Martinez; Joao V Horvat; Maxine S Jochelson; Maria Adele Marino; Daly Avendano; R Elena Ochoa-Albiztegui; Elizabeth J Sutton; Elizabeth A Morris; Sunitha B Thakur; Katja Pinker
Journal:  Mol Imaging Biol       Date:  2020-04       Impact factor: 3.488

6.  Detection and Classification of Breast Lesions With Readout-Segmented Diffusion-Weighted Imaging in a Large Chinese Cohort.

Authors:  Zhen Lu Yang; Yi Qi Hu; Jia Huang; Chen Ao Zhan; Min Xiong Zhou; Xiao Yong Zhang; Hui Ting Zhang; Li Ming Xia; Tao Ai
Journal:  Front Oncol       Date:  2021-03-22       Impact factor: 6.244

7.  Breast cancer and background parenchymal enhancement at breast magnetic resonance imaging: a meta-analysis.

Authors:  Na Hu; Jinghao Zhao; Yong Li; Quanshui Fu; Linwei Zhao; Hong Chen; Wei Qin; Guoqing Yang
Journal:  BMC Med Imaging       Date:  2021-02-19       Impact factor: 1.930

Review 8.  Diffusion-weighted imaging of the breast: current status as an imaging biomarker and future role.

Authors:  Julia Camps-Herrero
Journal:  BJR Open       Date:  2019-03-08
  8 in total

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