Role of Diffusion Weighted Imaging with Corresponding Apparent Diffusion Coefficient Values in Differentiating Benign and Malignant Breast Lesions

Document Type : Original Paper

Authors

Department of Radiodiagnosis, Sri Devaraj Urs Medical College, SDUAHER, Tamaka, Kolar, Karnataka, India.

Abstract

Introduction: The objective of this study is to assess the role of diffusion weighted (DW) magnetic resonance imaging (MRI) along with its corresponding apparent diffusion coefficient (ADC) values in differentiating malignant from benign breast lesions.
Material and Methods: Patients with breast lesions and those who met inclusion and exclusion criteria were included in this study. MR Mammography (MRM) was performed on 1.5 Tesla MR Scanner (Siemens® Magnetom Avanto®). DWI was performed at b-values of 50, 400 and 800 s/mm2 followed by ADC sequence.
Results: 50 patients with a total of 81 breast lesions and whose diagnosis was histopathologically confirmed following MRM were included in the study. We observed that benign lesions showed no restricted diffusion with an ADC value of >1.3 x 10-3 mm2/s. Most of the malignant lesions showed restricted diffusion with ADC value of < 1.3 10-3 mm2/s. A non-malignant condition, Benign Phyllodes tumor (n=1) showed no restricted diffusion but had a low ADC of 1.1 x 10-3 giving false positive result. Mucinous carcinomas (n=5) showed no restricted diffusion and had a mean ADC value of >1.3 x 10-3. We observed sensitivity of DWI along with ADC value to be 86.8% and specificity as 97.6%.
Conclusion: DW-MRI can be employed as a fast unenhanced screening modality for breast cancer with high sensitivity. Considering ADC values along with DW-MRI increased its detection rates and hence both can be incorporated as supplementary techniques in multiparametric MRM.

Keywords

Main Subjects

References

  1. Balasubramanian P, Murugesan VK, Boopathy V. The role of MR mammography in differentiating benign from malignant in suspicious breast masses. J Clin Diagn Res. 2016;10:5-8.
  2. Zendehdel M, Niakan B, Keshtkar A, Rafiei E, Salamat F. Subtypes of Benign Breast Disease as a Risk Factor for Breast Cancer: A Systematic Review and Meta-Analysis Protocol. Iran J Med Sci. 2018;43:1–
  3. World Health Organization. Breast cancer. WHO/B. Anderson; [cited 2021 March 26] Available from: https://www.who.int/news-room/fact-sheets/detail/breast-cancer
  4. Woolf DK, Padhani AR, Makris A. Magnetic resonance imaging, digital mammography, and sonography: tumor characteristics and tumor biology in primary setting. JNCI Monographs. 2015;51:15–
  5. Iranmakani S, Mortezazadeh T, Sajadian F, Ghaziani MF, Ghafari A, Khezerloo D, et al. A review of various modalities in breast imaging: technical aspects and clinical outcomes. Egypt J Radiol Nucl Med. 2020;51:57.
  6. Dogan B, Scoggins M, Son J, Wei W, Candelaria R, Yang W, et al. American College of Radiology–Compliant Short Protocol Breast MRI for High-Risk Breast Cancer Screening: A Prospective Feasibility Study. Am J Roentgenol. 2018; 210, 214-21.
  7. Yılmaz E, Sarı O, Yılmaz A, Ucar N, Aslan A, Inan I, Parlakkılıc UT. Diffusion-weighted imaging for the discrimination of benign and malignant breast masses; utility of ADC and relative ADC. journal of the Belgian society of radiology. 2018;102(1).
  8. Yadav P, Chauhan S. Effectivity of combined diffusion-weighted imaging and contrast-enhanced MRI in malignant and benign breast lesions. Pol J Radiol. 2018; 83:82-93.
  9. El Ameen NF, Gawad EA, Ghany HA. Diffusion-weighted imaging versus dynamic contrast-enhanced MRI: a new horizon for characterisation of suspicious breast lesions. Clinical Radiology. 2021 Jan 1;76(1):80-e1.
  10. Bokacheva L, Kaplan JB, Giri DD, Patil S, Gnanasigamani M, Nyman CG, et al. Intravoxel incoherent motion diffusion‐weighted MRI at 3.0 T differentiates malignant breast lesions from benign lesions and breast parenchyma. Journal of Magnetic Resonance Imaging. 2014 Oct;40(4):813-23.
  11. Bidari Z, Yazdi Sotoodeh Z, Shahraki F. Comparison between MRS and DWI in MRI of breast cancer. Iranian Journal of Medical Physics. 2018 Dec 1;15(Special Issue-12th. Iranian Congress of Medical Physics):37.
  12. Partridge SC, Amornsiripanitch N. The role of DWI in the assessment of breast lesions. Topics in magnetic resonance imaging: TMRI. 2017 Oct;26(5):201-9.
  13. Hirano M, Satake H, Ishigaki S, Ikeda M, Kawai H, Naganawa S. Diffusion-weighted imaging of breast masses: comparison of diagnostic performance using various apparent diffusion coefficient parameters. American Journal of Roentgenology. 2012 Mar;198(3):717-22.
  14. Park EK, Cho KR, Seo BK, Woo OH, Cho SB, Bae JW. Additional value of diffusion-weighted imaging to evaluate prognostic factors of breast cancer: correlation with the apparent diffusion coefficient. Iran J Radiol. 2016;13:3313.
  15. Cabuk G, Nass Duce M, O¨ zgu¨ r A, Apaydın FD, Polat A, Orekici G. The diagnostic value of diffusion-weighted imaging and the apparent diffusion coefficient values in the differentiation of benign and malignant breast lesions. J Med Imaging Radiat Oncol. 2015;59:141-8.
  16. Partridge SC, Nissan N, Rahbar H, Kitsch AE, Sigmund EE. Diffusion-weighted breast MRI: clinical applications and emerging techniques. J Magn Reson Imaging. 2017;45:337-55.
  17. Qu RF, Guo DR, Chang ZX, Meng J, Sun Y, Hao SH, et al. Differential diagnosis of benign and malignant breast tumors using apparent diffusion coefficient value measured through diffusion-weighted magnetic resonance imaging. Journal of Computer Assisted Tomography. 2015 Jul 1;39(4):513-22.
  18. American Cancer Society. Breast Cancer Risk Factors You Cannot Change. The American Cancer Society medical and editorial content team [updated: 2021 December 16].
  19. Available from: https://www.cancer.org/cancer/breast-cancer/risk-and-prevention/breast-cancer-risk-factors-you-cannot-change.html.

 

 

 

 

 

 

Iranian Journal of Medical Physics
Volume 19, Issue 6
November and December 2022
Pages 383-389

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History

  • Receive Date: 13 October 2021
  • Revise Date: 19 January 2022
  • Accept Date: 31 January 2022
  • First Publish Date: 31 January 2022

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