The value of breast MRI in the classification of BI-RADS IV subdivisions

Authors

  • Zainab Almusawi College of medicine

Keywords:

BI-RADS IV subdivisions, breast MRI, breast cancer

Abstract

Background: breast cancer is the most common type of cancer among females worldwide and is the most prevalent cancer in Iraq.

Aims: to determine the value of breast MRI in the assessment of BI-RADS IV subdivisions. Trying to reflect the likelihood of malignancy and to determine whether they correspond well to target ranges for mammography and ultrasound (up grading or down-grading).

Patients and methods: a cross-sectional study carried out on selected 32 ladies with 47 suspicious lesions by means of ultrasonography and/ or mammography and were recruited for MRI unit of Al-Imamein Al-Kadhimein Medical city in Baghdad from February 2019 to December 2019. Two independent radiologists analyzed the images; subcategorized the findings as BI-RADS 4A, 4B, or 4C.

Results: from the 47 lesions, 21 were proved malignant, giving sensitivity of 100% and specificity of 34.6%. The referral BI-RADS IV subdivisions by US/ mammography (IVA= 20 (55% of them given IV A on MRI), IVB= 18 (27.7% of them were IVB on MRI) and IVC= 9 (77% were given IV C on MRI)) were significantly correlated to that of DCE- MRI (P-value <0.001). There was statistically significant correlation of lesional size (P- value=0.003), shape (P- value=0.003), margins (P- value < 0.001), type of dynamic curve (P-value = 0.02), T2 signal intensity (P-value= 0.009) with the lesion type (benign or malignant). While patients age, breast density, family history of breast malignancy, background parenchymal enhancement and the location of lesion showed no statistical significant correlation with benignity of a lesion.

Conclusion: risk stratification of suspicious lesions (BI-RADS IV subdivisions) was satisfactorily performed with DCE-MRI as it can concur to U/S and mammography in the assessment of ACR BI-RADS IV subdivisions.

References

Iraqi Ministry of Health and Environment. Annual Statistical report 2016. 2017 Chapter 5, p 195
2. Alwan NA. Breast Cancer Among Iraqi Women: Preliminary Findings From a Regional Comparative Breast Cancer Research Project. Journal of Global Oncology. 2016 Mar 16;2(5):255-8.
3. World Health Organization (WHO) Cancer \ breast cancer (Accessed at 25-10-2019) available at http://www.who.int/cancer/breast cancer/en/
4. Division of Cancer Prevention and Control, Centers for Disease Control and Prevention(CDC), Breast cancer, (Accessed on 15-11-2019) available at : https://www.cdc.gov/cancer/breast cancer/en
5. Karunakaran U, Thekkandathil N, Joseph M, Kannankai S, Kumaran JA. Clinical breast cancer screening- A campbased study among rural women in North Kerala. J. Evid. Based Med. Healthc. 2017; 4(54), 3323-3328. DOI: 10.18410/jebmh/2017/660.
5. Di Muzio B, Pacifici S. Terminal Ductal Terminal Unit [Internet]. Radiopaedia. Radiopaedia Reference Articles; 2017 [cited 2019Nov15]. Available from: https://radiopaedia.org/articles/terminal-ductal-lobular-unit
6. Dietzel M, Ellmann S, Schulz-Wendtland R, Clauser P, Wenkel E, Uder M, Baltzer PA. Breast MRI in the era of diffusion weighted imaging: do we still need signal-intensity time curves?. European radiology. 2019 Jul 29:1-0.
7. Dietzel M, Ellmann S, Schulz-Wendtland R, Clauser P, Wenkel E, Uder M, Baltzer PA. Breast MRI in the era of diffusion weighted imaging: do we still need signal-intensity time curves?. European radiology. 2019 Jul 29:1-0.
8. Dawoud BM, Elarabawy RA, Dewan A, El-Wehab KA, Barakat AF. DYNAMIC CONTRAST-ENHANCED MR IMAGING IN DIAGNOSIS OF BREAST LESIONS. Zagazig University Medical Journal. 2018 Nov 1;24(6):501-11.
9. Thigpen D, Kappler A, Brem R. The Role of Ultrasound in Screening Dense Breasts-A Review of the Literature and Practical Solutions for Implementation. Diagnostics (Basel). 2018;8(1):20. Al-Saadi WI, Shallab EN, Naji S. Diffusion weighted MRI in the characterization of solitary breast mass. The Egyptian Journal of Radiology and Nuclear Medicine. 2015 Dec 1;46(4):1337-41.
10. Miyake KK, Ikeda DM, Daniel BL. Magnetic Resonance Imaging of Breast Cancer and Magnetic Resonance Imaging–Guided Breast Biopsy. In: THE REQUISITES: Breast Imaging. 3rd ed. St. Louis, Missouri: Elsevier; 2017. p. 259–315.
11. Mann RM, Cho N, Moy L. Breast MRI: State of the Art [Internet]. Radiology. RSNA; 2019 [cited 2019Dec16]. Available from: https://pubs.rsna.org/doi/10.1148/radiol.2019182947
12. Spick C, Pinker-Domenig K, Rudas M, Helbich TH and Baltzer PA. MRI-only lesions: application of diffusion-weighted imaging obviates unnecessary MR-guided breast biopsies. Eur Radiol 2014; 24: 1204-1210.
13. Heywang-Köbrunner SH, Hacker A and Sedlacek S. Magnetic resonance imaging: the evolution of breast imaging. Breast 2013; 22 Suppl 2: S77-82.
14. Zhang F, Ba Z, Zhang Y, Wang Z, Liu D, Ni X, Song L. Sub-classification of BI-RADS by MRI dynamic enhanced vascular imaging and diffusion weighted imaging. Int J Clin Exp Med. 2017 Jan 1;10(7):10324-32.
15. Dijkstra H, Dorrius MD, Wielema M, Pijnappel RM, Oudkerk M, Sijens PE. Quantitative DWI implemented after DCE‐MRI yields increased specificity for BI‐RADS 3 and 4 breast lesions. Journal of Magnetic Resonance Imaging. 2016 Dec;44(6):1642-9.
16. Tan S, Rahmat K, Rozalli F, Mohd-Shah M, Aziz Y, Yip C et al. Differentiation between benign and malignant breast lesions using quantitative diffusion-weighted sequence on 3 T MRI. 2014;54:67-73.
17. Hassan H, Mahmoud Zahran M, El-Prince Hassan H, Mohamed Abdel-Hamid A, Abdel Shafy Fadaly G. Diffusion magnetic resonance imaging of breast lesions: Initial experience at Alexandria University. 2019.
18. Almeida JRM, Gomes AB, Barros TP, Fahel PE, de Seixas Rocha M. Subcategorization of suspicious breast lesions (BI-RADS category 4) according to MRI criteria: role of dynamic contrast-enhanced and diffusion-weighted imaging. American Journal of Roentgenology. 2015 Jul;205(1):222-31.
19. Chevrier MC, David J, Khoury ME, Lalonde L, Labelle M, Trop I. Breast biopsies under magnetic resonance imaging guidance: challenges of an essential but imperfect technique. Curr Probl Diagn Radiol. 2016; 45:193–204. [PubMed: 26272705]
20. Torres-Tabanera M, Cلrdenas-Rebollo JM, Villar- Castaٌo P, et al. Analysis of the positive predictive value of the subcategories of BI-RADS 4 lesions: preliminary results in 880 lesions [in Spanish]. Radiologia 2012; 54:520–531
21. Strigel RM, Burnside ES, Elezaby M, Fowler AM, Kelcz F, Salkowski LR, DeMartini WB. Utility of BI-RADS assessment category 4 subdivisions for screening breast MRI. American Journal of Roentgenology. 2017 Jun;208(6):1392-9.
22. Almeida JR, Gomes AB, Barros TP, Fahel PE, Rocha MD. Predictive performance of BI-RADS magnetic resonance imaging descriptors in the context of suspicious (category 4) findings. Radiologia brasileira. 2016 Jun;49(3):137-43.
23. Al-Khawari H, Athyal R, Kovacs A, et al. Accuracy of the Fischer scoring system and the breast imaging reporting and data system in identification of malignant breast lesions. Hematol Oncol Stem Cell Ther. 2009;2(3):403–10.
24. Henderson LM, Hubbard RA, Zhu W, Weiss J, Wernli KJ, Goodrich ME, Kerlikowske K, DeMartini W, Ozanne EM, Onega T. Preoperative Breast Magnetic Resonance Imaging Use by Breast Density and Family History of Breast Cancer. Journal of Women's Health. 2018 Aug 1;27(8):987-93.
25. Telegrafo M, Rella L, Ianora AA, Angelelli G, Moschetta M. Breast MRI background parenchymal enhancement (BPE) correlates with the risk of breast cancer. Magnetic resonance imaging. 2016 Feb 1;34(2):173-6.
26. Grimm LJ, Saha A, Ghate SV, Kim C, Soo MS, Yoon SC, Mazurowski MA. Relationship between background parenchymal enhancement on high-risk screening MRI and future breast cancer risk. Academic radiology. 2019 Jan 1;26(1):69-75.

Published

2021-06-29