Value of MRI in Differentiation between Benign and Malignant Breast Mass

Authors

  • Zina Adnan Layth Diyala Health Directorate, Ministry of Health, Diyala, Iraq.
  • Zainab Sami Yaseen Diyala Health Directorate, Ministry of Health, Diyala, Iraq.

DOI:

https://doi.org/10.22317/imj.v6i3.1196

Keywords:

Magnetic Resonance Imaging, Circumscribed Breast Mass, Iraq

Abstract

Objectives: This study aimed to evaluate the role of MRI in differentiation between benign and malignant well-circumscribed breast masses.

Methods: A prospective cross-sectional study conducted on selected female patients with Breast mass who their age older than 35 years. All patients underwent examination using 1.5 Tesla magnetic resonance unit (MAGNETOM AERA, SIMENS).

Results: 30 female patients were selected (mean age of 44.2±9.2 years, range between 35-69). Final findings of MRI revealed that 6 (20%) women had malignant breast mass while 24 (80%) women had benign breast mass. The histopathology revealed that 4 (13.3%) women were having malignancy while 26 (86.6%) were having benign breast tumor. There was a highly significant association between malignancy and hyperdense mammography findings of women (p<0.001), multiple lymph nodes for women (p<0.001), increased size of mass by MRI (p<0.001), circumscribed macrolabular lesion on MRI, rapid early kinetic phase of enhanced MRI (p<0.001), washout late kinetic phase enhanced MRI (p<0.001), and MRI kinetic curve type 3(p<0.001). There was a highly significant association between homogenous enhanced MRI findings of women and benign lesions (p<0.001).

Conclusion: The validity results of MRI in differentiation between benign and malignant circumscribed breast masses are high, except for positive predictive value, and application of kinetic curve dynamic contrast enhancement increases magnetic resonance in differentiation between benign and malignant circumscribed breast masses.

References

Yoo JL, Woo OH, Kim YK, Cho KR, Yong HS, Seo BK, et al. Can MR Imaging contribute in characterizing well-circumscribed breast carcinomas? Radiographics 2010; 30(6):1689-1702.

Shah N, Patel S, Goswami K, Gohil Y, Shah D. Well circumscribed breast carcinoma: mammographic and sonographic finding—report of five cases. Indian J Radiol Imaging 2005; 15:77–80.

Kuhl CK. MRI of breast tumors. Eur Radiol 2005; 10(1):46–58.

Lam WW, Tang AP, Tse G, Chu WC. Radiologypathology conference: papillary carcinoma of the breast. Clin Imaging 2005; 29(6):396–400.

Thomassin-Naggara I, Tardivon A, Chopier J. Standardized diagnosis and reporting of breast cancer. Diagnostic and Interventional Imaging 2014; 95 (7–8):759-766.

Lazarus E, Mainiero MB, Schepps B, Koelliker SL, Livingston LS. BI- RADS lexicon for US and mammography: interobserver variability and positive predictive value. Radiology. 2006; 239:385– 391.

Alwan NA, Al-Attar WM, Eliessa RA, Madfaie ZA, Tawfeeq FN. Knowledge, attitude and practice regarding breast cancer and breast self- examination among a sample of the educated population in Iraq. East Mediterr Health J 2012; 18(4):337-345.

Giess CS, Frost EP, Birdwell R Interpreting one-view mammographic findings: minimizing callbacks while maximizing cancer detection. Radiographics 2014; 34(4):928-9240.

Cheng L, Li X. Breast magnetic resonance imaging: kinetic curve assessment. Gland Surgery 2013; 2(1):50-53.

Agrawal G, Su M-Y, Nalcioglu O, Feig SA, Chen J-H. Significance of Breast Lesion Descriptors in the ACR BI-RADS MRI Lexicon. Cancer 2009; 115(7):1363-1380.

Kim YR, Kim HS, Kim H-W. Are Irregular Hypoechoic Breast Masses on Ultrasound Always Malignancies? A Pictorial Essay. Korean Journal of Radiology 2015; 16(6):1266-1275.

Leong LCH, Gombos EC, Jagadeesan J, Fook-Chong SMC. MRI Kinetics With Volumetric Analysis in Correlation With Hormonal Receptor Subtypes and Histologic Grade of Invasive Breast Cancers. AJR American journal of roentgenology 2015; 204(3):W348-W356.

Fujiwara K, Yamada T, Kanemaki Y, Okamoto S, Kojima Y, Tsugawa K, et al. Grading System to Categorize Breast MRI in BI-RADS 5th Edition: A Multivariate Study of Breast Mass Descriptors in Terms of Probability of Malignancy. AJR Am J Roentgenol 2018; 210(3):W118- W127.

Pinker K, Bogner W, Baltzer P, Karanikas G, Magometschnigg H, Brader P, et al. Improved differentiation of benign and malignant breast tumors with multiparametric 18 fluorodeoxyglucose positron emission tomography magnetic resonance imaging: a feasibility study. Clin Cancer Res 2014; 20(13):3540-3549.

Min Q, Shao K, Zhai L. Differential diagnosis of benign and malignant breast masses using diffusion-weighted magnetic resonance imaging. World Journal of Surgical Oncology 2015; 13:32.

Yamaguchi K, Schacht D, Sennett CA, Newstead GM, Imaizumi T, Irie H, et al. Decision making for breast lesions initially detected at contrast- enhanced breast MRI. AJR Am J Roentgenol 2013; 201(6):1376-1385.

Al-Maammory BAS, Hussain HAR. Distinguishing Benign and Malignant Breast Mass using kinetic Curve of Dynamic contrast Enhanced MRI Scanning in Comparison with Histopathological Results. Medical Journal of Babylon 2017; 14 (3):450 – 460. Available at: http://www.medicaljb.com

Teama AH, Hassanien OA, Hashish AAE, Shaarawy HA. The role of conventional and functional MRI in diagnosis of breast masses. The Egyptian Journal of Radiology and Nuclear Medicine 2015; 46 (4): 1215-1230.

Hong AS, Rosen EL, Soo MS, Baker JA. BI-RADS for sonography: positive and negative predictive values of sonographic features. AJR Am J Roentgenol 2005; 184(4):1260–1265.

Downloads

Published

2022-09-26

How to Cite

1.
Layth ZA, Yaseen ZS. Value of MRI in Differentiation between Benign and Malignant Breast Mass. Iraq Med J [Internet]. 2022 Sep. 26 [cited 2024 Nov. 21];6(3). Available from: https://iraqmedj.org/index.php/imj/article/view/1196

Issue

Section

Articles