Diagnostic value of BIRADS method using sonography in evaluating the level of malignancy of breast masses compared with biopsy

Document Type : Original Article

Authors

1 Associate professor, Department of Radiology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.

2 Resident, Department of Radiology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.

Abstract

Introduction: Ultrasound is a valuable diagnostic imaging modality in the clinical evaluation of breast masses. BIRADS (Breast Imaging Reporting and Data System) classification in ultrasound is an important and reliable method for assessment and estimation of the risk of malignancy in breast lesions. This study was performed with aim to evaluate the accuracy of the results of BIRADS classification (Grade 3 and 4) using sonography in evaluating the level of malignancy of breast masses and comparing it with pathology results.
Methods: This study was performed on 139 patients referred to Imam Reza hospital, Omid Oncology hospital and some private clinics in Mashhad and evaluated the patients with palpable breast mass who were ultrasound candidates for further examination of the nature of mass in 2014-2016. Axilla breast ultrasound was performed by two radiology professors. Based on the classification of the American Radiology Society and BIRADS system, various degrees of breast masses malignancy were identified, and then the patients were referred for biopsy. The pathologic results were compared with ultrasound reports, and consistency of the results and accuracy of ultrasound were examined with statistical tests. Data were analyzed by SPSS software (version 16).
Results: Out of 37 biopsies of lesions with BIRADS-3 in ultrasound, two (5.4%) of the lesions resulted in malignant pathology. Out of 102 biopsies of lesions with BIRADS-4 in ultrasound, 65 (64%) resulted in benign pathology which indicates no consistency of pathology results with sonography in these cases. The sensitivity of the BIRADS-3 system for diagnosis of benign breast masses was 94% and its specificity was 64%. The sensitivity of the BIRADS-4 system for diagnosis of malignant breast cancers was 75% and its specificity was 79%.
Conclusion: There was consistency between the results obtained from the classification by the BIRADS method and pathology; so regarding the relatively high accuracy of this method, radiologic-pathologic consistency can be used to determine how to follow the patients and choose the appropriate treatment method.

Keywords


  1. Merz E. 25 Years of 3D ultrasound in prenatal diagnosis (1989-2014). Ultraschall Med 2015; 36(1):3-8.
  2. Kovatcheva R, Guglielmina JN, Abehsera M, Boulanger L, Laurent N, Poncelet E. Ultrasound-guided high-intensity focused ultrasound treatment of breast fibroadenoma-a multicenter experience. J Ther Ultrasound 2015; 3(1):1.
  3. Xiao Y, Zhou Q, Chen Z. Automated breast volume scanning versus conventional ultrasound in breast cancer screening. Acad Radiol 2015; 22(3):387-99.
  4. Brem RF, Lenihan MJ, Lieberman J, Torrente J. Screening breast ultrasound: past, present, and future. AJR Am J Roentgenol 2015; 204(2):234-40.
  5. Andersen I, Kolodziejczyk C, Thielen K, Heinesen E, Diderichsen F. The effect of breast cancer on personal income three years after diagnosis by cancer stage and education: a register-based cohort study among Danish females. BMC Public Health 2015; 15(1):50.
  6. Mohaghegh P, Yavari P, Akbari ME, Abadi A, Ahmadi F. The correlation between the family levels of socioeconomic status and stage at diagnosis of breast cancer. Iran J Cancer Prev 2014; 7(4):232-8.
  7. Ghorbani A, Moradi A, Gookizadeh A, Jokar S, Sonbolestan SA. Evaluation of relationship between breast cancer and migraine. Adv Biomed Res 2015; 4:14.
  8. Bonafede MM, Kalra VB, Miller JD, Fajardo LL. Value analysis of digital breast tomosynthesis for breast cancer screening in a commercially-insured US population. Clinicoecon Outcomes Res 2015; 7:53-63.
  9. Thomas M, De Brabanter K, Suykens JA, De Moor B. Predicting breast cancer using an expression values weighted clinical classifier. BMC Bioinformatics 2014; 15:411.
  10. Gharekhanloo F, Torabian S, Kamrani S. Survey of the role of combined screening method with ultrasonography in the diagnosis of breast cancer. Sci J Hamadan Univ Med Sci 2011; 17(4):57-60.
  11. Tozaki M, Fukuma E. Does power Doppler ultrasonography improve the BI-RADS category assessment and diagnostic accuracy of solid breast lesions? Acta Radiol 2011; 52(7):706-10.
  12. Li E, Li J, Song Y, Xue M, Zhou C. A comparative study of the diagnostic value of contrast-enhanced breast MR imaging and mammography on patients with BI-RADS 3-5 microcalcifications. PLoS One 2014; 9(11):e111217.
  13. Hille H, Vetter M, Hackelöer BJ. The accuracy of BI-RADS classification of breast ultrasound as a first-line imaging method. Ultraschall Med 2012; 33(2):160-3.
  14. Heinig J, Witteler R, Schmitz R, Kiesel L, Steinhard J. Accuracy of classification of breast ultrasound findings based on criteria used for BI-RADS. Ultrasound Obstet Gynecol 2008; 32(4):573-8.
  15. Johnson L, Gunasekera A, Douek M. Applications of nanotechnology in cancer. Discov. Med. 2010;9:374–379.
  16. Liberman L, Abramson AF, Squires FB, Glassman JR, Morris EA, Dershaw DD. The breast imaging reporting and data system: positive predictive value of mammographic features and final assessment categories. AJR Am J Roentgenol. 1998 Jul;171(1):35-40.
  17. Bérubé M, Curpen B, Ugolini P, Lalonde L, Ouimet-Oliva D. Level of suspicion of a mammographic lesion: use of features defined by BI-RADS lexicon and correlation with large-core breast biopsy. Can Assoc Radiol J. 1998 Aug;49(4):223-8 .
  18. Orel SG, Kay N, Reynolds C, Sullivan DC. BI-RADS categorization as a predictor of malignancy. Radiology. 1999 Jun;211(3):845-50.
  19. Mendez A, Cabanillas F, Echenique M, Malekshamran K, Perez I, Ramos E. Mammographic features and correlation with biopsy findings using 11-gauge stereotactic vacuum-assisted breast biopsy (SVABB). Ann Oncol. 2004 Mar;15(3):450-4.
  20. Sosthène Mayi-Tsonga, Jean-François Meye, Jean-Pierre Ngou-Mve-Ngou, Gabriel Mendome, Mathieu Mounanga. Corrélation radio-histologique des lésions mammaires infracliniques à partir de la classification BI-RADS (étude gabonaise) Volume 16, numéro 3, Juillet-Août-Septembre 2006.