Correlation and Diagnostic Accuracy between Clinical Manifestation and Ultrasound BI-RADS Scoring Finding with Pathological Findings for Breast Disease Among Women in Sulaymaniyah Governorate, Iraq

Volume 16 , Issue 1 , July 2026

Authors

Hezha Muhammad Mirza 1 ; Mezjda Ismail Rashaan 2

1 College of medicine - University of Sulaimani

2 University of Sulaimani - College of Medicine

DOI logo 10.17656/jsmc.10511

Keywords

Abstract

Background: The Breast Imaging-Reporting and Data System (BIRADS) is a crucial tool for assessing and categorizing breast lesions, particularly breast lumps.

Objective: To assess the correlation and diagnostic accuracy between clinical manifestation and ultrasound BI-RADS scoring findings with pathological findings for breast disease among women. Furthermore, it also assess the sensitivity and specificity of clinical and ultrasonographic findings in breast lesions at the Sulaimani Breast Disease Treatment Center.

Materials and Methods:

 A cross-sectional study was conducted at the Sulaimani Breast Disease Treatment Center to evaluate 250 female patients with breast lesions from January 2023 to February 2025. In this study, the association between American College of Radiology - Breast Imaging-Reporting and Data System (ACR-BIRADS) results and histopathology reports were evaluated using the chi-square test.

Results: The mean age was calculated as 46.8 + 11.6 years. Amongst the total, 104 (41.6%) and 63 (24.9%) of all breast lesions were in the range of BIRADS 3 and 5, respectively. Furthermore, 133 (53.2%) of the breast lesions amongst the total 250 were malignant, with the remaining 117 (46.8%) lesions being benign on histopathology. Diagnostic accuracy, sensitivity, and specificity for ultrasound BI-RADS turned out to be 90.8%, 86.5%, and 95.7%, respectively. The correlation between the ACR-BIRADS system and histopathology results was found as highly significant.

Conclusion: High sensitivity and specificity are demonstrated by BI-RADS-guided ultrasound in differentiating benign from malignant breast tumors. While it aids early detection of malignancy and reduces unnecessary biopsies, BI-RADS cannot replace histopathology as the diagnostic gold standard.

References

  1. 1. Chavan SG, Vemuri N. Diagnosis of breast lumps based on breast imaging reporting and data system score and histopathological examination: a comparative study. Int J Res Med Sci. 2020;8(4):1468–73. doi:10.18203/2320-6012.ijrms20201410.
  2. 2. Navya B, Thomas S, Hiremath R, Alva SR. Comparison of diagnostic accuracy of BIRADS score with pathologic findings in breast lumps. Ann Pathol Lab Med. 2017;4(3):A236–42.
  3. 3. Athanasiou A, Tardivon A, Ollivier L, Thibault FE, El Khoury C, Neuenschwander S. How to optimize breast ultrasound. Eur J Radiol. 2009;69(1):6–13. doi:10.1016/j.ejrad.2008.07.035.
  4. 4. Abhinaya KSL. Evaluation of breast lesions with ultrasonography and mammography in correlation with FNAC/HPE. IOSR J Dent Med Sci. 2020 Jul;19(7):46–55. doi:10.9790/0853-1907154655.
  5. 5. Taori K, Dhakate S, Rathod J, Hatgaonkar A, Disawal A, Wavare P, et al. Evaluation of breast masses using mammography and sonography as first line investigations. Open J Med Imaging. 2013;3(1):40–9. doi:10.4236/ojmi.2013.31007.
  6. 6. Mundinger A. Advanced breast ultrasound and interventions: an update. In: Hodler J, von Schulthess GK, Zollikofer CHL, editors. Musculoskeletal Diseases 2013–2016: Diagnostic Imaging and Interventional Techniques. Milan (IT): Springer-Verlag Italia; 2013. p. 282–9. doi:10.1007/978-88-470-5292-5_39.
  7. 7. Mustafa AA. BI-RADS 4 and 5 breast lesions: correlation between sonographic findings and histopathological results following ultrasound-guided FNAC. Kufa J Nurs Sci. 2014;4(2):188–95. doi:10.36321/kjns.vi20142.2573.
  8. 8. Gokhale S. Ultrasound characterization of breast masses. Indian J Radiol Imaging. 2009 Jul-Sep;19(3):242–7. doi:10.4103/0971-3026.54878.
  9. 9. Stavros AT. Breast ultrasound. Philadelphia (PA): Lippincott Williams & Wilkins; 2004.
  10. 10. Saha A, Mukhopadhyay M, Das C, Sarkar K, Saha AK, Sarkar DK. FNAC versus core needle biopsy: a comparative study in evaluation of palpable breast lump. J Clin Diagn Res. 2016;10(2):EC05–8. doi:10.7860/JCDR/2016/16889.7223.
  11. 11. D’Orsi CJ, Sickles EA, Mendelson EB, Morris EA, et al. ACR BI-RADS® Atlas, Breast Imaging Reporting and Data System. 5th ed. Reston (VA): American College of Radiology; 2013.
  12. 12. Quratulain S, Bibi S, Gul S, Khatoon S, Mahmood H, Sadia H. The diagnostic accuracy of conventional breast ultrasound in diagnosing malignant breast lesions taking histopathology as gold standard. Pak J Health Sci. 2024;5(6):36–41. doi:10.54393/pjhs.v5i06.1657.
  13. 13. Alessawi RW, Jasim S. The accuracy of ultrasound elastography versus histopathology in differentiation between malignant and benign breast masses. Iraq Med J. 2018;2(4):[page numbers].
  14. 14. Singh P, Chaudhry M, Nauhria S, Rao D. Cytomorphological patterns of breast lesions diagnosed on fine-needle aspiration cytology in a tertiary care hospital. Int J Med Sci Public Health. 2015;4:1–5. doi:10.5455/ijmsph.2015.22012015194.
  15. 15. Kumbhakar D. Histopathological patterns of breast lesions: a hospital-based study. J Evid Based Med Healthc. 2021;8:1671–5. doi:10.18410/jebmh/2021/309.
  16. 16. Chaitanya IN, Prabhala S, Srirambhatla DA. Comparison of histopathologic findings with BIRADS score in Tru-cut biopsies of breast lesions. Indian J Pathol Res Pract. 2020;9(1):35–41. doi:10.21088/ijprp.2278.148X.9120.5.
  17. 17. Kiyak G, Dumlu EG, Kilinc I, Tokaç M, Akbaba S, Gurer A, et al. Management of idiopathic granulomatous mastitis: dilemmas in diagnosis and treatment. BMC Surg. 2014;14:66. doi:10.1186/1471-2482-14-66.
  18. 18. Sarangan A, Geetha R, Sahaya R. Study of histopathological correlation of breast mass with radiological and cytological findings. IOSR J Dent Med Sci. 2017;16(3):4–8. doi:10.9790/0853-1603060408.
  19. 19. Chae EY, Cha JH, Shin HJ, Choi WJ, Kim HH. Reassessment and follow-up results of BI-RADS category 3 lesions detected on screening breast ultrasound. AJR Am J Roentgenol. 2016;206(3):666–72. doi:10.2214/AJR.15.15416.
  20. 20. Ha SM, Chae EY, Cha JH, Shin HJ, Choi WJ, Kim HH. Growing BI-RADS category 3 lesions on follow-up breast ultrasound: malignancy rates and worrisome features. Br J Radiol. 2018;91(1087):20170787. doi:10.1259/bjr.20170787.
  21. 21. Berg WA. BI-RADS 3 on screening breast ultrasound: what is it and what is the appropriate management? J Breast Imaging. 2021;3(5):527–38. doi:10.1093/jbi/wbab041.
  22. 22. Aslan Ö, Oktay A, Eroğlu F. Follow-up results of BI-RADS 3 lesions on magnetic resonance imaging: a retrospective study. Diagn Interv Radiol. 2024;30(3):175–82. doi:10.5152/dir.2023.232320.
  23. 23. Nisar U, Anwar J, Ihsan HR, Yadain SH, Sultana SM, Khan M. Diagnostic accuracy of ultrasound BI-RADS in diagnosing breast lesions utilizing the core needle biopsy keeping histopathology as a gold standard. J Med Sci. 2022;30(4):275–9. doi:10.53350/pjmhs20221611721.
  24. 24. Ghaemian N, Haji Ghazi Tehrani N, Nabahati M. Accuracy of mammography and ultrasonography and their BI-RADS in detection of breast malignancy. Caspian J Intern Med. 2021;12(4):573–9. doi:10.22088/cjim.12.4.573.
  25. 25. Badu-Peprah A, Otoo OK, Amamoo M, Quarshie F, Adomako B. Breast imaging reporting and data system for sonography: positive and negative predictive values of sonographic features in Kumasi, Ghana. Transl Oncol. 2024;45:101976. doi:10.1016/j.tranon.2024.101976.
  26. 26. Lin M, Wu S. Ultrasound classification of non-mass breast lesions following BI-RADS presents high positive predictive value. PLoS One. 2022;17(11):e0278299. doi:10.1371/journal.pone.0278299.
  27. 27. Azarpey N. Sensitivity and specificity of ultrasound and mammography for detection of breast malignancy: a systematic review and meta-analysis. Onkol Radioter. 2023;17(9):333–9. doi:10.5603/OiR.2023.0041.
  28. 28. Weber BW, Mao L, Salem K, Hitchcock M, Keller AH, Elezaby MA, et al. Performance of diagnostic breast imaging in symptomatic pregnant and lactating patients: systematic review and meta-analysis. Radiol Imaging Cancer. 2025;7(3):e240281. doi:10.1148/rycan.240281.
  29. 29. Hussain MA, Alhamami QS, Almetlag MH, Alyami AR, Al Hashan GM. Correlation of ultrasound and mammography to histopathology results in breast cancer: a one year study at King Khalid Hospital, Najran, Saudi Arabia. Egypt J Hosp Med. 2018;71(2):2603–9. doi:10.12816/0045311.
  30. 30. Khan TS, Malik N, Ishtiaq M, Rashid T, Fatima S. Role of ultrasound as an adjunct modality to mammography in the diagnostic evaluation of breast cancer. J Rawalpindi Med Coll. 2016;20(3):187–90.
  31. 31. Aziz S, Mohamad M, Zin R. Histopathological correlation of breast carcinoma with breast imaging-reporting and data system. Malays J Med Sci. 2022;29:65–74. doi:10.21315/mjms2022.29.2.7.
  32. 32. Mohan R, Selvakumar AS, SR K, KM M, SS P, Kathiah R, et al. Correlation of histopathology and radiological findings among the diverse breast lesions in a tertiary care centre. Cureus. 2024;16(1):e52097. doi:10.7759/cureus.52097.
  33. 33. Saxena S, Rekhi B, Bansal A, Bagga A, Chintamani, Murthy NS. Clinico-morphological patterns of breast cancer including family history in a New Delhi hospital, India: a cross-sectional study. World J Surg Oncol. 2005;3:67. doi:10.1186/1477-7819-3-67.
  34. 34. AlShamlan NA, AlOmar RS, Almukhadhib OY, Algarni SA, Alshaibani AK, Elmaki SA, et al. Characteristics of breast masses of female patients referred for diagnostic breast ultrasound from a Saudi primary health care setting. Int J Gen Med. 2021;14:755–63. doi:10.2147/IJGM.S298389
  35. 35. Ader DN, Shriver CD. Cyclical mastalgia: prevalence and impact in an outpatient breast clinic sample. J Am Coll Surg. 1997;185(5):466–70. doi:10.1016/S1072-7515(97)00132-3.
  36. 36. Badu-Peprah A, Adu-Sarkodie Y. Accuracy of clinical diagnosis, mammography and ultrasonography in preoperative assessment of breast cancer. Ghana Med J. 2018
  37. ;52(3):133–9. doi:10.4314/gmj.v52i3.5.
Statistics
  • Article view21
  • Downloads3
  • First online2 July 2026
  • Published at2 July 2026

  • RIS
  • BibTeX
  • EndNote
  • Mendeley
  • APA (7th edition)
  • MLA (9th edition)
  • Chicago
  • Harvard
  • IEEE
  • Vancouver