Diagnostic Accuracy of Ultrasound Bi-RADS Classification Among Females Having Breast Lumps, by Taking Histopathology as Gold Standard

  • Naushaba Malik Head of Radiology Department, PESSI Hospital, I-12, I.J.Principal Road,Islamabad
  • Maryam Rauf Consultant Radiologist, PESSI Hospital, I-12, I.J.Principal Road, Islamabad
  • Ghazala Malik Radiologist, Pakistan Institute of Medical Sciences, G-8/3, Islamabad
Keywords: Benign lump, BI-RADS, histopathology

Abstract

Objective:  To determine the diagnostic accuracy of ultrasound BI-RADS classification in patients presented with breast lump by cytology as histopathology as “a benchmark”.

Methodology: This cross-sectional study was conducted at the Department of Radiology at Islamabad Diagnostic Center, F-8, Markaz, Islamabad from February 2018 to July 2018. All the patients who presented with breast lumps were included and underwent mammograms (Digital Mammogram DRE by GE USA). Mammogram reports were categorized 0-VI according to Breast Imaging-Reporting and Data System (BI-RADS) scores 0-VI. Patients having BI-RADS score 0-III were considered as negative and BI-RADS score IV-V were considered as positive Patients further underwent fine needle aspiration of breast lump for cytology. Data was collected via self-made performa and analyzed by using SPSS version 20.

Results: Total 72 females presented with breast lump were studied; their mean age was 40.27+4.48 years. 22 patients had breast cancer according to BI-RADS classification, and out of these 16 patients were confirmed on histopathology. The sensitivity and specificity of BI-RADS classifications were 75% and 82% respectively, while diagnostic accuracy was 80% by taking histopathology as gold standard. There was a significant positive correlation between BI-RADS classification and lump size on ultrasound r-value 0.279 and p-value 0.001.

Conclusion: Ultrasound BI-RADS classification is the effective reliable modality with a sensitivity was 75% and specificity 82% in the diagnosis of a breast lump to decrease the burden of unnecessary biopsies.

Published
2020-04-29
Section
Original Articles