RT Journal Article
SR Electronic
T1 Accuracy of imaging of BI-RADS 4 subcategorizations in breast lesion diagnosis
JF Saudi Medical Journal
JO Saudi Med J
FD Prince Sultan Military Medical City
SP 1228
OP 1237
DO 10.15537/smj.2024.45.11.20240001
VO 45
IS 11
A1 Ghunaim, Hadeel A.
A1 Alatawi, Rana E.
A1 Borhan, Walaa M.
A1 Daqqaq, Tareef S.
A1 Alhasan, Ayman S.
A1 Aboualkheir, Mervat M.
A1 Elkady, Reem M.
YR 2024
UL http://smj.org.sa/content/45/11/1228.abstract
AB Objectives: To correlate breast imaging-reporting and data system (BI-RADS) category 4 lesions with histopathology results to assess the accuracy of subcategorization.Methods: A retrospective study was carried out from September 2021 to June 2022. A total of 247 breast lesions were reviewed categorized as BI-RADS 4 using ultrasound (US) and digital mammography. Feature analysis of the lesions were obtained using BI-RADS terminology and assigned to subcategories (4A, 4B, and 4C). Pathological analysis was carried out on tissue obtained through US-guided core biopsy. A p-value of <0.05 was considered significant.Results: Of the 247 lesions, 135 were categorized as subcategory 4A, 68 as 4B, and 44 as 4C. Overall, 41 (16.6%) had malignant lesions, while 206 (83.4%) had benign lesions. The mean age of the patients with benign versus malignant lesions was (43.18±14.02 vs. 51.24±14.15 years; p<0.001). Mean size of benign versus malignant lesions was (1.93±1.65 vs. 3.82±3.89 cm; p<0.001). Findings were compared with histopathology, and the positive predictive value fell within the reference range for subcategories 4C (>70%). High reliability was observed between the 2 readers, with a weighted Cohen’s Kappa value of 0.79 (0.73-0.85). Significant disagreements in the assignment of features on radiological lesion characterization were observed between the 2 readers regarding lesion density, shape, echo pattern, vascularity, and borders.Conclusion: The results of this study contribute to the existing body of knowledge, emphasizing the need for standardized guidelines for the characterization of BI-RADS 4 subcategories and improved diagnostic accuracy in the management of breast lesions.