Comparative study of breast core needle biopsy (CNB) findings with ultrasound BI-RADS subtyping.

Autor: Zahir, Shokouh Taghipour, Aminpour, Sara, Nodoushan, Jamal Jafari, Rahmani, Koorosh, SafiDahaj, Farzan
Předmět:
Zdroj: Polish Journal of Surgery; 2023, Vol. 95 Issue 2, p1-6, 6p
Abstrakt: Introduction: Given the high prevalence of breast cancer, developing quick and accessible diagnostics solutions is critical. The BIRADS classification is a reliable method for assessing and estimating the risk of malignancy in breast lesions. Aim: The aim of this study was to compare the results of core needle biopsy of breast lesions and sonographic findings based on the BIRADS category in Yazd. Materials and methods: This retrospective analytical study was done on all core needle biopsy specimens referred to Mortaz hospital, Yazd, Iran from 2010 to 2019. Demographic data such as age, laterality of the lesion, BIRADS category, and pathology reports were extracted from patients' hospital folders. Data were analyzed by SPSS version 21. P < 0.05 was considered statistically significant. Results: In total, 514 cases with a mean age of 43.9 ± 9.4 years were studied. Among them, 104 cases (20.2%) were malignant and 410 cases (79.8%) were benign. The most common benign and malignant lesions were fibroadenoma (24.9%), and infiltrative ductal carcinoma (83.7%) respectively. The most common BIRADS was class 4A (54.9%). Patients with benign lesions were mostly in the 3rd and 4th decade of life, while malignant lesions were more in the 4th and 5th decades, and this difference was statistically significant (P = 0.001). The correlation between ultrasound diagnoses (BIRADS) and pathology findings was statistically significant (P < 0.001). Conclusion: Based on the results, there is a significant correlation between ultrasound outcomes according to BIRADS and pathology results, and the radiology-pathology accordance, owing to its high accuracy, can be very helpful in correctly diagnosing, monitoring, and managing the lesion. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index