Histopathological and Ultrasound Correlation in Women Presenting with Breast Lumps in Yaoundé, Cameroon

Context: Breast cancer is very deadly among women with higher rates in the developing world. Imaging tools such as ultrasound, can be used to differentiate between the types of breast lumps. This study aimed to determine the value of ultrasound as a first-line examination in the diagnosis of breast masses. Methods: This was a retrospective cross-sectional study of women presenting with breast lumps from November 2022 to June 2023 at the Yaounde General Hospital, which lasted seven months, from November 2022 to June 2023. The sampling was exhaustive and consecutive. Association between variables was studied using the x2 test and concordance between ultrasound and histopathological findings was assessed using the Kappa correlation coefficient. Results: 234 women were included in the study. Their mean age was 46.3 ± 11.4 years. Overall, 15 (6.4%) lumps were benign while 219 (93.6%) were malignant. Triple negative (5.6%) was the most recurrent genomic classification. The correlation between the ultrasound and histopathological findings was significant, with an observed concordance rate at 85.1%, kappa = 0.322 and a p-value Conclusion: The performance of ultrasound in differentiating benign and malignant lesion was high. However, the discordant cases highlight the need for a diagnosis system which blends histopathological and radiological findings for an improved management of patients with breast lumps.

Study on the Anti-Inflammatory and Analgesic Mechanisms of Breast Lump Resolution Detergent in a Rat Model of Breast Hyperplasia

Objective: This study aimed to investigate the anti-inflammatory and analgesic mechanisms of a breast lump resolution detergent in a rat model of breast hyperplasia. Methods: A rat model of breast hyperplasia was established using injections of estradiol benzoate combined with progesterone. The effects of the breast lump resolution detergent on nipple height and diameter in the rat model were observed, along with its impact on serum levels of estradiol (E2), prolactin (PRL), and progesterone (P). Additionally, the study examined the morphological changes in breast tissue. The impact of the breast nodule detergent on blood rheology parameters was also observed. Furthermore, the anti-inflammatory effect of the breast nodule detergent was assessed using the cotton ball granuloma experiment, and the analgesic effect was observed using the writhing test. Results: The breast lump resolution detergent reduced nipple height and diameter in the rat model, decreased serum levels of E2, PRL, and P, and alleviated pathological changes in breast tissue. It also lowered hemorheological parameters including whole blood high, medium, and low shear viscosity, plasma viscosity, red blood cell hematocrit, red blood cell aggregation index, red blood cell deformability index, red blood cell electrophoresis time, and erythrocyte sedimentation rate in the acute “blood stasis” rat model. The detergent reduced the weight of cotton ball granulomas in mice and decreased the number of writhing episodes caused by acetic acid. Conclusion: The breast lump resolution detergent demonstrates favorable therapeutic effects in treating breast hyperplasia, promoting blood circulation and removing blood stasis, exerting anti-inflammatory properties, and providing analgesic effects. The downregulation of serum E2 and PRL levels and the upregulation of P levels may be critical mechanisms underlying its efficacy.

Breast Lump Recognition Algorithms Based on Ultrasound Radio-Frequency Signals

A method for evaluating the benign and malignant breast tumors based on radio?frequency(RF)data was explored by extracting the characteristic parameters of breast ultrasound RF signals.The breast biopsy data were used as the reference data for judging the lump benign or malignant.The extracted ultrasound RF data were reconstructed and segmented by computer aided method to obtain the breast tumor region of interest(ROI)and its characteristic parameters(entropy and standard deviation).The characteristic parameters were statistically analyzed to evaluate the relationship between characteristic parameters and benign or malignant breast tumors.The results indicate the entropy and standard deviation of normal region is much higher than that of lump region,which shows that the standard deviation and entropy characteristic parameters of ultrasonic RF signals are meaningful in the diagnosis of breast tumors.The proposed method provides a new direction for computer?aided diagnosis of benign and malignant breast tumors.