Ultrasound Image Features under Deep Learning in Breast Conservation Surgery for Breast Cancer.

Hongxu Zhang,Lihui Ma,Haiwang Liu,Jianping Liu,Dawei Hu,Enas Abdulhay

doi:10.1155/2021/6318936

Abstract

This study was to analyze the effect of the combined application of deep learning technology and ultrasound imaging on the effect of breast-conserving surgery for breast cancer. A deep label distribution learning (LDL) model was designed, and the semiautomatic segmentation algorithm based on the region growing and active contour technology (RA) and the segmentation model based on optimized nearest neighbors (ON) were introduced for comparison. The designed algorithm was applied to the breast-conserving surgery of breast cancer patients. According to the difference in intraoperative guidance methods, 102 female patients with early breast cancer were divided into three groups: 34 cases in W1 group (ultrasound guidance based on deep learning segmentation model), 34 cases in W2 group (ultrasound guidance), and 34 cases in W3 group (palpation guidance). The results revealed that the tumor area segmented by the LDL algorithm constructed in this study was closer to the real tumor area; the segmentation accuracy (AC), Jaccard, and true-positive (TP) values of the LDL algorithm were obviously greater than those of the RA and ON algorithms, while the false-positive (FP) value was significantly lower in contrast to the RA and ON algorithms, showing statistically observable differences (P < 0.05); the actual resection volume of the patients in the W1 group was the closest to the ideal resection volume, which was much smaller in contrast to that of the patients in the W2 and W3 groups, showing statistical differences (P < 0.05); the positive margins of the patients in the W1 group were statistically lower than those in the W2 and W3 groups (P < 0.05). In addition, 1 patient in the W1 group was not satisfied with the cosmetic effect, 3 patients in the W2 group were not satisfied with the cosmetic effect, and 9 patients in the W3 group were not satisfied with the cosmetic effect. Finally, it was found that the ultrasound image based on the deep LDL model effectively improved the AC of tumor resection and negative margins, reduced the probability of normal tissue being removed, and improved the postoperative cosmetic effect of breast.

Highlights

Breast cancer is a malignant tumor that occurs on the ductal epithelium and terminal ductal epithelium of the breast
According to the different guidance methods used in the surgery, the research objects were rolled into three groups: 34 cases in W1 group, 34 cases in W2 group, and 34 cases in W3 group
According to the difference in intraoperative guidance methods, 102 female patients with early breast cancer were divided into three groups: 34 cases in W1 group, 34 cases in W2 group, and 34 cases in W3 group. e results suggested that the actual resection volume of the patients in the W1 group was the closest to the ideal resection volume, which was much smaller in contrast to that of the patients in the W2 and W3 groups, showing statistical differences (P < 0.05)

Summary

Introduction

Breast cancer is a malignant tumor that occurs on the ductal epithelium and terminal ductal epithelium of the breast. It can manifest as breast lumps, nipple discharge, nipple retraction, skin adhesions, skin edema, and breast pain [1]. The breast cancer was treated by removing the breasts for the classic surgical treatment, the expanded radical mastectomy, and modified radical mastectomy, which would leave women’s chest long and ugly scar after the surgery [3]. Erefore, modern clinical treatment recommends breast cancer conserving surgery. Breast-conserving surgery has the characteristics of less trauma and less pain. The current surgery is still generally based on modified radical mastectomy, breast-conserving surgery will gradually replace modified radical mastectomy as the main

Methods

Results

Conclusion