Park CW, et al. J Korean Med Sci. 2020 Oct;35(42):e379. https://doi.org/10.3346/jkms.2020.35.e379

Breast-conserving surgery is the most frequently performed surgical procedure for breast cancer treatment. However, 34.0% of patients with breast cancer in the Republic of Korea require mastectomy.¹ Nipple-sparing mastectomy (NSM), which evolved from skin-sparing mastectomy, is characterized by the preservation of the entire nipple-areola complex (NAC) and breast skin envelope despite removal of the mammary tissue.

Breast cancer is a common cancer among women, and screening mammography is the primary tool for diagnosing this condition. Recent advancements in deep-learning technologies have triggered the implementation of research studies via mammography. Semi-supervised or unsupervised methods are often used to overcome the limitations of supervised learning, such as manpower and time, for labeling in clinical situations where abnormal data are significantly lacking. Accordingly, we proposed a generative model that uses a state-of-the-art generative network (StyleGAN2) to create high-quality synthetic mammographic images and an anomaly detection method to detect breast cancer on mammograms in unsupervised methods. The generation model was trained via only normal mammograms and breast cancer classification was performed via anomaly detection using 50 breast cancer and 50 normal mammograms that did not overlap with the dataset for generative model learning. Our generative model has shown comparable fidelity to real images, and the anomaly detection method via this generative model showed high sensitivity, demonstrating its potential for breast cancer screening. This method could differentiate between normal and cancer-positive mammogram and help overcome the weakness of current supervised methods.

Breast cancer is one of the major female health problems worldwide. Although there is growing evidence indicating that air pollution increases the risk of breast cancer, there is still inconsistency among previous studies. Unlike the previous studies those had case-control or cohort study designs, we performed a nationwide, whole-population census study. In all 252 administrative districts in South Korea, the associations between ambient NO₂ and particulate matter 10 (PM₁₀) concentration, and age-adjusted breast cancer mortality rate in females (from 2005 to 2016, N_mortality = 23,565), and incidence rate (from 2004 to 2013, N_incidence = 133,373) were investigated via multivariable beta regression. Population density, altitude, rate of higher education, smoking rate, obesity rate, parity, unemployment rate, breastfeeding rate, oral contraceptive usage rate, and Gross Regional Domestic Product per capita were considered as potential confounders. Ambient air pollutant concentrations were positively and significantly associated with the breast cancer incidence rate: per 100 ppb CO increase, Odds Ratio OR = 1.08 (95% Confidence Interval CI = 1.06–1.10), per 10 ppb NO₂, OR = 1.14 (95% CI = 1.12–1.16), per 1 ppb SO₂, OR = 1.04 (95% CI = 1.02–1.05), per 10 µg/m³ PM₁₀, OR = 1.13 (95% CI = 1.09–1.17). However, no significant association between the air pollutants and the breast cancer mortality rate was observed except for PM₁₀: per 10 µg/m³ PM₁₀, OR = 1.05 (95% CI = 1.01–1.09).

The surgical management of breast cancer has evolved substantially in recent decades. Breast-conserving surgery has replaced radical treatment approaches and is now an established standard of care. However, there has been a reversing trend in which the mastectomy rate is increasing owing to a growing preference for postmastectomy breast reconstruction and a paradigm shift in mastectomy patterns.^1,2 Nipple-sparing mastectomy (NSM) or skin-sparing mastectomy (SSM) with immediate breast reconstruction (IBR) has gained popularity in the treatment of selected patients with breast cancer owing to increasing recognition of the improved aesthetic results and quality of life without compromising oncologic safety.³