Mammary tuberculosis is a rare entity. The incidence of the disease varies from 0.025% to 4.5% of all surgically treated breast diseases. The surgical resection is required for diagnosis of mammary tuberculosis, since the clinician may confuse tuberculosis mastitis with either carcinoma or breast abscess. Treatment is the combination of resection and chemotherapy. We report a case of mammary tuberculosis diagnosed by fine-needle aspiration and biopsy (FNAB), along with a review of literature.
Abscess ; Biopsy ; Biopsy, Fine-Needle ; Breast ; Breast Diseases ; Diagnosis ; Drug Therapy ; Female ; Incidence ; Mastitis ; Tuberculosis*

Noroviruses (NoV) are the major viral pathogen causing epidemic acute gastroenteritis and outbreaks of foodborne and waterborne illness. During the local festival in Chungnam province, group food poisoning occurred outbreak by NoV infections in Jan 2019. In this study, epidemiological analysis and molecular characterization were conducted such as genotyping, phylogeny. The prevalent genotypes of food poisoning events were NoV GII.3 and GII.17, and NoV GII.3 and GII.17 isolates of this study were completely matched in nucleotide sequence comparison of capsid gene region, respectively. In underground water and stream water, various multiple genotypes of noroviruses were detected including NoV GII.3, GII.8 and GI.4 in aquatic environment of the local festival site. Among 32 worker samples, various NoVs of five genotypes (GI.7, GI.8, GII.3, GII.8, GII.17) were detected in 12 samples and expected to causing NoV contaminated by exposure to groundwater. NoV genotype GII.3, which was detected from groundwater 2, was completely consistent with that of patients and workers. Therefore, groundwater within the local festival site could be main cause of food poisoning event. Because NoV outbreaks are caused by fecal to oral transmission, proper management of sewage purification facilities, groundwater and sanitary toilets is required for many visitors, and efforts are needed to maintain clean environment.
Base Sequence ; Capsid ; Chungcheongnam-do ; Disease Outbreaks ; Epidemiologic Studies ; Foodborne Diseases ; Gastroenteritis ; Genotype ; Groundwater ; Holidays ; Humans ; Korea ; Norovirus ; Phylogeny ; Rivers ; Sewage ; Water

Objective: To investigate the feasibility of using a deep learning-based analysis of auscultation data to predict significant stenosis of arteriovenous fistulas (AVF) in patients undergoing hemodialysis requiring percutaneous transluminal angioplasty (PTA). Materials and Methods: Forty patients (24 male and 16 female; median age, 62.5 years) with dysfunctional native AVF were prospectively recruited. Digital sounds from the AVF shunt were recorded using a wireless electronic stethoscope before (pre-PTA) and after PTA (post-PTA), and the audio files were subsequently converted to mel spectrograms, which were used to construct various deep convolutional neural network (DCNN) models (DenseNet201, EfficientNetB5, and ResNet50). The performance of these models for diagnosing ≥ 50% AVF stenosis was assessed and compared. The ground truth for the presence of ≥ 50% AVF stenosis was obtained using digital subtraction angiography. Gradient-weighted class activation mapping (Grad-CAM) was used to produce visual explanations for DCNN model decisions. Results: Eighty audio files were obtained from the 40 recruited patients and pooled for the study. Mel spectrograms of “pre-PTA” shunt sounds showed patterns corresponding to abnormal high-pitched bruits with systolic accentuation observed in patients with stenotic AVF. The ResNet50 and EfficientNetB5 models yielded an area under the receiver operating characteristic curve of 0.99 and 0.98, respectively, at optimized epochs for predicting ≥ 50% AVF stenosis. However, GradCAM heatmaps revealed that only ResNet50 highlighted areas relevant to AVF stenosis in the mel spectrogram. Conclusion Mel spectrogram-based DCNN models, particularly ResNet50, successfully predicted the presence of significant AVF stenosis requiring PTA in this feasibility study and may potentially be used in AVF surveillance.

Multiple primary malignancies are defined as the presence of more than one malignant neoplasm with a distinct histology occurring at different sites in the same individual. They are classified as synchronous or metachronous according to the diagnostic time interval of different malignancies. Diagnosis of multiple primary malignancies should avoid misclassification from multifocal/multicentric tumors or recurrent/metastatic lesions.In multiple primary malignancies, with increase in the number of primary tumors, the frequency rapidly decreases. Here, we report an exceptionally rare case of a woman who was diagnosed with metachronous sporadic sextuple primary malignancies including bilateral breast cancers (gastric cancer, ovarian Sertoli-Leydig cell tumor, left breast cancer, thyroid cancer, right breast cancer, and rectal neuroendocrine tumor). The sextuple primary malignancies in this case involved 5 different organs: the stomach, ovary, thyroid, rectum, and bilateral breasts. Further studies are needed to elucidate the current epidemiologic status of patients with multiple primary malignancies.

Background: Few studies have evaluated the use of automated artificial intelligence (AI)-based pain recognition in postoperative settings or the correlation with pain intensity. In this study, various machine learning (ML)-based models using facial expressions, the analgesia nociception index (ANI), and vital signs were developed to predict postoperative pain intensity, and their performances for predicting severe postoperative pain were compared. Methods: In total, 155 facial expressions from patients who underwent gastrectomy were recorded postoperatively; one blinded anesthesiologist simultaneously recorded the ANI score, vital signs, and patient self-assessed pain intensity based on the 11-point numerical rating scale (NRS). The ML models’ area under the receiver operating characteristic curves (AUROCs) were calculated and compared using DeLong’s test. Results: ML models were constructed using facial expressions, ANI, vital signs, and different combinations of the three datasets. The ML model constructed using facial expressions best predicted an NRS ≥ 7 (AUROC 0.93) followed by the ML model combining facial expressions and vital signs (AUROC 0.84) in the test-set. ML models constructed using combined physiological signals (vital signs, ANI) performed better than models based on individual parameters for predicting NRS ≥ 7, although the AUROCs were inferior to those of the ML model based on facial expressions (all P < 0.050). Among these parameters, absolute and relative ANI had the worst AUROCs (0.69 and 0.68, respectively) for predicting NRS ≥ 7. Conclusions The ML model constructed using facial expressions best predicted severe postoperative pain (NRS ≥ 7) and outperformed models constructed from physiological signals.

PURPOSE: To decide the optimal treatment for breast cancer patients with locoregional recurrence (LRR), it is important to determine which group has the highest risk of subsequent distant metastasis (DM). We aimed to investigate the factors associated with DM in patients with LRR. METHODS: We reviewed the data of 208 patients with LRR as the first event after primary surgery for breast cancer at our institution between 1997 and 2010, to identify significant factors associated with DM. Subsequently, Kaplan-Meier curves and the Cox regression method were used to analyze the correlation between clinical factors and survival. RESULTS: DM occurred in 33.2% (68/208) of LRR patients. The median DM-free interval was 23 months. Some clinical factors were associated with DM in univariate analysis, including the type of primary surgery (p=0.026), tumor size (p=0.005), nodal status (p=0.011), and administration of initial adjuvant chemotherapy (p=0.001). In addition, regional rather than local recurrence and a disease-free interval (DFI; duration between primary surgery and LRR) < or =30 months were also significant (p<0.001 for both). However, only a shorter DFI reached significance in multiple logistic regression analysis. Cox regression analysis of DM-free survival showed that both a shorter DFI and regional recurrence were significant factors with hazard ratios of 2.1 (95% confidence interval [CI], 1.21-3.65) and 1.85 (95% CI, 1.04-3.28), respectively. CONCLUSION: DFI was the most important factor associated with subsequent DM in patients with LRR as a first event of failure.
Breast Neoplasms* ; Chemotherapy, Adjuvant ; Humans ; Logistic Models ; Neoplasm Metastasis* ; Neoplasm Recurrence, Local ; Prognosis ; Recurrence* ; Risk Factors*

PURPOSE: The 21-gene (Oncotype DX) recurrence score (RS) assay is useful in predicting the benefits of adjuvant chemotherapy for early breast cancer patients and is widely used in Western countries. However, to date, it has not gained much popularity in East Asia. We analyzed the results from five institutions' experience from using the 21-gene assay and examined the impact of assay results on decision making of chemotherapy in Korean breast cancer patients and the associations between RS and clinicopathologic characteristics. MATERIALS AND METHODS: The 21-gene assay was performed on 212 patients with estrogen receptor-positive early breast cancer in five institutions. Each center made systemic treatment decisions both before and after the knowledge of assay results. RESULTS: Among the 212 patients, 132 (62.3%) had a low RS of < 18, 60 (28.3%) had an intermediate RS of 18-30, and 20 (9.4%) had a high RS of > or = 31. Histologic grade, presence of micrometastases, Ki-67, and presence of lymphatic invasion were statistically associated with the RS results. Treatment decisions were changed in 115 of 212 patients (54.2%) in 109 of 212 (51.4%) from chemotherapy plus hormone therapy to hormone therapy, and in six of 212 (2.8%) from hormone therapy to chemotherapy plus hormone therapy. CONCLUSION: The 21-gene breast cancer assay proved to have a significant impact on treatment decision- making. The test reduces chemotherapy use in more than 50% of Korean estrogen receptor-positive, early breast cancer patients.
Breast Neoplasms* ; Chemotherapy, Adjuvant ; Decision Making ; Drug Therapy ; Estrogens ; Far East ; Humans ; Korea ; Neoplasm Micrometastasis ; Recurrence*

PURPOSE: This study investigated the role of the education level (EL) as a prognostic factor for breast cancer and analyzed the relationship between the EL and various confounding factors. MATERIALS AND METHODS: The data for 64,129 primary breast cancer patients from the Korean Breast Cancer Registry were analyzed. The EL was classified into two groups according to the education period; the high EL group (≥ 12 years) and low EL group (< 12 years). Survival analyses were performed with respect to the overall survival between the two groups. RESULTS: A high EL conferred a superior prognosis compared to a low EL in the subgroup aged > 50 years (hazard ratio, 0.626; 95% confidence interval [CI], 0.577 to 0.678) but not in the subgroup aged ≤ 50 years (hazard ratio, 0.941; 95% CI, 0.865 to 1.024). The EL was a significant independent factor in the subgroup aged > 50 years according to multivariate analyses. The high EL group showed more favorable clinicopathologic features and a higher proportion of patients in this group received lumpectomy, radiation therapy, and endocrine therapy. In the high EL group, a higher proportion of patients received chemotherapy in the subgroups with unfavorable clinicopathologic features. The EL was a significant prognosticator across all molecular subtypes of breast cancer. CONCLUSION: The EL is a strong independent prognostic factor for breast cancer in the subgroup aged > 50 years regardless of the molecular subtype, but not in the subgroup aged ≤ 50 years. Favorable clinicopathologic features and active treatments can explain the main causality of the superior prognosis in the high EL group.
Breast Neoplasms* ; Breast* ; Drug Therapy ; Education* ; Educational Status ; Humans ; Mastectomy, Segmental ; Multivariate Analysis ; Prognosis ; Survival Analysis

Breast Neoplasms ; Breast ; Classification ; Genome ; Methylation ; Multivariate Analysis ; Mutation Rate ; Phenobarbital ; Prognosis ; ras Proteins ; RNA ; RNA, Messenger

Sparganosis is a parasitic infestation caused by sparganum, a plerocercoid tapeworm larva of the genus Spirometra. Since the first case of human sparganosis reported in 1908, sparganosis has been a global disease, and is common in China, Japan, and Southeast Asian countries. Consumption of raw snakes, frogs, fish, or drinking contaminated beverages are sources of human infections. Human sparganosis usually manifests in subcutaneous fat in areas such as the abdomen, genitourinary tract, and limbs. Breast sparganosis cases are rare, representing less than 2% of total cases of human infections. Complete surgical extraction of the sparganum is the treatment of choice. Because of the rarity of the disease, clinical suspicion is vital to reach the diagnosis of breast sparganosis. Here we report 2 rare cases of breast sparganosis presenting with a painless breast lump, both treated with surgical excision and sparganum extraction.
Abdomen ; Asian Continental Ancestry Group ; Beverages ; Breast ; Cestoda ; China ; Diagnosis ; Drinking ; Extremities ; Humans ; Japan ; Larva ; Snakes ; Sparganosis ; Sparganum ; Spirometra ; Subcutaneous Fat