Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Background/Aims: The Korean guidelines for Helicobacter pylori treatment were revised in 2020, however, the extent of adherence to these guidelines in clinical practice remains unclear. Herein, we initiated a prospective, nationwide, multicenter registry study in 2021 to evaluate the current management of H.pylori infection in Korea. Methods: This interim report describes the adherence to the revised guidelines and their impact on firstline eradication rates. Data on patient demographics, diagnoses, treatments, and eradication outcomes were collected using a web-based electronic case report form. Results: A total of 7,261 patients from 66 hospitals who received first-line treatment were analyzed.The modified intention-to-treat eradication rate for first-line treatment was 81.0%, with 80.4% of the prescriptions adhering to the revised guidelines. The most commonly prescribed regimen was the 14-day clarithromycin-based triple therapy (CTT; 42.0%), followed by tailored therapy (TT; 21.2%), 7-day CTT (14.1%), and 10-day concomitant therapy (CT; 10.1%). Time-trend analysis demonstrated significant increases in guideline adherence and the use of 10-day CT and TT, along with a decrease in the use of 7-day CTT (all p<0.001). Multivariate logistic regression analysis revealed that guideline adherence was significantly associated with first-line eradication success (odds ratio, 2.03; 95% confidence interval, 1.61 to 2.56; p<0.001). Conclusions The revised guidelines for the treatment of H. pylori infection have been increasingly adopted in routine clinical practice in Korea, which may have contributed to improved first-line eradication rates. Notably, the 14-day CTT, 10-day CT, and TT regimens are emerging as the preferred first-line treatment options among Korean physicians.

Pancreatic ductal adenocarcinoma (PDAC) exhibits an altered metabolic profile compared to normal pancreatic tissue. However, studies on actual pancreatic tissues are limited. Untargeted metabolomics analysis was conducted on 54 pairs of tumor and matched normal tissues. Taurine levels were validated via immunohistochemistry (IHC) on separate PDAC and normal tissues.Bioinformatics analysis of transcriptomics and proteomics data evaluated genes associated with taurine metabolism. Identified taurine-associated gene was validated through gene modulation. Clinical implications were evaluated using patient data. Metabolomics analysis showed a 2.51-fold increase in taurine in PDAC compared to normal tissues (n=54). IHC confirmed this in independent samples (n=99 PDAC, 19 normal). Bioinformatics identified 2-aminoethanethiol dioxygenase (ADO) as a key gene modulating taurine metabolism. IHC on a tissue microarray (39 PDAC, 10 normal) confirmed elevated ADO in PDAC. The ADOTaurine axis correlated with PDAC recurrence and disease-free survival. ADO knockdown reduced cancer cell proliferation and tumor growth in a mouse xenograft model. The MEK-related signaling pathway is suggested to be modulated by ADO-Taurine metabolism. Our multi-omics investigation revealed elevated taurine synthesis mediated by ADO upregulation in PDAC. The ADOTaurine axis may serve as a biomarker for PDAC prognosis and a therapeutic target.

Purpose: This study aimed to evaluate long-term treatment outcomes in patients with localized gastric mucosa-associated lymphoid tissue (MALT) lymphoma treated with radiotherapy (RT). Materials and Methods: A total of 229 patients who received RT in 10 tertiary hospitals between 2010 and 2019 were included in this multicenter analysis. Response after RT was based on esophagogastroduodenoscopy after RT. Locoregional relapse-free survival (LRFS) and disease-free survival (DFS), and overall survival (OS) were evaluated. Results: After a median follow-up time of 93.2 months, 5-year LRFS, DFS, and OS rates were 92.8%, 90.4%, and 96.1%, respectively. LRFS, DFS, and OS rates at 10 years were 90.3%, 87.7%, and 92.8%, respectively. Of 229 patients, 228 patients (99.6%) achieved complete remission after RT. Five-year LRFS was significantly lower in patients with stage IIE than in those with stage IE (77.4% vs. 94.2%, p=0.047). Patients with age ≥ 60 had significantly lower LRFS than patients with age < 60 (89.3% vs. 95.1%, p=0.003). In the multivariate analysis, old age (≥ 60 years) was a poor prognostic factor for LRFS (hazard ratio, 3.72; confidence interval, 1.38 to 10.03; p=0.009). Grade 2 or higher gastritis was reported in 69 patients (30.1%). Secondary malignancies including gastric adenocarcinoma, malignant lymphoma, lung cancer, breast cancer, and prostate cancer were observed in 11 patients (4.8%) after RT. Conclusion Patients treated with RT for localized gastric MALT lymphoma showed favorable 10-year outcomes. Radiation therapy is an effective treatment without an increased risk of secondary cancer. The toxicity for RT to the stomach is not high.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Background: Healthcare-associated infections impose a significant burden on antibiotic usage, healthcare expenditures, and morbidity. Therefore, it is crucial to revise policies to minimize such losses. This nationwide survey aimed to evaluate infection prevention and control (IPC) components in healthcare facilities and encourage improvements in acute care hospitals with inadequate infection prevention settings. This study aims to enhance the infection control capabilities of healthcare facilities. Methods: From December 27, 2021, to May 13, 2022, we conducted a survey of 1,767 acute care hospitals in the Republic of Korea. A survey was conducted to evaluate the infection control components in 1,767 acute care hospitals. Infection control officers provided direct responses to a systematically developed questionnaire. Subsequently, 10% of the respondents were randomly selected for the site investigation. Results: Overall, 1,197 (67.7%) hospitals responded to the online survey. On-site investigations were conducted at 125 hospitals. Hospitals with ≥ 150 beds are advised to have an IPC team under Article 3 of the Medical Service Act; however, only 87.0% (598/687) of hospitals with ≥ 100 beds had one. Conversely, 22.7% (116/510) of hospitals with < 100 beds had an IPC team. Regulations for hand hygiene, waste management, healthcare worker protection and safety, environmental cleaning, standard precautions, and prevention of the transmission of multidrug-resistant pathogens were present in 84.2%, 80.1%, 77.4%, 76.2%, 75.8%, and 63.5% of the hospitals, respectively. Hospitals with < 100 beds had low availability of all categories of standard operating procedures. Conclusion This study is the first national survey of acute care hospitals in the Republic of Korea. The data presented in the current study will improve the understanding of IPC status and will help establish a survey system. Our survey provides a basis for improving policies related to IPC in healthcare facilities.

Background: Healthcare-associated infections impose a significant burden on antibiotic usage, healthcare expenditures, and morbidity. Therefore, it is crucial to revise policies to minimize such losses. This nationwide survey aimed to evaluate infection prevention and control (IPC) components in healthcare facilities and encourage improvements in acute care hospitals with inadequate infection prevention settings. This study aims to enhance the infection control capabilities of healthcare facilities. Methods: From December 27, 2021, to May 13, 2022, we conducted a survey of 1,767 acute care hospitals in the Republic of Korea. A survey was conducted to evaluate the infection control components in 1,767 acute care hospitals. Infection control officers provided direct responses to a systematically developed questionnaire. Subsequently, 10% of the respondents were randomly selected for the site investigation. Results: Overall, 1,197 (67.7%) hospitals responded to the online survey. On-site investigations were conducted at 125 hospitals. Hospitals with ≥ 150 beds are advised to have an IPC team under Article 3 of the Medical Service Act; however, only 87.0% (598/687) of hospitals with ≥ 100 beds had one. Conversely, 22.7% (116/510) of hospitals with < 100 beds had an IPC team. Regulations for hand hygiene, waste management, healthcare worker protection and safety, environmental cleaning, standard precautions, and prevention of the transmission of multidrug-resistant pathogens were present in 84.2%, 80.1%, 77.4%, 76.2%, 75.8%, and 63.5% of the hospitals, respectively. Hospitals with < 100 beds had low availability of all categories of standard operating procedures. Conclusion This study is the first national survey of acute care hospitals in the Republic of Korea. The data presented in the current study will improve the understanding of IPC status and will help establish a survey system. Our survey provides a basis for improving policies related to IPC in healthcare facilities.