This study explores the development, roles, and key initiatives of the Regional Environmental Health Centers in Korea, detailing their evolution through four distinct phases and their impact on environmental health policy and local governance. It chronicles the establishment and transformation of these centers from their inception in May 2007, through four developmental stages. Originally named Environmental Disease Research Centers, they were subsequently renamed Environmental Health Centers following legislative changes. The analysis includes the expansion in the number of centers, the transfer of responsibilities to local governments, and the launch of significant projects such as the Korean Children’s Environmental Health Study (Ko-CHENS ). During the initial phase (May 2007–February 2009), the 10 centers concentrated on research-driven activities, shifting from a media-centered to a receptor-centered approach. In the second phase, prompted by the enactment of the Environmental Health Act, six additional centers were established, broadening their scope to address national environmental health issues. The third phase introduced Ko-CHENS, a 20-year national cohort project designed to influence environmental health policy by integrating research findings into policy frameworks. The fourth phase marked a decentralization of authority, empowering local governments and redefining the centers' roles to focus on regional environmental health challenges. The Regional Environmental Health Centers have significantly evolved and now play a crucial role in addressing local environmental health issues and supporting local government policies. Their capacity to adapt and respond to region-specific challenges is essential for the effective implementation of environmental health policies, reflecting geographical, socioeconomic, and demographic differences.

Purpose: This study investigated the recurrence patterns and timing in patients with pathologic N2 (pN2) non-small cell lung cancer (NSCLC) according to the residual tumor (R) descriptor proposed by the International Association for the Study of Lung Cancer (IASLC). Materials and Methods: From 2004 to 2021, patients with pN2 NSCLC who underwent anatomical resection were analyzed according to the IASLC R criteria using medical records from a single center. Survival analysis was performed using Cox proportional hazards models. Recurrence patterns between complete (R0) and uncertain resections (R[un]) were compared. Results: In total, 1,373 patients were enrolled in this study: 576 (42.0%) in R0, 286 (20.8%) in R(un), and 511 (37.2%) in R1/R2 according to the IASLC R criteria. The most common reason for R(un) classification was positivity for the highest lymph node (88.8%). In multivariable analysis, the hazard ratios for recurrence in R(un) and R1/R2 compared to R0 were 1.18 (95% confidence interval [CI], 0.96–1.46) and 1.58 (1.31–1.90), respectively. The hazard rate curves displayed similar patterns among groups, peaking at approximately 12 months after surgery. There was a significant difference in distant recurrence patterns between R0 and R(un). Further analysis after stratification with the IASLC N2 descriptor showed significant differences in distant recurrence patterns between R0 and R(un) in patients pN2a1 and pN2a2 disease, but not in those with pN2b disease. Conclusion The IASLC R criteria has prognostic relevance in patients with pN2 NSCLC. R(un) is a highly heterogeneous group, and the involvement of the highest mediastinal lymph node can affect distant recurrence patterns.

Purpose: The International Association for the Study of Lung Cancer suggests further subdivision of pathologic N (pN) category in non–small-cell lung cancer (NSCLC) by incorporating the location and number of involved lymph node (LN) stations. We reclassified patients with the station-based N2b disease into single-zone and multi-zone N2b groups and compared survival outcomes between the groups. Materials and Methods: This retrospective study included patients with pN2 NSCLC who underwent lobectomy from 2006 to 2019. The N2 disease was subdivided into four categories: single-station N2 without N1 (N2a1), single-station N2 with N1 (N2a2), multiple-station N2 with single zone involvement (single-zone N2b), and multiple-station N2 with multiple zone involvement (multi-zone N2b). LN zones included in the subdivision of N2 disease were upper mediastinal, lower mediastinal, aortopulmonary, and subcarinal. Results: Among 996 eligible patients, 211 (21.2%), 394 (39.6%), and 391 (39.3%) were confirmed to have pN2a1, pN2a2, and pN2b disease, respectively. In multivariable analysis after adjustment for sex, age, pT category, and adjuvant chemotherapy, overall survival was significantly better with single-zone N2b disease (n=125, 12.6%) than with multi-zone N2b disease (n=266, 26.7%) (hazard ratio [HR], 0.67; 95% confidence interval [CI], 0.49 to 0.90; p=0.009) and was comparable to that of N2a2 disease (HR, 1.12; 95% CI, 0.83 to 1.49; p=0.46). Conclusion Prognosis of single-zone LN metastasis was better than that of multiple-zone LN metastasis in patients with N2b NSCLC. Along with the station-based N descriptors, zone-based descriptors might ensure optimal staging, enabling the most appropriate decision-making on adjuvant therapy for patients with pN2 NSCLC.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

This study explores the development, roles, and key initiatives of the Regional Environmental Health Centers in Korea, detailing their evolution through four distinct phases and their impact on environmental health policy and local governance. It chronicles the establishment and transformation of these centers from their inception in May 2007, through four developmental stages. Originally named Environmental Disease Research Centers, they were subsequently renamed Environmental Health Centers following legislative changes. The analysis includes the expansion in the number of centers, the transfer of responsibilities to local governments, and the launch of significant projects such as the Korean Children’s Environmental Health Study (Ko-CHENS ). During the initial phase (May 2007–February 2009), the 10 centers concentrated on research-driven activities, shifting from a media-centered to a receptor-centered approach. In the second phase, prompted by the enactment of the Environmental Health Act, six additional centers were established, broadening their scope to address national environmental health issues. The third phase introduced Ko-CHENS, a 20-year national cohort project designed to influence environmental health policy by integrating research findings into policy frameworks. The fourth phase marked a decentralization of authority, empowering local governments and redefining the centers' roles to focus on regional environmental health challenges. The Regional Environmental Health Centers have significantly evolved and now play a crucial role in addressing local environmental health issues and supporting local government policies. Their capacity to adapt and respond to region-specific challenges is essential for the effective implementation of environmental health policies, reflecting geographical, socioeconomic, and demographic differences.

This study explores the development, roles, and key initiatives of the Regional Environmental Health Centers in Korea, detailing their evolution through four distinct phases and their impact on environmental health policy and local governance. It chronicles the establishment and transformation of these centers from their inception in May 2007, through four developmental stages. Originally named Environmental Disease Research Centers, they were subsequently renamed Environmental Health Centers following legislative changes. The analysis includes the expansion in the number of centers, the transfer of responsibilities to local governments, and the launch of significant projects such as the Korean Children’s Environmental Health Study (Ko-CHENS ). During the initial phase (May 2007–February 2009), the 10 centers concentrated on research-driven activities, shifting from a media-centered to a receptor-centered approach. In the second phase, prompted by the enactment of the Environmental Health Act, six additional centers were established, broadening their scope to address national environmental health issues. The third phase introduced Ko-CHENS, a 20-year national cohort project designed to influence environmental health policy by integrating research findings into policy frameworks. The fourth phase marked a decentralization of authority, empowering local governments and redefining the centers' roles to focus on regional environmental health challenges. The Regional Environmental Health Centers have significantly evolved and now play a crucial role in addressing local environmental health issues and supporting local government policies. Their capacity to adapt and respond to region-specific challenges is essential for the effective implementation of environmental health policies, reflecting geographical, socioeconomic, and demographic differences.

Purpose: This study investigated the recurrence patterns and timing in patients with pathologic N2 (pN2) non-small cell lung cancer (NSCLC) according to the residual tumor (R) descriptor proposed by the International Association for the Study of Lung Cancer (IASLC). Materials and Methods: From 2004 to 2021, patients with pN2 NSCLC who underwent anatomical resection were analyzed according to the IASLC R criteria using medical records from a single center. Survival analysis was performed using Cox proportional hazards models. Recurrence patterns between complete (R0) and uncertain resections (R[un]) were compared. Results: In total, 1,373 patients were enrolled in this study: 576 (42.0%) in R0, 286 (20.8%) in R(un), and 511 (37.2%) in R1/R2 according to the IASLC R criteria. The most common reason for R(un) classification was positivity for the highest lymph node (88.8%). In multivariable analysis, the hazard ratios for recurrence in R(un) and R1/R2 compared to R0 were 1.18 (95% confidence interval [CI], 0.96–1.46) and 1.58 (1.31–1.90), respectively. The hazard rate curves displayed similar patterns among groups, peaking at approximately 12 months after surgery. There was a significant difference in distant recurrence patterns between R0 and R(un). Further analysis after stratification with the IASLC N2 descriptor showed significant differences in distant recurrence patterns between R0 and R(un) in patients pN2a1 and pN2a2 disease, but not in those with pN2b disease. Conclusion The IASLC R criteria has prognostic relevance in patients with pN2 NSCLC. R(un) is a highly heterogeneous group, and the involvement of the highest mediastinal lymph node can affect distant recurrence patterns.

Purpose: The International Association for the Study of Lung Cancer suggests further subdivision of pathologic N (pN) category in non–small-cell lung cancer (NSCLC) by incorporating the location and number of involved lymph node (LN) stations. We reclassified patients with the station-based N2b disease into single-zone and multi-zone N2b groups and compared survival outcomes between the groups. Materials and Methods: This retrospective study included patients with pN2 NSCLC who underwent lobectomy from 2006 to 2019. The N2 disease was subdivided into four categories: single-station N2 without N1 (N2a1), single-station N2 with N1 (N2a2), multiple-station N2 with single zone involvement (single-zone N2b), and multiple-station N2 with multiple zone involvement (multi-zone N2b). LN zones included in the subdivision of N2 disease were upper mediastinal, lower mediastinal, aortopulmonary, and subcarinal. Results: Among 996 eligible patients, 211 (21.2%), 394 (39.6%), and 391 (39.3%) were confirmed to have pN2a1, pN2a2, and pN2b disease, respectively. In multivariable analysis after adjustment for sex, age, pT category, and adjuvant chemotherapy, overall survival was significantly better with single-zone N2b disease (n=125, 12.6%) than with multi-zone N2b disease (n=266, 26.7%) (hazard ratio [HR], 0.67; 95% confidence interval [CI], 0.49 to 0.90; p=0.009) and was comparable to that of N2a2 disease (HR, 1.12; 95% CI, 0.83 to 1.49; p=0.46). Conclusion Prognosis of single-zone LN metastasis was better than that of multiple-zone LN metastasis in patients with N2b NSCLC. Along with the station-based N descriptors, zone-based descriptors might ensure optimal staging, enabling the most appropriate decision-making on adjuvant therapy for patients with pN2 NSCLC.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

This study explores the development, roles, and key initiatives of the Regional Environmental Health Centers in Korea, detailing their evolution through four distinct phases and their impact on environmental health policy and local governance. It chronicles the establishment and transformation of these centers from their inception in May 2007, through four developmental stages. Originally named Environmental Disease Research Centers, they were subsequently renamed Environmental Health Centers following legislative changes. The analysis includes the expansion in the number of centers, the transfer of responsibilities to local governments, and the launch of significant projects such as the Korean Children’s Environmental Health Study (Ko-CHENS ). During the initial phase (May 2007–February 2009), the 10 centers concentrated on research-driven activities, shifting from a media-centered to a receptor-centered approach. In the second phase, prompted by the enactment of the Environmental Health Act, six additional centers were established, broadening their scope to address national environmental health issues. The third phase introduced Ko-CHENS, a 20-year national cohort project designed to influence environmental health policy by integrating research findings into policy frameworks. The fourth phase marked a decentralization of authority, empowering local governments and redefining the centers' roles to focus on regional environmental health challenges. The Regional Environmental Health Centers have significantly evolved and now play a crucial role in addressing local environmental health issues and supporting local government policies. Their capacity to adapt and respond to region-specific challenges is essential for the effective implementation of environmental health policies, reflecting geographical, socioeconomic, and demographic differences.