Purpose: To identify US findings suggestive of malignancy in thyroid nodules with follicular lesions of undetermined significance (FLUS) or follicular neoplasm (FN) on fine-needle aspiration cytology (FNAC) and evaluate the diagnostic performance. Materials and Methods: Seventy FLUS (n = 57) or FN (n = 13) nodules on FNAC that underwent surgical excision between February 2018 and November 2020 were selected. US findings were retrospectively reviewed. Orientation, margin, echogenicity, calcification, additional findings of the rim, echogenicity, heterogeneity of the solid portion, and the ratio of anterior posterior diameter to lateral diameter (criteria) were assessed. The diagnostic performances of US findings, criteria, and the Korean Society of Thyroid Radiology Thyroid Imaging Reporting and Data System (K-TIRADS) were evaluated using logistic regression analysis. Results: Microcalcification, homogeneous solid echotexture, and thickened rims were suggestive of malignancy. Our criteria showed a highest area under the ROC curve (AUC) value of 0.771, sensitivity of 97.14%, accuracy of 77.14%, positive predictive value of 93.33%, negative predictive value of 95.24%, and specificity of 97.14%. The criteria showed a significantly higher AUC value than K-TIRADS. Conclusion US findings of homogenous solid portions, thick rims, and microcalcifications suggested malignancy in nodules with FLUS or FN on FNAC. These additional US findings could improve the diagnostic performance of K-TIRADS.

Purpose: To identify US findings suggestive of malignancy in thyroid nodules with follicular lesions of undetermined significance (FLUS) or follicular neoplasm (FN) on fine-needle aspiration cytology (FNAC) and evaluate the diagnostic performance. Materials and Methods: Seventy FLUS (n = 57) or FN (n = 13) nodules on FNAC that underwent surgical excision between February 2018 and November 2020 were selected. US findings were retrospectively reviewed. Orientation, margin, echogenicity, calcification, additional findings of the rim, echogenicity, heterogeneity of the solid portion, and the ratio of anterior posterior diameter to lateral diameter (criteria) were assessed. The diagnostic performances of US findings, criteria, and the Korean Society of Thyroid Radiology Thyroid Imaging Reporting and Data System (K-TIRADS) were evaluated using logistic regression analysis. Results: Microcalcification, homogeneous solid echotexture, and thickened rims were suggestive of malignancy. Our criteria showed a highest area under the ROC curve (AUC) value of 0.771, sensitivity of 97.14%, accuracy of 77.14%, positive predictive value of 93.33%, negative predictive value of 95.24%, and specificity of 97.14%. The criteria showed a significantly higher AUC value than K-TIRADS. Conclusion US findings of homogenous solid portions, thick rims, and microcalcifications suggested malignancy in nodules with FLUS or FN on FNAC. These additional US findings could improve the diagnostic performance of K-TIRADS.

Purpose: To identify US findings suggestive of malignancy in thyroid nodules with follicular lesions of undetermined significance (FLUS) or follicular neoplasm (FN) on fine-needle aspiration cytology (FNAC) and evaluate the diagnostic performance. Materials and Methods: Seventy FLUS (n = 57) or FN (n = 13) nodules on FNAC that underwent surgical excision between February 2018 and November 2020 were selected. US findings were retrospectively reviewed. Orientation, margin, echogenicity, calcification, additional findings of the rim, echogenicity, heterogeneity of the solid portion, and the ratio of anterior posterior diameter to lateral diameter (criteria) were assessed. The diagnostic performances of US findings, criteria, and the Korean Society of Thyroid Radiology Thyroid Imaging Reporting and Data System (K-TIRADS) were evaluated using logistic regression analysis. Results: Microcalcification, homogeneous solid echotexture, and thickened rims were suggestive of malignancy. Our criteria showed a highest area under the ROC curve (AUC) value of 0.771, sensitivity of 97.14%, accuracy of 77.14%, positive predictive value of 93.33%, negative predictive value of 95.24%, and specificity of 97.14%. The criteria showed a significantly higher AUC value than K-TIRADS. Conclusion US findings of homogenous solid portions, thick rims, and microcalcifications suggested malignancy in nodules with FLUS or FN on FNAC. These additional US findings could improve the diagnostic performance of K-TIRADS.

Purpose: This study aimed to systematically evaluate the effectiveness of case-based learning (CBL) within a basic-clinical integrated educational program using the Context, Input, Process, and Product (CIPP) evaluation model. Methods: The CBL program was integrated into the Pharmacology–Clinical Case Practice component of the pharmacology course, a mandatory course for first-year medical students. To evaluate the program, a CIPP model-based questionnaire was developed, assessing needs, goals, resources, educational management, and outcomes. To ensure the reliability and validity of the variables, factor analysis was performed, reducing an initial set of 28 items to 18 final observation variables distributed across four factors. The survey, designed to measure learner satisfaction, was administered to 37 students who participated in the Pharmacology–Clinical Case Practice course during the first semester of 2022. Results: Participants rated their satisfaction with the CBL program based on the CIPP model (on a 5-point scale), giving an average score of 4.17. This suggests that learners who followed the CBL program combining basic and clinical components generally found the program operationally effective with positive outcomes. Conclusion The teaching model and evaluation model applied in this study can be utilized in various majors when operating CBL classes that link basic and clinical education in medical schools in the future.

Purpose: This study aimed to systematically evaluate the effectiveness of case-based learning (CBL) within a basic-clinical integrated educational program using the Context, Input, Process, and Product (CIPP) evaluation model. Methods: The CBL program was integrated into the Pharmacology–Clinical Case Practice component of the pharmacology course, a mandatory course for first-year medical students. To evaluate the program, a CIPP model-based questionnaire was developed, assessing needs, goals, resources, educational management, and outcomes. To ensure the reliability and validity of the variables, factor analysis was performed, reducing an initial set of 28 items to 18 final observation variables distributed across four factors. The survey, designed to measure learner satisfaction, was administered to 37 students who participated in the Pharmacology–Clinical Case Practice course during the first semester of 2022. Results: Participants rated their satisfaction with the CBL program based on the CIPP model (on a 5-point scale), giving an average score of 4.17. This suggests that learners who followed the CBL program combining basic and clinical components generally found the program operationally effective with positive outcomes. Conclusion The teaching model and evaluation model applied in this study can be utilized in various majors when operating CBL classes that link basic and clinical education in medical schools in the future.

Purpose: This study aimed to systematically evaluate the effectiveness of case-based learning (CBL) within a basic-clinical integrated educational program using the Context, Input, Process, and Product (CIPP) evaluation model. Methods: The CBL program was integrated into the Pharmacology–Clinical Case Practice component of the pharmacology course, a mandatory course for first-year medical students. To evaluate the program, a CIPP model-based questionnaire was developed, assessing needs, goals, resources, educational management, and outcomes. To ensure the reliability and validity of the variables, factor analysis was performed, reducing an initial set of 28 items to 18 final observation variables distributed across four factors. The survey, designed to measure learner satisfaction, was administered to 37 students who participated in the Pharmacology–Clinical Case Practice course during the first semester of 2022. Results: Participants rated their satisfaction with the CBL program based on the CIPP model (on a 5-point scale), giving an average score of 4.17. This suggests that learners who followed the CBL program combining basic and clinical components generally found the program operationally effective with positive outcomes. Conclusion The teaching model and evaluation model applied in this study can be utilized in various majors when operating CBL classes that link basic and clinical education in medical schools in the future.

Purpose: This study aimed to systematically evaluate the effectiveness of case-based learning (CBL) within a basic-clinical integrated educational program using the Context, Input, Process, and Product (CIPP) evaluation model. Methods: The CBL program was integrated into the Pharmacology–Clinical Case Practice component of the pharmacology course, a mandatory course for first-year medical students. To evaluate the program, a CIPP model-based questionnaire was developed, assessing needs, goals, resources, educational management, and outcomes. To ensure the reliability and validity of the variables, factor analysis was performed, reducing an initial set of 28 items to 18 final observation variables distributed across four factors. The survey, designed to measure learner satisfaction, was administered to 37 students who participated in the Pharmacology–Clinical Case Practice course during the first semester of 2022. Results: Participants rated their satisfaction with the CBL program based on the CIPP model (on a 5-point scale), giving an average score of 4.17. This suggests that learners who followed the CBL program combining basic and clinical components generally found the program operationally effective with positive outcomes. Conclusion The teaching model and evaluation model applied in this study can be utilized in various majors when operating CBL classes that link basic and clinical education in medical schools in the future.

Background/Aims: Chronic hepatitis B (CHB) is a risk factor for non-Hodgkin lymphoma (NHL). Our recent study suggested that antiviral treatment may reduce the incidence of NHL in CHB patients. This study compared the prognoses of hepatitis B virus (HBV)-associated diffuse large B-cell lymphoma (DLBCL) patients receiving antiviral treatment and HBV-unassociated DLBCL patients. Methods: This study comprised 928 DLBCL patients who were treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) at two referral centers in Korea. All patients with CHB received antiviral treatment. Time-to-progression (TTP) and overall survival (OS) were the primary and secondary endpoints, respectively. Results: Among the 928 patients in this study, 82 were hepatitis B surface antigen (HBsAg)-positive (the CHB group) and 846 were HBsAg-negative (the non-CHB group). The median follow-up time was 50.5 months (interquartile range [IQR]=25.6–69.7 months). Multivariable analyses showed longer TTP in the CHB group than the non-CHB group both before inverse probability of treatment weighting (IPTW; adjusted hazard ratio [aHR]=0.49, 95% confidence interval [CI]=0.29–0.82, p=0.007) and after IPTW (aHR=0.42, 95% CI=0.26–0.70, p<0.001). The CHB group also had a longer OS than the non-CHB group both before IPTW (HR=0.55, 95% CI=0.33–0.92, log-rank p=0.02) and after IPTW (HR=0.53, 95% CI=0.32–0.99, log-rank p=0.02). Although liver-related deaths did not occur in the non-CHB group, two deaths occurred in the CHB group due to hepatocellular carcinoma and acute liver failure, respectively. Conclusions Our findings indicate that HBV-associated DLBCL patients receiving antiviral treatment have significantly longer TTP and OS after R-CHOP treatment than HBV-unassociated DLBCL patients.

Purpose: We propose the Lifelog Bigdata Platform as a sustainable digital healthcare system based on individual-centric lifelog datasets and describe the standardization of lifelog and clinical data in its full-cycle management system. Materials and Methods: The Lifelog Bigdata Platform was developed by Yonsei Wonju Health System on the cloud to support digital healthcare and precision medicine. It consists of five core components: data acquisition system, de-identification of individual information, lifelog integration, analyzer, and service. We designed a gathering system into a dedicated virtual machine to save lifelog or clinical outcomes and established standard guidelines for maintaining the quality of gathering procedures. We used standard integration keys to integrate the lifelog and clinical data. Metadata were generated from the data warehouse after loading combined or fragmented data on it. We analyzed the de-identified lifelog and clinical data using the lifelog analyzer to prevent and manage acute and chronic diseases through providing results of statistics on analysis. Results: The big data centers were built in four hospitals and seven companies for integrating lifelog and clinical data to develop the Lifelog Bigdata Platform. We integrated and loaded lifelog big data and clinical data for 3 years. In the first year, we uploaded 94 types of data on the platform with a total capacity of 221 GB. Conclusion The Lifelog Bigdata Platform is the first to combine lifelog and clinical data. The proposed standardization guidelines can be used for future platforms to achieve a virtuous cycle structure of lifelogging big data and an industrial ecosystem.

Purpose: This study evaluated how artificial intelligence-based computer-assisted diagnosis (AICAD) for breast ultrasonography (US) influences diagnostic performance and agreement between radiologists with varying experience levels in different workflows. Methods: Images of 492 breast lesions (200 malignant and 292 benign masses) in 472 women taken from April 2017 to June 2018 were included. Six radiologists (three inexperienced [<1 year of experience] and three experienced [10-15 years of experience]) individually reviewed US images with and without the aid of AI-CAD, first sequentially and then simultaneously. Diagnostic performance and interobserver agreement were calculated and compared between radiologists and AI-CAD. Results: After implementing AI-CAD, the specificity, positive predictive value (PPV), and accuracy significantly improved, regardless of experience and workflow (all P<0.001, respectively). The overall area under the receiver operating characteristic curve significantly increased in simultaneous reading, but only for inexperienced radiologists. The agreement for Breast Imaging Reporting and Database System (BI-RADS) descriptors generally increased when AI-CAD was used (κ=0.29-0.63 to 0.35-0.73). Inexperienced radiologists tended to concede to AI-CAD results more easily than experienced radiologists, especially in simultaneous reading (P<0.001). The conversion rates for final assessment changes from BI-RADS 2 or 3 to BI-RADS higher than 4a or vice versa were also significantly higher in simultaneous reading than sequential reading (overall, 15.8% and 6.2%, respectively; P<0.001) for both inexperienced and experienced radiologists. Conclusion Using AI-CAD to interpret breast US improved the specificity, PPV, and accuracy of radiologists regardless of experience level. AI-CAD may work better in simultaneous reading to improve diagnostic performance and agreement between radiologists, especially for inexperienced radiologists.