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/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.

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.

Purpose: Claudin 18.2 (CLDN18.2) has emerged as a promising therapeutic target for CLDN18.2-expressing gastric cancer (GC). We sought to examine the heterogeneity of CLDN18.2 expression between primary GC (PGC) and metastatic GC (MGC) using various scoring methods. Materials and Methods: We retrospectively analyzed data from 102 patients with pathologically confirmed paired primary and metastatic gastric or gastroesophageal junction adenocarcinomas. CLDN18.2 expression was evaluated through immunohistochemistry on formalin-fixed paraffin-embedded tissue samples. We assessed CLDN18.2 positivity using multiple scoring approaches, including the immunoreactivity score, H-score, and the percentage of tumor cells showing moderate-to-strong staining intensity. We analyzed the concordance rates between PGC and MGC and the association of CLDN18.2 positivity with clinicopathological features. Results: CLDN18.2 positivity varied from 25% to 65% depending on the scoring method, with PGC consistently showing higher expression levels than MGC. Intratumoral heterogeneity was noted in 25.5% of PGCs and 19.6% of MGCs. Intertumoral heterogeneity, manifesting as discordance in CLDN18.2 positivity between PGC and MGC, was observed in about 20% of cases, with moderate agreement across scoring methods (κ=0.47 to 0.60).In PGC, higher CLDN18.2 positivity correlated with synchronous metastasis, presence of peritoneal metastasis, poorly differentiated grade, and biopsy specimens. In MGC, positivity was associated with synchronous metastasis, presence of peritoneal metastasis, and metastatic peritoneal tissues. Conclusions CLDN18.2 expression demonstrates significant heterogeneity between PGC and MGC, with a 20% discordance rate. Comprehensive tissue sampling and reassessment of CLDN18.2 status are crucial, especially before initiating CLDN18.2-targeted therapies.

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.

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.

Purpose: Claudin 18.2 (CLDN18.2) has emerged as a promising therapeutic target for CLDN18.2-expressing gastric cancer (GC). We sought to examine the heterogeneity of CLDN18.2 expression between primary GC (PGC) and metastatic GC (MGC) using various scoring methods. Materials and Methods: We retrospectively analyzed data from 102 patients with pathologically confirmed paired primary and metastatic gastric or gastroesophageal junction adenocarcinomas. CLDN18.2 expression was evaluated through immunohistochemistry on formalin-fixed paraffin-embedded tissue samples. We assessed CLDN18.2 positivity using multiple scoring approaches, including the immunoreactivity score, H-score, and the percentage of tumor cells showing moderate-to-strong staining intensity. We analyzed the concordance rates between PGC and MGC and the association of CLDN18.2 positivity with clinicopathological features. Results: CLDN18.2 positivity varied from 25% to 65% depending on the scoring method, with PGC consistently showing higher expression levels than MGC. Intratumoral heterogeneity was noted in 25.5% of PGCs and 19.6% of MGCs. Intertumoral heterogeneity, manifesting as discordance in CLDN18.2 positivity between PGC and MGC, was observed in about 20% of cases, with moderate agreement across scoring methods (κ=0.47 to 0.60).In PGC, higher CLDN18.2 positivity correlated with synchronous metastasis, presence of peritoneal metastasis, poorly differentiated grade, and biopsy specimens. In MGC, positivity was associated with synchronous metastasis, presence of peritoneal metastasis, and metastatic peritoneal tissues. Conclusions CLDN18.2 expression demonstrates significant heterogeneity between PGC and MGC, with a 20% discordance rate. Comprehensive tissue sampling and reassessment of CLDN18.2 status are crucial, especially before initiating CLDN18.2-targeted therapies.

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/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.