Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Echinochrome A (Ech A) isolated from marine organisms is a therapeutic effector for various cardiovascular diseases, but its precise mechanisms are unclear.This study identified the role and mechanisms mediating the effects of Ech A on the migration of vascular smooth muscle cells (VSMCs) induced by high-mobility group box 1 (HMGB1). Compared to the control cells, the migration of VSMCs stimulated with HMGB1 (100 ng/ml) was markedly increased, which was significantly attenuated in cells pretreated with MPIIIB10 (100 ng/ml), a neutralizing monoclonal antibody for osteopontin (OPN). In VSMCs stimulated with HMGB1, the increased expression of OPN mRNA and protein was accompanied by an increased OPN promoter activity. In reporter gene assays using OPN promoter-luciferase constructs, the promoter region 538-234 bp of the transcription start site containing the binding sites for activator protein 1 (AP-1) was shown to be responsible for the increased transcriptional activity by HMGB1. In addition, the binding activity of AP-1 was increased in HMGB1-stimulated cells, highlighting the pivotal role of AP-1 on OPN expression in HMGB1-stimulated VSMCs. An examination of the vascular effects of Ech A showed that the increased AP-1 binding/promoter activities and OPN expression induced by HMGB1 were attenuated in cells pretreated with Ech A (3 or 10 μM). Similarly, Ech A inhibited HMGB1-induced VSMC migration in a concentration-dependent manner. These findings suggest that Ech A inhibits VSMC migration by suppressing OPN expression.Hence, Ech A is suggested as a potential therapeutic strategy for vascular remodeling in the injured vasculatures.

Purpose: This study assessed the impact of hepatic fibrosis on the diagnostic performance of the controlled attenuation parameter (CAP) in quantifying hepatic steatosis in patients with chronic hepatitis B (CHB). Methods: CHB patients who underwent liver stiffness measurement (LSM) and CAP assessment using transient elastography before liver resection between 2019 and 2022 were retrospectively evaluated. Clinical data included body mass index (BMI) and laboratory parameters. The histologically determined hepatic fat fraction (HFF) and fibrosis stages were reviewed by pathologists blinded to clinical and radiologic data. The Pearson correlation coefficient between CAP and HFF was calculated. The diagnostic performance of CAP for significant hepatic steatosis (HFF ≥10%) was assessed using areas under the receiver operating curve (AUCs), stratified by fibrosis stages (F0-1 vs. F2-4). Factors significantly associated with CAP were determined by univariable and multivariable linear regression analyses. Results: Among 399 CHB patients (median age 59 years; 306 men), 16.3% showed significant steatosis. HFF ranged from 0% to 60%. Of these patients, 9.8%, 19.8%, 29.3%, and 41.1% had fibrosis stages F0-1, F2, F3, and F4, respectively. CAP positively correlated with HFF (r=0.445, P<0.001). The AUC of CAP for diagnosing significant steatosis was 0.786 (95% confidence interval [CI], 0.726 to 0.845) overall, and significantly lower in F2-4 (0.772; 95% CI, 0.708 to 0.836) than in F0-1 (0.924; 95% CI, 0.835 to 1.000) (P=0.006). Multivariable analysis showed that BMI (P<0.001) and HFF (P<0.001) significantly affected CAP, whereas LSM and fibrosis stages did not. Conclusion CAP evaluations of significant hepatic steatosis are less reliable in CHB patients with significant or more advanced (F2-4) than with no or mild (F0-1) fibrosis.

Purpose: This study compared the diagnostic performance of two attenuation imaging (ATI) modes—low-frequency (3 MHz) and high-frequency (4 MHz)—for assessing hepatic steatosis, with histopathological hepatic fat fraction (HFF) as the reference standard. Methods: This prospective single-center study enrolled participants with suspected metabolic dysfunction-associated steatotic liver disease (MASLD) scheduled for liver biopsy or surgery between June 2023 and June 2024. Attenuation coefficient (AC) values were consecutively measured using low- and high-frequency ATI modes, while the skin-to-region of interest distance (SRD) was measured simultaneously. Spearman correlation analysis evaluated the relationships of AC with HFF and SRD, and linear regression identified factors affecting AC. Diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUROC). Results: In total, 119 participants (mean age, 37.2±12.0 years; 87 men) were included, with 73 (61.3%) diagnosed with MASLD. HFF ranged from 0% to 50%. The AC values in the lowfrequency mode were significantly higher than those in the high-frequency mode (0.61 vs. 0.54 dB/cm/MHz, P<0.001). HFF significantly influenced AC in both modes, whereas SRD affected AC only in the high-frequency mode (P<0.001). AC correlated positively with HFF in both modes (r_s≥0.514, P<0.001) and negatively with SRD in the high-frequency mode (r_s=-0.338, P<0.001). The AUROC for hepatic steatosis did not differ significantly between the two modes (0.751 vs. 0.771; P=0.609). Conclusion The low-frequency mode produced higher AC values than the high-frequency mode and demonstrated comparable diagnostic accuracy for assessing hepatic steatosis. Unlike the high-frequency mode, the low-frequency mode was not influenced by SRD.

Purpose: This study aimed to evaluate the prognosis of the not evaluated (NE) group by comparing it with the lost to follow-up (LTFU) group among patients with multidrug/rifampin-resistant tuberculosis (MDR/RR-TB). Materials and Methods: This was a retrospective longitudinal follow-up study using an integrated database constructed by data linkage of the three national databases. This database included 7226 cases of MDR/RR-TB notified between 2011 and 2017 in South Korea. Results: Among the 7226 MDR/RR-TB cases, 730 (10.1%) were classified as LTFU group, and 353 (4.9%) as NE group. When comparing NE group with LTFU group, there were no significant differences in the all-cause mortality rate (18.1% vs. 13.8%, p=0.065), median time to death [404 days (interquartile range, IQR 46–850) vs. 443 days (IQR 185–1157), p=0.140], and retreatment rate (26.9% vs.22.2%, p=0.090). After adjusting for potential confounders, the adjusted hazard ratio (aHR) for all-cause mortality (aHR 1.11; 95% confidence interval 0.80-1.53; p=0.531) in NE group was not significantly different than that in LTFU group. Among retreated cases, NE group had a higher treatment success rate (57.9% vs 43.8%, p=0.029) and a lower LTFU rate (11.6% vs 38.3%, p<0.001) compared to LTFU group. Conclusion NE group had an unfavorable outcome comparable to LTFU group, suggesting undetected cases of LTFU or deaths during the referral process. Establishing an efficient patient referral system would contribute to reducing the incidence of NE cases.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

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.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

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.

Endometriosis, a prevalent but debilitating condition affecting women, poses significant challenges in diagnosis and management. The current 2024 guideline, developed by the Korean Society of Endometriosis (KSE), builds upon the 2018 KSE guideline. This guideline aims to provide customized recommendations tailored to Korea’s unique clinical aspects and medical environment, and addresses key areas such as diagnosis, medical and surgical management, considerations for special populations, and its complex relationship with cancer.