This study aimed to determine the prevalence of human epidermal growth factor receptor 2 (HER2)–ultralow breast cancer among cases initially classified as HER2 immunohistochemistry (IHC) 0 and assess interobserver variability in interpreting low-level HER2 expression. Methods: In this multicenter retrospective study, all invasive breast cancer cases diagnosed between January and December 2022 across 10 Korean institutions were retrieved. Institutional pathologists reexamined HER2 IHC slides originally reported as IHC 0 according to the 2018 American Society of Clinical Oncology/College of American Pathologists guidelines and reclassified them as HER2-null (0), HER2-ultralow (0+), or HER2-low (1+). Slides from 10% of HER2-null and HER2-ultralow cases were digitized for central review and independently assessed by two pathologists, with discrepancies resolved by consensus. Results: Among 8,026 cases, 2,836 cases (35.5%) were initially reported as IHC 0. Upon re-review, 1,673 (59.0%), 1,139 (40.2%), and 24 (0.8%) cases were reclassified as HER2-null, HER2-ultralow, and HER2-low, respectively. The prevalence of HER2-ultralow breast cancer varied considerably across institutions (23.7%–78.1%). Central review of 268 digitized cases showed concordance in 193 cases (72.0%). Among the 75 discordant cases, 54 tumors (72.0%) were upgraded from HER2-null to HER2-ultralow, and 18 (24.0%) tumors were upgraded from HER2-ultralow to HER2-low. Furthermore, two tumors (2.7%) were downgraded from HER2-ultralow to HER2-null. Conclusions: Approximately 40% of cases initially categorized as IHC 0 were reclassified as HER2-ultralow. The substantial inter-institutional variability observed in interpreting low-level HER2 expression highlights the need for standardized training and quality assurance to ensure accurate identification of patients eligible for HER2-targeted antibody–drug conjugates.

The recent approval of trastuzumab deruxtecan for human epidermal growth factor receptor 2 (HER2)–low and HER2-ultralow breast cancer mandates an adequate assessment of these categories. Methods: Seven breast pathologists from the Breast Pathology Study Group of the Korean Society of Pathologists held an on-site expert consensus meeting. Fifteen sets of virtual whole slide images (WSI) of hematoxylin and eosin stain and HER2 immunohistochemistry were provided. The pathologists were given 60 minutes to submit their diagnosis of HER2 expression into null, ultralow, 1+, 2+, or 3+. Afterwards, in-depth discussion and consensus diagnoses were made by real-time visualization of the WSI. Results: After the consensus meeting, unanimous 100% agreements were seen only in five (33.3%) of the examined cases, which consisted of three 1+ cases and two 2+ cases. Two cases (13.3%) had mild disagreement, with only one pathologist’s disagreement. Of note, eight cases (53.3%) showed significant disagreement, defined by more than two pathologists’ disagreement. All HER2-null cases were reclassified as ultralow after consensus review, suggesting potential widespread underclassification of ultralow cases in clinical practice. Conclusions: Experts had significant discrepancies in interpreting HER2-low/ultralow status. It is important to assess if the distinction between HER2-low and ultralow is strictly required and if HER2-null breast cancer exists in reality.

Objective: This study aims to compare the incidence of active tuberculosis (TB) among Korean patients with rheumatoid arthritis (RA) initiating treatment with tumor necrosis factor inhibitors (TNFi) or tofacitinib. Methods: Using the Korean National Health Insurance database, we conducted a nationwide, retrospective cohort study of RA patients who started TNFi or tofacitinib therapy between 2015 and 2018. We calculated the incidence rates of active TB based on the treatment type and results from latent tuberculosis infection (LTBI) screening tests. A multivariable Cox proportional hazards model was employed to evaluate the risk of active TB in RA patients beginning TNFi or tofacitinib treatment. Results: Among 3,382 RA patients (596 on tofacitinib and 2,786 on TNFi), LTBI screening was predominantly conducted using the IGRA (interferon-gamma release assays) test. Of these patients, 624 (18.5%) with a positive LTBI test received prophylactic treatment. No cases of active TB occurred in tofacitinib users, while 32 cases were observed in TNFi users. The adjusted hazard ratio for active TB in LTBI-positive patients was 5.47 (95% confidence interval 2.74 to 10.92) compared to LTBI-negative patients.In subgroup analyses, TB incidence was significantly higher among individuals aged over 65 years. Conclusion Despite LTBI treatment, active TB remains prevalent among RA patients on TNFi therapy and in those with positive LTBI tests.

In forensic medicine, age estimation commonly involves assessing age-related changes in teeth and skeletal structures. Vertebral morphological alterations, such as osteophyte formation, serve as age indicators. Recent studies using deep-learning techniques, such as neural networks, for age estimation from radiographic images have been conducted, reporting significantly higher accuracy than previous studies. This study aimed to estimate age using neural network-based deep-learning techniques applied to computed tomography (CT) cross-sectional images of the spine and evaluate its feasibility. Postmortem CT scans of 214 cadavers with varying decomposition levels were used. Coronal and sagittal cross-sectional images penetrating the center of each vertebral body were extracted for the 11th and 12th thoracic vertebrae and the first to fifth lumbar vertebrae. Using these images, along with the chronological ages of deceased individuals, an age estimation model was developed through regression analysis in PyTorch, employing a convolutional neural networks architecture with five-fold cross-validation. The model achieved a mean absolute error of 5.385 years, root mean squared error of 7.029 years, and coefficient of determination of 0.793. Although the sample size was relatively small, the results suggested the potential applicability of vertebral imagingbased age estimation in the Korean population. Further research using a larger dataset may improve the accuracy and reliability of the model.

Purpose: This developmental study explored the conceptual feasibility and applicability of a metaverse-based clinical assessment platform as a complementary tool to conventional objective structured clinical examinations in undergraduate medical education. Methods: A targeted literature review and expert consensus process were conducted to identify domains of clinical competence in which metaverse technologies could provide added value. Based on these findings, prototype virtual patient simulations were developed within a metaverse environment. Large language models (LLMs) were integrated to support dynamic, interactive history-taking simulations, and pilot modules for physical examination were also created. Results: Integration of LLMs into virtual patient scenarios enabled realistic, context-sensitive medical interviews, facilitating interactive dialogue between examinees and simulated patients. In contrast, physical examination modules faced technical limitations, particularly in replicating procedures requiring tactile or haptic feedback, such as palpation and percussion. Nevertheless, the metaverse environment enabled delivery of consistent and reproducible scenarios, supporting objective assessment of communication and diagnostic reasoning skills. Conclusion Metaverse-based simulations augmented by LLMs offer a promising approach to scalable and standardized clinical assessment, particularly within cognitive and interpersonal competency domains. Although current technological constraints limit the fidelity of physical examination simulations, rapid advancements in immersive and haptic technologies may help overcome these barriers in the near future. Further research is needed to evaluate the educational efficacy, validity, and feasibility of deploying such platforms in summative, high-stakes assessment contexts.

Objective: Although most gallbladder polyps are benign, some neoplastic polyps may be malignant or may serve as precursors to malignancy. Distinguishing neoplastic and non-neoplastic polyps using imaging examinations remains a major challenge.This meta-analysis aimed to identify the ultrasound (US) features that are significantly associated with neoplastic polyps. Materials and Methods: The MEDLINE, EMBASE, Cochrane, and KoreaMed databases were searched for articles published up to August 31, 2025. Bivariate random-effects models were used to calculate the meta-analytic pooled diagnostic odds ratios (DORs), sensitivities, and specificities, along with their 95% confidence intervals (CIs), for each US imaging feature in the diagnosis of neoplastic polyps. Results: Thirty studies evaluating 8,953 patients, including 1,216 (13.6%) patients with neoplastic polyps, were included.Among the nine evaluated US imaging features, namely, size ≥10 mm, sessile morphology, single polyp, coexisting gallstones, hypoechogenicity, heterogeneous echogenicity, gallbladder wall thickening (GBWT), absence of hyperechoic spot, and vascularity, eight were significantly associated with neoplastic polyps: size ≥10 mm (DOR: 6.23 [95% CI: 1.86– 20.90]), sessile morphology (DOR: 3.54 [1.93–5.97]), single polyp (DOR: 2.21 [1.76–2.74]), coexisting gallstones (DOR:1.86 [1.29–2.60]), hypoechogenicity (DOR: 3.55 [1.47–7.30]), GBWT (DOR: 9.38 [1.47–32.20]), absence of hyperechoic spots (DOR: 4.23 [2.46–6.83]), and vascularity (DOR: 9.72 [5.81–15.30]). Of these, size ≥10 mm demonstrated the highest pooled sensitivity (0.79 [95% CI: 0.68–0.87]), whereas hypoechogenicity showed the highest pooled specificity (0.93 [95% CI: 0.82–0.98]). Conclusion Eight US imaging features (size ≥10 mm, sessile morphology, single polyp, coexisting gallstones, hypoechogenicity, GBWT, absence of hyperechoic spots, and vascularity) were significantly associated with the presence of neoplastic polyps.These features may facilitate the management of gallbladder polyps.

Objective: To evaluate the diagnostic performance of the “probable hepatocellular carcinoma (HCC)” category in the Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) v2022 guidelines. Materials and Methods: This multicenter retrospective study included patients at risk of HCC who underwent gadoxetic acid-enhanced MRI between January 2015 and June 2018; a subgroup of these patients also underwent liver CT. Eligible patients had at least one non-cystic lesion (≥10 mm) with a reference standard. Four radiologists interpreted the images independently and the results were pooled. The performance of “definite HCC” and “probable HCC” together and “probable HCC” alone were compared between v2018 and v2022. Results: A total of 2,237 patients (1,666 men; mean age, 59 ± 11 years) with 2,445 lesions were included. In v2022, 1.5% (143/9,780) of the lesions were additionally categorized as “probable HCC” by four reviewers on MRI; among these, 104 lesions were not HCCs. Focal nodular hyperplasia (FNH) or FNH-like nodules constituted 90.4% (94/104) of the false positives. When “definite HCC” and “probable HCC” were combined, v2022 showed higher sensitivity (83.7% [5,670/6,776] vs. 83.1% [5,631/6,776]) but lower specificity (77.1% [2,316/3,004] vs. 80.6% [2,420/3,004]) than v2018 (P < 0.001). For “probable HCC” alone, v2022 showed a lower positive predictive value (PPV) than v2018 (64.1% [373/582] vs. 76.1% [334/439], P < 0.001). In v2022, lesions with non-rim arterial-phase hyperenhancement (APHE) showed a lower PPV than those without APHE (42.3% [91/215] vs. 76.8% [282/367], P < 0.001). In the CT subgroup (n = 1,590), 1.6% (99/6,360) of the lesions were reassessed as “probable HCC,” and its PPV was 83.8% (83/99) in v2022 whereas no lesions were classified as “probable HCC” under v2018. Conclusion The revised “probable HCC” category in the KLCA-NCC v2022 aligns with updates in the diagnostic flow, demonstrating acceptable performance on MRI and CT. Notably, FNH or FNH-like nodules can be misclassified as “probable HCC” when MRI is used.

Objective: This study aimed to compare the therapeutic outcomes of no-touch (NT) radiofrequency ablation (RFA) vs. tumorpuncture microwave ablation (MWA) in the treatment of single hepatocellular carcinomas (HCCs) measuring ≤3 cm. Materials and Methods: This multicenter retrospective study included 304 patients who underwent either NT-RFA (n = 144) or MWA (n = 160) for a single HCC measuring ≤3 cm. Comparative analyses were conducted for the overall cohort, while 81 patients per group were matched using propensity score matching (PSM). The analyzed outcomes included technical success, primary technique efficacy, local tumor progression (LTP), and major complications. Cumulative LTP was estimated using Kaplan–Meier analysis and compared using the log-rank text, while the rate of ablative margin ≥5 mm and ablation time were compared using Chi-squared and Mann–Whitney U tests, respectively. Results: Technical success was achieved in 98.6% (142/144) and 100% (160/160) of in the NT-RFA and MWA patients, respectively before PSM (P = 0.224), and 98.8% (80/81) and 100% (81/81) after PSM (P = 1.000). The primary technique efficacies were 98.6% (142/144) and 100% (160/160) before PSM (P = 0.224), and 97.5 % (79/81) and 100% (81/81) after PSM (P = 0.497), respectively. The 1-, 2-, and 3-year cumulative LTP rates were 1.4%, 1.4%, and 2.3%, respectively, for NTRFA and 5.1%, 8.6%, and 8.6%, respectively, for MWA before PSM (P = 0.013). After PSM, the corresponding rates were 0%, 0%, and 0% for NT-RFA, and 7.6%, 10.4%, and 10.4% for MWA (P = 0.006). Major complications were not observed. NT-RFA achieved a higher proportion, with an ablative margin ≥5 mm (88.7% [126/142] vs. 71.9% [115/160]; P < 0.001), but required longer ablation times (median, 10.0 vs. 6.0 min; P < 0.001). Conclusion NT-RFA showed superior local tumor control compared to MWA, despite greater procedural complexity and longer ablation times.

Objective: This study aimed to evaluate the accuracy of predicting final adult height (FAH) in Korean girls with central precocious puberty (CPP) using artificial intelligence (AI)-derived bone age assessments integrated into the Bayley–Pinneau (BP) or Korean National Growth Chart (KGC) prediction models. Materials and Methods: This single-center, retrospective study included 122 Korean girls with CPP who received gonadotropinreleasing hormone agonist (GnRHa) treatment for at least two years between January 2000 and November 2022. We assessed bone age and predicted adult height at the initiation and completion of GnRHa treatment. We used three bone age assessment methods: human expert assessment based on the Greulich-Pyle (GP) atlas (Human-GP), AI-derived GP (AI-GP), and AI-weighted GP scoring (AI-GPw). We calculated predicted adult heights (PAHs) using both the BP and KGC models, generating 12 PAH estimates per patient (2 time points x 3 bone-age methods x 2 height-prediction models). We assessed prediction accuracy and agreement with FAH using linear regression analysis and Bland–Altman plots and performed multivariable analysis to identify significant predictors of FAH. Results: Human-GP, AI-GP, and AI-GPw demonstrated comparable overall performance in predicting FAH (R 2 : 0.470–0.646 and 0.691–0.822 for treatment initiation and completion, respectively). AI-GPw combined with BP yielded slightly better point estimates but showed no statistically significant differences. At both time points, the BP model demonstrated consistently narrower 95% limits of agreement (LoA) than the KGC model. Multivariable analysis identified AI-GPw-BP and height percentile score as significant predictors of FAH at both time points; mid-parental height was significant only at treatment initiation. Conclusion Human-GP, AI-GP, and AI-GPw demonstrated comparable accuracy in predicting FAH. The BP model demonstrated consistently narrower 95% LoA than did the KGC model. AI-GPw-BP was an independent predictor of FAH. These findings support the clinical utility of AI-derived bone age assessments for individualized FAH prediction in patients with CPP.

Background: Seborrheic dermatitis (SD) is a chronic inflammatory scalp disorder associated with Malassezia dysbiosis and increased sebum production. AMPamide has been suggested to have anti-inflammatory and sebum-regulating effects, but its clinical efficacy and microbiome-modulating effects in SD remain unclear. Objective: To evaluate the clinical efficacy and scalp microbiome changes following 4 weeks of use of an AMPamide-containing shampoo in patients with SD. Methods: In this observational study, 30 patients with SD applied an AMPamide-containing shampoo for 4 consecutive weeks. Clinical outcomes, including sebum levels and overall severity scores, were assessed. Scalp bacterial and fungal communities were analyzed to evaluate α- and β-diversity and changes in Malassezia composition. Results: Treatment resulted in significant reductions in sebum levels and clinical severity scores, particularly in erythema, dandruff, and pruritus. Bacterial community composition remained largely stable, while fungal α-diversity increased, and β-diversity analysis revealed a decrease in the ratio of Malassezia restricta to Malassezia globosa. Conclusion AMPamide-containing shampoo was associated with improved clinical symptoms and a shift toward a more balanced fungal community composition in patients with SD, supporting its potential as a non-steroidal therapeutic option for SD.