In patients with differentiated thyroid cancer (DTC), initial recurrence risk stratification based on clinical, histopathological, and perioperative data remains the key determinant for guiding management strategies during the first 1-2 years post-treatment. However, the adoption of ongoing risk stratification (ORS), which dynamically reassesses risk by integrating longitudinal clinical data and treatment response, enables more precise long-term prognostic assessment and facilitates highly individualized management. Building upon recent guidelines, the 2026 KTA guideline has been further refined by incorporating robust evidence from large-scale national cohorts and comprehensive systematic reviews. These updated recommendations outline contemporary concepts of ORS, risk-adapted TSH suppression targets, optimized surveillance modalities for recurrence detection, and disease-specific long-term follow-up strategies. Reflecting the paradigm shift toward de-escalated treatment, this revision integrates evolved perspectives on TSH suppression intensity, the clinical interpretation of thyroglobulin levels, and tailored follow-up intervals. These evidence-based recommendations aim to minimize unnecessary treatment and excessive surveillance in the large proportion of patients with excellent prognosis after initial therapy, while ensuring that each patient receives appropriately tailored and effective long-term management.

Background/Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. Methods: Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. Results: After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. Conclusions We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.

Background: This study aimed to generate a Z score calculation model for coronary artery diameter of normal children and adolescents to be adopted as the standard calculation method with consensus in clinical practice. Methods: This study was a retrospective, multicenter study that collected data from multiple institutions across South Korea. Data were analyzed to determine the model that best fit the relationship between the diameter of coronary arteries and independent demographic parameters. Linear, power, logarithmic, exponential, and square root polynomial models were tested for best fit. Results: Data of 2,030 subjects were collected from 16 institutions. Separate calculation models for each sex were developed because the impact of demographic variables on the diameter of coronary arteries differs according to sex. The final model was the polynomial formula with an exponential relationship between the diameter of coronary arteries and body surface area using the DuBois formula. Conclusion A new coronary artery diameter Z score model was developed and is anticipated to be applicable in clinical practice. The new model will help establish a consensus-based Z score model.

Objective: To evaluate the role of visual and quantitative chest CT parameters in assessing treatment response in patients with severe asthma. Materials and Methods: Korean participants enrolled in a prospective multicenter study, named the Precision Medicine Intervention in Severe Asthma study, from May 2020 to August 2021, underwent baseline and follow-up chest CT scans (inspiration/expiration) 10–12 months apart, before and after biologic treatment. Two radiologists scored bronchiectasis severity and mucus plugging extent. Quantitative parameters were obtained from each CT scan as follows: normal lung area (normal), air trapping without emphysema (AT without emph), air trapping with emphysema (AT with emph), and airway (total branch count, Pi10). Clinical parameters, including pulmonary function tests (forced expiratory volume in 1 s [FEV1] and FEV1/ forced vital capacity [FVC]), sputum and blood eosinophil count, were assessed at initial and follow-up stages. Changes in CT parameters were correlated with changes in clinical parameters using Pearson or Spearman correlation. Results: Thirty-four participants (female:male, 20:14; median age, 50.5 years) diagnosed with severe asthma from three centers were included. Changes in the bronchiectasis and mucus plugging extent scores were negatively correlated with changes in FEV1 and FEV1/FVC (ρ = from -0.544 to -0.368, all P < 0.05). Changes in quantitative CT parameters were correlated with changes in FEV1 (normal, r = 0.373 [P = 0.030], AT without emph, r = -0.351 [P = 0.042]), FEV1/FVC (normal, r = 0.390 [P = 0.022], AT without emph, r = -0.370 [P = 0.031]). Changes in total branch count were positively correlated with changes in FEV1 (r = 0.349 [P = 0.043]). There was no correlation between changes in Pi10 and the clinical parameters (P > 0.05). Conclusion Visual and quantitative CT parameters of normal, AT without emph, and total branch count may be effective for evaluating treatment response in patients with severe asthma.

Lecanemab (product name Leqembi ® ) is an anti-amyloid monoclonal antibody treatment approved for use in Korea for patients with mild cognitive impairment (MCI) or mild dementia due to Alzheimer's disease. The Korean Dementia Association has created recommendations for the appropriate use of lecanemab to assist clinicians. These recommendations include selecting patients for administration, necessary pre-administration tests and preparations,administration methods, monitoring for amyloid related imaging abnormalities (ARIA), and communication with patients and caregivers. Lecanemab is recommended for patients with MCI or mild dementia who confirmed positive amyloid biomarkers, and should not be administered to patients with severe hypersensitivity to lecanemab or those unable to undergo magnetic resonance imaging (MRI) evaluation. To predict the risk of ARIA before administration, apolipoprotein E genotyping is conducted, and regular brain MRI evaluations are recommended to monitor for ARIA during treatment. The most common adverse reactions are infusion-related reactions, which require appropriate management upon occurrence. Additional caution is needed when co-administering with anticoagulants or tissue plasminogen activator due to the risk of macrohemorrhage. Clinicians should consider the efficacy and necessary conditions for administration, as well as the safety of lecanemab, to make a comprehensive decision regarding its use.

Lecanemab (product name Leqembi ® ) is an anti-amyloid monoclonal antibody treatment approved for use in Korea for patients with mild cognitive impairment (MCI) or mild dementia due to Alzheimer's disease. The Korean Dementia Association has created recommendations for the appropriate use of lecanemab to assist clinicians. These recommendations include selecting patients for administration, necessary pre-administration tests and preparations,administration methods, monitoring for amyloid related imaging abnormalities (ARIA), and communication with patients and caregivers. Lecanemab is recommended for patients with MCI or mild dementia who confirmed positive amyloid biomarkers, and should not be administered to patients with severe hypersensitivity to lecanemab or those unable to undergo magnetic resonance imaging (MRI) evaluation. To predict the risk of ARIA before administration, apolipoprotein E genotyping is conducted, and regular brain MRI evaluations are recommended to monitor for ARIA during treatment. The most common adverse reactions are infusion-related reactions, which require appropriate management upon occurrence. Additional caution is needed when co-administering with anticoagulants or tissue plasminogen activator due to the risk of macrohemorrhage. Clinicians should consider the efficacy and necessary conditions for administration, as well as the safety of lecanemab, to make a comprehensive decision regarding its use.