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: We aimed to determine whether individuals at immediate risk of suicide could be identified using data from a commercially available wearable device. Methods: Thirty-nine participants experiencing acute depressive episodes and 20 age- and sex-matched healthy controls wore a commercially available wearable device (Galaxy Watch Active2) for two months. We collected data on activities, sleep, and physiological metrics like heart rate and heart rate variability using the wearable device. Participants rated their mood spontaneously twice daily on a Likert scale displayed on the device. Mood ratings by clinicians were performed at weeks 0, 2, 4, and 8. The suicide risk was assessed using the Hamilton Depression Rating Scale’s suicide item score (HAMD-3). We developed two predictive models using machine learning: a single-level model that processed all data simultaneously to identify those at immediate suicide risk (HAMD-3 scores ≥1) and a multilevel model. We compared the predictions of imminent suicide risk from both models. Results: Both the single-step and multi-step models effectively predicted imminent suicide risk. The multi-step model outperformed the single-step model in predicting imminent suicide risk with area under the curve scores of 0.89 compared to 0.88. In the multi-step model, the HAMD total score and heart rate variability were most significant, whereas in the single-step model, the HAMD total score and diagnosis were key predictors. Conclusion Wearable devices are a promising tool for identifying individuals at immediate risk of suicide. Future research with more refined temporal resolution is recommended.

Background/Aims: Portal vein thrombosis (PVT) frequently occurs in patients with inflammatory bowel disease (IBD), particularly when influenced by factors such as abdominal infections, IBD flare-ups, or surgical procedures. The implications of PVT range from immediate issues such as intestinal ischemia to long-term concerns including portal hypertension and its complications. However, there is a notable gap in comprehensive studies on PVT in IBD, especially with the increasing incidence of IBD in Asia. This research aimed to evaluate the clinical features and outcomes of PVT in patients with IBD at a leading hospital in South Korea. Methods: This retrospective analysis reviewed adult patients diagnosed with both IBD and PVT from 1989 to 2021 at a renowned South Korean medical center. The study focused on patient characteristics, specifics of PVT, administered treatments, and outcomes, all confirmed through enhanced CT scans. Results: A total of 78 patients met the study’s criteria. Notably, only 20.5% (16/78) were treated with oral anticoagulants; however, a vast majority (96.2%; 75/78) achieved complete radiographic resolution (CRR). When comparing patients receiving anticoagulants to those who did not, a significant preference for anticoagulant use was observed in cases where the main portal vein was affected, as opposed to just the left or right veins (p = 0.006). However, multivariable analysis indicated that neither anticoagulant use nor previous surgeries significantly impacted CRR. Conclusions Patients with IBD and PVT generally had favorable outcomes, regardless of anticoagulant use.

Purpose: Pediatric papillary thyroid cancer (PTC) is recommended to perform aggressive surgery to reduce the risk of recurrence.This study was designed to evaluate the concurrent association between multifocality, bilaterality, and the risk of recurrence in pediatric PTC. Materials and Methods: This retrospective cohort study included pediatric patients (age <19 years) who underwent total thyroidectomy for PTC between 1996 and 2014 in a single tertiary center. Clinicopathological parameters were analyzed to evaluate the prevalence of multifocality, bilaterality, recurrence, and their association. Results: We analyzed 58 pediatric patients with PTC. There was no factor related to the presence of multifocality or bilaterality in multivariate analysis. Also, in univariate analysis, multifocality and bilaterality were not independent risk factors of each other’s presentation (p=0.061 and p=0.061, respectively). Recurrence was observed in 19 (32.8%) patients. In multivariate analysis of recurrence, clear cell subtype, multifocality, and gross extrathyroidal extension (ETE) were independent risk factors (p=0.027, p=0.035, and p=0.038, respectively). Most recurrences (68.4%) happened during the first 4 years of follow-up after the initial thyroidectomy. Conclusion Multifocality and bilaterality were not independent risk factors of each other’s presentation; however, multifocality was the risk factor for recurrence in pediatric PTC. For pediatric PTC, close monitoring for recurrence within the initial 4 years is recommended, particularly in patients with clear cell subtype, multifocality, and gross ETE.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Background/Aims: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC. Methods: We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC. We developed AI models to predict LNM using four algorithms: regularized logistic regression classifier (RLRC), random forest classifier (RFC), CatBoost classifier (CBC), and the voting classifier (VC). Four histological factors and four endoscopic findings were included to develop AI models. Areas under the receiver operating characteristics curves (AUROCs) were measured to distinguish AI model performance in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines. Results: Among 1,386 patients with T1 CRC, 173 patients (12.5%) had LNM. The AUROC values of the RLRC, RFC, CBC, and VC models for LNM prediction were significantly higher (0.673, 0.640, 0.679, and 0.677, respectively) than the 0.525 suggested in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines (vs RLRC, p<0.001; vs RFC, p=0.001; vs CBC, p<0.001; vs VC, p<0.001). The AUROC value was similar between T1 colon versus T1 rectal cancers (0.718 vs 0.615, p=0.700). The AUROC value was also similar between the initial endoscopic resection and initial surgery groups (0.581 vs 0.746, p=0.845). Conclusions AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.

Background/Aims: The study investigated the incidence, risk factors, and clinical outcomes of chronic antibiotic-refractory pouchitis (CARP) in Korean patients with ulcerative colitis (UC). Methods: This single-center retrospective study included patients with UC who underwent total proctocolectomy with ileal pouch-anal anastomosis at the Asan Medical Center in Korea between January 1987 and December 2022. The primary outcomes were endoscopic remission and pouch failure. The Cox’s proportional hazard model was used to identify the risk factors for CARP. Results: The clinical data of 232 patients were analyzed. The most common cause of surgery was steroid refractoriness (50.9%), followed by dysplasia/colorectal cancer (26.7%). Among 74 patients (31.9%) with chronic pouchitis (CP), 31 (13.4%) had CARP, and 43 (18.5%) had chronic antibiotic-dependent pouchitis (CADP). The most frequent endoscopic phenotype was focal inflammation of the pouch (CP, 47.3%; CARP, 35.5%; CADP, 55.8%). Patients with CARP were less likely to use concomitant probiotics than patients with CADP (29.0% vs 72.1%, p<0.01). The endoscopic remission rate of CP, CARP, and CADP was 14.9%, 9.7%, and 18.6%, respectively.The pouch failure rate associated with CP, CARP, and CADP was 13.5%, 16.1%, and 11.6%, respectively. Current smoking status (adjusted hazard ratio [aHR], 2.96; 95% confidence interval [CI], 1.27 to 6.90; p=0.01) and previous use of biologics/small molecules (aHR, 2.40; 95% CI, 1.05 to 5.53; p=0.04) were significantly associated with CARP development. Conclusions UC patients who were current smokers and previously used biologics/small molecules had a higher risk of developing CARP. Concomitant use of probiotics was less likely to be associated with CARP development.

Human rhinovirus (HRV) causes the common cold and exacerbates chronic respiratory diseases, such as asthma and chronic obstructive pulmonary disease. Despite its significant impact on public health, there are currently no approved vaccines or antiviral treatments for HRV infection. Apoptosis is the process through which cells eliminate themselves through the systematic activation of intrinsic death pathways in response to various stimuli. It plays an important role in viral infections and serves as a key immune defense mechanism in the interactions between viruses and the host. In the present study, we investigated the antiviral effects of quercetin-3-methyl ether, a flavonoid isolated from Serratula coronata, on human rhinovirus 1B (HRV1B). Quercetin-3-methyl ether significantly inhibited HRV1B replication in HeLa cells in a concentration-dependent manner, thereby reducing cytopathic effects and viral RNA levels. Time-course and time-of-addition analyses confirmed that quercetin-3-methyl ether exhibited antiviral activity during the early stages of viral infection, potentially targeting the replication and translation phases. Gene expression analysis using microarrays revealed that pro-apoptotic genes were upregulated in quercetin-3-methyl ether-treated cells, suggesting that quercetin-3-methyl ether enhances early apoptosis to counteract HRV1B-induced immune evasion. In vivo administration of quercetin-3-methyl ether to HRV1B-infected mice significantly reduced viral RNA levels and inflammatory cytokine production in the lung tissues. Our findings demonstrated the potential of quercetin-3-methyl ether as a novel antiviral agent against HRV1B, thereby providing a promising therapeutic strategy for the management of HRV1B infections and related complications.

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: We aimed to determine whether individuals at immediate risk of suicide could be identified using data from a commercially available wearable device. Methods: Thirty-nine participants experiencing acute depressive episodes and 20 age- and sex-matched healthy controls wore a commercially available wearable device (Galaxy Watch Active2) for two months. We collected data on activities, sleep, and physiological metrics like heart rate and heart rate variability using the wearable device. Participants rated their mood spontaneously twice daily on a Likert scale displayed on the device. Mood ratings by clinicians were performed at weeks 0, 2, 4, and 8. The suicide risk was assessed using the Hamilton Depression Rating Scale’s suicide item score (HAMD-3). We developed two predictive models using machine learning: a single-level model that processed all data simultaneously to identify those at immediate suicide risk (HAMD-3 scores ≥1) and a multilevel model. We compared the predictions of imminent suicide risk from both models. Results: Both the single-step and multi-step models effectively predicted imminent suicide risk. The multi-step model outperformed the single-step model in predicting imminent suicide risk with area under the curve scores of 0.89 compared to 0.88. In the multi-step model, the HAMD total score and heart rate variability were most significant, whereas in the single-step model, the HAMD total score and diagnosis were key predictors. Conclusion Wearable devices are a promising tool for identifying individuals at immediate risk of suicide. Future research with more refined temporal resolution is recommended.