Only a small percentage of patients (2-5%) with differentiated thyroid cancer (DTC) exhibit distant metastasis at the initial diagnosis or during the disease course. The most common metastatic sites of DTC are the lungs, followed by the bones. Radioactive iodine (RAI) therapy is considered the primary treatment for RAI-avid distant metastatic DTC. Depending on the characteristics of metastatic lesions, local treatment such as surgical resection, radiofrequency ablation, and external beam radiation therapy may be considered for some patients with metastatic DTC. Slowly growing and asymptomatic metastases can be monitored with follow-up while receiving thyroid-stimulating hormone (TSH) suppression therapy. In patients with a limited number of lung metastases and good performance status, surgical removal of the metastatic lesions may be considered. Systemic therapy should be considered for patients with progressive RAI refractory DTC. In this clinical guideline, we aim to outline the treatment principles for patients with lung, bone, and brain metastases of DTC.

Differentiated thyroid cancer demonstrates a wide range of clinical presentations, from very indolent cases to those with an aggressive prognosis. Therefore, diagnosing and treating each cancer appropriately based on its risk status is important. The Korean Thyroid Association (KTA) has provided and amended the clinical guidelines for thyroid cancer management since 2007. The main changes in this revised 2024 guideline include 1) individualization of surgical extent according to pathological tests and clinical findings, 2) application of active surveillance in low-risk papillary thyroid microcarcinoma, 3) indications for minimally invasive surgery, 4) adoption of World Health Organization pathological diagnostic criteria and definition of terminology in Korean, 5) update on literature evidence of recurrence risk for initial risk stratification, 6) addition of the role of molecular testing, 7) addition of definition of initial risk stratification and targeting thyroid stimulating hormone (TSH) concentrations according to ongoing risk stratification (ORS), 8) addition of treatment of perioperative hypoparathyroidism, 9) update on systemic chemotherapy, and 10) addition of treatment for pediatric patients with thyroid cancer.

Background: Bladder cancer is characterized by frequent mutations, which provide potential therapeutic targets for most patients. The effectiveness of emerging personalized therapies depends on an accurate molecular diagnosis, for which the accurate estimation of the neoplastic cell percentage (NCP) is a crucial initial step. However, the established method for determining the NCP, manual counting by a pathologist, is time-consuming and not easily executable. Methods: To address this, artificial intelligence (AI) models were developed to estimate the NCP using nine convolutional neural networks and the scanned images of 39 cases of urinary tract cancer. The performance of the AI models was compared to that of six pathologists for 119 cases in the validation cohort. The ground truth value was obtained through multiplexed immunofluorescence. The AI model was then applied to 41 cases in the application cohort that underwent next-generation sequencing testing, and its impact on the copy number variation (CNV) was analyzed. Results: Each AI model demonstrated high reliability, with intraclass correlation coefficients (ICCs) ranging from 0.82 to 0.88. These values were comparable or better to those of pathologists, whose ICCs ranged from 0.78 to 0.91 in urothelial carcinoma cases, both with and without divergent differentiation/ subtypes. After applying AI-driven NCP, 190 CNV (24.2%) were reclassified with 66 (8.4%) and 78 (9.9%) moved to amplification and loss, respectively, from neutral/minor CNV. The neutral/minor CNV proportion decreased by 6%. Conclusions These results suggest that AI models could assist human pathologists in repetitive and cumbersome NCP calculations.

The occlusal treatment including prosthetic treatment should be considered when the pathologic symptom was observed with the excessive discrepancy between the centric relation occlusion (CRO) and the maximum intercuspal position (MIP). Through careful diagnosis, the malocclusion and interarch relationship can be analyzed, and occlusal adjustment, restorative treatment, orthodontic therapy, or orthognathic surgery can be performed depending on the degree of disharmony. The patient in this case report complained the unstable occlusion and loss of masticatory function that had been occurring for several years. At the time of the visit, the patient showed severe occlusal disharmony, with only the upper right second molar contacting the lower jaw at the maximum intercuspal position. Based on the analysis of the occlusion, it was difficult to solve the problem with just occlusal adjustment or restorative treatment. In addition, the patient had the skeletal class II malocclusion between the upper and lower jaws. Therefore, for resolving the severe skeletal class II malocclusion, pre- and post-orthodontic treatment, bilateral sagittal split ramus osteotomy (BSSRO) was performed. After that, the occlusal adjustment was performed for stable occlusion, and the missing teeth area was restored with dental implants. During the follow-up period, a periodic follow-up visits and additional occlusal adjustments were performed to achieve a stable centric occlusion and harmonious anterior and lateral guidance. As a result, the final prosthodontic treatment was completed, and the patient’s masticatory function was restored.

The aim of this study was to develop evidence-based recommendations for determining the surgical extent in patients with locally invasive differentiated thyroid cancer (DTC). Locally invasive DTC with gross extrathyroidal extension invading surrounding anatomical structures may lead to several functional deficits and poor oncological outcomes. At present, the optimal extent of surgery in locally invasive DTC remains a matter of debate, and there are no adequate guidelines. On October 8, 2021, four experts searched the PubMed, Embase, and Cochrane Library databases; the identified papers were reviewed by 39 experts in thyroid and head and neck surgery. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was used to assess the quality of evidence, and to develop and report recommendations. The strength of a recommendation reflects the confidence of a guideline panel that the desirable effects of an intervention outweigh any undesirable effects, across all patients for whom the recommendation is applicable. After completing the draft guidelines, Delphi questionnaires were completed by members of the Korean Society of Head and Neck Surgery. Twenty-seven evidence-based recommendations were made for several factors, including the preoperative workup; surgical extent of thyroidectomy; surgery for cancer invading the strap muscles, recurrent laryngeal nerve, laryngeal framework, trachea, or esophagus; and surgery for patients with central and lateral cervical lymph node involvement. Evidence-based guidelines were devised to help clinicians make safer and more efficient clinical decisions for the optimal surgical treatment of patients with locally invasive DTC.

Background: The purpose of this study was to verify the accuracy and validity of using machine learning (ML) to select risk factors, to discriminate differences in feature selection by ML between men and women, and to develop predictive models for patients with osteoporosis in a big database. Methods: The data on 968 observed features from a total of 3,484 the Korea National Health and Nutrition Examination Survey participants were collected. To find preliminary features that were well-related to osteoporosis, logistic regression, random forest, gradient boosting, adaptive boosting, and support vector machine were used. Results: In osteoporosis feature selection by 5 ML models in this study, the most selected variables as risk factors in men and women were body mass index, monthly alcohol consumption, and dietary surveys. However, differences between men and women in osteoporosis feature selection by ML models were age, smoking, and blood glucose level. The receiver operating characteristic (ROC) analysis revealed that the area under the ROC curve for each ML model was not significantly different for either gender. Conclusions ML performed a feature selection of osteoporosis, considering hidden differences between men and women. The present study considers the preprocessing of input data and the feature selection process as well as the ML technique to be important factors for the accuracy of the osteoporosis prediction model.

Background: Dual energy X-ray absorptiometry (DXA) is a preferred modality for screening or diagnosis of osteoporosis and can predict the risk of hip fracture. However, the DXA test is difficult to implement easily in some developing countries, and fractures have been observed before patients underwent DXA. The purpose of this systematic review is to search for studies that predict the risk of hip fracture using artificial intelligence (AI) or machine learning, organize the results of each study, and analyze the usefulness of this technology. Methods: The PubMed, OVID Medline, Cochrane Collaboration Library, Web of Science, EMBASE, and AHRQ databases were searched including “hip fractures” AND “artificial intelligence”. Results: A total of 7 studies are included in this study. The total number of subjects included in the 7 studies was 330,099. There were 3 studies that included only women, and 4 studies included both men and women. One study conducted AI training after 1:1 matching between fractured and non-fractured patients. The area under the curve of AI prediction model for hip fracture risk was 0.39 to 0.96. The accuracy of AI prediction model for hip fracture risk was 70.26% to 90%. Conclusions We believe that predicting the risk of hip fracture by the AI model will help select patients with high fracture risk among osteoporosis patients. However, to apply the AI model to the prediction of hip fracture risk in clinical situations, it is necessary to identify the characteristics of the dataset and AI model and use it after performing appropriate validation.

Background: This study aimed to investigate real-world data of C-terminal telopeptide (CTX), propeptide of type I collagen (P1NP), and osteocalcin through present multicenter clinical study, and retrospectively analyze the usefulness of bone turnover markers (BTMs) in Koreans. Methods: The study focused on pre- and post-menopausal patients diagnosed with osteoporosis and excluded patients without certain test results or with test intervals of over 1 year. The demographic data and 3 BTMs (CTX, P1NP, and osteocalcin) were collected. The patients were classified by demographic characteristics and the BTM concentrations were analyzed by the group. Results: Among women with no history of fractures, the levels of P1NP (N=2,100) were 43.544±36.902, CTX (N=1,855) were 0.373 ±0.927, and osteocalcin (N=219) were 10.81 ±20.631. Among men with no history of fractures, the levels of P1NP (N=221) were 48.498±52.892, CTX (N=201) were 0.370±0.351, and osteocalcin (N=15) were 7.868 ±10.674. Treatment with teriparatide increased the P1NP levels after 3 months in both men and women, with a 50% increase observed in women. Similarly, treatment with denosumab decreased the CTX levels after 3 months in both men and women, with a reduction of 50% observed in women. Conclusions The results of this study can contribute to the accurate assessment of bone replacement status in Koreans. We also provide the P1NP level in the Korean population for future comparative studies with other populations.

Purpose: The aim of this study is to evaluate the safety and efficacy of ex vivo activated and expanded natural killer (NK) cell therapy (SNK01) plus pembrolizumab in a randomized phase I/IIa clinical trial. Materials and Methods: Overall, 18 patients with advanced non–small cell lung cancer (NSCLC) and a programmed death ligand 1 tumor proportion score of 1% or greater who had a history of failed frontline platinum-based therapy were randomized (2:1) to receive pembrolizumab every 3 weeks +/– 6 weekly infusions of SNK01 at either 2×109 or 4×109 cells per infusion (pembrolizumab monotherapy vs. SNK01 combination). The primary endpoint was safety, whereas the secondary endpoints were the objective response rate (ORR), progression-free survival (PFS), overall survival, and quality of life. Results: Since no dose-limiting toxicity was observed, the maximum tolerated dose was determined as SNK01 4×109 cells/dose. The safety data did not show any new safety signals when SNK01 was combined with pembrolizumab. The ORR and the 1-year survival rate in the NK combination group were higher than those in patients who underwent pembrolizumab monotherapy (ORR, 41.7% vs. 0%; 1-year survival rate, 66.7% vs. 50.0%). Furthermore, the median PFS was higher in the SNK01 combination group (6.2 months vs. 1.6 months, p=0.001). Conclusion Based on the findings of this study, the NK cell combination therapy may consider as a safe treatment method for stage IV NSCLC patients who had a history of failed platinum-based therapy without an increase in adverse events.