Purpose: Recently, deep learning techniques have been introduced for age estimation, with automated methods based on radiographic analysis demonstrating high accuracy. In this study, we applied convolutional neural network (CNN) techniques to the lower dentition area on orthopantomograms (OPGs) of children to develop an automated age estimation model and evaluate its accuracy for use in forensic dentistry. Methods: In this study, OPGs of 2,856 subjects aged 3-14 years were analyzed. The You Only Look Once (YOLO) V8 object detection technique was applied to extract the mandibular dentition area on OPGs, designating it as the region of interest (ROI). First, 200 radiographs were randomly selected, and were used to train a model for extracting the ROI. The trained model was then applied to the entire dataset. For the CNN image classification task, 80% of OPGs were allocated to the training set, while the remaining 20% were used as the test set. A transfer learning approach was employed using the ResNet50 and VGG19 backbone models, with an ensemble technique combining these models to improve performance. The mean absolute error (MAE) on the test set was used as the validation metric, and the model with the lowest MAE was selected. Results: In this study, the age estimation model developed using mandibular dentition region from OPGs achieved MAE and root mean squared error (RMSE) values of 0.501 and 0.742, respectively, on the test set, and MAE and RMSE values of 0.273 and 0.354, respectively, on the training set. Conclusions The automated age estimation model developed in this study demonstrated accuracy comparable to that of previous research and shows potential for applications in forensic investigations. Increasing the sample size and incorporating diverse deep learning techniques are expected to further enhance the accuracy of future age estimation models.

Colorectal cancer is the third most common cancer in Korea and the third leading cause of death from cancer. Treatment outcomes for colon cancer are steadily improving due to national health screening programs with advances in diagnostic methods, surgical techniques, and therapeutic agents.. The Korea Colon Cancer Multidisciplinary (KCCM) Committee intends to provide professionals who treat colon cancer with the most up-to-date, evidence-based practice guidelines to improve outcomes and help them make decisions that reflect their patients’ values and preferences. These guidelines have been established by consensus reached by the KCCM Guideline Committee based on a systematic literature review and evidence synthesis and by considering the national health insurance system in real clinical practice settings. Each recommendation is presented with a recommendation strength and level of evidence based on the consensus of the committee.

Background: Since 1992, over 800 pancreas transplants have been performed in Korea.However, this number is significantly lower compared to the number of kidney or liver transplants. Methods: Between 2015 and July 2023, Pusan National University Yangsan Hospital conducted 100 pancreas transplants, accounting for about 20% of all transplants performed in Korea during this period. The study comprised 27 simultaneous pancreas and kidney (SPK) transplants, 23 pancreas after kidney (PAK) transplants, and 50 pancreas transplant alone (PTA) cases. Duodenoduodenostomy was the primary surgical technique employed for exocrine drainage, along with various modifications of the venous outflow anastomosis. Results: The availability of brain-dead donors for kidney transplants was lower compared to isolated pancreas transplants. Patients undergoing SPK transplants faced significantly longer waiting times than those receiving PTA or PAK transplants. The rate of surgical complications was acceptable, with a notably low thrombotic graft failure rate of 1.0%. In the PTA group, acute rejection of the graft pancreas occurred frequently (18.0%), though this was not statistically significant (P=0.328). The pancreas transplantation survival rates were 91.0%, 78.5%, and 75.4% at 1, 5, and 9 years, respectively. The PTA group exhibited a lower graft survival rate than the SPK and PAK groups, with marginal statistical significance (P=0.059). Conclusions Graft survival rates have improved over time due to advancements in surgical techniques and immunosuppressant strategies. By sharing our experiences, we aim to enhance the activity and success of pancreas transplantation in Korea.

Purpose: Despite the increasing use of immediate breast reconstruction (IBR), its oncologic safety in the setting of neoadjuvant chemotherapy (NACT) needs to be comprehensively clarified in breast cancer management. The objective of the present study was to analyze the oncologic safety of IBR following NACT. Methods: In total, 587 patients with breast cancer who underwent a total mastectomy (TM) with IBR after NACT between 2008 and 2017 at a single institution were retrospectively reviewed. The reviewed patients with IBR following skin-sparing mastectomy (SSM) or nipple-sparing mastectomy (NSM) were matched 1:3 to patients who underwent TM alone after NACT. Matching variables included age, clinical T and N stages before NACT, response to NACT, pathologic T and N stages, and molecular subtypes. Results: After propensity score matching, 95 patients who underwent IBR following SSM/ NSM after NACT (IBR group) and 228 patients who underwent TM alone after NACT (TM group) were selected. The median follow-up period was 73 (range, 5–181) months after matching. After matching, there were no significant differences between the two groups in 5-year locoregional recurrence-free survival (88.8% vs. 91.2%, p = 0.516), disease-free survival (67.3% vs. 76.6%, p = 0.099), distant metastasis-free survival (71.9% vs. 81.9%, p = 0.057), or overall survival (84.1% vs. 91.5, p = 0.061) rates. In multivariate analyses, conducting IBR was not associated with increased risks for locoregional recurrence, any recurrence, distant metastasis, or overall death. Conclusion Our findings suggest that IBR following SSM/NSM elicits comparable long-term oncologic outcomes to those of TM alone in the setting of NACT.

Objective: Dysphagia is a common clinical condition characterized by difficulty in swallowing. It is sub-classified into oropharyngeal dysphagia, which refers to problems in the mouth and pharynx, and esophageal dysphagia, which refers to problems in the esophageal body and esophagogastric junction. Dysphagia can have a significant negative impact one’s physical health and quality of life as its severity increases. Therefore, proper assessment and management of dysphagia are critical for improving swallowing function and preventing complications. Thus a guideline was developed to provide evidence-based recommendations for assessment and management in patients with dysphagia. Methods: Nineteen key questions on dysphagia were developed. These questions dealt with various aspects of problems related to dysphagia, including assessment, management, and complications. A literature search for relevant articles was conducted using Pubmed, Embase, the Cochrane Library, and one domestic database of KoreaMed, until April 2021. The level of evidence and recommendation grade were established according to the Grading of Recommendation Assessment, Development and Evaluation methodology. Results: Early screening and assessment of videofluoroscopic swallowing were recommended for assessing the presence of dysphagia. Therapeutic methods, such as tongue and pharyngeal muscle strengthening exercises and neuromuscular electrical stimulation with swallowing therapy, were effective in improving swallowing function and quality of life in patients with dysphagia. Nutritional intervention and an oral care program were also recommended. Conclusion This guideline presents recommendations for the assessment and management of patients with oropharyngeal dysphagia, including rehabilitative strategies.

In children and adolescents, dental age estimation is performed with the development of the teeth. Various statistical analysis methods have been used to determine the relationship between age and dental maturity and develop an accurate method of age calculation. This study attempted to apply a neural network model for the statistical analysis of dental age estimation in children and evaluated its applicability. This study used 1196 panoramic radiographs of patients aged 3–16 years, and 996 and 200 were randomly classified into training and test sets, respectively. The dental maturity of the mandibular left teeth was evaluated using Demirjian's method, the neural network model using the backpropagation algorithm was derived using training sets, and the errors were evaluated using 100 radiographs of each male and female as test sets. In addition, multiple linear regression analysis was conducted on the same training set, and the error was calculated by applying it to the test set and comparing it with the error of the neural network model. In the neural network model, the mean absolute error (MAE) and root mean squared error (RMSE) were 0.589 and 0.783 in male subjects and 0.529 and 0.760 in female subjects, respectively. In the multiple linear regression model, the MAE and RMSE were 0.600 and 0.748 in male subjects and 0.566 and 0.789 in female subjects, respectively. When applying the neural network model to the statistical analysis of the dental developmental stage, the results were as accurate as those of conventional statistical analysis methods. This study’s approach is expected to be useful for estimating the ages of children.