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The aim of this retrospective study was to evaluate the demographic characteristics of pediatric dental patients who underwent dental treatment under general anesthesia (DTGA) at the Seoul National University Dental Hospital from January 2011 through December 2020 and compare the patterns of repeated DTGA between dental patients with severe disabilities (DSD) and non-DSD (healthy or medically compromised patients without DSD). There were 1,857 DTGAs among 1,719 patients (mean age = 5.1 years; males = 59.3%; ASA 2 or above = 52.9%; DSD = 26.8%). Overall, 6.6% of patients underwent repeated DTGA, and the rate of repeated DTGA over a 10-year period was 7.4%. ASA 2 or above (p < 0.0001) and DSD (p < 0.0001) were more likely to undergo repeated DRGA compared to ASA 1 and non-DSD. At both GA1 and GA2, DSD received significantly more restorative treatment on permanent teeth than non-DSD (p = 0.002, p < 0.0001, respectively). There has been an increasing demand for DTGA in pediatric dentistry over the last 10 years. Regular check-ups and preventive oral health care are necessary for pediatric dental patients with severe disabilities to reduce the possibility of repeated DTGA.
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Background@#Targeted therapy and immunotherapy such as programmed death-1 (PD-1) targeting have been introduced for treating many types of cancers, including primary cutaneous angiosarcoma (CA). However, studies that examined other targeted molecules in CA are scarce. @*Objective@#We aim to declare the expression of endoglin and survivin in addition to PD-1 and assess the clinical correlation between the expression of these molecules and clinical variables, overall survival (OS), and progressionfree survival (PFS) in CA. @*Methods@#We identified 51 patients diagnosed with CA at Asan Medical Center over the last 14 years, based on the staining results of paraffin sections of tissue samples for endoglin, survivin, and PD-1 that were reviewed by two dermatologists. @*Results@#Statistical analysis for the correlation between results and clinical data of CA revealed that whereas 35 (63.6%) and 30 samples (54.5%) were positive for endoglin and survivin respectively, only nine samples were positive for PD-1 (16.4%). Co-expression of endoglin and survivin was detected in 24 lesions (p=0.013) and was significantly correlated to head, neck, face, and scalp (HNFS) lesions in CA (p=0.005, p=0.038, respectively). However, the expression of these target molecules did not correlate with the OS or PFS of CA. @*Conclusion@#Considering that HNFS type CA is associated with unfavorable clinical outcomes in similar populations, our findings can be helpful in matching patients with CA with effective targeted therapy.
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The effect of dupilumab on allergic contact dermatitis or patch testing is unknown. Here, we present a case of excited skin syndrome that appeared after patch testing during dupilumab treatment. A 21-year-old woman presented with atopic dermatitis that showed only a partial response to cyclosporine and dupilumab. A patch test was performed to check for underlying allergic contact dermatitis. The result was consistent with excited skin syndrome.Some studies argue that dupilumab suppresses allergic reactions triggered by allergens that activate the Th2 pathway. Others suggest that it does not affect the result of patch testing, regardless of the type of allergen tested. Even if dupilumab suppresses a certain allergic or immunologic pathway, this case shows that it cannot mask excited skin syndrome on patch testing.
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Objective@#: Deep learning is a machine learning approach based on artificial neural network training, and object detection algorithm using deep learning is used as the most powerful tool in image analysis. We analyzed and evaluated the diagnostic performance of a deep learning algorithm to identify skull fractures in plain radiographic images and investigated its clinical applicability. @*Methods@#: A total of 2026 plain radiographic images of the skull (fracture, 991; normal, 1035) were obtained from 741 patients. The RetinaNet architecture was used as a deep learning model. Precision, recall, and average precision were measured to evaluate the deep learning algorithm’s diagnostic performance. @*Results@#: In ResNet-152, the average precision for intersection over union (IOU) 0.1, 0.3, and 0.5, were 0.7240, 0.6698, and 0.3687, respectively. When the intersection over union (IOU) and confidence threshold were 0.1, the precision was 0.7292, and the recall was 0.7650. When the IOU threshold was 0.1, and the confidence threshold was 0.6, the true and false rates were 82.9% and 17.1%, respectively. There were significant differences in the true/false and false-positive/false-negative ratios between the anteriorposterior, towne, and both lateral views (p=0.032 and p=0.003). Objects detected in false positives had vascular grooves and suture lines. In false negatives, the detection performance of the diastatic fractures, fractures crossing the suture line, and fractures around the vascular grooves and orbit was poor. @*Conclusion@#: The object detection algorithm applied with deep learning is expected to be a valuable tool in diagnosing skull fractures.
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Purpose@#In this paper, we propose deep-learning methodology with which to enhance the mass differentiation performance of convolutional neural network (CNN)-based architecture. @*Materials and Methods@#We differentiated breast mass lesions from gray-scale X-ray mammography images based on regions of interest (ROIs). Our dataset comprised breast mammogram images for 150 cases of malignant masses from which we extracted the mass ROI, and we composed a CNN-based deep learning model trained on this dataset to identify ROI mass lesions. The test dataset was created by shifting some of the training data images. Thus, although both datasets were different, they retained a deep structural similarity. We then applied our trained deep-learning model to detect masses on 8-bit mammogram images containing malignant masses. The input images were preprocessed by applying a scaling parameter of intensity before being used to train the CNN model for mass differentiation. @*Results@#The highest area under the receiver operating characteristic curve was 0.897 (Î 20). @*Conclusion@#Our results indicated that the proposed patch-wise detection method can be utilized as a mass detection and segmentation tool.
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Background@#Nipple adenoma (NA) is a rare benign tumor arising in the lactiferous ducts of the nipple. It typically presents as a palpable nodule, erosion, or discharge with erythema of the nipple. NA is different from other mammary proliferative diseases of the nipple; however, its clinicopathologic characteristics have been scarcely elucidated. @*Objective@#In this study, we aimed to assess the clinical and histopathological characteristics of NA and compare them with mammary Paget’s diseases and breast carcinomas of the nipple. @*Methods@#We retrospectively reviewed fifteen patients with NA. Furthermore, we reviewed fifteen patients with nipple Paget’s diseases and five patients with breast carcinomas (ductal carcinoma in situ and invasive ductal carcinoma). Skin lesions’ clinical characteristics and general histopathological findings were investigated. @*Results@#NA showed significantly early onset (p=0.014), delayed time for onset to diagnosis (p=0.026), and smaller lesion than other nipple malignant diseases (p＜0.001). NA was predominantly localized on the right side and exhibited as more palpable mass and less nipple discharge as initial symptoms. Estimated prevalence of Korean cases (0.026%) was twice higher than Western countries (0.012%). p16 immunostaining in NA and other malignant diseases did not differ. @*Conclusion@#NA is a benign neoplasm arising on the nipple. NA showed earlier onset with smaller size at initial presentation than other malignant diseases which presented more crusts. Unnecessary surgical procedures for NA should be avoided with preceding clinical differential diagnosis.
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This study aimed to evaluate the effectiveness of deep convolutional neural networks (CNNs) for diagnosis of interproximal caries in pediatric intraoral radiographs. A total of 500 intraoral radiographic images of first and second primary molars were used for the study. A CNN model (Resnet 50) was applied for the detection of proximal caries. The diagnostic accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curve, and area under ROC curve (AUC) were calculated on the test dataset. The diagnostic accuracy was 0.84, sensitivity was 0.74, and specificity was 0.94. The trained CNN algorithm achieved AUC of 0.86. The diagnostic CNN model for pediatric intraoral radiographs showed good performance with high accuracy. Deep learning can assist dentists in diagnosis of proximal caries lesions in pediatric intraoral radiographs.
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The purpose of this in vivo study was to assess the clinical screening performance of a quantitative light-induced fluorescence (QLF) device in detecting proximal caries in primary molars. Fluorescence loss, red autofluorescence and a simplified QLF score for proximal caries (QS-proximal) were evaluated for their validity in detecting proximal caries in primary molars compared to bitewing radiography.Three hundred and forty-four primary molar surfaces were included in the study. Carious lesions were scored according to lesion severity assessed by visual-tactile and radiographic examinations. The QLF images were analyzed for two quantitative parameters, fluorescence loss and red autofluorescence, as well as for QS-proximal. For both quantitative parameters and QS-proximal, the sensitivity, specificity and area under receiver operating curve (AUROC) were calculated as a function of the radiographic scoring index at enamel and dentin caries levels.Both quantitative parameters showed fair AUROC values for detecting dentine level caries (△F = 0.794, △R = 0.750). QS-proximal showed higher AUROC values (0.757 - 0.769) than that of visual-tactile scores (0.653) in detecting dentine level caries.The QLF device showed fair screening performance in detecting proximal caries in primary molars compared to bitewing radiography.
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The aim of this study was to provide pathological information of pediatric oral lesions by retrospectively analyzing oral biopsy results from pediatric patients at the Seoul National University Dental Hospital.Biopsy results of all oral lesions from pediatric patients, aged 0 - 16 years, were collected from the files of the Department of Oral Pathology, Seoul National University Dental Hospital from January 2000 to April 2020. The patients were divided into 3 age groups: 0 - 5, 6 - 11 and 12 - 16 years. All oral lesions were classified into three main categories: inflammatory and reactive, tumor or tumor-like and cystic lesions.Among the total of 2928 biopsy specimens, tumor or tumor-like lesions(35.66%) were the most common, followed by inflammatory and reactive lesions(34.29%) and cystic lesions(30.05%). Regardless of the categories used in this study, odontoma was the most frequently found lesion, mucocele and dentigerous cyst being the next common. This study was the first retrospective review of pediatric oral pathology in Korea, and the results from this study may assist in providing informative insight into the pediatric oral pathology for pediatric dentists.
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The purpose of this study is to analyze morphological characteristics of maxillary primary molar’s root and root canal. 268 children aged 3 - 7 years (175 boys, 93 girls) who had CBCT (152 children) and 3D CT (116 children) taken in Seoul National University Dental Hospital from January 2006 to April 2020 were included. The number of roots and root canals were analyzed in 1002 teeth without any root resorption or periapical pathologies. Curvature, angulation, length of root and root canal, as well as cross-sectional shapes of the root canal were analyzed in 218 teeth. By using Mimics and 3-Matics software, volume, surface area, and volume ratio of root canal was analyzed in 48 teeth.More than half of maxillary primary molars have 3 roots and 3 root canals. The degree of symmetry of root canal type was about 0.63 (Cohen’s kappa coefficient). The most frequent shape of roots and canals was linear in 1st primary molars and curved in 2nd primary molars. Angulation, length of root and root canals was the largest on palatal roots. Most teeth showed ovoid or round shapes at apex. The largest root canal volume, surface area, volume ratio was found in the palatal roots.
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This study retrospectively analyzed the effect of clinical factors on the outcomes of REP(regenerative endodontic procedure). Patients who received the REP using triple antibiotic paste due to trauma or fracture of dens evaginatus from February, 2011 to January, 2020 were included in the study. Finally, 57 teeth in 54 patients were selected.Investigated clinical factors were as follows: intentional bleeding, etiology, and root development stage. Treatment outcomes evaluated were as follows: improvement of subjective symptoms, changes in the periapical lesion, and the amounts of root development after REP. To compensate for differences in angulation and position between repeated radiographic examinations, images were aligned by Turboreg plugin. To evaluate the amounts of root development, apical diameter, root area, and root length were measured by ImageJ software.Among the aforementioned factors, intentional bleeding had no significant effect on treatment results. Regarding the etiology, the increase in the root area and the root length was significantly less in trauma cases than in dens evaginatus fracture cases. Considering root development stage, more immature teeth presented more increase in the root area.
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A total of 580 patients, who visited and received an orthodontic diagnosis in the Department of Pediatric Dentistry, Seoul National University Dental Hospital from 2017 to 2019, were investigated in this study. The aim of this study was to evaluate skeletal patterns of pediatric orthodontic patients determined with lateral cephalometric analysis and to analyze the relationship between skeletal pattern and probable associated clinical features. Also, the modality of orthodontic treatment for each skeletal classification was investigated to aid in therapeutic decisions.Patients aged 7 year accounted for the largest age group; 54.2% of patients showed a skeletal class I pattern, 22.2% showed a skeletal class II pattern, and 23.6% showed a skeletal class III pattern. Bi-maxillary retrusion for skeletal class I, retruded mandible with normal positioning of the maxilla for skeletal class II, and retrusion of the maxilla with protrusion of the mandible for skeletal class III were the largest subgroups by skeletal pattern. Brachyfacial type accounted for 55.0% of patients, followed by 31.9% of mesofacial type and 13.1% of dolichofacial type. The prevalence of anterior crossbite in the study was 43.3%, higher than that in previous studies.
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Microcephalic osteodysplastic primordial dwarfism type II (MOPD II) is an autosomal recessive inherited disorder form of primordial dwarfism, caused by mutations in the pericentrin gene. The purpose of the study was to examine the clinical and radiological features, physicochemical properties and microstructures of the tooth affected with MOPD II.The mandibular 2nd molar was collected from the MOPD II patient. Micro-computerized tomography, scanning electron microscopy, energy dispersive spectrometry and Vickers microhardness analysis were performed on the MOPD II and the normal control.The morphology of the MOPD II tooth appeared to have malformed pulp and root and showed a small size. The mineral density measurement showed that the MOPD II tooth had similar scores in the enamel, but lower scores in the root 1/2 and apical dentin compared to the normal control. The microhardness values were smaller in the cusp enamel, root 1/2 dentin and apical dentin of the MOPD II compared to the normal control.In this study, the dental characteristics and the physicochemical properties of a tooth affected with MOPD II were analyzed to improve understanding of the oral manifestations of the disease and to assist in proper dental treatment by identifying precautions.
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The purpose of this study was to investigate the three-dimensional characteristics of mesiodens using Cone-beam Computed Tomography(CBCT) and analyze the factors affecting complications and anesthetic methods of extraction. This study evaluated 602 mesiodens of 452 patients who underwent extraction of mesiodens at the department of Pediatric Dentistry in Seoul National University Dental Hospital between 2017 and 2019.The ratio of mesiodens patients over total patient per year was gradually increased over the past 20 years. Mesiodens with labio-palatally horizontal direction while root directing labial were the most common among the mesiodens with horizontal direction. Mesiodens were the most common at the cervical side of the adjacent teeth(37.0%) and mesiodens located in the near-palatal side were observed about 3.83 times higher than the far-palatal side. Most of the mesiodens(82.1%) were in contact with adjacent permanent teeth on all three sides of the CBCT and 46.2% of mesiodens had curved roots. The patient’s age, vertical position, presence of complications, and proximity showed a significant difference in the selection of general anesthesia among anesthetic methods. The direction and vertical position of mesiodens had a significant effect on complications.These results provide a better understanding of mesiodens for establishing an accurate diagnosis and treatment plan.
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Observational studies of the ongoing coronavirus disease 2019 (COVID-19) outbreak suggest that a cytokine storm is involved in the pathogenesis of severe illness. However, the molecular mechanisms underlying the altered pathological inflammation in COVID-19 are largely unknown. We report here that toll-like receptor (TLR) 4-mediated inflammatory signaling molecules are upregulated in peripheral blood mononuclear cells (PBMCs) from COVID-19 patients, compared with healthy controls. Among the most highly increased inflammatory mediators in severe/critically ill patients, S100A9, an alarmin and TLR4 ligand, was found as a noteworthy biomarker, because it inversely correlated with the serum albumin levels. These data support a link between TLR4 signaling and pathological inflammation during COVID-19 and contribute to develop therapeutic approaches through targeting TLR4-mediated inflammation.
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Deep learning has recently become one of the most actively researched technologies in the field of medical imaging. The availability of sufficient data and the latest advances in algorithms are important factors that influence the development of deep learning models. However, several other factors should be considered in developing an optimal generalized deep learning model. All the steps, including data collection, labeling, and pre-processing and model training, validation, and complexity can affect the performance of deep learning models. Therefore, appropriate optimization methods should be considered for each step during the development of a deep learning model. In this review, we discuss the important factors to be considered for the optimal development of deep learning models.
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Purpose@#The practical examination portion of the National Dental Licensing Examination (NDLE) is slated to be administered in the latter half of 2021 in the form of a clinical performance examination that comprehensively evaluates the patient-dentist interaction using standardized patients (SPs). The SPs should be equipped with the basic qualities and capacity as evaluators for a fair and reliable administration of the test. @*Materials and Methods@#In this study, we analyzed the existing training materials for SPs who participated in domestic and overseas practical tests for the development of training materials for SPs through seminars and surveys of 11 dentistry schools and colleges.Result: First, SPs should be selected according to the basic quality criteria and capacity, which they must possess, and the preliminary basic training about the details which they must have knowledge of and be provided through videorecorded cases before the implementation of the preliminary field training. Second, the roles of SPs and the calibration process of the evaluation result forms are needed when conducting the preliminary field training for SPs. After watching video-recorded scenario cases, the SPs participate in discussions about the watched videos before proceeding to calibration practices of evaluation result forms. Third, because the Type A questionnaire of the practical examination of the NDLE is dependent on the SPs’ capacity and training, the fairness of the practical test is largely dependent on the SPs. Therefore, practicing the roles as evaluators and evaluation training should be provided using practical test items that can improve the reliability of the test and show a high level of reproducibility about the same case. @*Conclusion@#The findings of this study will be utilized for the development of training materials for SPs, so they can participate in the administration of a fair and reliable practical examination of the NDLE.
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Background@#Dental treatment has shifted to the center of the community, and the public policy of the country has expanded to support the vulnerable classes such as the disabled. The dental profession needs education regarding oral health services for persons with disabilities, and it is necessary to derive the competencies for this. Therefore, we conducted this study to derive the normative ability to understand the role of a dental hygienist in the oral health service for persons with disabilities and improvement plans for education. @*Methods@#We conducted a qualitative analysis for deriving competencies by analyzing the data collected through in-depth interviews with experts in order to obtain abilities through practical experience. Based on the competency criterion, relevant competency in the interview response was derived using the priori method, and it was confirmed whether the derived ability matched the ability determined by the respondent. @*Results@#The professional conduct competencies of dental hygienists, devised by the Korean Association of Dental Hygiene, consists of professional behavior, ethical decision-making, self-assessment skills, lifelong learning, and accumulated evidence. Also, core competencies of the American Dental Education Association competencies for dental hygienist classification such as ethics, responsibility for professional actions, and critical thinking skills were used as the criterion. The dental hygienist's abilities needed for oral health care for people with disabilities, especially in the detailed abilities to fulfill these social needs, were clarified. @*Conclusion@#To activate oral health care for people with disabilities, it is necessary for dental hygienists to fulfill their appropriate roles, and for this purpose, competency-based curriculum restructuring is indispensable. A social safety net for improving the oral health of people with disabilities can be secured by improving the required skills-based education system of dental hygienists and strengthening the related infrastructure.
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Purpose@#This study was conducted to evaluate the diagnostic performance of machine learning in differentiating follicular adenoma from carcinoma using preoperative ultrasonography (US). @*Methods@#In this retrospective study, preoperative US images of 348 nodules from 340 patients were collected from two tertiary referral hospitals. Two experienced radiologists independently reviewed each image and categorized the nodules according to the 2015 American Thyroid Association guideline. Categorization of a nodule as highly suspicious was considered a positive diagnosis for malignancy. The nodules were manually segmented, and 96 radiomic features were extracted from each region of interest. Ten significant features were selected and used as final input variables in our in-house developed classifier models based on an artificial neural network (ANN) and support vector machine (SVM). The diagnostic performance of radiologists and both classifier models was calculated and compared. @*Results@#In total, 252 nodules from 245 patients were confirmed as follicular adenoma and 96 nodules from 95 patients were diagnosed as follicular carcinoma. As measures of diagnostic performance, the average sensitivity, specificity, and accuracy of the two experienced radiologists in discriminating follicular adenoma from carcinoma on preoperative US images were 24.0%, 84.0%, and 64.8%, respectively. The sensitivity, specificity, and accuracy of the ANN and SVM-based models were 32.3%, 90.1%, and 74.1% and 41.7%, 79.4%, and 69.0%, respectively. The kappa value of the two radiologists was 0.076, corresponding to slight agreement. @*Conclusion@#Machine learning-based classifier models may aid in discriminating follicular adenoma from carcinoma using preoperative US.
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Objectives@#Changes in the pancreatic volume (PV) are useful as potential clinical markers for some pancreatic-related diseases. The objective of this study was to measure the volume of the pancreas using computed tomography (CT) volumetry and to evaluate the relationships between sex, age, body mass index (BMI), and sarcopenia. @*Methods@#We retrospectively analyzed the abdominal CT scans of 1,003 subjects whose ages ranged between 10 and 90 years. The pancreas was segmented manually to define the region of interest (ROI) based on CT images, and then the PVs were measured by counting the voxels in all ROIs within the pancreas boundary. Sarcopenia was identified by examination of CT images that determined the crosssectional area of the skeletal muscle around the third lumbar vertebra. @*Results@#The mean volume of the pancreas was 62.648 ± 19.094 cm3. The results indicated a negative correlation between the PV and age. There was a positive correlation between the PV and BMI for both sexes, females, and males (r = 0.343, p < 0.001; r = 0.461, p < 0.001; and r = 0.244, p < 0.001, respectively). Additionally, there was a positive correlation between the PV and sarcopenia for females (r = 0.253, p < 0.001) and males (r = 0.200, p < 0.001). @*Conclusions@#CT pancreas volumetry results may help physicians follow up or predict conditions of the pancreas after interventions for pancreatic-related disease in the future.
