2.Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography
Hyo Jung PARK ; Yongbin SHIN ; Jisuk PARK ; Hyosang KIM ; In Seob LEE ; Dong Woo SEO ; Jimi HUH ; Tae Young LEE ; TaeYong PARK ; Jeongjin LEE ; Kyung Won KIM
Korean Journal of Radiology 2020;21(1):88-100
dataset of 883 CT scans from 467 subjects. Axial CT images obtained at the inferior endplate level of the 3rd lumbar vertebra were used for the analysis. Manually drawn segmentation maps of the skeletal muscle, visceral fat, and subcutaneous fat were created to serve as ground truth data. The performance of the fully convolutional network-based segmentation system was evaluated using the Dice similarity coefficient and cross-sectional area error, for both a separate internal validation dataset (426 CT scans from 308 subjects) and an external validation dataset (171 CT scans from 171 subjects from two outside hospitals).RESULTS: The mean Dice similarity coefficients for muscle, subcutaneous fat, and visceral fat were high for both the internal (0.96, 0.97, and 0.97, respectively) and external (0.97, 0.97, and 0.97, respectively) validation datasets, while the mean cross-sectional area errors for muscle, subcutaneous fat, and visceral fat were low for both internal (2.1%, 3.8%, and 1.8%, respectively) and external (2.7%, 4.6%, and 2.3%, respectively) validation datasets.CONCLUSION: The fully convolutional network-based segmentation system exhibited high performance and accuracy in the automatic segmentation of abdominal muscle and fat on CT images.]]>
Abdominal Muscles
;
Adipose Tissue
;
Artificial Intelligence
;
Dataset
;
Intra-Abdominal Fat
;
Learning
;
Muscle, Skeletal
;
Muscles
;
Sarcopenia
;
Spine
;
Subcutaneous Fat
;
Tomography, X-Ray Computed
3.Involvement of the TNF-α Pathway in TKI Resistance and Suggestion of TNFR1 as a Predictive Biomarker for TKI Responsiveness in Clear Cell Renal Cell Carcinoma
Hee Sang HWANG ; Yun Yong PARK ; Su Jin SHIN ; Heounjeong GO ; Ja Min PARK ; Sun Young YOON ; Jae Lyun LEE ; Yong Mee CHO
Journal of Korean Medical Science 2020;35(5):31-
dataset from patient-derived xenograft model for TKI-treated ccRCC (GSE76068) was retrieved. Commonly altered pathways between the datasets were investigated by Ingenuity Pathway Analysis using commonly regulated differently expressed genes (DEGs). The significance of candidate DEG on intrinsic TKI resistance was assessed through immunohistochemistry in a separate cohort of 101 TKI-treated ccRCC cases.RESULTS: TNFRSF1A gene expression and tumor necrosis factor (TNF)-α pathway were upregulated in ccRCCs with acquired TKI resistance in both microarray datasets. Also, high expression (> 10% of labeled tumor cells) of TNF receptor 1 (TNFR1), the protein product of TNFRSF1A gene, was correlated with sarcomatoid dedifferentiation and was an independent predictive factor of clinically unfavorable response and shorter survivals in separated TKI-treated ccRCC cohort.CONCLUSION: TNF-α signaling may play a role in TKI resistance, and TNFR1 expression may serve as a predictive biomarker for clinically unfavorable TKI responses in ccRCC.]]>
Biomarkers
;
Carcinoma, Renal Cell
;
Cohort Studies
;
Dataset
;
Drug Resistance
;
Gene Expression
;
Gene Expression Profiling
;
Heterografts
;
Humans
;
Immunohistochemistry
;
Protein-Tyrosine Kinases
;
Receptors, Tumor Necrosis Factor
;
Receptors, Tumor Necrosis Factor, Type I
;
Tumor Necrosis Factor-alpha
4.Feasibility of fully automated classification of whole slide images based on deep learning
Kyung Ok CHO ; Sung Hak LEE ; Hyun Jong JANG
The Korean Journal of Physiology and Pharmacology 2020;24(1):89-99
Although microscopic analysis of tissue slides has been the basis for disease diagnosis for decades, intra- and inter-observer variabilities remain issues to be resolved. The recent introduction of digital scanners has allowed for using deep learning in the analysis of tissue images because many whole slide images (WSIs) are accessible to researchers. In the present study, we investigated the possibility of a deep learning-based, fully automated, computer-aided diagnosis system with WSIs from a stomach adenocarcinoma dataset. Three different convolutional neural network architectures were tested to determine the better architecture for tissue classifier. Each network was trained to classify small tissue patches into normal or tumor. Based on the patch-level classification, tumor probability heatmaps can be overlaid on tissue images. We observed three different tissue patterns, including clear normal, clear tumor and ambiguous cases. We suggest that longer inspection time can be assigned to ambiguous cases compared to clear normal cases, increasing the accuracy and efficiency of histopathologic diagnosis by pre-evaluating the status of the WSIs. When the classifier was tested with completely different WSI dataset, the performance was not optimal because of the different tissue preparation quality. By including a small amount of data from the new dataset for training, the performance for the new dataset was much enhanced. These results indicated that WSI dataset should include tissues prepared from many different preparation conditions to construct a generalized tissue classifier. Thus, multi-national/multi-center dataset should be built for the application of deep learning in the real world medical practice.
Adenocarcinoma
;
Classification
;
Dataset
;
Diagnosis
;
Learning
;
Observer Variation
;
Stomach
5.Pathologic discrepancies between colposcopy-directed biopsy and loop electrosurgical excision procedure of the uterine cervix in women with cytologic high-grade squamous intraepithelial lesions
Se Ik KIM ; Se Jeong KIM ; Dong Hoon SUH ; Kidong KIM ; Jae Hong NO ; Yong Beom KIM
Journal of Gynecologic Oncology 2020;31(2):13-
OBJECTIVE: To investigate pathologic discrepancies between colposcopy-directed biopsy (CDB) of the cervix and loop electrosurgical excision procedure (LEEP) in women with cytologic high-grade squamous intraepithelial lesions (HSILs).METHODS: We retrospectively identified 297 patients who underwent both CDB and LEEP for HSILs in cervical cytology between 2015 and 2018, and compared their pathologic results. Considering the LEEP to be the gold standard, we evaluated the diagnostic performance of CDB for identifying cervical intraepithelial neoplasia (CIN) grades 2 and 3, adenocarcinoma in situ, and cancer (HSIL+). We also performed age subgroup analyses.RESULTS: Among the study population, 90.9% (270/297) had pathologic HSIL+ using the LEEP. The diagnostic performance of CDB for identifying HSIL+ was as follows: sensitivity, 87.8%; specificity, 59.3%; balanced accuracy, 73.6%; positive predictive value, 95.6%; and negative predictive value, 32.7%. Thirty-three false negative cases of CDB included CIN2,3 (n=29) and cervical cancer (n=4). The pathologic HSIL+ rate in patients with HSIL− by CDB was 67.3% (33/49). CDB exhibited a significant difference in the diagnosis of HSIL+ compared to LEEP in all patients (p<0.001). In age subgroup analyses, age groups <35 years and 35–50 years showed good agreement with the entire data set (p=0.496 and p=0.406, respectively), while age group ≥50 years did not (p=0.036).CONCLUSION: A significant pathologic discrepancy was observed between CDB and LEEP results in women with cytologic HSILs. The diagnostic inaccuracy of CDB increased in those ≥50 years of age.
Adenocarcinoma in Situ
;
Biopsy
;
Cervical Intraepithelial Neoplasia
;
Cervix Uteri
;
Colposcopy
;
Conization
;
Dataset
;
Diagnosis
;
Early Detection of Cancer
;
Female
;
Humans
;
Papanicolaou Test
;
Retrospective Studies
;
Sensitivity and Specificity
;
Squamous Intraepithelial Lesions of the Cervix
;
Uterine Cervical Neoplasms
6.Nationwide Cross-sectional Study of Association between Pterygium and Alkaline Phosphatase in a Population from Korea
Hyun Joon KIM ; Sang Hoon RAH ; Sun Woong KIM ; Soo Han KIM
Journal of the Korean Ophthalmological Society 2020;61(1):9-16
PURPOSE: We determined whether elevated serum alkaline phosphatase (ALP) was related to prevalence, location, type, length, and recurrence of pterygium in a population from the Republic of Korea.METHODS: A nationwide cross-sectional dataset, the Korean National Health and Nutrition Examination Survey (2008–2011), was used in this study. All participants were > 30 years of age and underwent the ALP test and ophthalmic evaluation (n = 22,359). One-way analysis of variance, the chi-square test, and Fisher's exact test were used to compare characteristics and outcomes among participants. Multivariable logistic regression was used to examine the possible associations between serum ALP levels and various types of pterygium. Data were adjusted for known risk factors for development of pterygium and ALP elevation (age, sex, residence, sunlight exposure, drinking, smoking, hypertension, diabetes, BMI, AST, ALT, vitamin D, and HDL).RESULTS: The overall prevalence of pterygium was 8.1%, and participants with pterygium had higher levels of serum ALP (p < 0.001). Participants with higher serum ALP had a significantly higher prevalence of all types of pterygium than those in the lower serum ALP quartiles. After adjusting for potential confounding factors, multivariate logistic regression analysis revealed that ALP was associated with the prevalence of pterygium (odds ratio [OR], 1.001; p = 0.038). Trend analysis between the OR and ALP quartiles revealed a linear trend in overall prevalence and in the intermediate type of pterygium. Subgroup analysis revealed a stronger correlation in participants > 50 years of age. One-way analysis of variance revealed an association between the size of pterygium and serum ALP quartile levels. Serum ALP was not associated with recurrence of pterygium.CONCLUSIONS: Increased serum ALP was associated with the prevalence and size of pterygium.
Alkaline Phosphatase
;
Cross-Sectional Studies
;
Dataset
;
Drinking
;
Hypertension
;
Korea
;
Logistic Models
;
Nutrition Surveys
;
Prevalence
;
Pterygium
;
Recurrence
;
Republic of Korea
;
Risk Factors
;
Smoke
;
Smoking
;
Sunlight
;
Vitamin D
7.Keywords analysis of the Journal of the Korean Society of Emergency Medicine using text mining
Ki Cheon HWANG ; Gyu Chong CHO ; Youdong SOHN ; Youngsuk CHO ; Jinhyuck LEE ; Hyung Jung LEE ; Hyun Min CHA ; Hyung Woo CHANG
Journal of the Korean Society of Emergency Medicine 2019;30(1):94-99
OBJECTIVE: Data mining extracts meaningful information from large datasets. In this study, text mining techniques were used to extract keywords from the Journal of the Korean Society of Emergency Medicine, and the change trend was examined. METHODS: The rvest package in R was used to extract all papers published in the Journal of the Korean Society of Emergency Medicine from 2006 to 2016 that could be searched online. Among them, 3,952 keywords were extracted and studied. Using the selected keywords, the corpus was formed by refining keywords that did not correspond to MeSH (Medical Subject Headings) or were misspelled and had similar meanings based on agreement of researchers. Using the refined keywords, the frequencies of the keywords in the first and second halves of the studies were calculated and visualized. RESULTS: Word Cloud revealed that emergency medical service and cardiopulmonary resuscitation (CPR) were most frequently mentioned in both the first and second halves of the studies. In the first half, ultrasonography, stroke, poisoning, injury, and education were frequently mentioned, while in the second half, poisoning, injury, stroke, acute, and tomography were frequently mentioned. A pyramid graph revealed that the frequencies of emergency medical service and CPR were commonly high. CONCLUSION: Core keywords of the Journal of the Korean Society of Emergency Medicine were analyzed for correlations and trends. Changes in study topics according to key topics of interest and period were visually identified.
Cardiopulmonary Resuscitation
;
Data Mining
;
Dataset
;
Education
;
Emergencies
;
Emergency Medical Services
;
Emergency Medicine
;
Poisoning
;
Stroke
;
Ultrasonography
8.Now and Future of Data Sharing : Brain Magnetic Resonance Imaging Repositories
Eun NAMGUNG ; Seunghee KIM ; Jaeuk HWANG
Journal of the Korean Society of Biological Therapies in Psychiatry 2019;25(1):13-27
Over the past decade, practice of sharing brain magnetic resonance imaging (MRI) data is increasing given significance of reproducibility and transparency in human neuroscience. Larger multimodal brain MRI databases are needed for more robust research findings considering potential possibilities of large variability in human neuroscience. There are currently more than tens of thousands of shared brain MRI datasets across multiple conditions and hundreds of neuroimaging studies using multimodality through shared brain MRI data repositories. This article critically reviews aims, procedures, and current state of brain MRI data sharing. This review focuses on projects and research findings using structural and functional MRI open databases and is further divided into T1- and diffusion-weighted images for structural MRI as well as resting-state and task-based functional MRI. The challenges and directions are finally discussed. Advances in brain MRI data sharing will lead to more rapid progression in human neuroscience by fostering effective longitudinal, multi-site, multimodal neuroimaging research.
Brain
;
Dataset
;
Foster Home Care
;
Humans
;
Information Dissemination
;
Magnetic Resonance Imaging
;
Neuroimaging
;
Neurosciences
;
Transcutaneous Electric Nerve Stimulation
9.Relationship between Dietary Intake and Depression among Korean Adults: Korea National Health and Nutrition Examination Survey 2014
Suh Yeon PARK ; A Lum HAN ; Sae Ron SHIN ; Jae Eun EO
Korean Journal of Family Practice 2019;9(2):139-146
BACKGROUND: Many studies have assessed the relationship between each nutrient element and depression independently, but few have assessed the effect of dietary intake on depression, as diagnosed using the Patient Health Questionnaire (PHQ-9). This study investigated the relationship between dietary intake and depression, which was diagnosed using the PHQ-9.METHODS: This study used the second data set (2014) from the sixth Korea National Health and Nutrition Examination Survey (KNHNES). Our analysis included 5,897 persons who answered the PHQ-9, aged 20 to 60 years. They were categorized into either a male or female group, which were then subdivided into a depression group of patients who were diagnosed using the PHQ-9, and those without depression (control group). The patients' dietary intakes were obtained using the 24-hr recollection method in KNHNES. The relationship between dietary intake and depression was investigated for each group.RESULTS: In males, dietary intake was not associated with depression in both groups, except in relation to carotene. While in females, the depression group had lower fiber and vitamin C dietary intake than the control group (fiber P=0.015, vitamin C P=0.020). The dietary intakes of all other nutrients had no associations between the depression and control groups, in both males and females.CONCLUSION: According to our results, low dietary intake of fiber and vitamin C may be associated with depression in females. These results suggest that a diet regimen that includes fiber and vitamin C may help prevent and reduce depression in females.
Adult
;
Ascorbic Acid
;
Carotenoids
;
Dataset
;
Depression
;
Diet
;
Female
;
Humans
;
Korea
;
Male
;
Methods
;
Nutrition Surveys
10.Identifying Minimum Data Sets of Oral Mucous Integrity Assessment for Documentation Systematization
Myoung Soo KIM ; Hyun Kyeong JUNG ; Myung Ja KANG ; Nam Jung PARK ; Hyun Hee KIM ; Jeong Mi RYU
Journal of Korean Critical Care Nursing 2019;12(1):46-56
PURPOSE: The purpose of this study was to identify minimum data sets for oral mucous integrity-related documentation and to analyze nursing records for oral care.METHODS: To identify minimum data sets for oral status, the authors reviewed 26 assessment tools and a practical guideline for oral care. The content validity of the minimum data sets was assessed by three nurse specialists. To map the minimum data sets to nursing records, the authors examined 107 nursing records derived from 44 patients who received chemotherapy or hematopoietic stem cell transplantation in one tertiary hospital.RESULTS: The minimum data sets were 10 elements such as location, mucositis grade, pain, hygiene, dysphagia, exudate, inflammation, difficulty speaking, and moisture. Inflammation contained two value sets: type and color. Mucositis grade, pain, dysphagia and inflammation were recorded well, accounting for a complete mapping rate of 100%. Hygiene (100%) was incompletely mapped, and there were no records for exudate (83.2%), difficulty speaking (99.1%), or moisture (88.8%).CONCLUSION: This study found that nursing records on oral mucous integrity were not sufficient and could be improved by adopting minimum data sets as identified in this study.
Dataset
;
Deglutition Disorders
;
Drug Therapy
;
Exudates and Transudates
;
Hematopoietic Stem Cell Transplantation
;
Humans
;
Hygiene
;
Inflammation
;
Mucositis
;
Nursing Records
;
Oral Health
;
Oral Hygiene
;
Oral Ulcer
;
Specialization
;
Tertiary Care Centers

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