• Kosin Medical Journal
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• v.33 no.3
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• pp.297-306
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• 2018

Objectives: Identification of axillary metastases in breast cancer is important for staging disease and planning treatment, but current techniques are associated with a number of adverse events. This report evaluates the diagnostic accuracy of superparamagnetic iron oxide (SPIO)-enhanced magnetic resonance imaging (MRI) techniques for identification of axillary metastases in breast cancer patients. Methods: We performed a meta-analysis of previous studies that compared SPIO enhanced MRI with histological diagnosis after surgery or biopsy. We searched PubMed, Ovid, Springer Link, and Cochrane library to identify studies reporting data for SPIO enhanced MRI for detection of axillary lymph node metastases in breast cancer until December 2013. The following keywords were used: "magnetic resonance imaging AND axilla" and "superparamagnetic iron oxide AND axilla". Eligible studies were those that compared SPIO enhanced MRI with histological diagnosis. Sensitivity and specificity were calculated for every study; summary receiver operating characteristic and subgroup analyses were done. Study quality and heterogeneity were also assessed. Results: There were 7 publications that met the criteria for inclusion in our meta-analysis. SROC curve analysis for per patient data showed an overall sensitivity of 0.83 (95% Confidence interval (CI): 0.75-0.89) and overall specificity of 0.97 (95% CI: 0.94-0.98). Overall weighted area under the curve was 0.9563. Conclusions: SPIO enhanced MRI showed a trend toward high diagnostic accuracy in detection of lymph node metastases for breast cancer. So, when the breast cancer patients has axillary metastases histologically, SPIO enhanced MRI may be effective diagnostic imaging modality for axillary metastases.

• Neonatal Medicine
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• v.25 no.4
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• pp.178-185
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• 2018

Purpose: We aim to assess the Bayley Scales of Infant and Toddler Development, third edition (Bayley-III), Adaptive Behavior (AB) and Social-Emotional (SE) scales at 18 to 24 months of corrected age (CA) to examine their associations with school-age cognitive and behavioral outcomes in children born preterm. Methods: Eighty-eight infants born with a very low birth weight (<1,500 g) or a gestational age of less than 32 weeks who were admitted to the neonatal intensive care unit from 2008 to 2009 were included. Of the 88 children who completed school-age tests at 6 to 8 years of age, 37 were assessed using the Bayley-III, including the AB and SE scales, at 18 to 24 months of CA. Correlation, cross-tabulation, and receiver operating characteristic analyses were performed to assess the longitudinal associations. Results: A significant association was observed between communication scores on the Bayley-III AB scale at 18 to 24 months of CA and the Korean version of the Wechsler Intelligence Scale for Children (K-WISC) full-scale intelligence quotient (FSIQ) at school age (r=0.531). The total behavior problem scores of the Korean version of the Child Behavior Checklist (K-CBCL) at school age were significantly negatively related to the Bayley-III SE and AB scales but not to the cognitive, language, or motor scales. Conclusion: Our findings encourage AB and SE assessments during the toddler stage and have important implications for the early identification of children in need of intervention and the establishment of guidelines for follow-up with high-risk infants.

• Journal of Gynecologic Oncology
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• v.29 no.6
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• pp.98.1-98.13
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• 2018

Objective: We describe a systematic review and meta-analysis of the performance of ${18}F$-fluorodeoxyglucose ($^{18}F-FDG$) positron emission tomography/computed tomography (PET/CT) for detecting metastasis in ovarian cancer. Methods: MEDLINE and Embase were searched for diagnostic accuracy studies that used $^{18}F-FDG$ PET or PET/CT for pre-treatment staging, using surgical findings as the reference standard. Sensitivities and specificities were pooled and plotted in a hierarchic summary receiver operating characteristic plot. Potential causes of heterogeneity were explored through sensitivity analyses. Results: Eight studies with 594 patients were included. The overall pooled sensitivity and specificity for metastasis were 0.72 (95% confidence interval [CI]=0.61-0.81) and 0.93 (95% CI=0.85-0.97), respectively. There was considerable heterogeneity in sensitivity ($I^2=97.57%$) and specificity ($I^2=96.74%$). In sensitivity analyses, studies that used laparotomy as the reference standard showed significantly higher sensitivity and specificity (0.77; 95% CI=0.67-0.87 and 0.96; 95% CI=0.92-0.99, respectively) than those including diagnostic laparoscopy (0.62; 95% CI=0.46-0.77 and 0.84; 95% CI=0.69-0.99, respectively). Higher specificity was shown in studies that confirmed surgical findings by pathologic evaluation (0.95; 95% CI=0.90-0.99) than in a study without pathologic confirmation (0.69; 95% CI=0.24-1.00). Studies with a lower prevalence of the FDG-avid subtype showed higher specificity (0.97; 95% CI=0.94-1.00) than those with a greater prevalence (0.89; 95% CI=0.80-0.97). Conclusion: Pre-treatment $^{18}F-FDG$ PET/CT shows moderate sensitivity and high specificity for detecting metastasis in ovarian cancer. With its low false-positive rate, it can help select surgical approaches or alternative treatment options.

• Journal of radiological science and technology
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• v.44 no.4
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• pp.307-313
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• 2021

The purpose of this study was to analyze the risk factors for uterine myoma diagnosed by ultrasonography in Korea women and to evaluate the risk. Among the patients who visited the outpatient department of obstetrics and gynecology at I hospital in Busin between January 2019 and March 2021 for the purpose of examination, 98 patients in the experimental group diagnosed with uterine myoma and 163 patients in the normal control group without other diseases were retrospectively conducted. Among the general characteristics of the subjects, age, body mass index, parity, and menopause showed significant differences between the myoma group and the normal control group. ROC(receiver operating characteristic) curve analysis and logistic regression analysis were performed to obtain the cut off value and odds ratio that can predict the occurrence of uterine myoma. The cut off value for the prediction of uterine myoma was determined to be 30 years old and a body mass index of 23 kg/m². After that adjusting for menopause, non menopausal cases with a body mass index of 23 kg/m² and over 39 years of age had the highest odds ratio of 6.04. Therefore, premenopausal women over 40 years of age require regular checkups and thorough weight management. This study was conducted with a small number of subjects. Therefore, there is a limit to generalizing to all Korean women. However, based on this study if a large scale prospective study considering various variables is made, it can play a role as a predictive marker in early detection of uterine myoma.

• Journal of Korean Neurosurgical Society
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• v.64 no.2
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• pp.189-197
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• 2021

Objective : This study aims to investigate the relationship between aneurysm wall enhancement and clinical rupture risks based on the magnetic resonance vessel wall imaging (MR-VWI) quantitative methods. Methods : One hundred and eight patients with 127 unruptured aneurysms were prospectively enrolled from Feburary 2016 to October 2017. Aneurysms were divided into high risk (≥10) and intermediate-low risk group (<10) according to the PHASES (Population, Hypertension, Age, Size of aneurysm, Earlier SAH history from another aneurysm, Site of aneurysm) scores. Clinical risk factors, aneurysm morphology, and wall enhancement index (WEI) calculated using 3D MR-VWI were analyzed and compared. Results : In comparison of high-risk and intermediated-low risk groups, univariate analysis showed that neck width (4.5±3.3 mm vs. 3.4±1.7 mm, p=0.002), the presence of wall enhancement (100.0% vs. 62.9%, p<0.001), and WEI (1.6±0.6 vs. 0.8±0.8, p<0.001) were significantly associated with high rupture risk. Multivariate regression analysis revealed that WEI was the most important factor in predicting high rupture risk (odds ratio, 2.6; 95% confidence interval, 1.4-4.9; p=0.002). The receiver operating characteristic (ROC) curve analysis can efficiently differentiate higher risk aneurysms (area under the curve, 0.780; p<0.001) which have a reliable WEI cutoff value (1.04; sensitivity, 0.833; specificity, 0.67) predictive of high rupture risk. Conclusion : Aneurysms with higher rupture risk based on PHASES score demonstrate increased neck width, wall enhancement, and the enhancement intensity. Higher WEI in unruptured aneurysms has a predictive value for increased rupture risk.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.64-76
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• 2020

Purpose: Several screening tools have been developed to identify sarcopenia in rural community-dwelling older adults. We aimed to compare the diagnostic accuracy of two such tools, namely the SARC-F and SARC-CalF assessments. Methods: This cross-sectional study on 388 community-dwelling older adults comprised 254 women and 134 men with a mean age of 77.8 ± 6.26 year in Korea. We assessed muscle mass, muscle strength, and physical performance using a bioimpedance analysis device, hydraulic hand dynamometer, and 4 m gait speed test, respectively. Three widely-used diagnostic criteria [the Asian Working Group for Sarcopenia (AWGS), European Working Group on Sarcopenia in Older People, and the International Working Group on Sarcopenia] were applied. Sensitivity and specificity analyses were performed on the SARC-CalF and SARC-F tests. We used receiver-operating characteristic curves and the area under the curves (AUCs) to compare the diagnostic accuracy of the assessments with regard to sarcopenia. Results: An analysis using four sets of diagnostic criteria showed that the prevalence of sarcopenia was 27.6% to 41.0%. Using the AWGS 2019 criteria as a reference standard, the SARC-CalF had a sensitivity of 83.02% and a specificity of 53.71% in the entire study population, whereas the SARC-F had a sensitivity of 79.87% and a specificity of 41.92%. The AUCs for the SARC-CalF and SARC-F tests were 0.725 (95% confidence interval 0.678-0.769) and 0.645 (95% confidence interval 0.595-0.693), respectively (p<001). In the analyses using the other three diagnostic criteria, similarity was also confirmed. Conclusion: SARC-CalF showed better sensitivity than did SARC-F when diagnosing sarcopenia in rural community-dwelling older adults. Further studies are needed to verify this finding in different populations.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.23-30
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• 2020

In this study, the relationship between natural gas (NG) data and gas-related environmental elements was performed using machine learning algorithms to predict the level of gas leakage risk without directly measuring gas leakage data. The study was based on open data provided by the server using the IoT-based remote control Picarro gas sensor specification. The naturel gas leaks into the air, it is a big problem for air pollution, environment and the health. The proposed method is multivariate outlier removing method based Random Forest (RF) classification for predicting risk of NG leak. After, unsupervised k-means clustering, the experimental dataset has done imbalanced data. Therefore, we focusing our proposed models can predict medium and high risk so best. In this case, we compared the receiver operating characteristic (ROC) curve, accuracy, area under the ROC curve (AUC), and mean standard error (MSE) for each classification model. As a result of our experiments, the evaluation measurements include accuracy, area under the ROC curve (AUC), and MSE; 99.71%, 99.57%, and 0.0016 for MOL_RF respectively.

• Investigative Magnetic Resonance Imaging
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• v.25 no.2
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• pp.118-128
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• 2021

Purpose: To investigate the value of MR textural analysis, including use of diffusion-weighted imaging (DWI) to differentiate malignant from benign soft-tissue tumors on 3T MRI. Materials and Methods: We enrolled 69 patients (25 men, 44 women, ages 18 to 84 years) with pathologically confirmed soft-tissue tumors (29 benign, 40 malignant) who underwent pre-treatment 3T-MRI. We calculated MR texture, including mean, standard deviation (SD), skewness, kurtosis, mean of positive pixels (MPP), and entropy, according to different spatial-scale factors (SSF, 0, 2, 4, 6) on axial T1- and T2-weighted images (T1WI, T2WI), contrast-enhanced T1WI (CE-T1WI), high b-value DWI (800 sec/mm²), and apparent diffusion coefficient (ADC) map. We used the Mann-Whitney U test, logistic regression, and area under the receiver operating characteristic curve (AUC) for statistical analysis. Results: Malignant soft-tissue tumors had significantly lower mean values of DWI, ADC, T2WI and CE-T1WI, MPP of ADC, and CE-T1WI, but significantly higher kurtosis of DWI, T1WI, and CE-T1WI, and entropy of DWI, ADC, and T2WI than did benign tumors (P < 0.050). In multivariate logistic regression, the mean ADC value (SSF, 6) and kurtosis of CE-T1WI (SSF, 4) were independently associated with malignancy (P ≤ 0.009). A multivariate model of MR features worked well for diagnosis of malignant soft-tissue tumors (AUC, 0.909). Conclusion: Accurate diagnosis could be obtained using MR textural analysis with DWI and CE-T1WI in differentiating benign from malignant soft-tissue tumors.

• Journal of dental hygiene science
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• v.20 no.4
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• pp.206-212
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• 2020

Background: A Teachable Machine is a kind of machine learning web-based tool for general persons. In this paper, the feasibility of Google's Teachable Machine (ver. 2.0) was studied in the diagnosis of the tooth-marked tongue. Methods: For machine learning of tooth-marked tongue diagnosis, a total of 1,250 tongue images were used on Kaggle's web site. Ninety percent of the images were used for the training data set, and the remaining 10% were used for the test data set. Using Google's Teachable Machine (ver. 2.0), machine learning was performed using separated images. To optimize the machine learning parameters, I measured the diagnosis accuracies according to the value of epoch, batch size, and learning rate. After hyper-parameter tuning, the ROC (receiver operating characteristic) analysis method determined the sensitivity (true positive rate, TPR) and specificity (false positive rate, FPR) of the machine learning model to diagnose the tooth-marked tongue. Results: To evaluate the usefulness of the Teachable Machine in clinical application, I used 634 tooth-marked tongue images and 491 no-marked tongue images for machine learning. When the epoch, batch size, and learning rate as hyper-parameters were 75, 0.0001, and 128, respectively, the accuracy of the tooth-marked tongue's diagnosis was best. The accuracies for the tooth-marked tongue and the no-marked tongue were 92.1% and 72.6%, respectively. And, the sensitivity (TPR) and specificity (FPR) were 0.92 and 0.28, respectively. Conclusion: These results are more accurate than Li's experimental results calculated with convolution neural network. Google's Teachable Machines show good performance by hyper-parameters tuning in the diagnosis of the tooth-marked tongue. We confirmed that the tool is useful for several clinical applications.

• Journal of The Korean Society of Clinical Toxicology
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• v.18 no.2
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• pp.130-135
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• 2020

Purpose: Taking large amounts of glyphosate is life-threatening, but the amounts of glyphosate taken by patients for suicide are not known precisely. The purpose of this study was to find the predictors of large amounts of glyphosate ingestion. Methods: This retrospective study analyzed patients presenting to an emergency department with glyphosate intoxication between 2010 and 2019, in a single tertiary hospital. The variables associated with the intake amounts were investigated. The parameters were analyzed by multivariate variate logistic regression analyses and the receiver operating characteristic (ROC) curve. Results: Of the 28 patients with glyphosate intoxication, 15 (53.6%) were in the large amounts group. Univariate analysis showed that metabolic acidosis, lactic acid, and corrected QT (QTc) interval were significant factors. In contrast, multivariate analysis presented the QTc interval as the only independent factor with intoxication from large amounts of glyphosate. (odds ratio, 95% confidence interval: 1.073, 1.011-1.139; p=0.020) The area under the ROC curve of the QTc interval was 0.838. Conclusion: The QTc interval is associated significantly with patients who visit the emergency department after being intoxicated by large amounts of glyphosate. These conclusions will help in the initial triage of patients with glyphosate intoxication.