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Effect of Experimental Factors on Reduction of Nitrogen Compounds Contained in Crude Methylnaphthalene Oil by Formamide Extraction (포름아미드 추출에 의한 조제 메틸나프탈렌유에 함유된 질소화합물의 저감에 관한 실험인자의 영향)

  • Su Jin Kim
    • Applied Chemistry for Engineering
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    • v.34 no.6
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    • pp.665-669
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    • 2023
  • The crude methylnaphthalene oil (CMNO) contains nitrogen compounds (NCs) such as quinoline (QU), isoquinoline (IQU), and indole (IN). These NCs in the CMNO are treated as impurities contained in the CMNO due to contamination of the atmospheric environment and unpleasant odors. In order to improve the quality of CMNO, this study examined the effect of extraction experimental factors on the reduction of NCs contained in CMNO using CMNO as a raw material and an aqueous formamide solution as a solvent, respectively. The increase in the volume ratio of solvent to feed in initial (S/F)0 in initial increased the distribution coefficient of NCs and the selectivity of NCs in reference to 2-methylnaphthalene (2MNA). Additionally, an increase in operating temperature (T) increased the distribution coefficient of NCs but conversely decreased selectivity. The compositions of QU, IQU, and IN in the raffinate oil recovered through equilibrium extraction under a constant condition (volume fraction of water to solvent in initial (yw,0) = 0.1, (S/F)0 = 9, T = 303 K, liquid-liquid contacting time = 72 h) were reduced by about 58.5 wt%, 61.9 wt%, and 73.4 wt%, respectively, compared to those of CMNO. The formamide extraction method in this study was expected to be an effective reduction method for NCs contained in CMNO.

A Study on Non-financial Factors Affecting the Insolvency of Social Enterprises (사회적기업의 부실에 영향을 미치는 비재무요인에 관한 연구 )

  • Yong-Chan, Chun;Hyeok, Kim;Dong-Myung, Lee
    • Journal of Industrial Convergence
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    • v.21 no.11
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    • pp.13-27
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    • 2023
  • This study aims to contribute to the reduction of the failure rate and social costs resulting from business failures by analyzing factors that affect the insolvency of social enterprises, as the role of social enterprises is increasing in our economy. The data used in this study were classified as normal and insolvent companies among social enterprises (including prospective social enterprises) that were established between 2009 and 2018 and received credit guarantees from credit guarantee institutions as of the end of June 2022. Among the collected data, 439 social enterprises with available financial information were targeted; 406 (92.5%) were normal enterprises, and 33 (7.5%) were insolvent enterprises. Through a literature review, eight non-financial factors commonly used for insolvency prediction were selected. The cross-analysis results showed that four of these factors were significant. Logistic regression analysis revealed that two variables, including corporate credit rating and the personal credit rating of the representative, were significant. Financial factors such as debt ratio, sales operating profit rate, and total asset turnover were used as control variables. The empirical analysis confirmed that the two independent variables maintained their influence even after controlling for financial factors. Given that government-led support and development policies have limitations, there is a need to shift policy direction so that various companies aspiring to create social value can enter the social enterprise sector through private and regional initiatives. This would enable the social economy to create an environment where local residents can collaborate to realize social value, and the government should actively support this.

MRI Findings Suggestive of Metastatic Axillary Lymph Nodes in Patients with Invasive Breast Cancer (유방암 환자에서 액와부 림프절 전이를 시사하는 자기공명영상 소견)

  • Ka Eun Kim;Shin Young Kim;Eun Young Ko
    • Journal of the Korean Society of Radiology
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    • v.83 no.3
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    • pp.620-631
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    • 2022
  • Purpose This study aimed to investigate the diagnostic performance of features suggestive of nodal metastasis on preoperative MRI in patients with invasive breast cancer. Materials and Methods We retrospectively reviewed the preoperative breast MRI of 192 consecutive patients with surgically proven invasive breast cancer. We analyzed MRI findings of axillary lymph nodes with regard to the size, long/short ratio, cortical thickness, shape and margin of the cortex, loss of hilum, asymmetry, signal intensity (SI) on T2-weighted images (T2WI), degree of enhancement in the early phase, and enhancement kinetics. Receiver operating characteristic (ROC) analysis, chi-square test, t test, and McNemar's test were used for statistical analysis. Results Increased shorter diameter, uneven cortical shape, increased cortical thickness, loss of hilum, asymmetry, irregular cortical margin, and low SI on T2WI were significantly suggestive of metastasis. ROC analysis revealed the cutoff value for the shorter diameter and cortical thickness as 8.05 mm and 2.75 mm, respectively. Increased cortical thickness (> 2.75 mm) and uneven cortical shape showed significantly higher sensitivity than other findings in McNemar's test. Irregular cortical margins showed the highest specificity (100%). Conclusion Cortical thickness > 2.75 mm and uneven cortical shape are more sensitive parameters than other findings, and an irregular cortical margin is the most specific parameter for predicting axillary metastasis in patients with invasive breast cancer.

Prognostic Value of 18F-FDG PET/CT Radiomics in Extranodal Nasal-Type NK/T Cell Lymphoma

  • Yu Luo;Zhun Huang;Zihan Gao;Bingbing Wang;Yanwei Zhang;Yan Bai;Qingxia Wu;Meiyun Wang
    • Korean Journal of Radiology
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    • v.25 no.2
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    • pp.189-198
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    • 2024
  • Objective: To investigate the prognostic utility of radiomics features extracted from 18F-fluorodeoxyglucose (FDG) PET/CT combined with clinical factors and metabolic parameters in predicting progression-free survival (PFS) and overall survival (OS) in individuals diagnosed with extranodal nasal-type NK/T cell lymphoma (ENKTCL). Materials and Methods: A total of 126 adults with ENKTCL who underwent 18F-FDG PET/CT examination before treatment were retrospectively included and randomly divided into training (n = 88) and validation cohorts (n = 38) at a ratio of 7:3. Least absolute shrinkage and selection operation Cox regression analysis was used to select the best radiomics features and calculate each patient's radiomics scores (RadPFS and RadOS). Kaplan-Meier curve and Log-rank test were used to compare survival between patient groups risk-stratified by the radiomics scores. Various models to predict PFS and OS were constructed, including clinical, metabolic, clinical + metabolic, and clinical + metabolic + radiomics models. The discriminative ability of each model was evaluated using Harrell's C index. The performance of each model in predicting PFS and OS for 1-, 3-, and 5-years was evaluated using the time-dependent receiver operating characteristic (ROC) curve. Results: Kaplan-Meier curve analysis demonstrated that the radiomics scores effectively identified high- and low-risk patients (all P < 0.05). Multivariable Cox analysis showed that the Ann Arbor stage, maximum standardized uptake value (SUVmax), and RadPFS were independent risk factors associated with PFS. Further, β2-microglobulin, Eastern Cooperative Oncology Group performance status score, SUVmax, and RadOS were independent risk factors for OS. The clinical + metabolic + radiomics model exhibited the greatest discriminative ability for both PFS (Harrell's C-index: 0.805 in the validation cohort) and OS (Harrell's C-index: 0.833 in the validation cohort). The time-dependent ROC analysis indicated that the clinical + metabolic + radiomics model had the best predictive performance. Conclusion: The PET/CT-based clinical + metabolic + radiomics model can enhance prognostication among patients with ENKTCL and may be a non-invasive and efficient risk stratification tool for clinical practice.

Development and Testing of a Machine Learning Model Using 18F-Fluorodeoxyglucose PET/CT-Derived Metabolic Parameters to Classify Human Papillomavirus Status in Oropharyngeal Squamous Carcinoma

  • Changsoo Woo;Kwan Hyeong Jo;Beomseok Sohn;Kisung Park;Hojin Cho;Won Jun Kang;Jinna Kim;Seung-Koo Lee
    • Korean Journal of Radiology
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    • v.24 no.1
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    • pp.51-61
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    • 2023
  • Objective: To develop and test a machine learning model for classifying human papillomavirus (HPV) status of patients with oropharyngeal squamous cell carcinoma (OPSCC) using 18F-fluorodeoxyglucose (18F-FDG) PET-derived parameters in derived parameters and an appropriate combination of machine learning methods in patients with OPSCC. Materials and Methods: This retrospective study enrolled 126 patients (118 male; mean age, 60 years) with newly diagnosed, pathologically confirmed OPSCC, that underwent 18F-FDG PET-computed tomography (CT) between January 2012 and February 2020. Patients were randomly assigned to training and internal validation sets in a 7:3 ratio. An external test set of 19 patients (16 male; mean age, 65.3 years) was recruited sequentially from two other tertiary hospitals. Model 1 used only PET parameters, Model 2 used only clinical features, and Model 3 used both PET and clinical parameters. Multiple feature transforms, feature selection, oversampling, and training models are all investigated. The external test set was used to test the three models that performed best in the internal validation set. The values for area under the receiver operating characteristic curve (AUC) were compared between models. Results: In the external test set, ExtraTrees-based Model 3, which uses two PET-derived parameters and three clinical features, with a combination of MinMaxScaler, mutual information selection, and adaptive synthetic sampling approach, showed the best performance (AUC = 0.78; 95% confidence interval, 0.46-1). Model 3 outperformed Model 1 using PET parameters alone (AUC = 0.48, p = 0.047) and Model 2 using clinical parameters alone (AUC = 0.52, p = 0.142) in predicting HPV status. Conclusion: Using oversampling and mutual information selection, an ExtraTree-based HPV status classifier was developed by combining metabolic parameters derived from 18F-FDG PET/CT and clinical parameters in OPSCC, which exhibited higher performance than the models using either PET or clinical parameters alone.

Pre- and Immediate Post-Kasai Portoenterostomy Shear Wave Elastography for Predicting Hepatic Fibrosis and Native Liver Outcomes in Patients With Biliary Atresia

  • Haesung Yoon;Kyong Ihn;Jisoo Kim;Hyun Ji Lim;Sowon Park;Seok Joo Han;Kyunghwa Han;Hong Koh;Mi-Jung Lee
    • Korean Journal of Radiology
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    • v.24 no.5
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    • pp.465-475
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    • 2023
  • Objective: To evaluate the feasibility of ultrasound shear wave elastography (SWE) for predicting hepatic fibrosis and native liver outcomes in patients with biliary atresia. Materials and Methods: This prospective study included 33 consecutive patients with biliary atresia (median age, 8 weeks [interquartile range, 6-10 weeks]; male:female ratio, 15:18) from Severance Children's Hospital between May 2019 and February 2022. Preoperative (within 1 week from surgery) and immediate postoperative (on postoperative days [PODs] 3, 5, and 7) ultrasonographic findings were obtained and analyzed, including the SWE of the liver and spleen. Hepatic fibrosis, according to the METAVIR score at the time of Kasai portoenterostomy and native liver outcomes during postsurgical follow-up, were compared and correlated with imaging and laboratory findings. Poor outcomes were defined as intractable cholangitis or liver transplantation. The diagnostic performance of SWE in predicting METAVIR F3-F4 and poor hepatic outcomes was analyzed using receiver operating characteristic (ROC) analyses. Results: All patients were analyzed without exclusion. Perioperative advanced hepatic fibrosis (F3-F4) was associated with older age and higher preoperative direct bilirubin and SWE values in the liver and spleen. Preoperative liver SWE showed a ROC area of 0.806 and 63.6% (7/11) sensitivity and 86.4% (19/22) specificity at a cutoff of 17.5 kPa for diagnosing F3-F4. The poor outcome group included five patients with intractable cholangitis and three undergoing liver transplantation who showed high postoperative liver SWE values. Liver SWE on PODs 3-7 showed ROC areas of 0.783-0.891 for predicting poor outcomes, and a cutoff value of 10.3 kPa for SWE on POD 3 had 100% (8/8) sensitivity and 73.9% (17/23) specificity. Conclusion: Preoperative liver SWE can predict advanced hepatic fibrosis, and immediate postoperative liver SWE can predict poor native liver outcomes in patients with biliary atresia.

Qualitative and Quantitative Magnetic Resonance Imaging Phenotypes May Predict CDKN2A/B Homozygous Deletion Status in Isocitrate Dehydrogenase-Mutant Astrocytomas: A Multicenter Study

  • Yae Won Park;Ki Sung Park;Ji Eun Park;Sung Soo Ahn;Inho Park;Ho Sung Kim;Jong Hee Chang;Seung-Koo Lee;Se Hoon Kim
    • Korean Journal of Radiology
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    • v.24 no.2
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    • pp.133-144
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    • 2023
  • Objective: Cyclin-dependent kinase inhibitor (CDKN)2A/B homozygous deletion is a key molecular marker of isocitrate dehydrogenase (IDH)-mutant astrocytomas in the 2021 World Health Organization. We aimed to investigate whether qualitative and quantitative MRI parameters can predict CDKN2A/B homozygous deletion status in IDH-mutant astrocytomas. Materials and Methods: Preoperative MRI data of 88 patients (mean age ± standard deviation, 42.0 ± 11.9 years; 40 females and 48 males) with IDH-mutant astrocytomas (76 without and 12 with CDKN2A/B homozygous deletion) from two institutions were included. A qualitative imaging assessment was performed. Mean apparent diffusion coefficient (ADC), 5th percentile of ADC, mean normalized cerebral blood volume (nCBV), and 95th percentile of nCBV were assessed via automatic tumor segmentation. Logistic regression was performed to determine the factors associated with CDKN2A/B homozygous deletion in all 88 patients and a subgroup of 47 patients with histological grades 3 and 4. The discrimination performance of the logistic regression models was evaluated using the area under the receiver operating characteristic curve (AUC). Results: In multivariable analysis of all patients, infiltrative pattern (odds ratio [OR] = 4.25, p = 0.034), maximal diameter (OR = 1.07, p = 0.013), and 95th percentile of nCBV (OR = 1.34, p = 0.049) were independent predictors of CDKN2A/B homozygous deletion. The AUC, accuracy, sensitivity, and specificity of the corresponding model were 0.83 (95% confidence interval [CI], 0.72-0.91), 90.4%, 83.3%, and 75.0%, respectively. On multivariable analysis of the subgroup with histological grades 3 and 4, infiltrative pattern (OR = 10.39, p = 0.012) and 95th percentile of nCBV (OR = 1.24, p = 0.047) were independent predictors of CDKN2A/B homozygous deletion, with an AUC accuracy, sensitivity, and specificity of the corresponding model of 0.76 (95% CI, 0.60-0.88), 87.8%, 80.0%, and 58.1%, respectively. Conclusion: The presence of an infiltrative pattern, larger maximal diameter, and higher 95th percentile of the nCBV may be useful MRI biomarkers for CDKN2A/B homozygous deletion in IDH-mutant astrocytomas.

Deep Learning-Based Assessment of Functional Liver Capacity Using Gadoxetic Acid-Enhanced Hepatobiliary Phase MRI

  • Hyo Jung Park;Jee Seok Yoon;Seung Soo Lee;Heung-Il Suk;Bumwoo Park;Yu Sub Sung;Seung Baek Hong;Hwaseong Ryu
    • Korean Journal of Radiology
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    • v.23 no.7
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    • pp.720-731
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    • 2022
  • Objective: We aimed to develop and test a deep learning algorithm (DLA) for fully automated measurement of the volume and signal intensity (SI) of the liver and spleen using gadoxetic acid-enhanced hepatobiliary phase (HBP)-magnetic resonance imaging (MRI) and to evaluate the clinical utility of DLA-assisted assessment of functional liver capacity. Materials and Methods: The DLA was developed using HBP-MRI data from 1014 patients. Using an independent test dataset (110 internal and 90 external MRI data), the segmentation performance of the DLA was measured using the Dice similarity score (DSS), and the agreement between the DLA and the ground truth for the volume and SI measurements was assessed with a Bland-Altman 95% limit of agreement (LOA). In 276 separate patients (male:female, 191:85; mean age ± standard deviation, 40 ± 15 years) who underwent hepatic resection, we evaluated the correlations between various DLA-based MRI indices, including liver volume normalized by body surface area (LVBSA), liver-to-spleen SI ratio (LSSR), MRI parameter-adjusted LSSR (aLSSR), LSSR × LVBSA, and aLSSR × LVBSA, and the indocyanine green retention rate at 15 minutes (ICG-R15), and determined the diagnostic performance of the DLA-based MRI indices to detect ICG-R15 ≥ 20%. Results: In the test dataset, the mean DSS was 0.977 for liver segmentation and 0.946 for spleen segmentation. The Bland-Altman 95% LOAs were 0.08% ± 3.70% for the liver volume, 0.20% ± 7.89% for the spleen volume, -0.02% ± 1.28% for the liver SI, and -0.01% ± 1.70% for the spleen SI. Among DLA-based MRI indices, aLSSR × LVBSA showed the strongest correlation with ICG-R15 (r = -0.54, p < 0.001), with area under receiver operating characteristic curve of 0.932 (95% confidence interval, 0.895-0.959) to diagnose ICG-R15 ≥ 20%. Conclusion: Our DLA can accurately measure the volume and SI of the liver and spleen and may be useful for assessing functional liver capacity using gadoxetic acid-enhanced HBP-MRI.

Non-Contrast Cine Cardiac Magnetic Resonance Derived-Radiomics for the Prediction of Left Ventricular Adverse Remodeling in Patients With ST-Segment Elevation Myocardial Infarction

  • Xin A;Mingliang Liu;Tong Chen;Feng Chen;Geng Qian;Ying Zhang;Yundai Chen
    • Korean Journal of Radiology
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    • v.24 no.9
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    • pp.827-837
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    • 2023
  • Objective: To investigate the predictive value of radiomics features based on cardiac magnetic resonance (CMR) cine images for left ventricular adverse remodeling (LVAR) after acute ST-segment elevation myocardial infarction (STEMI). Materials and Methods: We conducted a retrospective, single-center, cohort study involving 244 patients (random-split into 170 and 74 for training and testing, respectively) having an acute STEMI (88.5% males, 57.0 ± 10.3 years of age) who underwent CMR examination at one week and six months after percutaneous coronary intervention. LVAR was defined as a 20% increase in left ventricular end-diastolic volume 6 months after acute STEMI. Radiomics features were extracted from the oneweek CMR cine images using the least absolute shrinkage and selection operator regression (LASSO) analysis. The predictive performance of the selected features was evaluated using receiver operating characteristic curve analysis and the area under the curve (AUC). Results: Nine radiomics features with non-zero coefficients were included in the LASSO regression of the radiomics score (RAD score). Infarct size (odds ratio [OR]: 1.04 (1.00-1.07); P = 0.031) and RAD score (OR: 3.43 (2.34-5.28); P < 0.001) were independent predictors of LVAR. The RAD score predicted LVAR, with an AUC (95% confidence interval [CI]) of 0.82 (0.75-0.89) in the training set and 0.75 (0.62-0.89) in the testing set. Combining the RAD score with infarct size yielded favorable performance in predicting LVAR, with an AUC of 0.84 (0.72-0.95). Moreover, the addition of the RAD score to the left ventricular ejection fraction (LVEF) significantly increased the AUC from 0.68 (0.52-0.84) to 0.82 (0.70-0.93) (P = 0.018), which was also comparable to the prediction provided by the combined microvascular obstruction, infarct size, and LVEF with an AUC of 0.79 (0.65-0.94) (P = 0.727). Conclusion: Radiomics analysis using non-contrast cine CMR can predict LVAR after STEMI independently and incrementally to LVEF and may provide an alternative to traditional CMR parameters.

Total Bilirubin Level as a Predictor of Suboptimal Image Quality of the Hepatobiliary Phase of Gadoxetic Acid-Enhanced MRI in Patients with Extrahepatic Bile Duct Cancer

  • Jeong Ah Hwang;Ji Hye Min;Seong Hyun Kim;Seo-Youn Choi;Ji Eun Lee;Ji Yoon Moon
    • Korean Journal of Radiology
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    • v.23 no.4
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    • pp.389-401
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    • 2022
  • Objective: This study aimed to determine a factor for predicting suboptimal image quality of the hepatobiliary phase (HBP) of gadoxetic acid-enhanced MRI in patients with extrahepatic bile duct (EHD) cancer before MRI examination. Materials and Methods: We retrospectively evaluated 259 patients (mean age ± standard deviation: 68.0 ± 8.3 years; 162 male and 97 female) with EHD cancer who underwent gadoxetic acid-enhanced MRI between 2011 and 2017. Patients were divided into a primary analysis set (n = 184) and a validation set (n = 75) based on the diagnosis date of January 2014. Two reviewers assigned the functional liver imaging score (FLIS) to reflect the HBP image quality. The FLIS consists of the sum of three HBP features, each scored on a 0-2 scale: liver parenchymal enhancement, biliary excretion, and signal intensity of the portal vein. Patients were classified into low-FLIS (0-3) or high-FLIS (4-6) groups. Multivariable analysis was performed to determine a predictor of low FLIS using serum biochemical and imaging parameters of cholestasis severity. The optimal cutoff value for predicting low FLIS was obtained using receiver operating characteristic analysis, and validation was performed. Results: Of the 259 patients, 140 (54.0%) and 119 (46.0%) were classified into the low-FLIS and high-FLIS groups, respectively. In the primary analysis set, total bilirubin was an independent factor associated with low FLIS (adjusted odds ratio per 1-mg/dL increase, 1.62; 95% confidence interval [CI], 1.32-1.98). The optimal cutoff value of total bilirubin for predicting low FLIS was 2.1 mg/dL with a sensitivity of 95.1% (95% CI: 88.9-98.4) and a specificity of 89.0% (95% CI: 80.2-94.9). In the validation set, the total bilirubin cutoff showed a sensitivity of 92.1% (95% CI: 78.6-98.3) and a specificity of 83.8% (95% CI: 68.0-93.8). Conclusion: Serum total bilirubin before acquisition of gadoxetic acid-enhanced MRI may help predict suboptimal HBP image quality in patients with EHD cancer.