• Journal of the Korean Society of Radiology
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• v.82 no.5
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• pp.1218-1230
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• 2021

Purpose To compare the per-patient diagnostic performance of simulated abbreviated MRI (AMRI) to that of conventional MRI (CMRI) with full-sequence dynamic gadoxetic acid (GA) enhancement for early-stage hepatocellular carcinoma (HCC) screening in high-risk patients. Materials and Methods A total of 201 consecutive patients at high-risk for HCC, who underwent 3T liver MRI, were included in this retrospective study. The AMRI protocol comprised T2-weighted imaging, hepatobiliary phase imaging after GA injection, and diffusion-weighted imaging. For each patient, two AMRI and CMRI image sets were independently reviewed by two radiologists. Inter-reader agreement was assessed using Cohen's kappa value. A composite reference standard was used to determine the diagnostic performance of each image set for each reader. Results A total of 93 HCCs were detected in 79 patients. The inter-reader agreement was almost perfect for both image sets (κ = 0.839, 0.948). In AMRI, the per-patient sensitivity and negative predictive values (NPV) were 94.9% and 96.4%, respectively. In CMRI, the per-patient sensitivity and NPV were 96.2% and 97.5%, respectively. Conclusion AMRI, using only three sequences, had a comparable diagnostic performance to CMRI in screening early-stage HCC. AMRI could be an alternative HCC screening tool for high-risk HCC patients.

• Korean Journal of Radiology
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• v.23 no.10
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• pp.939-948
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• 2022

Objective: Evidence supports the efficacy of coronary computed tomography angiography (CCTA)-based risk scores in cardiovascular risk stratification of patients with suspected coronary artery disease (CAD). We aimed to compare two CCTA-based risk score algorithms, Leiden and Confirm scores, in patients with diabetes mellitus (DM) and suspected CAD. Materials and Methods: This single-center prospective cohort study consecutively included 1241 DM patients (54.1% male, 60.2 ± 10.4 years) referred for CCTA for suspected CAD in 2015-2017. Leiden and Confirm scores were calculated and stratified as < 5 (reference), 5-20, and > 20 for Leiden and < 14.3 (reference), 14.3-19.5, and > 19.5 for Confirm. Major adverse cardiovascular events (MACE) were defined as the composite outcomes of cardiovascular death, nonfatal myocardial infarction (MI), stroke, and unstable angina requiring hospitalization. The Cox model and Kaplan-Meier method were used to evaluate the effect size of the risk scores on MACE. The area under the curve (AUC) at the median follow-up time was also compared between score algorithms. Results: During a median follow-up of 31 months (interquartile range, 27.6-37.3 months), 131 of MACE were recorded, including 17 cardiovascular deaths, 28 nonfatal MIs, 64 unstable anginas requiring hospitalization, and 22 strokes. An incremental incidence of MACE was observed in both Leiden and Confirm scores, with an increase in the scores (log-rank p < 0.001). In the multivariable analysis, compared with Leiden score < 5, the hazard ratios for Leiden scores of 5-20 and > 20 were 2.37 (95% confidence interval [CI]: 1.53-3.69; p < 0.001) and 4.39 (95% CI: 2.40-8.01; p < 0.001), respectively, while the Confirm score did not demonstrate a statistically significant association with the risk of MACE. The Leiden score showed a greater AUC of 0.840 compared to 0.777 for the Confirm score (p < 0.001). Conclusion: CCTA-based risk score algorithms could be used as reliable cardiovascular risk predictors in patients with DM and suspected CAD, among which the Leiden score outperformed the Confirm score in predicting MACE.

• Korean Journal of Radiology
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• v.23 no.12
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• pp.1269-1280
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• 2022

Objective: This study aimed to evaluate the usefulness of quantitative indices obtained from deep learning analysis of gadoxetic acid-enhanced hepatobiliary phase (HBP) MRI and their longitudinal changes in predicting decompensation and death in patients with advanced chronic liver disease (ACLD). Materials and Methods: We included patients who underwent baseline and 1-year follow-up MRI from a prospective cohort that underwent gadoxetic acid-enhanced MRI for hepatocellular carcinoma surveillance between November 2011 and August 2012 at a tertiary medical center. Baseline liver condition was categorized as non-ACLD, compensated ACLD, and decompensated ACLD. The liver-to-spleen signal intensity ratio (LS-SIR) and liver-to-spleen volume ratio (LS-VR) were automatically measured on the HBP images using a deep learning algorithm, and their percentage changes at the 1-year follow-up (ΔLS-SIR and ΔLS-VR) were calculated. The associations of the MRI indices with hepatic decompensation and a composite endpoint of liver-related death or transplantation were evaluated using a competing risk analysis with multivariable Fine and Gray regression models, including baseline parameters alone and both baseline and follow-up parameters. Results: Our study included 280 patients (153 male; mean age ± standard deviation, 57 ± 7.95 years) with non-ACLD, compensated ACLD, and decompensated ACLD in 32, 186, and 62 patients, respectively. Patients were followed for 11-117 months (median, 104 months). In patients with compensated ACLD, baseline LS-SIR (sub-distribution hazard ratio [sHR], 0.81; p = 0.034) and LS-VR (sHR, 0.71; p = 0.01) were independently associated with hepatic decompensation. The ΔLS-VR (sHR, 0.54; p = 0.002) was predictive of hepatic decompensation after adjusting for baseline variables. ΔLS-VR was an independent predictor of liver-related death or transplantation in patients with compensated ACLD (sHR, 0.46; p = 0.026) and decompensated ACLD (sHR, 0.61; p = 0.023). Conclusion: MRI indices automatically derived from the deep learning analysis of gadoxetic acid-enhanced HBP MRI can be used as prognostic markers in patients with ACLD.

• Korean Journal of Radiology
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• v.21 no.8
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• pp.1007-1017
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• 2020

Objective: The purpose of our study was to investigate the predictive abilities of clinical and computed tomography (CT) features for outcome prediction in patients with coronavirus disease (COVID-19). Materials and Methods: The clinical and CT data of 238 patients with laboratory-confirmed COVID-19 in our two hospitals were retrospectively analyzed. One hundred sixty-six patients (103 males; age 43.8 ± 12.3 years) were allocated in the training cohort and 72 patients (38 males; age 45.1 ± 15.8 years) from another independent hospital were assigned in the validation cohort. The primary composite endpoint was admission to an intensive care unit, use of mechanical ventilation, or death. Univariate and multivariate Cox proportional hazard analyses were performed to identify independent predictors. A nomogram was constructed based on the combination of clinical and CT features, and its prognostic performance was externally tested in the validation group. The predictive value of the combined model was compared with models built on the clinical and radiological attributes alone. Results: Overall, 35 infected patients (21.1%) in the training cohort and 10 patients (13.9%) in the validation cohort experienced adverse outcomes. Underlying comorbidity (hazard ratio [HR], 3.35; 95% confidence interval [CI], 1.67-6.71; p < 0.001), lymphocyte count (HR, 0.12; 95% CI, 0.04-0.38; p < 0.001) and crazy-paving sign (HR, 2.15; 95% CI, 1.03-4.48; p = 0.042) were the independent factors. The nomogram displayed a concordance index (C-index) of 0.82 (95% CI, 0.76-0.88), and its prognostic value was confirmed in the validation cohort with a C-index of 0.89 (95% CI, 0.82-0.96). The combined model provided the best performance over the clinical or radiological model (p < 0.050). Conclusion: Underlying comorbidity, lymphocyte count and crazy-paving sign were independent predictors of adverse outcomes. The prognostic nomogram based on the combination of clinical and CT features could be a useful tool for predicting adverse outcomes of patients with COVID-19.

• Steel and Composite Structures
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• v.50 no.6
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• pp.705-720
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• 2024

Analyzing the collapse behavior of thin-walled steel structures holds significant importance in ensuring their safety and longevity. Geometric imperfections present on the surface of metal materials can diminish both the durability and mechanical integrity of steel shells. These imperfections, encompassing local geometric irregularities and deformations such as holes, cavities, notches, and cracks localized in specific regions of the shell surface, play a pivotal role in the assessment. They can induce stress concentration within the structure, thereby influencing its susceptibility to buckling. The intricate relationship between the buckling behavior of these structures and such imperfections is multifaceted, contingent upon a variety of factors. The buckling analysis of thin-walled steel shell structures, similar to other steel structures, commonly involves the determination of crucial material properties, including elastic modulus, shear modulus, tensile strength, and fracture toughness. An established method involves the emulation of distributed geometric imperfections, utilizing real test specimen data as a basis. This approach allows for the accurate representation and assessment of the diversity and distribution of imperfections encountered in real-world scenarios. Utilizing defect data obtained from actual test samples enhances the model's realism and applicability. The sizes and configurations of these defects are employed as inputs in the modeling process, aiding in the prediction of structural behavior. It's worth noting that there is a dearth of experimental studies addressing the influence of geometric defects on the buckling behavior of cylindrical steel shells. In this particular study, samples featuring geometric imperfections were subjected to experimental buckling tests. These same samples were also modeled using Finite Element Analysis (FEM), with results corroborating the experimental findings. Furthermore, the initial geometrical imperfections were measured using digital image correlation (DIC) techniques. In this way, the response of the test specimens can be estimated accurately by applying the initial imperfections to FE models. After validation of the test results with FEA, a numerical parametric study was conducted to develop more generalized design recommendations for the stainless-steel shell structures with the initial geometric imperfection. While the load-carrying capacity of samples with perfect surfaces was up to 140 kN, the load-carrying capacity of samples with 4 mm defects was around 130 kN. Likewise, while the load carrying capacity of samples with 10 mm defects was around 125 kN, the load carrying capacity of samples with 14 mm defects was measured around 120 kN.

• Composites Research
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• v.37 no.2
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• pp.101-107
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• 2024

Demand for submarine cable is increasing due to advances in submarine power transmission technology and submarine cable manufacturing technology. Submarine cable use various types of protective equipment to prevent problems such as high maintenance costs in the event of cable damage and power outages during maintenance periods. Among them, flexible protection tube is a representative protective equipment to protect cables and respond to external forces such as waves and current. The flexible protection tube is made of polyurethane 85A hyperelastic material, so the calculation of mechanical behavior is carried out using mechanical properties based on experimental results. In this study, a study was conducted to determine the bending performance and tensile performance of flexible protection tube through analytical methods. The physical properties obtained through the multiaxial tensile test of polyurethane 85A were used for the analysis. Bending and tensile performance were determined for the maximum bending moment standard of 15 kN·m and the tensile load standard of 50 kN. As a result, it was confirmed that when the maximum bending moment of 15 kN·m of the flexible protection tube occurred, the bending performance of the MBR was secured at 13 m and when a tensile load of 50 kN, it was applied the maximum vertical displacement was 968 mm, confirming that the tensile performance was secured.

• Composites Research
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• v.37 no.2
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• pp.86-93
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• 2024

The inner foam structure plays an important role in the performance of the carbon-fiber-reinforced plastic (CFRP) rear spoiler used in automobiles. However, there is still a lack of studies for the CFRP-based rear spoiler according to the type of inner foam, especially under the high-speed driving condition. With this motivation, we numerically analyze the performance of the CFRP rear spoiler using various cases of the inner foam under the highspeed driving condition. Here, polymethacrylimide (PMI), polyvinyl chloride (PVC), and styrene acrylonitrile (SAN) resins are employed as the inner foams in this work. The performances are evaluated using the deformation aspects and vibration characteristics when the driving condition is a high-speed condition (200 km/h). Furthermore, to specifically verify the importance of the inner foam in the high-speed condition, we additionally investigate the performance of the CFRP rear spoiler without the inner foam structure (i.e., hollow type). As a result, it is confirmed that among the types of inner foams utilized in this work, the PMI and PVC inner foams have the best deformation aspect and vibration characteristic, respectively. Note that the hollow-type inner foam has inferior performances compared to other inner foams invoked in this study. Consequently, through this study, it can be confirmed that the inner foam structure can significantly improve the performance of the CFRP spoiler under high-speed driving condition (200 km/h), and also that the strengths of the CFRP spoiler can manifest differently depending on the types of inner foam core.

• Applied Chemistry for Engineering
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• v.35 no.4
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• pp.309-315
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• 2024

Silicon and carbon composite (SiC) is considered one of the most promising anode materials for the commercialization of Si-based anodes, as it could simultaneously satisfy the high theoretical capacity of Si and the high electronic conductivity of carbon. However, SiC active material undergoes repeated volumetric changes during charge/discharge processes, leading to continuous electrolyte decomposition and capacity fading, which is still considered an issue that needs to be addressed. To solve this issue, we suggest a 4,4'-Methylenebis(cyclohexyl isocyanate) (H₁₂MDI)-based waterborne polyurethane binder (HPUD), which forms a 3D network structure through thermal cross-linking reaction. The cross-linked HPUD (denoted as CHPU) was prepared using an epoxy ring-opening reaction of the cross-linker, triglycidyl isocyanurate (TGIC), via simple thermal treatment during the SiC anode drying process. The SiC anode with the CHPU binder, which exhibited superior mechanical and adhesion properties, not only demonstrated excellent rate and cycling performance but also alleviated the volume expansion of the SiC anode. This work implies that eco-friendly binders with cross-linked structures could be utilized for various Si-based anodes.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.34 no.4
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• pp.125-130
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• 2024

Preparation of ferromagnetic powders for the mixture of hematite and pure Mg powders by ball milling has been investigated. Also, consolidation of the ball-milled powders was performed in a spark plasma sintering machine at 800-1,000℃. It is found that a ferromagnetic Fe-MgO composite powders are obtained by ball milling of hematite and pure Mg powders before 1 hour. The magnetization and coercivity of ball-milled samples change at the results of the solid state reaction of hematite by pure Mg during ball milling. The saturation magnetization of ball-milled samples increases with increasing ball milling time and reaches to a maximum value of 93.4 emu/g after 5 hours of ball milling. Shrinkage change after sintering of ball-milled sample for 5 hours was significant above 300℃ and gradually increased with increasing temperature up to 800℃. X-ray diffraction result shows that the average grain size of Fe in Fe-MgO bulk sample sintered at 900℃ is 50 nm. It can be also seen that the coercivity of bulk sample sintered at 900℃ is still high value of 90 Oe, indicating that the grain growth of magnetic Fe phase during sintering process tend to be suppressed.

• Journal of Life Science
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• v.34 no.8
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• pp.540-547
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• 2024

The continuous use of polymer materials has exacerbated waste and environmental challenges, spurring a growing interest in eco-friendly polymers, especially biodegradable polymers. These polymers are gaining attention for their potential as antimicrobial agents, particularly in fields like food packaging a need further underscored by the recent COVID-19 pandemic. This study focuses on the development of an antibacterial polymer by combining poly-butylene adipate terephthalate (PBAT) with zinc pyrithione (ZnPt). The antibacterial properties were assessed through turbidity analysis, the shaking flask method, and the film adhesion method. The antibacterial activities of the composites with varying ZnPt% (w/w) contents (0, 0.1, 0.3, and 0.5) were evaluated against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). Results revealed that even at a low concentration of 0.1% (w/w), the composites demonstrated significant antibacterial activity against both Gram-positive bacteria (S. aureus) and Gram-negative bacteria (E. coli). Composites with ZnPt concentrations of 0.3% (w/w) or higher achieved over 99.999% antibacterial efficacy. Field emission scanning electron microscopy (FE-SEM) analysis of the fracture surfaces of the composites confirmed the uniform distribution of ZnPt particles, ranging from 1-4 ㎛. Further FE-SEM analysis of bacterial suspensions exposed to the composite surfaces showed clear evidence of cell wall destruction in both E. coli and S. aureus. As an antimicrobial biodegradable polymer, PBAT-ZnPt composites show great promise for applications in various sectors, including food packaging.