• Journal of the Korean Society of Radiology
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• v.85 no.2
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• pp.445-450
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• 2024

Gastric metastasis (GM) from cervical cancer is extremely rare, and only a few cases have been reported in the English literature. Gastric-type mucinous adenocarcinomas (GAS) of the uterine cervix are rare. GAS is an aggressive cancer commonly found in advanced stages; however, GM has not been reported. This study presents a rare case of GM from GAS of the uterine cervix in a 61-year-old female and describes the radiological findings of both the GM and cervical mucinous adenocarcinoma. GM appeared as a poor enhancing submucosal mass. The cervical mucinous adenocarcinoma appeared as an infiltrating mass with poor contrast enhancement. It exhibited mildly high and low signal intensities on the diffusion-weighted image and apparent diffusion coefficient map, respectively. This case is extremely rare and challenging to diagnose; however, if cervical cancer is an human papillomavirus-independent GAS type and a submucosal lesion is found in the stomach, the possibility of metastasis with a pattern similar to our case could be considered.

• Journal of the Korean Society of Radiology
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• v.85 no.1
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• pp.171-183
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• 2024

Purpose This study aimed to investigate which indirect parameters on preoperative MRI were the principal predictors of subscapularis tendon tears (STTs) requiring surgical repair. Materials and Methods Preoperative MRI scans of 86 patients were retrospectively reviewed for visual assessment of the STT, pathology of the long head of the biceps tendon (LHBT), posterior decentering (PD) of the humeral head, humeral rotation, fatty degeneration, and subscapularis muscle atrophy. To evaluate atrophy, visual grading using the anatomical line connecting the coracoid tip to the glenoid base, designated as the base-to-tip line (BTL), and thickness measurements were performed in the en-face view. Results Arthroscopically, 31 patients (36%) exhibited Lafosse type III or IV STT and underwent surgical repair. LHBT pathology (p = 0.002), PD of the humeral head (p = 0.012), fatty degeneration (p < 0.001), and BTL grade (p = 0.003) significantly correlated with STT. In the multivariate analysis, PD of the humeral head (p = 0.011, odds ratio [OR] = 5.14) and fatty degeneration (p = 0.046, OR = 2.81) were independent predictors of STT. Conclusion PD of the humeral head and fatty degeneration of the subscapularis can help to diagnose clinically significant STT. Interpretation of these findings may contribute to the planning of an optimal surgical strategy.

• Journal of Ecology and Environment
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• v.48 no.1
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• pp.32-48
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• 2024

Background: Longitudinal connectivity in river systems strongly affects biological components related to ecosystem functioning, thereby playing an important role in shaping local biodiversity and ecosystem health. Environmental DNA (eDNA)-based metabarcoding has an advantage of enabling to sensitively diagnose the presence/absence of species, becoming an efficient/effective approach for studying the community structure of ecosystems. However, little attention has been paid to eDNA-based biomonitoring for river systems, particularly for assessing the river longitudinal connectivity. In this study, by using eDNA we analyzed and compared species diversity and composition among artificial barriers to assess the longitudinal connectivity of the fish community along down-, mid- and upstream in the Hotancheon from the Geum River basin. Moreover, we investigated temporal variation in eDNA fish community structure and species diversity according to season. Results: The results of species detected between eDNA and conventional surveys revealed higher sensitivity for eDNA and 61% of species (23/38) detected in both methods. The results showed that eDNA-based fish community structure differs from down-, mid- and upstream, and species diversity decreased from down to upstream regardless of season. We found that there was generally higher species diversity at the study sites in spring (a total number of species across the sites [n] = 29) than in autumn (n = 27). Nonmetric multidimensional scaling and heatmap analyses further suggest that there was a tendency for community clusters to form in the down-, mid- and upstream, and seasonal variation in the community structure also existed for the sites. Dominant species in the Hotancheon was Rhynchocypris oxycephalus (26.07%) regardless of season, and subdominant species was Nipponocypris koreanus (16.50%) in spring and Odontobutis platycephala (15.73%) in autumn. Artificial barriers appeared to negatively affect the connectivity of some fish species of high mobility. Conclusions: This study attempts to establish a biological monitoring system by highlighting the versatility and power of eDNA metabarcoding in monitoring native fish community and further evaluating the longitudinal connectivity of river ecosystems. The results of this study suggest that eDNA can be applied to identify fish community structure and species diversity in river systems, although some shortcomings remain still need to be resolved.

• Journal of the Korean earth science society
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• v.45 no.3
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• pp.192-202
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• 2024

Ocean reanalysis data are extensively used in ocean circulation and climate research by integrating observational data with numerical models. This approach overcomes the spatial and temporal limitations of observational data and provides high-resolution gridded information that considers the physical interactions between ocean variables. In this study, I extended the previously produced 12-year (2011-2022) Northwest Pacific regional ocean reanalysis data to create a long-term reanalysis dataset (K-ORA22E) with a horizontal resolution of 1/24° spanning 30 years (1993-2022). These data were analyzed to diagnose long-term ocean climate change in the Korean marginal seas. Analysis of the K-ORA22E data revealed that the axis of the Kuroshio extension has shifted northward by approximately 6 km per year over the past 30 years, with a significant increase in sea surface temperature north of the Kuroshio axis. Among the waters surrounding the Korean Peninsula, the East Sea exhibited the most significant temperature increase. In the East Sea, the temperature increase was more pronounced in the middle layer than in the surface layer, with the East Korea Warm Current showing a rate two to three times higher than the global average. In the central Yellow Sea, where the Yellow Sea Bottom Cold Water appears, temperatures increased over the long-term, but decreased along the west and south coasts of the Korean Peninsula. These spatial differences in long-term temperature changes appear to be closely related to the heat transport pathways of warm water from the Kuroshio Current. High-resolution regional ocean reanalysis data, such as the K-ORA22E produced in this study, are essential foundational data for understanding long-term variability in the Korean marginal seas and analyzing the impacts of climate change.

• Journal of the Korean Institute of Gas
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• v.28 no.2
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• pp.93-104
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• 2024

Facility diagnosis is essential for the smooth operation and life extension of rotating equipment used in industrial sites. Compared to other diagnostic methods, vibration diagnosis can find most of the initial defects, such as unbalance, alignment failure, bearing defects and resonance, compared to other diagnostic methods. Therefore, vibration analysis is the most commonly used facility diagnosis method in industrial sites, and is usefully used as a predictive preservation (PdM) technology to manage the condition of the facility. However, since the vibration diagnosis method is performed based on experience based on the standard, it is carried out by experts. Therefore, it is intended to contribute to the reliability of the facility by establishing a system that anyone can easily judge defects by establishing a vibration diagnosis method performed based on experience as a knowledgeable code system. An algorithm was developed based on the ISO-20816 standard for vibration measurement, and the reliability was verified by comparing the results of vibration measurement at various demonstration sites such as petrochemical plant compressors, hydrogen charging stations, and industrial machinery with the results of analysis using a development system. The developed algorithm can contribute to predictive maintenance (PdM) technology that anyone can diagnose the condition of the rotating machine at industrial sites and identify defects early to replace parts at the exact time of replacement. Furthermore, it is expected that it will contribute to reducing maintenance costs and downtime due to the failure of rotating machines when applied to various industrial sites such as oil refining facilities, transportation, production facilities, and aviation facilities.

• Journal of Venture Innovation
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• v.7 no.2
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• pp.143-152
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• 2024

Recently, as a lot of software with AI functions has been developed, the number of software products with various prediction functions is increasing, and as a result, the importance of software quality has increased. In particular, as consideration for functional safety of products with AI functions increases, software quality management is being conducted at a national level. In particular, the GS Quality Certification System is a quality certification system for software products that is being implemented at the national level, and the GS Certification System is also researching quality evaluation methods for AI products. In this study, we attempt to present an evaluation model that satisfies the basic conditions of software quality based on international standards among the various quality evaluation models presented to verify software reliability. Considering the software quality characteristics of the artificial intelligence sector, we study quality evaluation models, diagnose quality, and predict failures. .In this study, we propose an international standard model for artificial intelligence based on the software reliability growth model, present an evaluation model, and present a method for quality diagnosis through the model. In this respect, this study is considered to be important in that it can predict failures in advance and find failures in advance to prevent risks by predicting the failure time that will occur in software in the future. In particular, it is believed that predicting failures will be important in various safety-related software.

• Journal of the Korean Society of Radiology
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• v.85 no.4
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• pp.769-779
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• 2024

Purpose To determine the pros and cons of an artificial intelligence (AI) model developed to diagnose acute rib fractures in chest CT images of patients with chest trauma. Materials and Methods A total of 1209 chest CT images (acute rib fracture [n = 1159], normal [n = 50]) were selected among patients with chest trauma. Among 1159 acute rib fracture CT images, 9 were randomly selected for AI model training. 150 acute rib fracture CT images and 50 normal ones were tested, and the remaining 1000 acute rib fracture CT images was internally verified. We investigated the diagnostic accuracy and errors of AI model for the presence and location of acute rib fractures. Results Sensitivity, specificity, positive and negative predictive values, and accuracy for diagnosing acute rib fractures in chest CT images were 93.3%, 94%, 97.9%, 82.5%, and 95.6% respectively. However, the accuracy of the location of acute rib fractures was low at 76% (760/1000). The cause of error in the diagnosis of acute rib fracture seemed to be a result of considering the scapula or clavicle that were in the same position (66%) or some ribs that were not recognized (34%). Conclusion The AI model for diagnosing acute rib fractures showed high accuracy in detecting the presence of acute rib fractures, but diagnosis of the exact location of rib fractures was limited.

• Journal of the Korean Society of Radiology
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• v.85 no.4
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• pp.714-726
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• 2024

Researchers have developed various algorithms utilizing artificial intelligence (AI) to automatically and objectively diagnose patterns and extent of pulmonary emphysema or interstitial lung diseases on chest CT scans. Studies show that AI-based quantification of emphysema on chest CT scans reveals a connection between an increase in the relative percentage of emphysema and a decline in lung function. Notably, quantifying centrilobular emphysema has proven helpful in predicting clinical symptoms or mortality rates of chronic obstructive pulmonary disease. In the context of interstitial lung diseases, AI can classify the usual interstitial pneumonia pattern on CT scans into categories like normal, ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation. This classification accuracy is comparable to chest radiologists (70%-80%). However, the results generated by AI are influenced by factors such as scan parameters, reconstruction algorithms, radiation doses, and the training data used to develop the AI. These limitations currently restrict the widespread adoption of AI for quantifying pulmonary emphysema and interstitial lung diseases in daily clinical practice. This paper will showcase the authors' experience using AI for diagnosing and quantifying emphysema and interstitial lung diseases through case studies. We will primarily focus on the advantages and limitations of AI for these two diseases.

• Research in Plant Disease
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• v.30 no.3
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• pp.294-299
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• 2024

Polymerase chain reaction (PCR) methods, including conventional PCR (cPCR) and quantitative real-time PCR (qRT-PCR), with both plasmid- and chromosome-targeting primers, are currently the most reliable methods for detecting Erwinia amylovora due to their high sensitivity and specificity. Despite qRT-PCR's quantitative advantage, cPCR remains an attractive method to detect this bacterium in initial screenings of suspected host plants, as it is cost-effective and does not require skilled personnel in well-equipped laboratories. This study aimed to significantly improve cPCR robustness via application of bovine serum albumin (BSA) as a PCR facilitator, with a modified EaF/R primer pair, as previously reported. Experiments have shown that simple supplementation with BSA (10 mg/ml) enhances cPCR reactions using templates such as genomic DNA, bacterial cells, and infected symptomless host organs, including immature apple fruits and seedlings, with EaF/R primers. The cPCR method described in this study is simple, specific, and reliable, and can be applied in routine assays to diagnose fire blight.

• Clinical and Experimental Pediatrics
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• v.52 no.4
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• pp.458-463
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• 2009

Purpose : Schizencephaly is a uncommon congenital brain anomaly characterized by congenital clefts spanning the cerebral hemispheres from pial surface to lateral ventricles and lined by gray matter. In this study, we investigated the clinical manifestation and radiologic findings of pediatric schizencephaly. Methods : The data of 13 patients who were diagnosed with schizencephaly in Severance Childrens Hospital and Yongdong Severance Hospital from January 2005 to December 2007 were analyzed retrospectively. Results : The mean age at diagnosis was $9.08{\pm}2.67$ months old and ranged from 1 to 30 months. The ratio of male to female patients was 3.33:1. Five (38.5%) patients had bilateral clefts, while 8 (61.5%) had unilateral clefts. Five (38.5%) patients had closed lip clefts, and 4 (30.8%) had opened lip clefts. Four (30.8%) patients had multiple clefts. Associated anomalies showed in all cases. The clinical features consisted of mild unilateral weakness in 7 (53.8%) cases and a hemiparesis was present in 3 (23.1%) patients. A tetraparesis was in 3 (23.1%) patients. There was no difference in motor deficit between unilateral and bilateral clefts. Delayed development was observed in all cases. Epilepsy was present in 7 (53.8%) patients, 5 patients with unilateral clefts and 2 patients with bilateral clefts. Three (42.8%) patients showed intractable seizures. Conclusion : Schizencephaly showed variable clinical manifestations and radiologic findings in association with the types and locations of the clefts. It is necessary to diagnose schizencephaly early and to detect the development of epilepsy. Intensive and large studies of the correlation of clinical outcomes and radiologic findings should be continued for more effective treatment.