Purpose: Although the prevalence of a discoid lateral meniscus is relatively rare, estimated at approximately 0.4% to 5.0% in the Western world, studies have shown that the incidence is significantly higher in Asia, particularly in South Korea and Japan, ranging from 10.5% to 16.6%. On the other hand, previous studies that reported the incidence of discoid lateral meniscus mainly relied on patients who underwent arthroscopic or open surgery. This study examined the incidence of discoid lateral meniscus using a magnetic resonance imaging-based diagnostic approach. Materials and Methods: This study conducted a retrospective review of the prevalence of discoid lateral meniscus in 10,810 male patients with knee pain who underwent magnetic resonance imaging at the author’s single institution between January 2013 and January 2023. The mean age of the patients was 42.55±15.93 years old (range: 12 to 82). The patient demographics, including age, were analyzed.The characteristics of the discoid lateral meniscus were also analyzed, including the subtype and presence of a combined lateral meniscus tear. Results: This study identified 1,025 patients (9.5%) with a discoid lateral meniscus, including 129 with the complete subtype, 893 with the incomplete subtype, and 3 with the Wrisberg-type subtype. Although there was no significant difference in prevalence between sexes, the highest diagnosis rate of discoid lateral meniscus was observed in the 41–60-year-old (10.1%) age group, which was statistically significant (p=0.025). Among the 164 patients with a concurrent lateral meniscus tear, the horizontal type (80 patients, 48.8%) was the most frequently observed. Conclusion While the incidence in the present study was slightly lower than that reported in previous arthroscopic-based studies, the findings still suggest a relatively high prevalence of discoid lateral meniscus in Korea compared to other countries. In contrast to earlier research that suggested a decline in incidence with age, this study found that the incidence of discoid lateral meniscus was highest among individuals aged 41–60 years.

Purpose: Myosteatosis, defined as fat infiltration in muscle tissue, has been linked to poor outcomes in various cancers. However, the prognostic impact of myosteatosis on renal cell carcinoma (RCC) remains poorly understood. This study evaluated the predictive value of myosteatosis based on an artificial intelligence (AI)-driven computed tomography (CT) analysis in patients with localized RCC who underwent partial nephrectomy. Materials and Methods: This retrospective study included 170 patients with localized RCC who underwent partial nephrectomy at a single institution between 2011 and 2017. Myosteatosis was assessed on CT scans using an AI-based tool. The patients were categorized into 2 groups according to the presence or absence of myosteatosis. The clinical outcomes, including disease-free survival (DFS), were compared to determine the prognostic significance of myosteatosis. Results: Of 170 patients, 36 (21.2%) were diagnosed with myosteatosis. These patients were older and had a higher body mass index. The myosteatosis group had a higher proportion of females than the no myosteatosis group. Lymphovascular invasion and tumor necrosis were prevalent pathological features in patients with myosteatosis. Kaplan-Meier analysis demonstrated that myosteatosis was associated with significantly shorter DFS (p<0.05). Multivariate analysis confirmed that myosteatosis independently predicted adverse outcomes in patients with localized RCC. Conclusion AI-based CT analysis of myosteatosis is a reliable method for improving the risk stratification of patients with localized RCC. Patients with myosteatosis demonstrate poor pathological features and shorter DFS. These findings highlight the potential of AI-driven body composition analysis to refine prognostic models and personalized treatment strategies.

Purpose: Although the prevalence of a discoid lateral meniscus is relatively rare, estimated at approximately 0.4% to 5.0% in the Western world, studies have shown that the incidence is significantly higher in Asia, particularly in South Korea and Japan, ranging from 10.5% to 16.6%. On the other hand, previous studies that reported the incidence of discoid lateral meniscus mainly relied on patients who underwent arthroscopic or open surgery. This study examined the incidence of discoid lateral meniscus using a magnetic resonance imaging-based diagnostic approach. Materials and Methods: This study conducted a retrospective review of the prevalence of discoid lateral meniscus in 10,810 male patients with knee pain who underwent magnetic resonance imaging at the author’s single institution between January 2013 and January 2023. The mean age of the patients was 42.55±15.93 years old (range: 12 to 82). The patient demographics, including age, were analyzed.The characteristics of the discoid lateral meniscus were also analyzed, including the subtype and presence of a combined lateral meniscus tear. Results: This study identified 1,025 patients (9.5%) with a discoid lateral meniscus, including 129 with the complete subtype, 893 with the incomplete subtype, and 3 with the Wrisberg-type subtype. Although there was no significant difference in prevalence between sexes, the highest diagnosis rate of discoid lateral meniscus was observed in the 41–60-year-old (10.1%) age group, which was statistically significant (p=0.025). Among the 164 patients with a concurrent lateral meniscus tear, the horizontal type (80 patients, 48.8%) was the most frequently observed. Conclusion While the incidence in the present study was slightly lower than that reported in previous arthroscopic-based studies, the findings still suggest a relatively high prevalence of discoid lateral meniscus in Korea compared to other countries. In contrast to earlier research that suggested a decline in incidence with age, this study found that the incidence of discoid lateral meniscus was highest among individuals aged 41–60 years.

Purpose: Myosteatosis, defined as fat infiltration in muscle tissue, has been linked to poor outcomes in various cancers. However, the prognostic impact of myosteatosis on renal cell carcinoma (RCC) remains poorly understood. This study evaluated the predictive value of myosteatosis based on an artificial intelligence (AI)-driven computed tomography (CT) analysis in patients with localized RCC who underwent partial nephrectomy. Materials and Methods: This retrospective study included 170 patients with localized RCC who underwent partial nephrectomy at a single institution between 2011 and 2017. Myosteatosis was assessed on CT scans using an AI-based tool. The patients were categorized into 2 groups according to the presence or absence of myosteatosis. The clinical outcomes, including disease-free survival (DFS), were compared to determine the prognostic significance of myosteatosis. Results: Of 170 patients, 36 (21.2%) were diagnosed with myosteatosis. These patients were older and had a higher body mass index. The myosteatosis group had a higher proportion of females than the no myosteatosis group. Lymphovascular invasion and tumor necrosis were prevalent pathological features in patients with myosteatosis. Kaplan-Meier analysis demonstrated that myosteatosis was associated with significantly shorter DFS (p<0.05). Multivariate analysis confirmed that myosteatosis independently predicted adverse outcomes in patients with localized RCC. Conclusion AI-based CT analysis of myosteatosis is a reliable method for improving the risk stratification of patients with localized RCC. Patients with myosteatosis demonstrate poor pathological features and shorter DFS. These findings highlight the potential of AI-driven body composition analysis to refine prognostic models and personalized treatment strategies.

Purpose: Although the prevalence of a discoid lateral meniscus is relatively rare, estimated at approximately 0.4% to 5.0% in the Western world, studies have shown that the incidence is significantly higher in Asia, particularly in South Korea and Japan, ranging from 10.5% to 16.6%. On the other hand, previous studies that reported the incidence of discoid lateral meniscus mainly relied on patients who underwent arthroscopic or open surgery. This study examined the incidence of discoid lateral meniscus using a magnetic resonance imaging-based diagnostic approach. Materials and Methods: This study conducted a retrospective review of the prevalence of discoid lateral meniscus in 10,810 male patients with knee pain who underwent magnetic resonance imaging at the author’s single institution between January 2013 and January 2023. The mean age of the patients was 42.55±15.93 years old (range: 12 to 82). The patient demographics, including age, were analyzed.The characteristics of the discoid lateral meniscus were also analyzed, including the subtype and presence of a combined lateral meniscus tear. Results: This study identified 1,025 patients (9.5%) with a discoid lateral meniscus, including 129 with the complete subtype, 893 with the incomplete subtype, and 3 with the Wrisberg-type subtype. Although there was no significant difference in prevalence between sexes, the highest diagnosis rate of discoid lateral meniscus was observed in the 41–60-year-old (10.1%) age group, which was statistically significant (p=0.025). Among the 164 patients with a concurrent lateral meniscus tear, the horizontal type (80 patients, 48.8%) was the most frequently observed. Conclusion While the incidence in the present study was slightly lower than that reported in previous arthroscopic-based studies, the findings still suggest a relatively high prevalence of discoid lateral meniscus in Korea compared to other countries. In contrast to earlier research that suggested a decline in incidence with age, this study found that the incidence of discoid lateral meniscus was highest among individuals aged 41–60 years.

Purpose: Myosteatosis, defined as fat infiltration in muscle tissue, has been linked to poor outcomes in various cancers. However, the prognostic impact of myosteatosis on renal cell carcinoma (RCC) remains poorly understood. This study evaluated the predictive value of myosteatosis based on an artificial intelligence (AI)-driven computed tomography (CT) analysis in patients with localized RCC who underwent partial nephrectomy. Materials and Methods: This retrospective study included 170 patients with localized RCC who underwent partial nephrectomy at a single institution between 2011 and 2017. Myosteatosis was assessed on CT scans using an AI-based tool. The patients were categorized into 2 groups according to the presence or absence of myosteatosis. The clinical outcomes, including disease-free survival (DFS), were compared to determine the prognostic significance of myosteatosis. Results: Of 170 patients, 36 (21.2%) were diagnosed with myosteatosis. These patients were older and had a higher body mass index. The myosteatosis group had a higher proportion of females than the no myosteatosis group. Lymphovascular invasion and tumor necrosis were prevalent pathological features in patients with myosteatosis. Kaplan-Meier analysis demonstrated that myosteatosis was associated with significantly shorter DFS (p<0.05). Multivariate analysis confirmed that myosteatosis independently predicted adverse outcomes in patients with localized RCC. Conclusion AI-based CT analysis of myosteatosis is a reliable method for improving the risk stratification of patients with localized RCC. Patients with myosteatosis demonstrate poor pathological features and shorter DFS. These findings highlight the potential of AI-driven body composition analysis to refine prognostic models and personalized treatment strategies.

Background: This retrospective observational matched cohort study assessed the differences in critical infections caused by severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) during the omicron-predominant period of the coronavirus disease 2019 (COVID-19) pandemic. We evaluated the vaccine effectiveness of bivalent mRNA vaccine compared to unvaccinated individuals. Methods: We collected COVID-19 case data from the Korean COVID-19 vaccine effectiveness cohort. We calculated the probability of critical COVID-19 cases by comparing the vaccinated and unvaccinated groups. Results: The risk of being critically infected due to SAR-CoV-2 infection was 5.96 times higher (95% confidence interval, 5.63–6.38) among older individuals who were unvaccinated compared to those who received the bivalent COVID-19 vaccine. Conclusion Our findings indicate that the bivalent vaccine reduces the disease burden of the SARS-CoV-2 omicron variant, particularly among the older population. Further studies are warranted to determine the effectiveness of booster doses of vaccines for SARS-CoV-2 infection.

Background: Programmed death ligand 1 (PD-L1) expression cannot currently be predicted through radiological findings. This study aimed to develop a prediction model capable of differentiating between positive and negative PD-L1 expression through a radiomics-based investigation of computed tomography (CT) images in patients with urothelial carcinoma. Methods: Sixty-four patients with urothelial carcinoma who underwent immunohistochemical testing for PD-L1 were retrospectively reviewed. The number of patients in the positive and negative PD-L1 groups (PD-L1 expression >5%) was 14 and 50, respectively. CT images obtained 90 seconds after contrast medium administration were selected for radiomic extraction. For all tumors, 1,691 radiomic features were extracted from CT using a manually segmented three-dimensional volume of interest. Univariate and multivariate logistic regression analyses were performed to identify radiomic features that were significant predictors of PD-L1 expression. For the radiomics-based model, a receiver operating characteristic (ROC) analysis was performed. Results: Among 64 patients, 14 were included in the PD-L1 positive group. Logistic regression analysis found that the following radiomic features significantly predicted PD-L1 expression: wavelet-low-pass, low-pass, and high-pass filters (LLH)_gray-level size-zone matrix (GLSZM)_SmallAreaEmphasis, wavelet-LLH_firstorder_Energy, log-sigma-0-5-mm-3D_GLSZM_SmallAreaHighGrayLevelEmphasis, original_shape_Maximum2DDiameterColumn, wavelet-low-pass, low-pass, and low-pass filters (LLL)_gray-level run-length matrix (GLRLM)_ShortRunEmphasis, and exponential_firstorder_Kurtosis. The radiomics signature was –4.0934+21.6224 (wavelet-LLH_GLSZM_SmallAreaEmphasis)+0.0044 (wavelet-LLH_firstorder_Energy)–4.7389 (log-sigma-0-5-mm-3D_GLSZM_SmallAreaHighGrayLevelEmphasis)+0.0573 (original_shape_Maximum2DDiameterColumn)–29.5892 (wavelet-LLL_GLRLM_ShortRunEmphasis)–0.4324 (exponential_firstorder_Kurtosis). The area under the ROC curve model representing the radiomics signature for differentiating cases that were deemed PD-L1 positive based on immunohistochemistry was 0.96. Conclusions This preliminary radiomics model derived from contrast-enhanced CT predicted PD-L1 positivity in patients with urothelial cancer.