Purpose: This study aimed to differentiate well-differentiated liposarcoma (WDLPS) from lipoma using the magnetic resonance imaging (MRI) findings and improve the preoperative diagnostic accuracy between the two tumors. Although lipoma is a benign tumor that does not necessarily require surgical intervention, WDLPS exhibits local aggressiveness and typically necessitates surgical excision, making its differentiation clinically significant. Materials and Methods: Among 363 patients diagnosed with lipoma or WDLPS at the authors’ institution between January 2013 and April 2022, 45 patients with lipoma and 15 with WDLPS were selected using propensity score matching based on age and sex. The following six MRI features were analyzed: tumor size, shape, septal thickness, tumor depth, fat content ratio, and the presence of nodular non-fatty tissue components. The sensitivity and specificity of each feature were evaluated. Results: Among the MRI features, the fat content ratio (specificity 95%) and the presence of nodular non-fatty tissue components (specificity 98%) were useful for excluding WDLPS, but their sensitivities were relatively low (46% and 27%). The sensitivities of other features, such as tumor size, shape, septal thickness, and depth, ranged from 47% to 67%, suggesting that MRI alone has limitations in reliably distinguishing the two tumors. In addition, fat content ratios below 75% and the presence of nodular non-fatty tissue components were significantly more common in WDLPS than in lipoma. Conclusion The MRI findings can serve as a useful tool for excluding WDLPS when differentiating it from lipoma. Nevertheless, MRI alone has limitations in achieving a definitive diagnosis because of the low sensitivity of individual features. Therefore, additional approaches such as radiomics analysis, artificial intelligence algorithms, and multicenter studies, are needed to improve the diagnostic accuracy and establish personalized treatment strategies.

Objective: To evaluate the clinical efficacy of ultrafast dynamic contrast-enhanced (DCE)-MRI using a compressed sensing (CS) technique for differentiating benign and malignant soft-tissue tumors (STTs) and to evaluate the factors related to the grading of malignant STTs. Materials and Methods: A total of 165 patients (96 male; mean age, 61 years), comprising 111 with malignant STTs and 54 with benign STTs according to the 2020 WHO classification, underwent DCE-MRI with CS between June 2018 and June 2023. The clinical, qualitative, and quantitative parameters associated with conventional MRI were also obtained. During post-processing of the early arterial phase of DCE-MRI, the time-to-enhance (TTE), time-to-peak (TTP), initial area under the curve at 60 s (iAUC60), and maximum slope were calculated. Furthermore, the delayed arterial phase parameters of DCEMRI, including Ktrans , Kep, Ve, and iAUC values and time-concentration curve (TCC) types, were determined. Clinical and MRI parameters were statistically analyzed to differentiate between benign and malignant tumors and their correlation with tumor grading. Results: According to logistic regression analysis, the TTE value (P < 0.001) of the early arterial phase and Ve (P = 0.039) and iAUC (P = 0.006) values of the delayed arterial phase, as well as age, location, peritumoral edema, and contrast heterogeneity on conventional MRI, were significant (P = 0.001–0.015) in differentiating benign and malignant tumors. Among all the quantitative parameters, the TTE value had the highest accuracy, with an area under the receiver operating characteristic curve of 0.902. The grading of malignant tumors was significantly correlated with peritumoral edema; CE heterogeneity; visual diffusion restriction; minimum and mean ADC; TTP, Kep, and Ve values; and the TCC graph (all P < 0.05). Conclusion Among the quantitative parameters obtained using ultrafast DCE-MRI, early arterial phase TTE was the most accurate for distinguishing between benign and malignant tumors.

Objective: To evaluate the clinical efficacy of ultrafast dynamic contrast-enhanced (DCE)-MRI using a compressed sensing (CS) technique for differentiating benign and malignant soft-tissue tumors (STTs) and to evaluate the factors related to the grading of malignant STTs. Materials and Methods: A total of 165 patients (96 male; mean age, 61 years), comprising 111 with malignant STTs and 54 with benign STTs according to the 2020 WHO classification, underwent DCE-MRI with CS between June 2018 and June 2023. The clinical, qualitative, and quantitative parameters associated with conventional MRI were also obtained. During post-processing of the early arterial phase of DCE-MRI, the time-to-enhance (TTE), time-to-peak (TTP), initial area under the curve at 60 s (iAUC60), and maximum slope were calculated. Furthermore, the delayed arterial phase parameters of DCEMRI, including Ktrans , Kep, Ve, and iAUC values and time-concentration curve (TCC) types, were determined. Clinical and MRI parameters were statistically analyzed to differentiate between benign and malignant tumors and their correlation with tumor grading. Results: According to logistic regression analysis, the TTE value (P < 0.001) of the early arterial phase and Ve (P = 0.039) and iAUC (P = 0.006) values of the delayed arterial phase, as well as age, location, peritumoral edema, and contrast heterogeneity on conventional MRI, were significant (P = 0.001–0.015) in differentiating benign and malignant tumors. Among all the quantitative parameters, the TTE value had the highest accuracy, with an area under the receiver operating characteristic curve of 0.902. The grading of malignant tumors was significantly correlated with peritumoral edema; CE heterogeneity; visual diffusion restriction; minimum and mean ADC; TTP, Kep, and Ve values; and the TCC graph (all P < 0.05). Conclusion Among the quantitative parameters obtained using ultrafast DCE-MRI, early arterial phase TTE was the most accurate for distinguishing between benign and malignant tumors.

Objective: To evaluate the clinical efficacy of ultrafast dynamic contrast-enhanced (DCE)-MRI using a compressed sensing (CS) technique for differentiating benign and malignant soft-tissue tumors (STTs) and to evaluate the factors related to the grading of malignant STTs. Materials and Methods: A total of 165 patients (96 male; mean age, 61 years), comprising 111 with malignant STTs and 54 with benign STTs according to the 2020 WHO classification, underwent DCE-MRI with CS between June 2018 and June 2023. The clinical, qualitative, and quantitative parameters associated with conventional MRI were also obtained. During post-processing of the early arterial phase of DCE-MRI, the time-to-enhance (TTE), time-to-peak (TTP), initial area under the curve at 60 s (iAUC60), and maximum slope were calculated. Furthermore, the delayed arterial phase parameters of DCEMRI, including Ktrans , Kep, Ve, and iAUC values and time-concentration curve (TCC) types, were determined. Clinical and MRI parameters were statistically analyzed to differentiate between benign and malignant tumors and their correlation with tumor grading. Results: According to logistic regression analysis, the TTE value (P < 0.001) of the early arterial phase and Ve (P = 0.039) and iAUC (P = 0.006) values of the delayed arterial phase, as well as age, location, peritumoral edema, and contrast heterogeneity on conventional MRI, were significant (P = 0.001–0.015) in differentiating benign and malignant tumors. Among all the quantitative parameters, the TTE value had the highest accuracy, with an area under the receiver operating characteristic curve of 0.902. The grading of malignant tumors was significantly correlated with peritumoral edema; CE heterogeneity; visual diffusion restriction; minimum and mean ADC; TTP, Kep, and Ve values; and the TCC graph (all P < 0.05). Conclusion Among the quantitative parameters obtained using ultrafast DCE-MRI, early arterial phase TTE was the most accurate for distinguishing between benign and malignant tumors.

Objective: To evaluate the clinical efficacy of ultrafast dynamic contrast-enhanced (DCE)-MRI using a compressed sensing (CS) technique for differentiating benign and malignant soft-tissue tumors (STTs) and to evaluate the factors related to the grading of malignant STTs. Materials and Methods: A total of 165 patients (96 male; mean age, 61 years), comprising 111 with malignant STTs and 54 with benign STTs according to the 2020 WHO classification, underwent DCE-MRI with CS between June 2018 and June 2023. The clinical, qualitative, and quantitative parameters associated with conventional MRI were also obtained. During post-processing of the early arterial phase of DCE-MRI, the time-to-enhance (TTE), time-to-peak (TTP), initial area under the curve at 60 s (iAUC60), and maximum slope were calculated. Furthermore, the delayed arterial phase parameters of DCEMRI, including Ktrans , Kep, Ve, and iAUC values and time-concentration curve (TCC) types, were determined. Clinical and MRI parameters were statistically analyzed to differentiate between benign and malignant tumors and their correlation with tumor grading. Results: According to logistic regression analysis, the TTE value (P < 0.001) of the early arterial phase and Ve (P = 0.039) and iAUC (P = 0.006) values of the delayed arterial phase, as well as age, location, peritumoral edema, and contrast heterogeneity on conventional MRI, were significant (P = 0.001–0.015) in differentiating benign and malignant tumors. Among all the quantitative parameters, the TTE value had the highest accuracy, with an area under the receiver operating characteristic curve of 0.902. The grading of malignant tumors was significantly correlated with peritumoral edema; CE heterogeneity; visual diffusion restriction; minimum and mean ADC; TTP, Kep, and Ve values; and the TCC graph (all P < 0.05). Conclusion Among the quantitative parameters obtained using ultrafast DCE-MRI, early arterial phase TTE was the most accurate for distinguishing between benign and malignant tumors.

Objective: To evaluate the clinical efficacy of ultrafast dynamic contrast-enhanced (DCE)-MRI using a compressed sensing (CS) technique for differentiating benign and malignant soft-tissue tumors (STTs) and to evaluate the factors related to the grading of malignant STTs. Materials and Methods: A total of 165 patients (96 male; mean age, 61 years), comprising 111 with malignant STTs and 54 with benign STTs according to the 2020 WHO classification, underwent DCE-MRI with CS between June 2018 and June 2023. The clinical, qualitative, and quantitative parameters associated with conventional MRI were also obtained. During post-processing of the early arterial phase of DCE-MRI, the time-to-enhance (TTE), time-to-peak (TTP), initial area under the curve at 60 s (iAUC60), and maximum slope were calculated. Furthermore, the delayed arterial phase parameters of DCEMRI, including Ktrans , Kep, Ve, and iAUC values and time-concentration curve (TCC) types, were determined. Clinical and MRI parameters were statistically analyzed to differentiate between benign and malignant tumors and their correlation with tumor grading. Results: According to logistic regression analysis, the TTE value (P < 0.001) of the early arterial phase and Ve (P = 0.039) and iAUC (P = 0.006) values of the delayed arterial phase, as well as age, location, peritumoral edema, and contrast heterogeneity on conventional MRI, were significant (P = 0.001–0.015) in differentiating benign and malignant tumors. Among all the quantitative parameters, the TTE value had the highest accuracy, with an area under the receiver operating characteristic curve of 0.902. The grading of malignant tumors was significantly correlated with peritumoral edema; CE heterogeneity; visual diffusion restriction; minimum and mean ADC; TTP, Kep, and Ve values; and the TCC graph (all P < 0.05). Conclusion Among the quantitative parameters obtained using ultrafast DCE-MRI, early arterial phase TTE was the most accurate for distinguishing between benign and malignant tumors.

Background: It is well known that a large number of patients with diabetes also have dyslipidemia, which significantly increases the risk of cardiovascular disease (CVD). This study aimed to evaluate the efficacy and safety of combination drugs consisting of metformin and atorvastatin, widely used as therapeutic agents for diabetes and dyslipidemia. Methods: This randomized, double-blind, placebo-controlled, parallel-group and phase III multicenter study included adults with glycosylated hemoglobin (HbA1c) levels >7.0% and <10.0%, low-density lipoprotein cholesterol (LDL-C) >100 and <250 mg/dL. One hundred eighty-five eligible subjects were randomized to the combination group (metformin+atorvastatin), metformin group (metformin+atorvastatin placebo), and atorvastatin group (atorvastatin+metformin placebo). The primary efficacy endpoints were the percent changes in HbA1c and LDL-C levels from baseline at the end of the treatment. Results: After 16 weeks of treatment compared to baseline, HbA1c showed a significant difference of 0.94% compared to the atorvastatin group in the combination group (0.35% vs. −0.58%, respectively; P<0.0001), whereas the proportion of patients with increased HbA1c was also 62% and 15%, respectively, showing a significant difference (P<0.001). The combination group also showed a significant decrease in LDL-C levels compared to the metformin group (−55.20% vs. −7.69%, P<0.001) without previously unknown adverse drug events. Conclusion The addition of atorvastatin to metformin improved HbA1c and LDL-C levels to a significant extent compared to metformin or atorvastatin alone in diabetes and dyslipidemia patients. This study also suggested metformin’s preventive effect on the glucose-elevating potential of atorvastatin in patients with type 2 diabetes mellitus and dyslipidemia, insufficiently controlled with exercise and diet. Metformin and atorvastatin combination might be an effective treatment in reducing the CVD risk in patients with both diabetes and dyslipidemia because of its lowering effect on LDL-C and glucose.

Purpose: Tumors of the foot and ankle account for approximately 3%~5% of all musculoskeletal tumors, and accurate diagnosis is often delayed due to their rare prevalence. Therefore, the authors aimed to analyze the incidence, treatment methods, and prognostic factors of foot and ankle tumors treated at the authors’ hospital. Materials and Methods: A retrospective single-center study examined 342 patients treated for foot and ankle tumors at the authors’ hospital from January 2011 to February 2022. Data were collected from the electronic medical records (EMR) and picture archiving and communication systems (PACS). The information analyzed included gender, age, follow-up period, diagnosis, tumor occurrence and recurrence, treatment, and clinical outcomes. Results: Most cases (93.3%) were benign, but 6.7% were malignant. The main treatment for malignant tumors was surgical resection (91.3%). Approximately 53.1% of benign tumors and 91.3% of malignant tumors were treated with surgery, and two of the malignant tumors that did not undergo surgery had metastatic cancer. After surgery, 8.2% of benign lesions and 19.0% of malignant lesions recurred, and 9.5% of the patients with malignant tumors died after surgery. Conclusion Most foot and ankle tumors are benign tumors, and the prognosis is not poor if treated properly, but most malignant tumors often require amputation. In some cases, however, amputation can be avoided with a combination of chemotherapy and radiation therapy.

OBJECTIVES: We estimated the population prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including unreported infections, through a Korea Seroprevalence Study of Monitoring of SARS-CoV-2 Antibody Retention and Transmission (K-SEROSMART) in 258 communities throughout Korea. METHODS: In August 2022, a survey was conducted among 10,000 household members aged 5 years and older, in households selected through two stage probability random sampling. During face-to-face household interviews, participants self-reported their health status, COVID-19 diagnosis and vaccination history, and general characteristics. Subsequently, participants visited a community health center or medical clinic for blood sampling. Blood samples were analyzed for the presence of antibodies to spike proteins (anti-S) and antibodies to nucleocapsid proteins (anti-N) SARS-CoV-2 proteins using an electrochemiluminescence immunoassay. To estimate the population prevalence, the PROC SURVEYMEANS statistical procedure was employed, with weighting to reflect demographic data from July 2022. RESULTS: In total, 9,945 individuals from 5,041 households were surveyed across 258 communities, representing all basic local governments in Korea. The overall population-adjusted prevalence rates of anti-S and anti-N were 97.6% and 57.1%, respectively. Since the Korea Disease Control and Prevention Agency has reported a cumulative incidence of confirmed cases of 37.8% through July 31, 2022, the proportion of unreported infections among all COVID-19 infection was suggested to be 33.9%. CONCLUSIONS The K-SEROSMART represents the first nationwide, community-based seroepidemiologic survey of COVID-19, confirming that most individuals possess antibodies to SARS-CoV-2 and that a significant number of unreported cases existed. Furthermore, this study lays the foundation for a surveillance system to continuously monitor transmission at the community level and the response to COVID-19.

Background: Fibroblasts produce collagen molecules that support the structure of the skin.The decrease and hypersynthesis of collagen causes skin problems such as skin atrophy, wrinkles and scars. Objective: The purpose of this study is to investigate the mechanism of mitoxantrone on collagen synthesis in fibroblasts. Methods: Cultured fibroblasts were treated with mitoxantrone, and then collagen synthesis was confirmed by reverse transcription-polymerase chain reaction and Western blot. Results: Mitoxantrone inhibited the expression of type I collagen in fibroblasts at both the mRNA and protein levels. In the collagen gel contraction assay, mitoxantrone significantly inhibited gel contraction compared to the control group. Mitoxantrone inhibited transforming growth factor (TGF)-β-induced phosphorylation of SMAD3. Finally, mitoxantrone inhibited the expression of LARP6, an RNA-binding protein that regulates collagen mRNA stability. Conclusion These results suggest that mitoxantrone reduces collagen synthesis by inhibiting TGF-β/SMAD signaling and LARP6 expression in fibroblasts, which can be developed as a therapeutic agent for diseases caused by collagen hypersynthesis.