In forensic medicine, age estimation commonly involves assessing age-related changes in teeth and skeletal structures. Vertebral morphological alterations, such as osteophyte formation, serve as age indicators. Recent studies using deep-learning techniques, such as neural networks, for age estimation from radiographic images have been conducted, reporting significantly higher accuracy than previous studies. This study aimed to estimate age using neural network-based deep-learning techniques applied to computed tomography (CT) cross-sectional images of the spine and evaluate its feasibility. Postmortem CT scans of 214 cadavers with varying decomposition levels were used. Coronal and sagittal cross-sectional images penetrating the center of each vertebral body were extracted for the 11th and 12th thoracic vertebrae and the first to fifth lumbar vertebrae. Using these images, along with the chronological ages of deceased individuals, an age estimation model was developed through regression analysis in PyTorch, employing a convolutional neural networks architecture with five-fold cross-validation. The model achieved a mean absolute error of 5.385 years, root mean squared error of 7.029 years, and coefficient of determination of 0.793. Although the sample size was relatively small, the results suggested the potential applicability of vertebral imagingbased age estimation in the Korean population. Further research using a larger dataset may improve the accuracy and reliability of the model.

Myofibromas are rare mesenchymal neoplasms that primarily affect infants and young children, most commonly arising in the skin, subcutaneous tissue, muscle, or bone. These tumors present with a broad clinical spectrum, ranging from self-limiting lesions to disseminated and fatal cases. In adults, the solitary form is encountered more frequently than the multicentric type. Although myofibromas may occur in the oral region of the head and neck, isolated cases involving the nasal septum are exceedingly rare. Here, we describe a case of solitary adult-onset myofibroma of the nasal septum that was successfully excised through transnasal endoscopic surgery.

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.

Background: Complete revascularization has demonstrated better outcomes in patients with acute myocardial infarction (AMI) and multivessel disease. However, in the case of left main (LM) culprit lesion AMI with multivessel disease, there is limited evidence to suggest that complete revascularization is better. Methods: We reviewed 16,831 patients in the Korea Acute Myocardial Infarction Registry who were treated from July 2016 to June 2020, and 399 patients were enrolled with LM culprit lesion AMI treated with percutaneous coronary intervention. We categorized the patients as those treated with complete revascularization (n=295) or incomplete revascularization (n=104). The study endpoint was major adverse cardiac and cerebrovascular events (MACCE), a composite of all-cause death, myocardial infarction, ischemia-driven revascularization, stent thrombosis, and stroke. We performed propensity score matching (PSM) and analyzed the incidence of MACCE at 1 year. Results: After PSM, the two groups were well balanced. There was no significant difference between the two groups in MACCE at 1 year (12.1% vs. 15.2%; hazard ratio, 1.28; 95% confidence interval, 0.60–2.74; p=0.524) after PSM. The components of MACCE and major bleeding were also not significantly different. Conclusion There was no significant difference in clinical outcomes between the groups treated with complete or incomplete revascularization for LM culprit lesion AMI with multivessel disease.

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: Complete revascularization has demonstrated better outcomes in patients with acute myocardial infarction (AMI) and multivessel disease. However, in the case of left main (LM) culprit lesion AMI with multivessel disease, there is limited evidence to suggest that complete revascularization is better. Methods: We reviewed 16,831 patients in the Korea Acute Myocardial Infarction Registry who were treated from July 2016 to June 2020, and 399 patients were enrolled with LM culprit lesion AMI treated with percutaneous coronary intervention. We categorized the patients as those treated with complete revascularization (n=295) or incomplete revascularization (n=104). The study endpoint was major adverse cardiac and cerebrovascular events (MACCE), a composite of all-cause death, myocardial infarction, ischemia-driven revascularization, stent thrombosis, and stroke. We performed propensity score matching (PSM) and analyzed the incidence of MACCE at 1 year. Results: After PSM, the two groups were well balanced. There was no significant difference between the two groups in MACCE at 1 year (12.1% vs. 15.2%; hazard ratio, 1.28; 95% confidence interval, 0.60–2.74; p=0.524) after PSM. The components of MACCE and major bleeding were also not significantly different. Conclusion There was no significant difference in clinical outcomes between the groups treated with complete or incomplete revascularization for LM culprit lesion AMI with multivessel disease.

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.