This case study highlights craniofacial identification technology (CFIT) as a complementary and translational tool for reconstruction of cranial gunshot wounds (GSWs) and presenting evidence beyond forensic identification. In forensic cases involving GSWs, a visual demonstration of the bullet trajectory can improve communication between forensic pathologists and non-medical judicial agencies and the court. Postmortem computed tomography (PMCT) images and autopsy images are essential medical evidence, providing a robust visual display of the GSW and its bullet trajectory. PMCT images are useful for identifying the precise projectile localization and characteristics of bone fractures. However, PMCT images may not adequately present soft tissue injuries well, and autopsy images can be unpleasant to non-medical professionals, making it difficult for them to understand such specialized scientific evidence. CFIT is a well-established scientific tool with which forensic experts in craniofacial identification can create more advanced reconstructed three-dimensional (3D) images based on both postmortem findings and PMCT data. Intracranial bullet trajectory can be shown simply and directly in reconstructed 3D cranial images. CFIT can serve as an adjunctive tool to overcome the limitations of both PMCT images and autopsy images, thereby facilitating better understanding of such specialized medical evidence by non-medical professionals. Here, we present two cases of head GSWs, in which CFIT was newly implemented to reconstruct the cranial GSW including bullet trajectory, for evidence presentation—expanding its traditional use in forensic identification. Therefore, CFIT can help provide better forensic medical services for non-medical professionals.

This case study highlights craniofacial identification technology (CFIT) as a complementary and translational tool for reconstruction of cranial gunshot wounds (GSWs) and presenting evidence beyond forensic identification. In forensic cases involving GSWs, a visual demonstration of the bullet trajectory can improve communication between forensic pathologists and non-medical judicial agencies and the court. Postmortem computed tomography (PMCT) images and autopsy images are essential medical evidence, providing a robust visual display of the GSW and its bullet trajectory. PMCT images are useful for identifying the precise projectile localization and characteristics of bone fractures. However, PMCT images may not adequately present soft tissue injuries well, and autopsy images can be unpleasant to non-medical professionals, making it difficult for them to understand such specialized scientific evidence. CFIT is a well-established scientific tool with which forensic experts in craniofacial identification can create more advanced reconstructed three-dimensional (3D) images based on both postmortem findings and PMCT data. Intracranial bullet trajectory can be shown simply and directly in reconstructed 3D cranial images. CFIT can serve as an adjunctive tool to overcome the limitations of both PMCT images and autopsy images, thereby facilitating better understanding of such specialized medical evidence by non-medical professionals. Here, we present two cases of head GSWs, in which CFIT was newly implemented to reconstruct the cranial GSW including bullet trajectory, for evidence presentation—expanding its traditional use in forensic identification. Therefore, CFIT can help provide better forensic medical services for non-medical professionals.

This case study highlights craniofacial identification technology (CFIT) as a complementary and translational tool for reconstruction of cranial gunshot wounds (GSWs) and presenting evidence beyond forensic identification. In forensic cases involving GSWs, a visual demonstration of the bullet trajectory can improve communication between forensic pathologists and non-medical judicial agencies and the court. Postmortem computed tomography (PMCT) images and autopsy images are essential medical evidence, providing a robust visual display of the GSW and its bullet trajectory. PMCT images are useful for identifying the precise projectile localization and characteristics of bone fractures. However, PMCT images may not adequately present soft tissue injuries well, and autopsy images can be unpleasant to non-medical professionals, making it difficult for them to understand such specialized scientific evidence. CFIT is a well-established scientific tool with which forensic experts in craniofacial identification can create more advanced reconstructed three-dimensional (3D) images based on both postmortem findings and PMCT data. Intracranial bullet trajectory can be shown simply and directly in reconstructed 3D cranial images. CFIT can serve as an adjunctive tool to overcome the limitations of both PMCT images and autopsy images, thereby facilitating better understanding of such specialized medical evidence by non-medical professionals. Here, we present two cases of head GSWs, in which CFIT was newly implemented to reconstruct the cranial GSW including bullet trajectory, for evidence presentation—expanding its traditional use in forensic identification. Therefore, CFIT can help provide better forensic medical services for non-medical professionals.

This case study highlights craniofacial identification technology (CFIT) as a complementary and translational tool for reconstruction of cranial gunshot wounds (GSWs) and presenting evidence beyond forensic identification. In forensic cases involving GSWs, a visual demonstration of the bullet trajectory can improve communication between forensic pathologists and non-medical judicial agencies and the court. Postmortem computed tomography (PMCT) images and autopsy images are essential medical evidence, providing a robust visual display of the GSW and its bullet trajectory. PMCT images are useful for identifying the precise projectile localization and characteristics of bone fractures. However, PMCT images may not adequately present soft tissue injuries well, and autopsy images can be unpleasant to non-medical professionals, making it difficult for them to understand such specialized scientific evidence. CFIT is a well-established scientific tool with which forensic experts in craniofacial identification can create more advanced reconstructed three-dimensional (3D) images based on both postmortem findings and PMCT data. Intracranial bullet trajectory can be shown simply and directly in reconstructed 3D cranial images. CFIT can serve as an adjunctive tool to overcome the limitations of both PMCT images and autopsy images, thereby facilitating better understanding of such specialized medical evidence by non-medical professionals. Here, we present two cases of head GSWs, in which CFIT was newly implemented to reconstruct the cranial GSW including bullet trajectory, for evidence presentation—expanding its traditional use in forensic identification. Therefore, CFIT can help provide better forensic medical services for non-medical professionals.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: It is unclear whether performing endosonography first in non–small cell lung cancer (NSCLC) patients with radiological N1 (rN1) has any advantages over surgery without nodal staging. We aimed to compare surgery without endosonography to performing endosonography first in rN1 on the overall survival (OS) of patients with NSCLC. Materials and Methods: This is a retrospective analysis of patients with rN1 NSCLC between 2013 and 2019. Patients were divided into ‘no endosonography’ and ‘endosonography first’ groups. We investigated the effect of nodal staging through endosonography on OS using propensity score matching (PSM) and multivariable Cox proportional hazard regression analysis. Results: In the no endosonography group, pathologic N2 occurred in 23.0% of patients. In the endosonography first group, endosonographic N2 and N3 occurred in 8.6% and 1.6% of patients, respectively. Additionally, 51 patients were pathologic N2 among 249 patients who underwent surgery and mediastinal lymph node dissection (MLND) in endosonography first group. After PSM, the 5-year OSs were 68.1% and 70.6% in the no endosonography and endosonography first groups, respectively. However, the 5-year OS was 80.2% in the subgroup who underwent surgery and MLND of the endosonography first group. Moreover, in patients receiving surgical resection with MLND, the endosonography first group tended to have a better OS than the no endosonography group in adjusted analysis using various models. Conclusion In rN1 NSCLC, preoperative endosonography shows better OS than surgery without endosonography. For patients with rN1 NSCLC who are candidates for surgery, preoperative endosonography may help improve survival through patient selection.