Background: Decreased acetabular version and posterior acetabular coverage of the femoral head have been regarded as the leading causes of sport-related posterior hip dislocation or subluxation. This study aimed to examine the posterior acetabular coverage of the femoral head in 21 patients who sustained posterior hip dislocation or subluxation during sport activities. Methods: The anterior and posterior acetabular rims on 3-dimensional computed tomography (3D-CT) images were delineated on the normal side in these patients. Radiologic signs, including crossover and posterior wall signs, were examined. The fracture center level (FCL) of the posterior acetabular wall was identified on axial CT images of the injured hip and the level was marked on the normal side. The difference in the femoral head coverage by posterior and anterior acetabular rims was measured by measuring the horizontal distance between anterior and posterior acetabular rims at the FCL (posterior-anterior [P-A] index). The acetabular version was measured at the femoral head and FCL using axial CT images of the normal side. Femoral head coverage by the posterior acetabular wall on the normal side was measured using 3D-CT (areal coverage). Results: The crossover and posterior wall signs were positive in 14 and 10 patients, respectively, in 3D-CT images. The FCL was evenly distributed in the proximal half of the posterior acetabular wall. Seven patients had a P-A index of ≤ 0, and all were positive for the crossover sign. The anterior acetabular rim was relatively prominent in these patients. The acetabular version was lower at the FCL than at the femoral head center (p < 0.001). The proximal half areal coverage of the posterior acetabular wall was significantly smaller than the whole areal coverage (p = 0.003). Conclusions Superior–posterior coverage of the femoral head by the posterior acetabular wall was insufficient in patients who sustained hip posterior dislocation or subluxation during sports activities.

Background: Decreased acetabular version and posterior acetabular coverage of the femoral head have been regarded as the leading causes of sport-related posterior hip dislocation or subluxation. This study aimed to examine the posterior acetabular coverage of the femoral head in 21 patients who sustained posterior hip dislocation or subluxation during sport activities. Methods: The anterior and posterior acetabular rims on 3-dimensional computed tomography (3D-CT) images were delineated on the normal side in these patients. Radiologic signs, including crossover and posterior wall signs, were examined. The fracture center level (FCL) of the posterior acetabular wall was identified on axial CT images of the injured hip and the level was marked on the normal side. The difference in the femoral head coverage by posterior and anterior acetabular rims was measured by measuring the horizontal distance between anterior and posterior acetabular rims at the FCL (posterior-anterior [P-A] index). The acetabular version was measured at the femoral head and FCL using axial CT images of the normal side. Femoral head coverage by the posterior acetabular wall on the normal side was measured using 3D-CT (areal coverage). Results: The crossover and posterior wall signs were positive in 14 and 10 patients, respectively, in 3D-CT images. The FCL was evenly distributed in the proximal half of the posterior acetabular wall. Seven patients had a P-A index of ≤ 0, and all were positive for the crossover sign. The anterior acetabular rim was relatively prominent in these patients. The acetabular version was lower at the FCL than at the femoral head center (p < 0.001). The proximal half areal coverage of the posterior acetabular wall was significantly smaller than the whole areal coverage (p = 0.003). Conclusions Superior–posterior coverage of the femoral head by the posterior acetabular wall was insufficient in patients who sustained hip posterior dislocation or subluxation during sports activities.

Background: Decreased acetabular version and posterior acetabular coverage of the femoral head have been regarded as the leading causes of sport-related posterior hip dislocation or subluxation. This study aimed to examine the posterior acetabular coverage of the femoral head in 21 patients who sustained posterior hip dislocation or subluxation during sport activities. Methods: The anterior and posterior acetabular rims on 3-dimensional computed tomography (3D-CT) images were delineated on the normal side in these patients. Radiologic signs, including crossover and posterior wall signs, were examined. The fracture center level (FCL) of the posterior acetabular wall was identified on axial CT images of the injured hip and the level was marked on the normal side. The difference in the femoral head coverage by posterior and anterior acetabular rims was measured by measuring the horizontal distance between anterior and posterior acetabular rims at the FCL (posterior-anterior [P-A] index). The acetabular version was measured at the femoral head and FCL using axial CT images of the normal side. Femoral head coverage by the posterior acetabular wall on the normal side was measured using 3D-CT (areal coverage). Results: The crossover and posterior wall signs were positive in 14 and 10 patients, respectively, in 3D-CT images. The FCL was evenly distributed in the proximal half of the posterior acetabular wall. Seven patients had a P-A index of ≤ 0, and all were positive for the crossover sign. The anterior acetabular rim was relatively prominent in these patients. The acetabular version was lower at the FCL than at the femoral head center (p < 0.001). The proximal half areal coverage of the posterior acetabular wall was significantly smaller than the whole areal coverage (p = 0.003). Conclusions Superior–posterior coverage of the femoral head by the posterior acetabular wall was insufficient in patients who sustained hip posterior dislocation or subluxation during sports activities.

Background: Decreased acetabular version and posterior acetabular coverage of the femoral head have been regarded as the leading causes of sport-related posterior hip dislocation or subluxation. This study aimed to examine the posterior acetabular coverage of the femoral head in 21 patients who sustained posterior hip dislocation or subluxation during sport activities. Methods: The anterior and posterior acetabular rims on 3-dimensional computed tomography (3D-CT) images were delineated on the normal side in these patients. Radiologic signs, including crossover and posterior wall signs, were examined. The fracture center level (FCL) of the posterior acetabular wall was identified on axial CT images of the injured hip and the level was marked on the normal side. The difference in the femoral head coverage by posterior and anterior acetabular rims was measured by measuring the horizontal distance between anterior and posterior acetabular rims at the FCL (posterior-anterior [P-A] index). The acetabular version was measured at the femoral head and FCL using axial CT images of the normal side. Femoral head coverage by the posterior acetabular wall on the normal side was measured using 3D-CT (areal coverage). Results: The crossover and posterior wall signs were positive in 14 and 10 patients, respectively, in 3D-CT images. The FCL was evenly distributed in the proximal half of the posterior acetabular wall. Seven patients had a P-A index of ≤ 0, and all were positive for the crossover sign. The anterior acetabular rim was relatively prominent in these patients. The acetabular version was lower at the FCL than at the femoral head center (p < 0.001). The proximal half areal coverage of the posterior acetabular wall was significantly smaller than the whole areal coverage (p = 0.003). Conclusions Superior–posterior coverage of the femoral head by the posterior acetabular wall was insufficient in patients who sustained hip posterior dislocation or subluxation during sports activities.

Background and Objectives: Kawasaki disease (KD) is an acute vasculitis that primarily affects children under age 5 years. Approximately 20–25% of untreated children with KD and 3–5% of those treated with intravenous immunoglobulin therapy develop coronary artery aneurysms (CAAs). The prevalence of CAAs is much higher in male than in female patients with KD, but the underlying factors contributing to susceptibility to CAAs in patients with KD remain unclear. This study aimed to identify sex-specific susceptibility loci associated with CAAs in KD patients. Methods: A sex-stratified genome-wide association study (GWAS) was performed using previously obtained GWAS data from 296 KD patients and a new replication study in an independent set of 976 KD patients by comparing KD patients without CAA (controls) and KD patients with aneurysms (internal diameter ≥5 mm) (cases). Results: Six male-specific susceptibility loci, PDE1C, NOS3, DLG2, CPNE8, FUNDC1, and GABRQ (odds ratios [ORs], 2.25–9.98; p=0.00204–1.96×10−6 ), and 2 female-specific susceptibility loci, SMAD3 (OR, 4.59; p=0.00016) and IL1RAPL1 (OR, 4.35; p=0.00026), were significantly associated with CAAs in patients with KD. In addition, the numbers of CAA risk alleles additively contributed to the development of CAAs in patients with KD. Conclusions A sex-stratified GWAS identified 6 male-specific (PDE1C, NOS3, DLG2, CPNE8, FUNDC1, and GABRQ) and 2 female-specific (SMAD3 and IL1RAPL1) CAA susceptibility loci in patients with KD.

Background and Objectives: Kawasaki disease (KD) is an acute vasculitis that primarily affects children under age 5 years. Approximately 20–25% of untreated children with KD and 3–5% of those treated with intravenous immunoglobulin therapy develop coronary artery aneurysms (CAAs). The prevalence of CAAs is much higher in male than in female patients with KD, but the underlying factors contributing to susceptibility to CAAs in patients with KD remain unclear. This study aimed to identify sex-specific susceptibility loci associated with CAAs in KD patients. Methods: A sex-stratified genome-wide association study (GWAS) was performed using previously obtained GWAS data from 296 KD patients and a new replication study in an independent set of 976 KD patients by comparing KD patients without CAA (controls) and KD patients with aneurysms (internal diameter ≥5 mm) (cases). Results: Six male-specific susceptibility loci, PDE1C, NOS3, DLG2, CPNE8, FUNDC1, and GABRQ (odds ratios [ORs], 2.25–9.98; p=0.00204–1.96×10−6 ), and 2 female-specific susceptibility loci, SMAD3 (OR, 4.59; p=0.00016) and IL1RAPL1 (OR, 4.35; p=0.00026), were significantly associated with CAAs in patients with KD. In addition, the numbers of CAA risk alleles additively contributed to the development of CAAs in patients with KD. Conclusions A sex-stratified GWAS identified 6 male-specific (PDE1C, NOS3, DLG2, CPNE8, FUNDC1, and GABRQ) and 2 female-specific (SMAD3 and IL1RAPL1) CAA susceptibility loci in patients with KD.

Background: s/Aims: Artificial intelligence (AI) technology has been used to assess surgery quality, educate, and evaluate surgical performance using video recordings in the minimally invasive surgery era. Much attention has been paid to automating surgical workflow analysis from surgical videos for an effective evaluation to achieve the assessment and evaluation. This study aimed to design a deep learning model to automatically identify surgical phases using laparoscopic cholecystectomy videos and automatically assess the accuracy of recognizing surgical phases. Methods: One hundred and twenty cholecystectomy videos from a public dataset (Cholec80) and 40 laparoscopic cholecystectomy videos recorded between July 2022 and December 2022 at a single institution were collected. These datasets were split into training and testing datasets for the AI model at a 2:1 ratio. Test scenarios were constructed according to structural characteristics of the trained model. No pre- or post-processing of input data or inference output was performed to accurately analyze the effect of the label on model training. Results: A total of 98,234 frames were extracted from 40 cases as test data. The overall accuracy of the model was 91.2%. The most accurate phase was Calot’s triangle dissection (F1 score: 0.9421), whereas the least accurate phase was clipping and cutting (F1 score:0.7761). Conclusions Our AI model identified phases of laparoscopic cholecystectomy with a high accuracy.

Background: s/Aims: Artificial intelligence (AI) technology has been used to assess surgery quality, educate, and evaluate surgical performance using video recordings in the minimally invasive surgery era. Much attention has been paid to automating surgical workflow analysis from surgical videos for an effective evaluation to achieve the assessment and evaluation. This study aimed to design a deep learning model to automatically identify surgical phases using laparoscopic cholecystectomy videos and automatically assess the accuracy of recognizing surgical phases. Methods: One hundred and twenty cholecystectomy videos from a public dataset (Cholec80) and 40 laparoscopic cholecystectomy videos recorded between July 2022 and December 2022 at a single institution were collected. These datasets were split into training and testing datasets for the AI model at a 2:1 ratio. Test scenarios were constructed according to structural characteristics of the trained model. No pre- or post-processing of input data or inference output was performed to accurately analyze the effect of the label on model training. Results: A total of 98,234 frames were extracted from 40 cases as test data. The overall accuracy of the model was 91.2%. The most accurate phase was Calot’s triangle dissection (F1 score: 0.9421), whereas the least accurate phase was clipping and cutting (F1 score:0.7761). Conclusions Our AI model identified phases of laparoscopic cholecystectomy with a high accuracy.

Background and Objectives: Kawasaki disease (KD) is an acute vasculitis that primarily affects children under age 5 years. Approximately 20–25% of untreated children with KD and 3–5% of those treated with intravenous immunoglobulin therapy develop coronary artery aneurysms (CAAs). The prevalence of CAAs is much higher in male than in female patients with KD, but the underlying factors contributing to susceptibility to CAAs in patients with KD remain unclear. This study aimed to identify sex-specific susceptibility loci associated with CAAs in KD patients. Methods: A sex-stratified genome-wide association study (GWAS) was performed using previously obtained GWAS data from 296 KD patients and a new replication study in an independent set of 976 KD patients by comparing KD patients without CAA (controls) and KD patients with aneurysms (internal diameter ≥5 mm) (cases). Results: Six male-specific susceptibility loci, PDE1C, NOS3, DLG2, CPNE8, FUNDC1, and GABRQ (odds ratios [ORs], 2.25–9.98; p=0.00204–1.96×10−6 ), and 2 female-specific susceptibility loci, SMAD3 (OR, 4.59; p=0.00016) and IL1RAPL1 (OR, 4.35; p=0.00026), were significantly associated with CAAs in patients with KD. In addition, the numbers of CAA risk alleles additively contributed to the development of CAAs in patients with KD. Conclusions A sex-stratified GWAS identified 6 male-specific (PDE1C, NOS3, DLG2, CPNE8, FUNDC1, and GABRQ) and 2 female-specific (SMAD3 and IL1RAPL1) CAA susceptibility loci in patients with KD.

Background: s/Aims: Artificial intelligence (AI) technology has been used to assess surgery quality, educate, and evaluate surgical performance using video recordings in the minimally invasive surgery era. Much attention has been paid to automating surgical workflow analysis from surgical videos for an effective evaluation to achieve the assessment and evaluation. This study aimed to design a deep learning model to automatically identify surgical phases using laparoscopic cholecystectomy videos and automatically assess the accuracy of recognizing surgical phases. Methods: One hundred and twenty cholecystectomy videos from a public dataset (Cholec80) and 40 laparoscopic cholecystectomy videos recorded between July 2022 and December 2022 at a single institution were collected. These datasets were split into training and testing datasets for the AI model at a 2:1 ratio. Test scenarios were constructed according to structural characteristics of the trained model. No pre- or post-processing of input data or inference output was performed to accurately analyze the effect of the label on model training. Results: A total of 98,234 frames were extracted from 40 cases as test data. The overall accuracy of the model was 91.2%. The most accurate phase was Calot’s triangle dissection (F1 score: 0.9421), whereas the least accurate phase was clipping and cutting (F1 score:0.7761). Conclusions Our AI model identified phases of laparoscopic cholecystectomy with a high accuracy.