A retrospective evaluation of individual thigh muscle volume disparities based on hip fracture types in followed-up patients: an AI-based segmentation approach using UNETR.

Background: Hip fractures are a common and debilitating condition, particularly among older adults. Loss of muscle mass and strength is a common consequence of hip fractures, which further contribute to functional decline and increased disability. Assessing changes in individual thigh muscles volume in follow-up patients can provide valuable insights into the quantitative recovery process and guide rehabilitation interventions. However, accurately measuring anatomical individual thigh muscle volume can be challenging due to various, labor intensive and time-consuming. Materials and Methods: This study aimed to evaluate differences in thigh muscle volume in followed-up hip fracture patients computed tomography (CT) scans using an AI based automatic muscle segmentation model. The study included a total of 18 patients at Gyeongsang National University, who had undergone surgical treatment for a hip fracture. We utilized the automatic segmentation algorithm which we have already developed using UNETR (U-net Transformer) architecture, performance dice score = 0.84, relative absolute volume difference 0.019 ± 0.017%. Results: The results revealed intertrochanteric fractures result in more significant muscle volume loss (females: -97.4 cm3, males: -178.2 cm3) compared to femoral neck fractures (females: -83 cm3, males: -147.2 cm3). Additionally, the study uncovered substantial disparities in the susceptibility to volume loss among specific thigh muscles, including the Vastus lateralis, Adductor longus and brevis, and Gluteus maximus, particularly in cases of intertrochanteric fractures. Conclusions: The use of an automatic muscle segmentation model based on deep learning algorithms enables efficient and accurate analysis of thigh muscle volume differences in followed up hip fracture patients. Our findings emphasize the significant muscle loss tied to sarcopenia, a critical condition among the elderly. Intertrochanteric fractures resulted in greater muscle volume deformities, especially in key muscle groups, across both genders. Notably, while most muscles exhibited volume reduction following hip fractures, the sartorius, vastus and gluteus groups demonstrated more significant disparities in individuals who sustained intertrochanteric fractures. This non-invasive approach provides valuable insights into the extent of muscle atrophy following hip fracture and can inform targeted rehabilitation interventions.

Recent Update on the Prevalence of Sarcopenia in Koreans: Findings from the Korea National Health and Nutrition Examination Survey.

BACKGROUND: As recognized by the World Health Organization in 2016 with its inclusion in the International Classification of Diseases, Tenth Revision as M62.84, and by South Korea in 2021 as M62.5, the diagnostic guidelines for sarcopenia vary globally. Despite its prevalence in older populations, data on sarcopenia in Koreans aged 60 and above is scarce, highlighting the need for research on its prevalence in this demographic. METHODS: Utilizing the 2022 Korea National Health and Nutrition Examination Survey dataset, sarcopenia was assessed among 1,946 individuals aged 60 or older according to the Asian Working Group for Sarcopenia 2019 criteria, incorporating grip strength and bioelectrical impedance analysis measurements. Statistical analyses were performed to differentiate categorical and continuous variables using logistic regression and Student's t-tests, respectively. RESULTS: The prevalence of sarcopenia was found to increase with age, with the highest prevalence observed in the oldest age group (80 years and older). The overall prevalence of sarcopenia in our study population was 6.8%. Among men, the prevalence of sarcopenia was 5.5% in the 60 or older age group, 9.6% in the 70 or older age group, and 21.5% in the 80 or older age group. Among women, the prevalence of sarcopenia was 7.9%, 10.5%, and 25.9%, respectively. CONCLUSIONS: This study highlights the significant burden of sarcopenia in elderly Koreans, particularly among the oldest individuals. These findings call for targeted interventions to manage and prevent sarcopenia, along with further research on its risk factors, consequences, and effective mitigation strategies.

Patient Perception on Osteoporosis in Korean Female Patients with Osteoporosis.

BACKGROUND: Patient perception is a key element in improving compliance with medications for osteoporosis. This study evaluated the awareness, perception, sources of information, and knowledge of osteoporosis among Korean women with osteoporosis. METHODS: A questionnaire survey was conducted from July 22, 2021 to 13 August 2021. Patients who were followed up in endocrinology (Endo), orthopedic surgery (OS), and gynecology (GY) were recruited (N=40, 40, and 20 in each group). Patients were allocated according to their age, as follows: 15, 15, and 10 patients in their 60s, 70s, and 80s for Endo and OS, and 10 and 10 patients in their 60s and 70s for GY. The questionnaire was composed of the following topics: patient journey to the hospital, drug-related issues, communication with medical doctors, patient knowledge, and sources of information about osteoporosis. RESULTS: The results of medical check-ups were the most common reason for patient visits to the hospital for an initial diagnosis of osteoporosis (61%). A knowledge gap regarding mortality, refracture, and drug-induced osteoporosis was observed. Doctors were the most preferred and trustful source of information, while health-related TV shows were the second most common source of information. Patients with OS reported lower perceived severity and higher drug discontinuation, along with a higher proportion of fractures, as the initial reasons for hospital visits for osteoporosis. CONCLUSIONS: Variations in perceptions according to the issue and group were identified. These should be considered during patient consultations to improve compliance with osteoporosis treatment.

Optimization of Acetabular Cup Abduction by Adjusting Pelvic Pitch.

Background: The purposes of this study were to determine the accuracy of our cup positioning method and to evaluate the dislocation rate after total hip arthroplasty (THA). Methods: After positioning the patient in the lateral decubitus position on the operation table, an anteroposterior view of the hip was taken. The pelvic pitch was measured on the X-ray. A positive pitch was defined as the caudal rotation of the upper hemipelvis. Our target abduction of the cup was 43°. We used the cup holder to guesstimate the cup abduction. In a preliminary study, we found that the weight of the cup holder increased the pelvic pitch by 5°. Thus, the target abduction of the cup holder was calculated by a formula: 43° - pelvic pitch - 5°. During the cup insertion, the cup holder was anteverted to the calculated target according to the concept of combined anteversion. We evaluated 478 THAs (429 patients), which were done with the use of the method. Results: The mean cup abduction was 43.9° (range, 32.0°-53.0°) and the mean error of cup abduction was 2.4° (standard deviation [SD], 2.0°; range, 0.0°-11.0°). The mean cup anteversion was 28.5° (range, 10.0°-42.0°) and the mean error of cup anteversion was 6.7° (SD, 5.2°; range, 0.0°-27.6°). Of all, 82.4% of the cups (394 / 478) were within the safe zone: 30°-50° abduction and 10°-35° anteversion. During 2- to 5-year follow-up, no hip dislocated. Conclusions: Our adjusting method according to the pelvic pitch can be a reliable option for optimizing the cup abduction in THA.

Precise individual muscle segmentation in whole thigh CT scans for sarcopenia assessment using U-net transformer.

The study aims to develop a deep learning based automatic segmentation approach using the UNETR(U-net Transformer) architecture to quantify the volume of individual thigh muscles(27 muscles in 5 groups) for Sarcopenia assessment. By automating the segmentation process, this approach improves the efficiency and accuracy of muscle volume calculation, facilitating a comprehensive understanding of muscle composition and its relationship to Sarcopenia. The study utilized a dataset of 72 whole thigh CT scans from hip fracture patients, annotated by two radiologists. The UNETR model was trained to perform precise voxel-level segmentation and various metrics such as dice score, average symmetric surface distance, volume correlation, relative absolute volume difference and Hausdorff distance were employed to evaluate the model's performance. Additionally, the correlation between Sarcopenia and individual thigh muscle volumes was examined. The proposed model demonstrated superior segmentation performance compared to the baseline model, achieving higher dice scores (DC = 0.84) and lower average symmetric surface distances (ASSD = 1.4191 ± 0.91). The volume correlation between Sarcopenia and individual thigh muscles in the male group. Furthermore, the correlation analysis of grouped thigh muscles also showed negative associations with Sarcopenia in the male participants. This thesis presents a deep learning based automatic segmentation approach for quantifying individual thigh muscle volume in sarcopenia assessment. The results highlights the associations between Sarcopenia and specific individual muscles as well as grouped thigh muscle regions, particularly in males. The proposed method improves the efficiency and accuracy of muscle volume calculation, contributing to a comprehensive evaluation of Sarcopenia. This research enhances our understanding of muscle composition and performance, providing valuable insights for effective interventions in Sarcopenia management.