Purpose: For several decades, bone scintigraphy (BS) has been used as a diagnostic tool for arthritis in patients with synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome. Artificial intelligence (AI) diagnostic supporting systems are effective in BS. The bone scan index (BSI) on BS with AI diagnostic support systems has been used for bone tumors.However, its application in arthritis has not been validated. The current study aimed to evaluate the usefulness of BSI using an AI diagnostic supporting system for arthritis in patients with SAPHO syndrome. Methods: The regional BSI (rBSI) of arthritis uptake around the sternoclavicular and sternocostal joints on BS in patients with SAPHO syndrome was calculated using an AI diagnostic supporting system (VSBONE BSI®). For comparison, patients with degenerative changes on BS in the same region were evaluated. rBSI was calculated using the same process. Results: This study included 43 patients with SAPHO syndrome and 48 with degenerative changes. The rBSIs with the diagnostic supporting system were 0.19 ± 0.19 in patients with SAPHO syndrome and 0.043 ± 0.056 in those with degenerative changes. Patients with SAPHO syndrome had significantly higher rBSIs than those with degenerative changes (P < 0.001).A cutoff value of 0.030 for rBSI in the region of interest had a sensitivity of 0.98 and specificity of 0.63 for differentiating arthritis from degenerative changes (area under the curve: 0.87, 95% confidence interval: 0.81–0.92). Conclusion The objective evaluation of arthritis using rBSI calculated with an AI diagnostic supporting system may be useful.

Purpose: For several decades, bone scintigraphy (BS) has been used as a diagnostic tool for arthritis in patients with synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome. Artificial intelligence (AI) diagnostic supporting systems are effective in BS. The bone scan index (BSI) on BS with AI diagnostic support systems has been used for bone tumors.However, its application in arthritis has not been validated. The current study aimed to evaluate the usefulness of BSI using an AI diagnostic supporting system for arthritis in patients with SAPHO syndrome. Methods: The regional BSI (rBSI) of arthritis uptake around the sternoclavicular and sternocostal joints on BS in patients with SAPHO syndrome was calculated using an AI diagnostic supporting system (VSBONE BSI®). For comparison, patients with degenerative changes on BS in the same region were evaluated. rBSI was calculated using the same process. Results: This study included 43 patients with SAPHO syndrome and 48 with degenerative changes. The rBSIs with the diagnostic supporting system were 0.19 ± 0.19 in patients with SAPHO syndrome and 0.043 ± 0.056 in those with degenerative changes. Patients with SAPHO syndrome had significantly higher rBSIs than those with degenerative changes (P < 0.001).A cutoff value of 0.030 for rBSI in the region of interest had a sensitivity of 0.98 and specificity of 0.63 for differentiating arthritis from degenerative changes (area under the curve: 0.87, 95% confidence interval: 0.81–0.92). Conclusion The objective evaluation of arthritis using rBSI calculated with an AI diagnostic supporting system may be useful.

Purpose: For several decades, bone scintigraphy (BS) has been used as a diagnostic tool for arthritis in patients with synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome. Artificial intelligence (AI) diagnostic supporting systems are effective in BS. The bone scan index (BSI) on BS with AI diagnostic support systems has been used for bone tumors.However, its application in arthritis has not been validated. The current study aimed to evaluate the usefulness of BSI using an AI diagnostic supporting system for arthritis in patients with SAPHO syndrome. Methods: The regional BSI (rBSI) of arthritis uptake around the sternoclavicular and sternocostal joints on BS in patients with SAPHO syndrome was calculated using an AI diagnostic supporting system (VSBONE BSI®). For comparison, patients with degenerative changes on BS in the same region were evaluated. rBSI was calculated using the same process. Results: This study included 43 patients with SAPHO syndrome and 48 with degenerative changes. The rBSIs with the diagnostic supporting system were 0.19 ± 0.19 in patients with SAPHO syndrome and 0.043 ± 0.056 in those with degenerative changes. Patients with SAPHO syndrome had significantly higher rBSIs than those with degenerative changes (P < 0.001).A cutoff value of 0.030 for rBSI in the region of interest had a sensitivity of 0.98 and specificity of 0.63 for differentiating arthritis from degenerative changes (area under the curve: 0.87, 95% confidence interval: 0.81–0.92). Conclusion The objective evaluation of arthritis using rBSI calculated with an AI diagnostic supporting system may be useful.

Purpose: For several decades, bone scintigraphy (BS) has been used as a diagnostic tool for arthritis in patients with synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome. Artificial intelligence (AI) diagnostic supporting systems are effective in BS. The bone scan index (BSI) on BS with AI diagnostic support systems has been used for bone tumors.However, its application in arthritis has not been validated. The current study aimed to evaluate the usefulness of BSI using an AI diagnostic supporting system for arthritis in patients with SAPHO syndrome. Methods: The regional BSI (rBSI) of arthritis uptake around the sternoclavicular and sternocostal joints on BS in patients with SAPHO syndrome was calculated using an AI diagnostic supporting system (VSBONE BSI®). For comparison, patients with degenerative changes on BS in the same region were evaluated. rBSI was calculated using the same process. Results: This study included 43 patients with SAPHO syndrome and 48 with degenerative changes. The rBSIs with the diagnostic supporting system were 0.19 ± 0.19 in patients with SAPHO syndrome and 0.043 ± 0.056 in those with degenerative changes. Patients with SAPHO syndrome had significantly higher rBSIs than those with degenerative changes (P < 0.001).A cutoff value of 0.030 for rBSI in the region of interest had a sensitivity of 0.98 and specificity of 0.63 for differentiating arthritis from degenerative changes (area under the curve: 0.87, 95% confidence interval: 0.81–0.92). Conclusion The objective evaluation of arthritis using rBSI calculated with an AI diagnostic supporting system may be useful.

Purpose: For several decades, bone scintigraphy (BS) has been used as a diagnostic tool for arthritis in patients with synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome. Artificial intelligence (AI) diagnostic supporting systems are effective in BS. The bone scan index (BSI) on BS with AI diagnostic support systems has been used for bone tumors.However, its application in arthritis has not been validated. The current study aimed to evaluate the usefulness of BSI using an AI diagnostic supporting system for arthritis in patients with SAPHO syndrome. Methods: The regional BSI (rBSI) of arthritis uptake around the sternoclavicular and sternocostal joints on BS in patients with SAPHO syndrome was calculated using an AI diagnostic supporting system (VSBONE BSI®). For comparison, patients with degenerative changes on BS in the same region were evaluated. rBSI was calculated using the same process. Results: This study included 43 patients with SAPHO syndrome and 48 with degenerative changes. The rBSIs with the diagnostic supporting system were 0.19 ± 0.19 in patients with SAPHO syndrome and 0.043 ± 0.056 in those with degenerative changes. Patients with SAPHO syndrome had significantly higher rBSIs than those with degenerative changes (P < 0.001).A cutoff value of 0.030 for rBSI in the region of interest had a sensitivity of 0.98 and specificity of 0.63 for differentiating arthritis from degenerative changes (area under the curve: 0.87, 95% confidence interval: 0.81–0.92). Conclusion The objective evaluation of arthritis using rBSI calculated with an AI diagnostic supporting system may be useful.

Objectives: Locomotive syndrome stage 3 (LS3), which has been established recently, may imply a greater need for care than LS stage 0 (LS0), LS stage 1 (LS1), and LS stage 2 (LS2). The relationship between LS3 and long-term care in Japan is unclear. Therefore, this study aimed to examine this relationship. Methods: A total of 531 patients (314 women and 217 men; mean age, 75 years) who were not classified as requiring long-term care and underwent musculoskeletal examinations in 2012 were grouped according to their LS stage. Group L comprised patients with LS3 and Group N comprised those with LS0, LS1, and LS2. We compared these groups according to their epidemiology results and long-term care requirements from 2013 to 2018. Results: Fifty-nine patients (11.1%) were diagnosed with LS3. Group L comprised more patients (50.8%) who required long-term care than Group N (17.8%) (P < 0.001). Group L also comprised more patients with vertebral fractures and knee osteoarthritis than Group N (33.9% vs 19.5% [P = 0.011] and 78% vs 56.4% [P < 0.001], respectively). A Cox proportional hazards model and Kaplan–Meier analysis revealed a significant difference in the need for nursing care between Groups L and N (log-rank test, P < 0.001; hazard ratio, 2.236; 95% confidence interval, 1.451–3.447). Conclusions Between 2012 and 2018, 50% of patients with LS3 required nursing care. Therefore, LS3 is a highrisk condition that necessitates interventions. Approaches to vertebral fractures and osteoarthritis of the knee could be key.

The patient is a 66-year-old woman. She had been taking steroids for some years for rheumatoid arthritis and had been using crutches for some years because of multiple joint deformities. She presented herself to an orthopedic clinic for right upper extremity numbness and was diagnosed with cervical spondylosis and was kept under observation. However, 7 days later, a pulsatile mass on her right upper arm was found and she was referred to our hospital. Contrast-enhanced CT revealed a right brachial artery aneurysm (19×17×16 mm）, and the numbness was considered to be a symptom of nerve compression caused by the aneurysm. Since the cause of the brachial artery aneurysm was long-term inappropriate use of crutches, we confirmed that the patient would not use crutches and would use other assistive devices after the surgery, and then performed aneurysm resection and direct anastomosis under general anesthesia. Aneurysms of the upper extremities are rare and are often traumatic or iatrogenic pseudoaneurysms, and surgery is recommended because they can cause complications such as embolism, nerve compression, and rupture. In revascularization in cases where the aneurysm is caused by crutches, it is necessary to consider the risk of recurrence. In our case, we were able to perform direct anastomosis by switching the walking aid from crutches to Lofstrand clutches.