Purpose: To define patients and tumor characteristics as well as therapy results, patients with pelvic osteosarcoma who were registered in the Cooperative Osteosarcoma Study Group (COSS) were analyzed. Patients and Methods: Sixty-seven patients with a high-grade pelvic osteosarcoma were eligible for this analysis. Fifteen patients had primary metastases. All patients received chemotherapy according to COSS protocols. Thirty-eight patients underwent limb-sparing surgery, 12 patients underwent hemipelvectomy, and 17 patients did not undergo definitive surgery. Eleven patients received irradiation to the primary tumor site: four postoperatively and seven as the only form of local therapy. Results: Local failure occurred in 47 of all 67 patients (70%) and in 31 of 50 patients (62%) who underwent definitive surgery. Five-year overall survival (OS) and progression-free survival rates were 27% and 19%, respectively. Large tumor size (P = .0137), primary metastases (P = .0001), and no or intralesional surgery (P < .0001) were poor prognostic factors. In 30 patients with no or intralesional surgery, 11 patients with radiotherapy had better OS than 19 patients without radiotherapy (P = .0033). Among the variables, primary metastasis, large tumor, no or intralesional surgery, no radiotherapy, existence of primary metastasis (relative risk [RR] = 3.456; P = .0009), surgical margin (intralesional or no surgical excision; RR = 5.619; P < .0001), and no radiotherapy (RR = 4.196; P = .0059) were independent poor prognostic factors. Conclusion: An operative approach with wide or marginal margins improves local control and OS. If the surgical margin is intralesional or excision is impossible, additional radiotherapy has a positive influence on prognosis.

This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic performance over the image mode alone. For objective labeling, we collected a dataset containing 1131 images from patients who underwent both skeletal bone mineral density measurement and hip radiography at a single general hospital between 2014 and 2019. Osteoporosis was assessed from the hip radiographs using five convolutional neural network (CNN) models. We also investigated ensemble models with clinical covariates added to each CNN. The accuracy, precision, recall, specificity, negative predictive value (npv), F1 score, and area under the curve (AUC) score were calculated for each network. In the evaluation of the five CNN models using only hip radiographs, GoogleNet and EfficientNet b3 exhibited the best accuracy, precision, and specificity. Among the five ensemble models, EfficientNet b3 exhibited the best accuracy, recall, npv, F1 score, and AUC score when patient variables were included. The CNN models diagnosed osteoporosis from hip radiographs with high accuracy, and their performance improved further with the addition of clinical covariates from patient records.

Ewing sarcoma (ES) is rare in Japanese people, and only 30-40 patients develop the disease annually. To diagnose ES, molecular techniques that aim to detect characteristic fusion genes are commonly used in combination with conventional histological and immunohistochemical examinations. The treatment strategy for ES is characterized by multi-disciplinary collaboration between pediatric oncologists, medical oncologists, radiation oncologists, and orthopedic surgeons. In recent years, numerous large-scale national or international multi-institutional studies of ES have been performed. Pre- and postoperative intensive systemic chemotherapy with multiple anticancer drugs is the standard treatment method for ES. Depending on the obtained surgical margin, postoperative radiation might also be performed. If preoperative radiological examinations indicate that surgical excision would be difficult, preoperative radiation can be administered. As the treatment outcomes of ES have improved, late complications and secondary malignancies have become a problem. After treatment, patients with ES require very long-term follow-up in order to detect secondary malignancies and growth-related musculoskeletal complications.

How mechanical stress affects physical performance via tendons is not fully understood. Piezo1 is a mechanosensitive ion channel, and E756del PIEZO1 was recently found as a gain-of-function variant that is common in individuals of African descent. We generated tendon-specific knock-in mice using R2482H Piezo1 , a mouse gain-of-function variant, and found that they had higher jumping abilities and faster running speeds than wild-type or muscle-specific knock-in mice. These phenotypes were associated with enhanced tendon anabolism via an increase in tendon-specific transcription factors, Mohawk and Scleraxis, but there was no evidence of changes in muscle. Biomechanical analysis showed that the tendons of R2482H Piezo1 mice were more compliant and stored more elastic energy, consistent with the enhancement of jumping ability. These phenotypes were replicated in mice with tendon-specific R2482H Piezo1 replacement after tendon maturation, indicating that PIEZO1 could be a target for promoting physical performance by enhancing function in mature tendon. The frequency of E756del PIEZO1 was higher in sprinters than in population-matched nonathletic controls in a small Jamaican cohort, suggesting a similar function in humans. Together, this human and mouse genetic and physiological evidence revealed a critical function of tendons in physical performance, which is tightly and robustly regulated by PIEZO1 in tenocytes.