[Innovations in the classification of soft tissue tumors]. / Neuerungen in der Klassifikation von Weichteiltumoren.

Soft tissue tumors are a very heterogeneous group of tumors. Their classification is regularly updated by the World Health Organization (WHO), most recently in 2020. The current classification of soft tissue tumors emphasizes molecular biological tumor characteristics, which enable tumor-specific treatment. In addition to Ewing's sarcoma, which occurs as bone as well as extra-skeletal soft tissue tumors as a small round cell sarcoma, three other subtypes of undifferentiated, small and round cell sarcomas have been introduced. Some names of the new sarcomas can be derived from the gene mutations. The groups of adipocytic and (myo)fibroblastic tumors have been extended by three further entities. There were further additions to vascular soft tissue tumors, smooth muscle cell tumors, peripheral nerve sheath tumors and tumors of uncertain differentiation. A distinction is made between benign, intermediate locally aggressive, intermediate rarely metastatic and malignant soft tissue tumors.

Experimental and virtual testing of bone-implant systems equipped with the AO Fracture Monitor with regard to interfragmentary movement.

Introduction: The management of fractured bones is a key domain within orthopedic trauma surgery, with the prevention of delayed healing and non-unions forming a core challenge. This study evaluates the efficacy of the AO Fracture Monitor in conjunction with biomechanical simulations to better understand the local mechanics of fracture gaps, which is crucial for comprehending mechanotransduction, a key factor in bone healing. Through a series of experiments and corresponding simulations, the study tests four hypotheses to determine the relationship between physical measurements and the predictive power of biomechanical models. Methods: Employing the AO Fracture Monitor and Digital Image Correlation techniques, the study demonstrates a significant correlation between the surface strain of implants and interfragmentary movements. This provides a foundation for utilizing one-dimensional AO Fracture Monitor measurements to predict three-dimensional fracture behavior, thereby linking mechanical loading with fracture gap dynamics. Moreover, the research establishes that finite element simulations of bone-implant systems can be effectively validated using experimental data, underpinning the accuracy of simulations in replicating physical behaviors. Results and Discussion: The findings endorse the combined use of monitoring technologies and simulations to infer the local mechanical conditions at the fracture site, offering a potential leap in personalized therapy for bone healing. Clinically, this approach can enhance treatment outcomes by refining the assessment precision in trauma trials, fostering the early detection of healing disturbances, and guiding improvements in future implant design. Ultimately, this study paves the way for more sophisticated patient monitoring and tailored interventions, promising to elevate the standard of care in orthopedic trauma surgery.