PRIMARY OBJECTIVES:~I. To develop patient-specific computational walking models to predict the optimal combination of pelvic sarcoma surgical and rehabilitation decisions that will maximize each patient's post-surgery walking function.~II. To collect experimental movement and imaging data prospectively and retrospectively from individuals who have already received, or are going to receive, a type I or type II hemipelvectomy.~III. To use the data to develop computational modeling and simulation methodologies that can predict an individual patient's post-surgery walking function given pre-surgery movement and imaging data and the surgical decisions made by the surgeon.~OUTLINE:~Patients undergo walking function assessment using optical motion capture and bi-plane dynamic X-ray imaging pre- and post-hemipelvectomy.
This trial studies the development of patient-specific computational walking models to improve the surgical planning and rehabilitation treatment of patients with pelvic sarcomas. Every pelvis and pelvic sarcoma are different, and the orthopedic oncologist faces significant challenges when removing a tumor from the complex anatomy of the pelvis. These challenges make it difficult to achieve excellent oncological and functional outcomes together. Computational walking models may be used to predict the best combination of surgical methods and how to implement them to maximize each patient's post-surgery walking function.