Changes in Walking Function and Neural Control following Pelvic Cancer Surgery with Reconstruction

Abstract

Surgical planning and custom prosthesis design for pelvic cancer patients is challenging due to the unique clinical characteristics of each patient and the significant amount of pelvic bone and hip musculature often removed. Limb-sparing internal hemipelvectomy surgery with custom prosthesis reconstruction has become a viable option for this patient population. However, little is known about how post-surgery walking function and neural control change from pre-surgery conditions. This case study combined comprehensive human movement data collection with personalized neuromusculoskeletal computer modeling to provide a thorough assessment of pre-to post-surgery changes in walking function and neural control for a single pelvic sarcoma patient who received internal hemipelvectomy surgery with custom prosthesis reconstruction. Extensive walking data (video motion capture, ground reaction, and EMG) were collected from the patient before surgery and after plateau in recovery after surgery. Pre- and post-surgery personalized neuromusculoskeletal computer models of the patient were then constructed using the patient’s pre- and post-surgery walking data. These models were used to calculate the patient’s pre- and post-surgery joint motions, joint moments, and muscle synergies. The calculated muscle synergies were described by time-invariant synergy vectors and time-varying synergy activations, were consistent with the patient’s experimental EMG data, and produced the patient’s experimental joint moments found via inverse dynamics. The patient’s post-surgery walking function was marked by a slower self-selected walking speed coupled with several compensatory mechanisms necessitated by lost or impaired hip muscle function, while the patient’s post-surgery neural control demonstrated a dramatic change in coordination strategy (as evidenced by modified synergy vectors) with little change in recruitment timing (as evidenced by conserved synergy activations). Furthermore, the patient’s post-surgery muscle activations were fitted accurately using the patient’s pre-surgery synergy activations but poorly using the patient’s pre-surgery synergy vectors. These results provide valuable information about which aspects of post-surgery walking function could potentially be improved through modifications to surgical decisions, custom prosthesis design, or rehabilitation protocol, as well as how computational simulations could be formulated to predict post-surgery walking function reliably given a patient’s pre-surgery walking data and the planned surgical decisions and custom prosthesis design.

A Sensorized 3D-Printed Knee Test Rig for Preliminary Experimental Validation of Patellar Tracking and Contact Simulation

“…The use of musculoskeletal models in orthopedic surgeries offers significant potential to mitigate surgical complications through the prediction of post-treatment function. Computational simulations empower clinicians to assess diverse treatment options, diminish subjectivity in treatment planning, and enhance clinical outcomes for individual patients [3][4][5][6][7]. These virtual models and experiments emulate real-world phenomena using mathematical algorithms and computer software, facilitating the exploration, comprehension, and prediction of the behavior of complex systems or processes that may be difficult, costly, unsafe, or not ethical to study directly [8,9].…”