Changes in walking function and neural control following pelvic cancer surgery with reconstruction

Abstract

Introduction: Surgical planning and custom prosthesis design for pelvic cancer patients are 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. Methods: This case study combined comprehensive walking data (video motion capture, ground reaction, and electromyography) with personalized neuromusculoskeletal computer models to provide a thorough assessment of pre- to post-surgery changes in walking function (ground reactions, joint motions, and joint moments) and neural control (muscle synergies) for a single pelvic sarcoma patient who received internal hemipelvectomy surgery with custom prosthesis reconstruction. Pre- and post-surgery walking function and neural control were quantified using pre- and post-surgery neuromusculoskeletal models, respectively, whose pelvic anatomy, joint functional axes, muscle-tendon properties, and muscle synergy controls were personalized using the participant's pre-and post-surgery walking and imaging data. For the post-surgery model, virtual surgery was performed to emulate the implemented surgical decisions, including removal of hip muscles and implantation of a custom prosthesis with total hip replacement. Results: The participant'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 participant's post-surgery neural control demonstrated a dramatic change in coordination strategy (as evidenced by modified time-invariant synergy vectors) with little change in recruitment timing (as evidenced by conserved time-varying synergy activations). Furthermore, the participant's post-surgery muscle activations were fitted accurately using his pre-surgery synergy activations but fitted poorly using his pre-surgery synergy vectors. Discussion: 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.

Keywords: custom implant; instrumented gait analysis; muscle synergies; neuromusculoskeletal modeling; orthopedic oncology; pelvic sarcoma; walking biomechanics.

FIGURE 1

(A) Geometric model of the remaining pelvic bone, custom prosthesis, and total hip replacement. (B) Updated hip joint center on the operated side, as determined from the center of the sphere used to fit the inner surface of the acetabular component. The coordinate system is consistent with OpenSim coordinate system: +x points in anterior direction, +y points in the superior direction, and +z points in the lateral (right) direction.

FIGURE 2

Pre- and post-surgery ground reaction forces (mean ±1 standard deviation across 10 gait cycles), along with SPM test results (grey shaded area indicates significant difference between pre- and post-surgery data).

FIGURE 3

Pre- and post-surgery joint motions (mean ±1 standard deviation across 10 gait cycles) for all lower extremity joints, along with SPM test results (grey shaded area indicates significant difference between pre- and post-surgery data).

FIGURE 4

Pre- and post-surgery joint motions (mean ±1 standard deviation across 10 gait cycles) for pelvis and lumbosacral orientations, along with SPM test results (grey shaded area indicates significant difference between pre- and post-surgery data).

FIGURE 5

Pre- and post-surgery joint moments (mean ± standard deviation across 10 gait cycles) for all lower extremity joints, along with SPM test results (grey shaded area indicates significant difference between pre- and post-surgery data).

FIGURE 6

Optimal muscle fiber length and tendon slack length values for lower extremity muscles in the personalized pre-surgery (red) and post-surgery (blue) neuromusculoskeletal models.

FIGURE 7

Example plot of pre- and post-surgery muscle synergies (mean ±1 standard deviation across 10 gait cycles) for (A) Operated Leg and (B) Non-operated Leg. Cosine similarity was calculated using the mean values for each pair of synergy activations or synergy vectors.

FIGURE 8

Variability accounted for (VAF) by reconstructed post-surgery muscle controls using each method: FixedSynVec (Fixed Synergy Vector, red), FixedSynCtl (Fixed Synergy Control, blue), and ShiftedSynCtl (Shifted Synergy Control, green). Each marker with error bars indicates mean ±1 standard deviation for VAF values from 10 gait cycles. Open markers indicate reconstruction of muscle excitations while filled markers indicate reconstruction of muscle activations.