Background

Clinical assessment of thumb motion is challenging, due to the complex anatomy and motion of the thumb. It is especially difficult to measure hand movement during activity, and to measure the effects of surgery that changes the morphology of the thumb. A three-dimensional model of the hand may enable clinicians to better assess prehension and thumb motion at baseline, and following surgical intervention.

Methods

A kinematic model of the hand was developed to measure thumb and finger position during functional tasks, enabling the calculation of the volume of space in which prehension could occur. This method was validated by application to a mechanical model of the hand, and then applied to ten adult participants, using three-dimensional motion analysis with a marker array developed for the purpose of this study.

Findings

This method can be used to accurately measure three-dimensional thumb joint range of motion (RoM) and predicted functional workspace during functional activities. The thumb carpometacarpal joint was predominantly responsible for thumb position during functional tasks. Predicted functional workspace is proportional to hand morphometric measurements.

Interpretation

A kinematic model of the hand measures thumb RoM and predicts functional workspace during functional activities.

Study design

A longitudinal cohort study.

Objective

To define a set of objective biomechanical metrics that are representative of adult spinal deformity (ASD) post-surgical outcomes and that may forecast post-surgical mechanical complications. Current outcomes for ASD surgical planning and post-surgical assessment are limited to static radiographic alignment and patient-reported questionnaires. Little is known about the compensatory biomechanical strategies for stabilizing sagittal balance during functional movements in ASD patients.

Methods

We collected in-clinic motion data from 15 ASD patients and 10 controls during an unassisted sit-to-stand (STS) functional maneuver. Joint motions were measured using noninvasive 3D depth mapping sensor technology. Mathematical methods were used to attain high-fidelity joint-position tracking for biomechanical modeling. This approach provided reliable measurements for biomechanical behaviors at the spine, hip, and knee. These included peak sagittal vertical axis (SVA) over the course of the STS, as well as forces and muscular moments at various joints. We compared changes in dynamic sagittal balance (DSB) metrics between pre- and post-surgery and then separately compared pre- and post-surgical data to controls.

Results

Standard radiographic and patient-reported outcomes significantly improved following realignment surgery. From the DSB biomechanical metrics, peak SVA and biomechanical loads and muscular forces on the lower lumbar spine significantly reduced following surgery (- 19 to - 30%, all p < 0.05). In addition, as SVA improved, hip moments decreased (- 28 to - 65%, all p < 0.05) and knee moments increased (+ 7 to + 28%, p < 0.05), indicating changes in lower limb compensatory strategies. After surgery, DSB data approached values from the controls, with some post-surgical metrics becoming statistically equivalent to controls.

Conclusions

Longitudinal changes in DSB following successful multi-level spinal realignment indicate reduced forces on the lower lumbar spine along with altered lower limb dynamics matching that of controls. Inadequate improvement in DSB may indicate increased risk of post-surgical mechanical failure. These slides can be retrieved under Electronic Supplementary Material.