Karin W. Elder

High-speed, three-dimensional kinematic analysis of the normal wrist.

Carpal kinematics during a wrist flexion/extension motion using high-speed videodata acquisition was investigated. A cadaver forearm was stabilized, allowing unconstrained excursion of the wrist for passive range of motion (ROM). The extensor and flexor pairs of the wrist were looped together and a 1-lb weight was attached to each pair, simulating synergistic muscle tension. Capitate/radius and third metacarpal/radius angles were calculated to determine which measurement would be best for determining global wrist angle. The average difference in capitate/radius and third metacarpal/radius angles at each respective flexion/extension wrist angle for all wrists was 1.1 degrees +/- 1.6 degrees (the maximum difference was 4 degrees). Hence, the capitate-third metacarpal joint can be considered rigid. Capitate/lunate motion as described by capitate-radius Euler angles ranged from -16.9 to 23.5 with total capitate/lunate motion of 40.5 (35%) in the 114 degrees total global wrist ROM measured. Radius/lunate motion as described by lunate-radius angle ranged from -8.2 to 48.4 with total radius/lunate motion of 56.5 (49%) in the 114 degrees total global wrist ROM measured. During global wrist motion, the radiolunate joint contributes more motion in flexion than the capitolunate joint and the capitolunate joint contributes more motion in extension than the radiolunate joint. The instantaneous screw axes (ISAs) were calculated for each third metacarpal position with respect to the radius. The average distance difference between ISAs for the 4 wrists tested was -1.23 +/- 14.97 pixels. The maximum distance was 56.51 pixels and the minimum was -24.09 pixels. This new combination of motion analysis and 3-dimensional reconstructions of computed tomography images affords a high-speed, dynamic analysis of kinematics. It shows that during wrist flexion/extension, normal carpal kinematics does not have an ISA fixed in or limited to the capitate. In addition, the ISA data provide evidence that translational motion is a real and measurable component of normal carpal motion. These findings alter the understanding of carpal kinematics obtained from the results of previous studies which suggested that the center of rotation was fixed in the capitate.

Measurement of carpal bone geometry by computer analysis of three-dimensional CT images

The aim of this project was noninvasively to analyze and quantitate the geometry, load transfer characteristics, and spatial relationships of the carpal bones by using a new three-dimensional CT scan reconstruction technique. The determination of mechanical parameters such as distances between centroids and between bone surfaces, carpal alignment, volumes, surface areas, and contact areas can provide the basis for comparison between normal wrists and wrists with a variety of progressive instability patterns, types of fracture, pathologic and posttraumatic states, and different simulated surgical procedures. This new technology has demonstrated a volumetric accuracy of 94% and a linear accuracy of 97%. Simultaneous analysis of all articulating surfaces of multiple joints can be performed in cadavers and in patients because of the noninvasive nature of the imaging reconstruction technique. This new research offers much more information than has previously been available. It also promises direct application to the clinical setting and eliminates several limitations and questions that were inescapable with previous technology.

Location and geometric description of carpal bones in CT images

The carpal regions of ten cadaver extremities were imaged by CT. The images were combined into a 3-dimensional model of the carpus using a technique based on a dynamic programming algorithm to find an optimal estimate of the location of the bone boundaries in the CT images. The resulting set of surface points on each bone was used to compute volumes and principal and antipodal axes for the bones. A spatial coordinate system was established based on the positions of the centroids of three bones in the distal carpal row. The angular orientations of all carpal bones were determined with respect to this system. The principal axes for the same bone among ten wrist specimens proved to be more widely dispersed than the antipodal axes for the same bones. The antipodal axes also correspond more closely to an intuitive notion of the “longest axis” of the bones. We conclude that the antipodal axis is a more reliable and useful measure of bone orientation than the principal axis.

Building solid models from serial contour images

To create solid models of irregularly shaped objects, a mesh of curves consisting of two orthogonal sets of planar contours that define both transverse and longitudinal cross sections is usually required. By interpolating the in-slice contour-point list one can fairly easily obtain one set of such planar contours, but the question arises of how to produce the other orthogonal set of contours. In the approach reported here, the object contour data in slice images are first processed by an optimal triangulation algorithm of a surface modeler, and the output triangles are used as the initial guess of possible inter-slice point matches. Local contour features are computed and the prominent points of each 2D contour line are identified and classified (e.g. local curvature maxima or inflections). This information will guide our optimal vertical path search algorithm, and in the searching process the dominant points are given priorities for possible connections. This approach aims at retaining structures with rotational displacement, which are commonly seen in bone anatomy. A 2D bicubic spline interpolation is then employed to produce an isotropic mesh of curves. From the mesh of curves so obtained, an isotropic three dimensional (3D) bone object is created by an automatic filling and labeling algorithm developed by the author to permit volume rendering. Initial results of the visualization of bone solid models have been encouraging using AVS (Advanced Visual Systems Inc., Waltham, MA) as well as our own GUI. The results also showed advantages of our system over surface modeling techniques when used to visualize certain geometrical properties with fine resolution, such as proximity map, and to make more accurate volume and distance measurements.

Computer simulation of arm and leg kinematic structures

To obtain a visual and quantitative verification of the appropriateness of 1-, 2- and 3-degree-of-freedom (DOF) models for motion, we have developed an interactive system for the independent adjustment and definition of multiple-DOF linkage systems representative of human leg and arm motion. Once the kinematic structure is defined, control points for interactive definition of tendon and muscle parameters may also be defined and adjusted, leading the way to interactive musculoskeletal modeling and simulation. All kinematic transformation nodes are built as linkages within an OpenGL hierarchical structure. The structure for the independent adjustment of each axis of motion required tracking the inverse of all transformations applied to the axis during visualization and adjustment. The inverse is applied to all structures in the hierarchy below the axis of interest so that only the axis is affected during 3D adjustment. The result is a kinematic structure definition program with which the user interactively builds the kinematic model. The program has the capacity for unlimited rotational DOFs. The system allows for the visual adjustment and verification of the placement of axes. This interactive task is carried out through control of the observer viewpoint and the position and orientation of the view and of each axis. These dynamic commands are carried out simultaneously with rotational control of distal joint segments about their defined axes. With such flexibility, the user is able to rapidly iterate upon appropriate axis placement based on a 3D visual verification of joint congruence throughout the joint range of motion.

Kinematic Geometry of the Wrist: Preliminary Report

This research significantly advances the state of the art in our ability to visualize the dynamic kinematics of the wrist. Beginning 150 years ago, investigations into the kinematics of the wrist were anatomical descriptions5,6,8,10,20,21 with observations made by the eye and including the earliest use of the x-ray after its discovery in 1895. It was not until much later that McConail12 began to apply basic mechanical laws to the curiosities and movement of the wrist and its complex of eight carpal bones. Motion studies began with cineradiography1,26 and moved parallel with technological development of optical and electronic methods of measuring minute distances accurately while the joint is moving. Use of LED path generation on photographic plates was used in conjunction with both cineradiographic and cinematographic (movie film)26 methods in an attempt to improve and automate the laborious and error prone requirement of hand digitizing data. With the introduction of the spark gap, or sonic digitizer, 3-D positional data could be taken automatically from moving joint components.3,4,27 Experimental error associated with the sonic digitizing equipment, its dependency on acoustic related environmental conditions (temperature, humidity, air movement) and the physical size of the spark gap apparatus itself still left much to be desired. Because of these concerns, recent investigators have attempted to return to basic approaches (manual analysis of biplanar radiographs) to increase precision even at the expense of fewer data points and increase in digitization error.7,9,14