Statistical shape model-based femur kinematics from biplane fluoroscopy.

Studying joint kinematics is of interest to improve prosthesis design and to characterize postoperative motion. State of the art techniques register bones segmented from prior computed tomography or magnetic resonance scans with X-ray fluoroscopic sequences. Elimination of the prior 3D acquisition could potentially lower costs and radiation dose. Therefore, we propose to substitute the segmented bone surface with a statistical shape model based estimate. A dedicated dynamic reconstruction and tracking algorithm was developed estimating the shape based on all frames, and pose per frame. The algorithm minimizes the difference between the projected bone contour and image edges. To increase robustness, we employ a dynamic prior, image features, and prior knowledge about bone edge appearances. This enables tracking and reconstruction from a single initial pose per sequence. We evaluated our method on the distal femur using eight biplane fluoroscopic drop-landing sequences. The proposed dynamic prior and features increased the convergence rate of the reconstruction from 71% to 91%, using a convergence limit of 3 mm. The achieved root mean square point-to-surface accuracy at the converged frames was 1.48 ± 0.41 mm. The resulting tracking precision was 1-1.5 mm, with the largest errors occurring in the rotation around the femoral shaft (about 2.5° precision).

2D-3D shape reconstruction of the distal femur from stereo X-ray imaging using statistical shape models.

Three-dimensional patient specific bone models are required in a range of medical applications, such as pre-operative surgery planning and improved guidance during surgery, modeling and simulation, and in vivo bone motion tracking. Shape reconstruction from a small number of X-ray images is desired as it lowers both the acquisition costs and the radiation dose compared to CT. We propose a method for pose estimation and shape reconstruction of 3D bone surfaces from two (or more) calibrated X-ray images using a statistical shape model (SSM). User interaction is limited to manual initialization of the mean shape. The proposed method combines a 3D distance based objective function with automatic edge selection on a Canny edge map. Landmark-edge correspondences are weighted based on the orientation difference of the projected silhouette and the corresponding image edge. The method was evaluated by rigid pose estimation of ground truth shapes as well as 3D shape estimation using a SSM of the whole femur, from stereo cadaver X-rays, in vivo biplane fluoroscopy image-pairs, and an in vivo biplane fluoroscopic sequence. Ground truth shapes for all experiments were available in the form of CT segmentations. Rigid registration of the ground truth shape to the biplane fluoroscopy achieved sub-millimeter accuracy (0.68mm) measured as root mean squared (RMS) point-to-surface (P2S) distance. The non-rigid reconstruction from the biplane fluoroscopy using the SSM also showed promising results (1.68mm RMS P2S). A feasibility study on one fluoroscopic time series illustrates the potential of the method for motion and shape estimation from fluoroscopic sequences with minimal user interaction.

Relationship of anterior knee laxity to knee translations during drop landings: a bi-plane fluoroscopy study.

PURPOSE: Passive anterior knee laxity has been linked to non-contact ACL injury risk. High deceleration movements have been implicated in the non-contact ACL injury mechanism, and evidence suggests that greater anterior tibial translations (ATT) may occur in healthy knees that are lax compared to a tight knee. The purpose of this study was to determine the relationship between anterior knee laxity scores and ATT during drop landings using biplane fluoroscopy. METHODS: Sixteen healthy adults (10 women; 6 men) performed stiff drop landings (40 cm) while being filmed using a high-speed, biplane fluoroscopy system. Initial, peak and excursions for rotations and translations were calculated and regression analysis used to determine the 6DoF kinematic relationships with KT1000 scores with peak ATT occurring during the landing. RESULTS: KT1000 values were (+) correlated with peak ATT values for group (r = 0.89; P < 0.0001) and both genders (males, r = 0.97; P = 0.0003; females, r = 0.93; P = < 0.0001). Regression analysis yielded a significant linear fit for the group (r (2) = 0.80; Y (ATT-group) = - 0.516 + 1.2 × X (KT1000-group)) and for each gender (females: r(2) = 0.86; Y (ATT-females) = 0.074 + 1.2 × X (KT1000-females) and males: r (2) = 0.94; Y (ATT-males) = - 0.79 + 1.2 × X (KT1000-males)). CONCLUSION: A strong relationship was observed between passive anterior knee laxity measured via KT1000 and peak ATT experienced during dynamic activity in otherwise healthy persons performing a stiff drop-landing motion.

Postural control during lifting.

Any voluntary motion of the body causes an internal perturbation of balance. Load transfer during manual material handling may increase these perturbations. This study investigates effects of stance condition on postural control during lifting. Nineteen healthy subjects repeatedly lifted and lowered a load between a desk and a shelf. The base of support was varied between parallel and step stance. Ground reaction force and segmental kinematics were measured. Load transfer during lifting perturbed balance. In parallel stance postural response consisted of axial movements in the sagittal plane. Such strategy was accompanied by increased posterior shear forces after lift-off. Lifting in step stance provided extended support in anterior/posterior direction. The postural control mechanisms in the sagittal plane are less complex as compared to parallel stance. However, lifting in step stance was asymmetrical and thus accompanied by distinct lateral transfer of the body. Lateral shear forces were larger as compared to parallel stance. Both lifting techniques exhibit positive and negative aspects. We cannot recommend either one as being better in terms of postural control.

Development of new protocols and analysis procedures for the assessment of LBP by surface EMG techniques.

Spectral parameters of the surface electromyographic (EMG) signal from lumbar back muscles assessed during a fatiguing isometric contraction can be used to classify different categories of low back pain (LBP) subjects and control subjects without LBP. In the test protocol currently used at the NeuroMuscular Research Center at Boston University, subjects contract their back muscles at 80% of their maximal voluntary contraction (MVC) force. This fatigue-based protocol has been successfully applied to persons with subacute or chronic LBP; those in acute pain, however, have not been included because of their inability to perform a maximal exertion. In this paper we will examine the force sensitivity of the currently used EMG parameters and also give an overview of some of our efforts to develop new test procedures. Our goal is to develop force-insensitive surface EMG parameters that can be used for classification purposes in populations of subjects who develop low trunk extension forces. In addition, the development of a model to predict MVC from anthropometrical measurements will be presented.