Ischiofemoral impingement: the evolutionary cost of pelvic obstetric adaptation.

The risk for ischiofemoral impingement has been mainly related to a reduced ischiofemoral distance and morphological variance of the femur. From an evolutionary perspective, however, there are strong arguments that the condition may also be related to sexual dimorphism of the pelvis. We, therefore, investigated the impact of gender-specific differences in anatomy of the ischiofemoral space on the ischiofemoral clearance, during static and dynamic conditions. A random sampling Monte-Carlo experiment was performed to investigate ischiofemoral clearance during stance and gait in a large (n = 40 000) virtual study population, while using gender-specific kinematics. Subsequently, a validated gender-specific geometric morphometric analysis of the hip was performed and correlations between overall hip morphology (statistical shape analysis) and standard discrete measures (conventional metric approach) with the ischiofemoral distance were evaluated. The available ischiofemoral space is indeed highly sexually dimorphic and related primarily to differences in the pelvic anatomy. The mean ischiofemoral distance was 22.2 ± 4.3 mm in the females and 29.1 ± 4.1 mm in the males and this difference was statistically significant (P < 0.001). Additionally, the ischiofemoral distance was observed to be a dynamic measure, and smallest during femoral extension, and this in turn explains the clinical sign of pain in extension during long stride walking. In conclusion, the presence of a reduced ischiofemroal distance and related risk to develop a clinical syndrome of ischiofemoral impingement is strongly dominated by evolutionary effects in sexual dimorphism of the pelvis. This should be considered when female patients present with posterior thigh/buttock pain, particularly if worsened by extension. Controlled laboratory study.

4D in vivo quantification of ankle joint space width using dynamic MRI.

Spatio-temporal evolution of joint space width (JSW) during motion is of great importance to help with making early treatment plans for degenerative joint diseases like osteoarthritis (OA). These diseases can affect people of all ages leading to an acceleration of joint degeneration and to limitations in the activities of daily living. However, only a few studies have attempted to quantify the JSW from moving joints. In this paper, we present a generic pipeline to accurately determine the changes of the JSW during the joint motion cycle. The key idea is to combine spatial information of static MRI with temporal information of low-resolution (LR) dynamic MRI sequences via an intensity-based registration framework, leading to a high-resolution (HR) temporal reconstruction of the joint. This allows the temporal JSW to be measured in the HR domain using an Eulerian approach for solving partial differential equations (PDEs) inside a deforming inter-bone area where the HR reconstructed bone segmentations are considered as temporal Dirichlet boundaries. The proposed approach has been applied and evaluated on in vivo MRI data of five healthy children to non-invasively quantify the spatio-temporal evolution of the JSW of the ankle (tibiotalar joint) during the entire dorsi-plantar flexion motion cycle. Promising results were obtained, showing that this pipeline can be useful to perform large-scale studies containing subjects with OA for different joints like ankle and knee.

Temporal resolution enhancement of dynamic MRI sequences within a motion-based framework.

Dynamic MRI has made it possible to non-invasively capture the moving human joints in vivo. Real-time Fast Field Echo (FFE) sequences have the potential to reduce the effect of motion artifacts by acquiring the image data within a few milliseconds. However, the short acquisition times affect the temporal resolution of the acquired sequences. In this paper, we propose a post-processing technique to reconstruct the missing frames of the sequence given the reduced amount of acquired data, which leads to recover the entire joint trajectory outside the MR scanner. To do this, we generalize the Log-Euclidean polyrigid registration framework to deal with dynamic three-dimensional articulated structures by adding the time as fourth dimension : we first estimate the rigid motion of each bone from the acquired data using linear intensity-based registration. Then, we fuse these local transformations to compute the non-linear joint deformations between successive images using a spatio-temporal log-euclidean polyrigid framework. The idea is to reconstruct the missing time frames by interpolating the realistic joint deformation fields in the domain of matrix logarithms assuming the motion to be consistent over a short period of time. The algorithm has been applied and validated using dynamic data from five children performing passive ankle dorsi-plantar flexion.

Interactive patient-specific 3D approximation of scapula bone shape from 2D X-ray images using landmark-constrained statistical shape model fitting.

We report on an interactive tool for patientspecific 3D approximation of scapula bone shape from 2D X-ray images using landmark-constrained statistical shape model (SSM) fitting. The 3D localization of points on the 2D X-ray images was done through X-ray stereophotogrammetry. The inferior angle, acromion and the coracoid process were identified as reliable landmarks from the anteroposterior (AP) and oblique lateral views in a landmark selection study. The 3D scapula surface was approximated through fitting the scapula SSM to the 3D reconstructed coordinates of the selected landmarks. 3D point localization yielded average (X, Y, Z) coordinate reconstruction errors of (X=0.14, Y=0.07, Z=0.04) mm. The landmark-constrained fitting algorithm yielded an average error between the mean posterior model landmarks and the corresponding target landmarks of 0.49 mm using the three landmarks, and later 0.19 mm with sixteen landmarks. Average surface to surface error between the CT ground truth model and approximated model from within the dataset improved from 3.20 mm to 2.46 mm using three landmarks and using sixteen landmarks, respectively. Average surface to surface error between the CT ground truth model and the approximated model from outside the dataset improved from 4.28 mm to 3.20 mm using three landmarks and using sixteen landmarks, respectively.

In vivo patellofemoral contact mechanics during active extension using a novel dynamic MRI-based methodology.

OBJECTIVES: To establish an in vivo, normative patellofemoral (PF) cartilage contact mechanics database acquired during voluntary muscle control using a novel, dynamic, magnetic resonance (MR) imaging-based, computational methodology and validate the contact mechanics sensitivity to the known sub-millimeter methodological accuracies. DESIGN: Dynamic cine phase-contrast and multi-plane cine (MPC) images were acquired while female subjects (n = 20, sample of convenience) performed an open kinetic chain (knee flexion-extension) exercise inside a 3-T MR scanner. Static cartilage models were created from high resolution three-dimensional static MR data and accurately placed in their dynamic pose at each time frame based on the cine-PC (CPC) data. Cartilage contact parameters were calculated based on the surface overlap. Statistical analysis was performed using paired t-test and a one-sample repeated measures ANOVA. The sensitivity of the contact parameters to the known errors in the PF kinematics was determined. RESULTS: Peak mean PF contact area was 228.7 ± 173.6 mm(2) at 40° knee angle. During extension, contact centroid and peak strain locations tracked medially on the femoral and patellar cartilage and were not significantly different from each other. At 25°, 30°, 35°, and 40° of knee extension, contact area was significantly different. Contact area and centroid locations were insensitive to rotational and translational perturbations. CONCLUSION: This study is a first step towards unfolding the biomechanical pathways to anterior PF pain and osteoarthritis (OA) using dynamic, in vivo, and accurate methodologies. The database provides crucial data for future studies and for validation of, or as an input to, computational models.