The accuracy of statistical shape models in predicting bone shape: A systematic review

Adaptive Image Segmentation Reveals Substantial Cortical Bone Remodeling During Early Fracture Repair

The goal of this study was to develop an image analysis algorithm for quantifying the effects of remodeling on cortical bone during early fracture healing. An adaptive thresholding technique with boundary curvature and tortuosity control was developed to automatically identify the endocortical and pericortical boundaries in the presence of high-gradient bone mineral density (BMD) near the healing zone. The algorithm successfully segmented more than 47,000 microCT images from 12 healing ovine osteotomies and intact contralateral tibiae. Resampling techniques were used to achieve data dimensionality reduction on the segmented images, allowing characterization of radial and axial distributions of cortical BMD. Local (transverse slice) and total (whole bone) remodeling scores were produced. These surrogate measures of cortical remodeling derived from BMD revealed that cortical changes were detectable throughout the region covered by callus and that the localized loss of cortical BMD was highest near the osteotomy. Total remodeling score was moderately and significantly correlated with callus volume and mineral composition (r > 0.64, p < 0.05), suggesting that the cortex may be a source of mineral needed to build callus.

Instantaneous Generation of Subject-Specific Finite Element Models of the Hip Capsule

Subject-specific hip capsule models could offer insights into impingement and dislocation risk when coupled with computer-aided surgery, but model calibration is time-consuming using traditional techniques. This study developed a framework for instantaneously generating subject-specific finite element (FE) capsule representations from regression models trained with a probabilistic approach. A validated FE model of the implanted hip capsule was evaluated probabilistically to generate a training dataset relating capsule geometry and material properties to hip laxity. Multivariate regression models were trained using 90% of trials to predict capsule properties based on hip laxity and attachment site information. The regression models were validated using the remaining 10% of the training set by comparing differences in hip laxity between the original trials and the regression-derived capsules. Root mean square errors (RMSEs) in laxity predictions ranged from 1.8° to 2.3°, depending on the type of laxity used in the training set. The RMSE, when predicting the laxity measured from five cadaveric specimens with total hip arthroplasty, was 4.5°. Model generation time was reduced from days to milliseconds. The results demonstrated the potential of regression-based training to instantaneously generate subject-specific FE models and have implications for integrating subject-specific capsule models into surgical planning software.

Regional plantar forces and surface geometry variations of a chronic ankle instability population described by statistical shape modelling

BACKGROUND

Understanding detailed foot morphology as well as regional plantar forces could provide insight into foot function and provide recommendation for footwear design for chronic ankle instability (CAI) people.

RESEARCH QUESTION

This study presented 3-dimensional statistical shape models of feet from three different populations including CAI, copers and healthy individuals, with regional plantar forces also acquired.

METHODS

Sixty-six males (22 participants per group) were included in this study to capture 3-dimensional foot shapes under a standing condition and regional plantar forces during a cutting maneuver. Principal component analysis was performed to generate a mean foot shape of each group as well as modes of variations. A generalized procrustes analysis was used to achieve rapid registration of mean shapes. Besides, regional plantar forces and contact duration among these three populations were compared.

RESULTS

For 3-dimensional foot shapes, although no significant differences of the average distance between each mode and mean shape were found among three populations, there were subtle variations in mean shapes. The CAI population presented a more bulging of the lateral malleolus; copers were characterized by the flexion of the lesser toes, a more bulging of the medial foot in the sagittal plane; and healthy individuals showed a greater heel width and a more bulging of the heel in the sagittal plane. In terms of plantar forces, healthy individuals had significantly greater summated plantar forces and greater plantar forces in the lateral heel area during the early contact phase compared to copers and CAI participants.

SIGNIFICANCE

Overall, this study suggested that repetitive ankle sprains may lead to the bulging of the lateral malleolus. Further, CAI and copers seem to stabilize the ankle joint by medially shifting the center of pressure compared to healthy individuals under the static and less challenging dynamic conditions.

3D shape reconstruction of the femur from planar X-ray images using statistical shape and appearance models

Major trauma is a condition that can result in severe bone damage. Customised orthopaedic reconstruction allows for limb salvage surgery and helps to restore joint alignment. For the best possible outcome three dimensional (3D) medical imaging is necessary, but its availability and access, especially in developing countries, can be challenging. In this study, 3D bone shapes of the femur reconstructed from planar radiographs representing bone defects were evaluated for use in orthopaedic surgery. Statistical shape and appearance models generated from 40 cadaveric X-ray computed tomography (CT) images were used to reconstruct 3D bone shapes. The reconstruction simulated bone defects of between 0% and 50% of the whole bone, and the prediction accuracy using anterior-posterior (AP) and anterior-posterior/medial-lateral (AP/ML) X-rays were compared. As error metrics for the comparison, measures evaluating the distance between contour lines of the projections as well as a measure comparing similarities in image intensities were used. The results were evaluated using the root-mean-square distance for surface error as well as differences in commonly used anatomical measures, including bow, femoral neck, diaphyseal-condylar and version angles between reconstructed surfaces from the shape model and the intact shape reconstructed from the CT image. The reconstructions had average surface errors between 1.59 and 3.59 mm with reconstructions using the contour error metric from the AP/ML directions being the most accurate. Predictions of bow and femoral neck angles were well below the clinical threshold accuracy of 3°, diaphyseal-condylar angles were around the threshold of 3° and only version angle predictions of between 5.3° and 9.3° were above the clinical threshold, but below the range reported in clinical practice using computer navigation (i.e., 17° internal to 15° external rotation). This study shows that the reconstructions from partly available planar images using statistical shape and appearance models had an accuracy which would support their potential use in orthopaedic reconstruction.