The mechanical behavior of soft connective tissue is governed by a dense network of fibrillar proteins in the extracellular matrix. Characterization of this fibrous network requires the accurate extraction of descriptive structural parameters from imaging data, including fiber dispersion and mean fiber orientation. Common methods to quantify fiber parameters include fast Fourier transforms (FFT) and structure tensors, however, information is limited on the accuracy of these methods. In this study, we compared these two methods using test images of fiber networks with varying topology. The FFT method with a band-pass filter was the most accurate, with an error of 0.71 ± 0.43 degrees in measuring mean fiber orientation and an error of 7.4 ± 3.0% in measuring fiber dispersion in the test images. The accuracy of the structure tensor method was approximately 4 times worse than the FFT band-pass method when measuring fiber dispersion. A free software application, FiberFit, was then developed that utilizes an FFT band-pass filter to fit fiber orientations to a semicircular von Mises distribution. FiberFit was used to measure collagen fibril organization in confocal images of bovine ligament at magnifications of 63x and 20x. Grayscale conversion prior to FFT analysis gave the most accurate results, with errors of 3.3 ± 3.1 degrees for mean fiber orientation and 13.3 ± 8.2% for fiber dispersion when measuring confocal images at 63x. By developing and validating a software application that facilitates the automated analysis of fiber organization, this study can help advance a mechanistic understanding of collagen networks and help clarify the mechanobiology of soft tissue remodeling and repair.

No abstract

Novel PEM-enhancement of a FDL tendon transfer procedure holds promise as a method for improved treatment of AAFD. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.

Ligament mechanical behavior is primarily regulated by fibrous networks of type I collagen. Although these fibrous networks are typically highly aligned, healthy and injured ligament can also exhibit disorganized collagen architecture. The objective of this study was to determine whether variations in the collagen fibril network between neighboring ligaments can predict observed differences in mechanical behavior. Ligament specimens from two regions of bovine fetlock joints, which either exhibited highly aligned or disorganized collagen fibril networks, were mechanically tested in uniaxial tension. Confocal microscopy and FiberFit software were used to quantify the collagen fibril dispersion and mean fibril orientation in the mechanically tested specimens. These two structural parameters served as inputs into an established hyperelastic constitutive model that accounts for a continuous distribution of planar fibril orientations. The ability of the model to predict differences in the mechanical behavior between neighboring ligaments was tested by (1) curve fitting the model parameters to the stress response of the ligament with highly aligned fibrils and then (2) using this model to predict the stress response of the ligament with disorganized fibrils by only changing the parameter values for fibril dispersion and mean fibril orientation. This study found that when using parameter values for fibril dispersion and mean fibril orientation based on confocal imaging data, the model strongly predicted the average stress response of ligaments with disorganized fibrils ([Formula: see text]); however, the model only successfully predicted the individual stress response of ligaments with disorganized fibrils in half the specimens tested. Model predictions became worse when parameters for fibril dispersion and mean fibril orientation were not based on confocal imaging data. These findings emphasize the importance of collagen fibril alignment in ligament mechanics and help advance a mechanistic understanding of fibrillar networks in healthy and injured ligament.

Background: Malaligned ankle arthroplasty components have been associated with increased postoperative pain and reduced ankle range of motion. With this study, we aimed to quantify how anterior and posterior malalignment of the talar component affects foot bone kinematics and plantar pressures in a dynamic, cadaveric gait simulation. Methods: Ten cadaveric foot specimens received a modified ankle prosthesis. Proper alignment was defined as the prosthesis being neutral to a plantigrade foot, where varus/valgus and internal/external rotation were determined using the tibial alignment guide from the prosthesis manufacturer. Axially loaded lateral radiographs were made to measure the tibiotalar ratio (TTR) preoperatively and postoperatively. Specimens were prepared for gait simulation and mounted into the robotic gait simulator. Foot bone kinematics and plantar pressures were measured for each alignment condition. Results: Posterior malalignment of the talar component decreased mean sagittal-plane range of motion (p ≤ 0.0005) in the tibiotalar joint (by up to 3.9°) and in the first metatarsophalangeal joint (by up to 7.7°) and increased sagittal-plane range of motion (p ≤ 0.0005) in the calcaneocuboid joint (by up to 2.0°). Posterior malalignment increased mean transverse-plane range of motion (p ≤ 0.0005 and p = 0.012) in the tibiotalar joint (by up to 2.3°) and in the calcaneocuboid joint (by 2.3°). Posterior malalignment decreased mean peak plantar pressures (p = 0.001 and p = 0.013) under the hallux and the first metatarsal (by up to 82.1 and 110.1 kPa, respectively) and increased (p = 0.012 and p = 0.0006) peak plantar pressures under the third metatarsal and the hindfoot (by 23.0 and 47.8 kPa, respectively). Anterior malalignment decreased (p = 0.0006) mean hindfoot peak plantar pressure (by 127.7 kPa). Anterior and posterior malalignments shifted center of pressure laterally during early and late stance. The TTR weakly to moderately correlated with range-of-motion changes in the tibiotalar, calcaneocuboid, and first metatarsophalangeal joints (r2 ≤ 0.39) and weakly correlated with plantar pressure changes under the hindfoot, the first metatarsal, and the hallux (r2 ≤ 0.15). Conclusions: Anterior and posterior malalignments of the talar component altered foot bone kinematics and plantar pressures. Mild malalignments produced fewer significant differences than moderate and extreme malalignments. A greater number of significant differences were found for posterior malalignments than for anterior. The TTR weakly to moderately correlated with changes in range of motion and plantar pressures. Clinical Relevance: The observed changes in range of motion and plantar pressures may explain why malaligned ankle arthroplasties are associated with unfavorable clinical outcomes and poor prosthesis longevity. Posterior malalignments may produce worse clinical outcomes than anterior malalignments.