Biomechanical Analysis of Cervical Disc Replacement and Fusion Using Single Level, Two Level, and Hybrid Constructs.

STUDY DESIGN: A biomechanical study comparing arthroplasty with fusion using human cadaveric C2-T1 spines. OBJECTIVE: To compare the kinematics of the cervical spine after arthroplasty and fusion using single level, 2 level and hybrid constructs. SUMMARY OF BACKGROUND DATA: Previous studies have shown that spinal levels adjacent to a fusion experience increased motion and higher stress which may lead to adjacent segment disc degeneration. Cervical arthroplasty achieves similar decompression but preserves the motion at the operated level, potentially decreasing the occurrence of adjacent segment disc degeneration. METHODS: 11 specimens (C2-T1) were divided into 2 groups (BRYAN and PRESTIGE LP). The specimens were tested in the following order; intact, single level total disc replacement (TDR) at C5-C6, 2-level TDR at C5-C6-C7, fusion at C5-C6 and TDR at C6-C7 (Hybrid construct), and lastly a 2-level fusion. The intact specimens were tested up to a moment of 2.0 Nm. After each surgical intervention, the specimens were loaded until the primary motion (C2-T1) matched the motion of the respective intact state (hybrid control). RESULTS: An arthroplasty preserved motion at the implanted level and maintained normal motion at the nonoperative levels. Arthrodesis resulted in a significant decrease in motion at the fused level and an increase in motion at the unfused levels. In the hybrid construct, the TDR adjacent to fusion preserved motion at the arthroplasty level, thereby reducing the demand on the other levels. CONCLUSION: Cervical disc arthroplasty with both the BRYAN and PRESTIGE LP discs not only preserved the motion at the operated level, but also maintained the normal motion at the adjacent levels. Under simulated physiologic loading, the motion patterns of the spine with the BRYAN or PRESTIGE LP disc were very similar and were closer than fusion to the intact motion pattern. An adjacent segment disc replacement is biomechanically favorable to a fusion in the presence of a pre-existing fusion.

Biomechanical evaluation of medial patellofemoral ligament reconstruction.

BACKGROUND: The medial patellofemoral ligament (MPFL) is the most frequently injured soft tissue structure following acute lateral patellar dislocation. MPFL reconstruction has become a popular option to restore patellar stability following lateral patellar dislocation due to the high incidence of recurrent instability following conservative management. Anatomic reconstruction of the MPFL minimizes graft length changes during full knee range of motion and restores patellar stability. MATERIALS & METHODS: Four fresh frozen cadaver specimens underwent biomechanical testing in a materials testing machine. With the knee fixed in 30° of flexion, the patella was translated laterally a distance of 10 mm and continuous force-displace- ment data was collected with the intact MPFL and again following a newly described MPFL reconstruction technique. Lateral force-displacement and stiffness data were calculated, allowing comparison between the intact and reconstructed MPFL. RESULTS: The average lateral restraining force provided by the intact MPFL was 10.6 ± 5.7, 36.6 ± 2.7, and 69.0 ± 5.9 N while the lateral restraining force following MPFL reconstruction was 0.4 ± 4.3, 50.3 ± 16.3, and 110.2 ± 17.5 N at 1, 5, and 10 mm of lateral displacement, respectively. CONCLUSION: Anatomic MPFL reconstruction displays similar lateral restraining force compared to the intact MPFL at low levels of lateral displacement. At higher levels of displacement, the reconstructed MPFL provides increased lateral restraining force compared to the intact MPFL, improving patellar stability in pathologic knees.

Biomechanical analysis of the intact and destabilized sheep cervical spine.

STUDY DESIGN: An in vitro investigation of the biomechanics of the intact and destabilized sheep cervical spine. OBJECTIVE: To establish the primary and coupled behaviors of the sheep cervical spine, levels C2-C7. SUMMARY OF BACKGROUND DATA: Sheep spine models are often used as a precursor to human cadaveric and clinical trials. Several studies have focused on the sheep anatomy and functional spinal unit biomechanics. However, there has not been a comprehensive study of the multilevel sheep cervical spine. METHODS: Adult sheep cervical spines (C2-C7) were tested in flexion-extension, lateral bending, and axial rotation, using a 6-df testing apparatus. Moment-rotation curves were generated to understand the entire loading curve. Functional spinal units were tested at various levels of destabilization by sequentially removing the stabilizing structures (i.e., ligaments, facets). RESULTS: The range of motion increased with caudal progression. The average total range of motion was approximately 77°, 130°, and 64° for flexion-extension, lateral bending, and axial rotation, respectively. The neutral zone accounted for a large range of motion during flexion-extension (~63%) and lateral bending (~72%). The flexion, extension, and axial rotation motion greatly increased after the removal of the capsular ligaments and facets. The C2-C3 has the largest change in motion during the various stages of destabilization. CONCLUSION: The sheep cervical spine is extremely flexible, as seen by the large range of motion and neutral zone. The large neutral zone may account for the coupled motion between axial rotation and lateral bending. The facets and capsular ligaments provide significant stability, especially in axial rotation, flexion, and extension.

Ia-FEMesh: anatomic FE models--a check of mesh accuracy and validity.

Musculoskeletal finite element (FE) analysis is an invaluable tool in orthopaedic research. Unfortunately, the demands that accompany anatomic mesh development often limit its utility. To ease the burden of mesh development and to address the need for subject-specific analysis, we developed IA-FEMesh, a user-friendly toolkit for generating hexahedral FE models. This study compared our multiblock meshing technique to widely accepted meshing methods. Herein, the meshes under consideration consisted of the phalanx bones of the index finger. Both accuracy and validity of the models were addressed. Generating a hexahedral mesh using IA-FEMesh was found to be comparable to automated tetrahedral mesh generation in terms of preprocessing time. A convergence study suggested that the optimal number of hexahedral elements needed to mesh the distal, middle, and proximal phalanx bones were 3402, 4950, and 4550 respectively. Moreover, experimental studies were used to validate the mesh definitions. The contact areas predicted by the models compared favorably with the experimental findings (percent error < 13.2%). With the accuracy and validity of the models confirmed, accompanied by the relative ease with which the models can be generated, we believe IA-FEMesh holds the potential to contribute to multi-subject analyses, which are pertinent for clinical studies.

IA-FEMesh: an open-source, interactive, multiblock approach to anatomic finite element model development.

Finite element (FE) analysis is a valuable tool in musculoskeletal research. The demands associated with mesh development, however, often prove daunting. In an effort to facilitate anatomic FE model development we have developed an open-source software toolkit (IA-FEMesh). IA-FEMesh employs a multiblock meshing scheme aimed at hexahedral mesh generation. An emphasis has been placed on making the tools interactive, in an effort to create a user friendly environment. The goal is to provide an efficient and reliable method for model development, visualization, and mesh quality evaluation. While these tools have been developed, initially, in the context of skeletal structures they can be applied to countless applications.

Automated bony region identification using artificial neural networks: reliability and validation measurements.

OBJECTIVE: The objective was to develop tools for automating the identification of bony structures, to assess the reliability of this technique against manual raters, and to validate the resulting regions of interest against physical surface scans obtained from the same specimen. MATERIALS AND METHODS: Artificial intelligence-based algorithms have been used for image segmentation, specifically artificial neural networks (ANNs). For this study, an ANN was created and trained to identify the phalanges of the human hand. RESULTS: The relative overlap between the ANN and a manual tracer was 0.87, 0.82, and 0.76, for the proximal, middle, and distal index phalanx bones respectively. Compared with the physical surface scans, the ANN-generated surface representations differed on average by 0.35 mm, 0.29 mm, and 0.40 mm for the proximal, middle, and distal phalanges respectively. Furthermore, the ANN proved to segment the structures in less than one-tenth of the time required by a manual rater. CONCLUSIONS: The ANN has proven to be a reliable and valid means of segmenting the phalanx bones from CT images. Employing automated methods such as the ANN for segmentation, eliminates the likelihood of rater drift and inter-rater variability. Automated methods also decrease the amount of time and manual effort required to extract the data of interest, thereby making the feasibility of patient-specific modeling a reality.

Validation of phalanx bone three-dimensional surface segmentation from computed tomography images using laser scanning.

OBJECTIVE: To examine the validity of manually defined bony regions of interest from computed tomography (CT) scans. MATERIALS AND METHODS: Segmentation measurements were performed on the coronal reformatted CT images of the three phalanx bones of the index finger from five cadaveric specimens. Two smoothing algorithms (image-based and Laplacian surface-based) were evaluated to determine their ability to represent accurately the anatomic surface. The resulting surfaces were compared with laser surface scans of the corresponding cadaveric specimen. RESULTS: The average relative overlap between two tracers was 0.91 for all bones. The overall mean difference between the manual unsmoothed surface and the laser surface scan was 0.20 mm. Both image-based and Laplacian surface-based smoothing were compared; the overall mean difference for image-based smoothing was 0.21 mm and 0.20 mm for Laplacian smoothing. CONCLUSIONS: This study showed that manual segmentation of high-contrast, coronal, reformatted, CT datasets can accurately represent the true surface geometry of bones. Additionally, smoothing techniques did not significantly alter the surface representations. This validation technique should be extended to other bones, image segmentation and spatial filtering techniques.