Individualized prediction of pedicle screw fixation strength with a finite element model

Finite element analysis of different pedicle screw internal fixations for first lumbar vertebral fracture in different sports conditions

OBJECTIVE

Lumbar fractures are the most common spinal injuries, and surgery is required for severe fracture. This study aimed to investigate the variations in motion and stress in varying states of activity after minimally invasive and traditional open pedicle screw placement for L1 vertebral fracture stabilization.

METHODS

We studied a male volunteer (26 years old) with no history of chronic back pain or lumbar spine trauma. We used the finite element method for this investigation. Using finite element software, we created a three-dimensional model of L1 vertebral compression fracture. We also constructed models for four percutaneous pedicle screws spanning the fractured vertebra and four screws traversing the damaged vertebra with transverse fixation.

RESULTS

In all three-dimensional movement directions, the open pedicle fixation system experienced maximum stress higher than its percutaneous counterpart. With axial spinal rotation, von Mises stress on the traditional open pedicle screw was considerably lower than that with percutaneous pedicle fixation, but peak stress was elevated at the transverse connection. Traditional open pedicle fixation displayed less maximum displacement than percutaneous pedicle internal fixation.

CONCLUSIONS

During axial spinal movements, high peak stress is observed at the transverse connection. Patients should avoid excessive axial rotation of the spine during recovery.

Bone density optimized pedicle screw insertion

Background: Spinal fusion is the most common surgical treatment for the management of degenerative spinal disease. However, complications such as screw loosening lead to painful pseudoarthrosis, and are a common reason for revision. Optimization of screw trajectories to increase implant resistance to mechanical loading is essential. A recent optimization method has shown potential for determining optimal screw position and size based on areas of high bone elastic modulus (E-modulus). Aim: The aim of this biomechanical study was to verify the optimization algorithm for pedicle screw placement in a cadaveric study and to quantify the effect of optimization. The pull-out strength of pedicle screws with an optimized trajectory was compared to that of a traditional trajectory. Methods: Twenty-five lumbar vertebrae were instrumented with pedicle screws (on one side, the pedicle screws were inserted in the traditional way, on the other side, the screws were inserted using an optimized trajectory). Results: An improvement in pull-out strength and pull-out strain energy of the optimized screw trajectory compared to the traditional screw trajectory was only observed for E-modulus values greater than 3500 MPa cm3. For values of 3500 MPa cm3 or less, optimization showed no clear benefit. The median screw length of the optimized pedicle screws was significantly smaller than the median screw length of the traditionally inserted pedicle screws, p < 0.001. Discussion: Optimization of the pedicle screw trajectory is feasible, but seems to apply only to vertebrae with very high E-modulus values. This is likely because screw trajectory optimization resulted in a reduction in screw length and therefore a reduction in the implant-bone interface. Future efforts to predict the optimal pedicle screw trajectory should include screw length as a critical component of potential stability.

Finite element analysis of minimally invasive nail placement and traditional nail placement in the treatment of lumbar 1 vertebral compression fracture

Using the finite element analysis method to help us better understand the biomechanical changes of the spine after surgery and the changes in the stress distribution around the screw implantation area. The finite element model of L1 vertebral compression fracture was constructed by using a large number of finite element programs. On the fracture model, 2 kinds of internal fixation devices are set up, namely: the first type of 4 screws across the injured vertebra through the adjacent upper and lower vertebrae + transverse connector; the second type of 4 screws crosses the injured vertebra through the adjacent upper and lower vertebrae + non-transverse connector. To study the distribution of the maximum displacement and von Mises stress of the intramedullary pedicle screws and rods of the 2 types of internal fixation devices after implantation in the spine under certain loading conditions. In traditional open pedicle screw fixation, the maximum stress in the pedicle screw fixation system in the direction of 3D movement is higher than in percutaneous pedicle screw fixation. There is no significant difference in the Von Mises stress of the pedicle screw between the 2 procedures when the spine performs flexion-extension and lateral flexion activities. When the spine is rotating axially, the Von Mises stress of the pedicle screw in conventional open surgery is significantly less than that of the screw in percutaneous pedicle screw fixation. Traditional open internal fixation produces stress peaks of 891.7 MPa and 886.34 MPa at the transverse joint during axial rotation. Only when the spine is rotating in the axial direction, the maximum displacement of traditional open pedicle screw fixation is smaller than that of percutaneous pedicle screw fixation. There is no significant difference in the maximum displacement between the 2 procedures when the spine is moving in other directions. Traditional open pedicle screw fixation can strengthen the stability of the spine in the direction of axial rotation, and can also be greater to reduce the maximum stress of the pedicle screw axial rotation, so the clinical treatment of unstable fractures of the thoracolumbar spine instability is of great significance.

Development and validation of an automated planning tool for navigated lumbosacral pedicle screws using a convolutional neural network

BACKGROUND CONTEXT

Navigation and robotic systems have been increasingly applied to spinal instrumentation but dedicated screw planning is a time-consuming prerequisite to tap the full potential of these techniques.

PURPOSE

To develop and validate an automated planning tool for lumbosacral pedicle screw placement using a convolutional neural network (CNN) to facilitate the planning process.

STUDY DESIGN/SETTING

Retrospective analysis and processing of CT and screw planning data randomly selected from a consecutive registry of CT-navigated instrumentations from a single academic institution.

PATIENT SAMPLE

Data from 179 cases was processed for CNN training and validation (155 for training, 24 for validation) leveraging a total of 1182 screws (1052 for training, 130 for validation).

OUTCOME MEASURES

Quantitative and qualitative (Gertzbein-Robbins classification [GR]) validation via comparison of automatically and manually planned reference screws, inter-rater and intra-rater variability.

METHODS

Annotated data from CT-navigated instrumentation was used to train a CNN operating in a vertebra instance-based approach employing a state-of-the-art U-Net framework. Internal five-fold cross-validation and external validation on an independent cohort not previously involved in training was performed. Quantitative validation of automatically planned screws was performed in comparison to corresponding manually planned screws by calculating the minimal absolute difference (MAD) of screw head and tip points, length and diameter, screw direction and Dice coefficient. Results were evaluated in relation to inter-rater and intra-rater variability of manual screw planning.

RESULTS

Automated screw planning was successful in all targeted 130 screws. Compared with manually planned screws as a reference, mean MAD of automatically planned screws was 4.61±2.27 mm for screw head, 3.96±2.19 mm for tip points and 5.51±3.64° for screw direction. These differences were either statistically comparable or significantly smaller when compared with interrater variability of manual screw planning (p>.99 for head point and direction, p=.004 for tip point, respectively). Mean Dice coefficient of 0.61±0.16 indicated significantly greater agreement of automatic screws with the manual reference compared with interrater agreement (Dice 0.56±0.18, p<.001). Automatically planned screws were marginally shorter (MAD 3.4±3.2 mm) and thinner (MAD mean 0.3±0.6 mm) compared with the manual reference, but with statistical significance (p<.0001, respectively). Automatically planned screws were GR grade A in 96.2% in qualitative validation. Planning time was significantly shorter with the automatic approach (0:41 min vs. 6:41 min, p<.0001).

CONCLUSIONS

We derived and validated a fully automated planning tool for lumbosacral pedicle screws using a CNN. Our validation showed noninferiority to manual screw planning and provided sufficient accuracy to facilitate and expedite the screw planning process. These results offer a high potential to improve workflows in spine surgery when integrated into navigation or robotic assistance systems.

Location of pedicle screw hold in relation to bone quality and loads

Introduction: Sufficient screw hold is an indispensable requirement for successful spinal fusion, but pedicle screw loosening is a highly prevalent burden. The aim of this study was to quantify the contribution of the pedicle and corpus region in relation to bone quality and loading amplitude of pedicle screws with traditional trajectories.

Methods: After CT examination to classify bone quality, 14 pedicle screws were inserted into seven L5. Subsequently, Micro-CT images were acquired to analyze the screw’s location and the vertebrae were split in the midsagittal plane and horizontally along the screw’s axis to allow imprint tests with 6 mm long sections of the pedicle screws in a caudal direction perpendicular to the screw’s surface. Force-displacement curves in combination with the micro-CT data were used to reconstruct the resistance of the pedicle and corpus region at different loading amplitudes.

Results: Bone quality was classified as normal in three specimens, as moderate in two and as bad in two specimens, resulting in six, four, and four pedicle screws per group. The screw length in the pedicle region in relation to the inserted screw length was measured at an average of 63%, 62%, and 52% for the three groups, respectively. At a calculated 100 N axial load acting on the whole pedicle screw, the pedicle region contributed an average of 55%, 58%, and 58% resistance for the normal, moderate, and bad bone quality specimens, respectively. With 500 N load, these values were measured at 59%, 63%, and 73% and with 1000 N load, they were quantified at 71%, 75%, and 81%.

Conclusion: At lower loading amplitudes, the contribution of the pedicle and corpus region on pedicle screw hold are largely balanced and independent of bone quality. With increasing loading amplitudes, the contribution of the pedicle region increases disproportionally, and this increase is even more pronounced in situations with reduced bone quality. These results demonstrate the importance of the pedicle region for screw hold, especially for reduced bone quality.

CT-Navigated Spinal Instrumentations-Three-Dimensional Evaluation of Screw Placement Accuracy in Relation to a Screw Trajectory Plan

Background and Objectives: In the literature, spinal navigation and robot-assisted surgery improved screw placement accuracy, but the majority of studies only qualitatively report on screw positioning within the vertebra. We sought to evaluate screw placement accuracy in relation to a preoperative trajectory plan by three-dimensional quantification to elucidate technical benefits of navigation for lumbar pedicle screws. Materials and Methods: In 27 CT-navigated instrumentations for degenerative disease, a dedicated intraoperative 3D-trajectory plan was created for all screws. Final screw positions were defined on postoperative CT. Trajectory plans and final screw positions were co-registered and quantitatively compared computing minimal absolute differences (MAD) of screw head and tip points (mm) and screw axis (degree) in 3D-space, respectively. Differences were evaluated with consideration of the navigation target registration error. Clinical acceptability of screws was evaluated using the Gertzbein−Robbins (GR) classification. Results: Data included 140 screws covering levels L1-S1. While screw placement was clinically acceptable in all cases (GR grade A and B in 112 (80%) and 28 (20%) cases, respectively), implanted screws showed considerable deviation compared to the trajectory plan: Mean axis deviation was 6.3° ± 3.6°, screw head and tip points showed mean MAD of 5.2 ± 2.4 mm and 5.5 ± 2.7 mm, respectively. Deviations significantly exceeded the mean navigation registration error of 0.87 ± 0.22 mm (p < 0.001). Conclusions: Screw placement was clinically acceptable in all screws after navigated placement but nevertheless, considerable deviation in implanted screws was noted compared to the initial trajectory plan. Our data provides a 3D-quantitative benchmark for screw accuracy achievable by CT-navigation in routine spine surgery and suggests a framework for objective comparison of screw outcome after navigated or robot-assisted procedures. Factors contributing to screw deviations should be considered to assure optimal surgical results when applying navigation for spinal instrumentation.

THE FIXATION EFFECT OF DIFFERENT TYPES OF SCREWS IN THE WHOLE OSTEOPOROTIC LUMBAR VERTEBRAE: AN FEA STUDY

Purpose: The aim of this study is to explore how pedicle screws (PSs) and cortical bone trajectory (CBT) screws differ in fixation strength when implanted in L1–L5 with osteoporosis, providing support for choosing implants and trajectories in spine internal fixation surgeries. Methods: We filtered 30 lumbar segments out from CT images of eight osteoporotic participants and simulated PS or CBT screw implantation in each segment, generating 60 vertebra-screw assembly FE models. To evaluate the fixation effect, we performed a pull-out force test simulation in each model and analyzed the maximal pull-out force, pull-out stiffness, and equivalent stress of vertebrae and screws. Results: The maximal pull-out force of PS and CBT screws in L1–L5 was in the range of 905–1552 (N) and 587–1012 (N), while the pull-out stiffness was in the range of 1990–2617 (N/mm) and 1007–1681 (N/mm). The fixation strength of PS in L4 and L5 was higher ([Formula: see text]), while in L1–L3 PS and CBT screws are similar ([Formula: see text]). The maximal stress of vertebrae and screws when PS was pulled at 0.25[Formula: see text]mm was larger than that of CBT screws. Conclusions: For patients with moderate osteoporosis, it is recommended to insert PS into L4 and L5 to attain better fixation strength, but vertebrae are more prone to fracture. Consequently, under severe osteoporosis, the implantation of CBT screws should be considered first. Bone cement injection may be necessary to consolidate the screw-vertebrae interface with osteoporosis.

Computational model predicts risk of spinal screw loosening in patients

PURPOSE

Pedicle screw loosening is a frequent complication in lumbar spine fixation, most commonly among patients with poor bone quality. Determining patients at high risk for insufficient implant stability would allow clinicians to adapt the treatment accordingly. The aim of this study was to develop a computational model for quantitative and reliable assessment of the risk of screw loosening.

METHODS

A cohort of patient vertebrae with diagnosed screw loosening was juxtaposed to a control group with stable fusion. Imaging data from the two cohorts were used to generate patient-specific biomechanical models of lumbar instrumented vertebral bodies. Single-level finite element models loading the screw in axial or caudo-cranial direction were generated. Further, multi-level models incorporating individualized joint loading were created.

RESULTS

The simulation results indicate that there is no association between screw pull-out strength and the manifestation of implant loosening (p = 0.8). For patient models incorporating multiple instrumented vertebrae, CT-values and stress in the bone were significantly different between loose screws and non-loose screws (p = 0.017 and p = 0.029, for CT-values and stress, respectively). However, very high distinction (p = 0.001) and predictability (R²_Pseudo = 0.358, AUC = 0.85) were achieved when considering the relationship between local bone strength and the predicted stress (loading factor). Screws surrounded by bone with a loading factor higher than 25% were likely to be loose, while the chances of screw loosening were close to 0 with a loading factor below 15%.

CONCLUSION

The use of a biomechanics-based score for risk assessment of implant fixation failure might represent a paradigm shift in addressing screw loosening after spondylodesis surgery.

Influence of bone quality and pedicle screw design on the fixation strength during Axial Pull-out test: A 2D Axisymmetric FE study

Pedicle screw fixations are widely used to provide support and improve stability for the treatment of spinal pathologies. The effectiveness of treatment depends on the anchorage strength between the screw and bone. In this study, the influence of pedicle screw half-angle and bone quality on the displacement of fixation and stress transfer are analyzed using a 2D axisymmetric finite element model. The pedicle screw proximal half-angle is varied between 0° and 60° in steps of 10°, along with two different distal half-angles of 30° and 40°. Three bone models are considered for cancellous bone to simulate various degrees of bone quality, namely, poor, moderate and good. The mechanical properties of cortical bone are kept constant throughout the study. The material properties and boundary conditions are applied based on previous studies. Frictional contact is considered between the bone and screw. Results show that, the displacement of fixation is observed to be minimum at a proximal half angle of 0° and maximum at an angle of 60°, independent of bone quality. The highest implant displacement is observed in case of poor bone quality. All the bone model showed similar patterns of stress distribution, with high stress concentration around the first few threads. The highest peak von Mises stress is obtained at a proximal half-angle of 60°. Furthermore, the stress transfer increased with increase in proximal half-angle and bone quality, with maximum stress transfer at a proximal half-angle of 60°. It appears that, this study might aid to improve the design of pedicle screw for treatment of degenerative spinal diseases.Clinical Relevance- This study analyses the impact of bone quality on pedicle screw design.

Bone density optimized pedicle screw instrumentation improves screw pull-out force in lumbar vertebrae

Pedicle screw instrumentation is performed in the surgical treatment of a wide variety of spinal pathologies. A common postoperative complication associated with this procedure is screw loosening. It has been shown that patient-specific screw fixation can be automated to match standard clinical practice and that failure can be estimated preoperatively using computed tomography images. Hence, we set out to optimize three-dimensional preoperative planning to achieve more mechanically robust screw purchase allowing deviation from intuitive, standard screw parameters. Toward this purpose, we employed a genetic algorithm optimization to find optimal screw sizes and trajectories by maximizing the CT derived bone mechanical properties. The method was tested on cadaveric lumbar vertebrae (L1 to L5) of four human spines (2 female/2 male; age range 60-78 years). The main boundary conditions were the predefined, level-dependent areas of possible screw entry points, as well as the automatically located pedicle structures. Finite element analysis was used to compare the genetic algorithm output to standard clinical planning of screw positioning in terms of the simulated pull-out strength. The genetic algorithm optimization successfully found screw sizes and trajectories that maximize the sum of the Young's modulus within the screw's volume for all 40 pedicle screws included in this study. Overall, there was a 26% increase in simulated pull-out strength for optimized compared to traditional screw trajectories and sizes. Our results indicate that optimizing pedicle screw instrumentation in lumbar vertebrae based on bone quality measures improves screw purchase as compared to traditional instrumentation.

Finite Element Analysis of Fracture Fixation

PURPOSE OF REVIEW

Fracture fixation aims to provide stability and promote healing, but remains challenging in unstable and osteoporotic fractures with increased risk of construct failure and nonunion. The first part of this article reviews the clinical motivation behind finite element analysis of fracture fixation, its strengths and weaknesses, how models are developed and validated, and how outputs are typically interpreted. The second part reviews recent modeling studies of the femur and proximal humerus, areas with particular relevance to fragility fractures.

RECENT FINDINGS

There is some consensus in the literature around how certain modeling aspects are pragmatically formulated, including bone and implant geometries, meshing, material properties, interactions, and loads and boundary conditions. Studies most often focus on predicted implant stress, bone strain surrounding screws, or interfragmentary displacements. However, most models are not rigorously validated. With refined modeling methods, improved validation efforts, and large-scale systematic analyses, finite element analysis is poised to advance the understanding of fracture fixation failure, enable optimization of implant designs, and improve surgical guidance.

Different fixation pattern for thoracolumbar fracture of ankylosing spondylitis: A finite element analysis

The objective of this study is to establish an ankylosing spondylitis (AS) thoracolumbar fracture finite element (FE) model and provide a proper posterior fixation choice from the biomechanical perspective. The ankylosing spondylitis T9-L5 FE model was built and the range of motion (ROM) was compared to previous studies. The L1 transverse fracture was simulated and was separately fixed by five different patterns. The pull force and yielding force of the screws, the von Mises stress of the internal fixation, and the displacement of fracture site were analyzed to evaluate the proper fixation pattern for thoracolumbar fracture of AS. ROM of AS model was obviously restricted comparing to the normal vertebral experimental data. All the fixation patterns can stabilize the fracture. At least four levels of fixation can reduce the von Mises stress of the internal fixation. Four levels fixation has a higher pull force than the six levels fixation. Skipped level fixation did not reduce the stress, pull force and yielding force. The kyphosis correction did not change the biomechanical load. At least 4 levels fixation was needed for AS thoracolumbar fracture. The cemented screws should be chosen in 4 levels fixation to increase the holding of the screws. The skipped fixation has no advantage. The kyphosis correction can be chosen after weighing the pros and cons.

Patient-Specific Finite Element Models of Posterior Pedicle Screw Fixation: Effect of Screw's Size and Geometry

Pedicle screw fixation is extensively performed to treat spine injuries or diseases and it is common for thoracolumbar fractures. Post-operative complications may arise from this surgery leading to back pain or revisions. Finite element (FE) models could be used to predict the outcomes of surgeries but should be verified when both simplified and realistic designs of screws are used. The aim of this study was to generate patient-specific Computed Tomography (CT)-based FE models of human vertebrae with two pedicle screws, verify the models, and use them to evaluate the effect of the screws' size and geometry on the mechanical properties of the screws-vertebra structure. FE models of the lumbar vertebra implanted with two pedicle screws were created from anonymized CT-scans of three patients. Compressive loads were applied to the head of the screws. The mesh size was optimized for realistic and simplified geometry of the screws with a mesh refinement study. Finally, the optimal mesh size was used to evaluate the sensitivity of the model to changes in screw's size (diameter and length) and geometry (realistic or simplified). For both simplified and realistic models, element sizes of 0.6 mm in the screw and 1.0 mm in the bone allowed to obtain relative differences of approximately 5% or lower. Changes in screw's length resulted in 4-10% differences in maximum deflection, 1-6% differences in peak stress in the screws, 10-22% differences in mean strain in the bone around the screw; changes in screw's diameter resulted in 28-36% differences in maximum deflection, 6-27% differences in peak stress in the screws, and 30-47% differences in mean strain in the bone around the screw. The maximum deflection predicted with realistic or simplified screws correlated very well (R ² = 0.99). The peak stress in screws with realistic or simplified design correlated well (R ² = 0.82) but simplified models underestimated the peak stress. In conclusion, the results showed that the diameter of the screw has a major role on the mechanics of the screw-vertebral structure for each patient. Simplified screws can be used to estimate the mechanical properties of the implanted vertebrae, but the systematic underestimation of the peak stress should be considered when interpreting the results from the FE analyses.

Automated Pipeline to Generate Anatomically Accurate Patient-Specific Biomechanical Models of Healthy and Pathological FSUs

State-of-the-art preoperative biomechanical analysis for the planning of spinal surgery not only requires the generation of three-dimensional patient-specific models but also the accurate biomechanical representation of vertebral joints. The benefits offered by computational models suitable for such purposes are still outweighed by the time and effort required for their generation, thus compromising their applicability in a clinical environment. In this work, we aim to ease the integration of computerized methods into patient-specific planning of spinal surgery. We present the first pipeline combining deep learning and finite element methods that allows a completely automated model generation of functional spine units (FSUs) of the lumbar spine for patient-specific FE simulations (FEBio). The pipeline consists of three steps: (a) multiclass segmentation of cropped 3D CT images containing lumbar vertebrae using the DenseVNet network, (b) automatic landmark-based mesh fitting of statistical shape models onto 3D semantic segmented meshes of the vertebral models, and (c) automatic generation of patient-specific FE models of lumbar segments for the simulation of flexion-extension, lateral bending, and axial rotation movements. The automatic segmentation of FSUs was evaluated against the gold standard (manual segmentation) using 10-fold cross-validation. The obtained Dice coefficient was 93.7% on average, with a mean surface distance of 0.88 mm and a mean Hausdorff distance of 11.16 mm (N = 150). Automatic generation of finite element models to simulate the range of motion (ROM) was successfully performed for five healthy and five pathological FSUs. The results of the simulations were evaluated against the literature and showed comparable ROMs in both healthy and pathological cases, including the alteration of ROM typically observed in severely degenerated FSUs. The major intent of this work is to automate the creation of anatomically accurate patient-specific models by a single pipeline allowing functional modeling of spinal motion in healthy and pathological FSUs. Our approach reduces manual efforts to a minimum and the execution of the entire pipeline including simulations takes approximately 2 h. The automation, time-efficiency and robustness level of the pipeline represents a first step toward its clinical integration.