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

Widmer, Jonas; Fasser, Marie-Rosa; Croci, Eleonora; Spirig, José Miguel; Snedeker, Jess G.; Farshad, Mazda

doi:10.1080/10255842.2019.1709173

Cited by 22 publications

(20 citation statements)

References 48 publications

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“…Simulated resistance to axial pullout was compared between different FE models for the optimized vs. the traditional screws' positions. A custom developed computational testbench to simulate pull-out tests with FE models of screw-vertebra constructs has previously been validated with in vitro tests (Widmer et al 2020). Two FE models with unilateral screw placement were constructed for every pedicle of every vertebra of all cadaveric lumbar spines.…”

Section: The Fe Modelmentioning

confidence: 99%

“…In a final step, the GA output was evaluated through comparison with screw positioning according to clinical standard. For this purpose, automatically generated FE models of single screw pullout were used (Widmer et al 2020). The advantage of the implemented GA method is that it can discover non-intuitive screw placements that have the potential to surpass performance of screw purchase in standard clinical planning, according to the FE analysis.…”

Section: Introductionmentioning

confidence: 99%

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

Caprara

Fasser

Spirig

et al. 2021

Computer Methods in Biomechanics and Biomedical Engineering

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Section: The Fe Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Caprara

Fasser

Spirig

et al. 2021

Computer Methods in Biomechanics and Biomedical Engineering

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“…Similarly, Costa et al (2019) reported that element size of 1 mm was required for CT-based subject specific heterogeneous FE models of healthy noninstrumented vertebrae loaded in compression. Widmer et al (2020) reported the results from a validation study for CTbased subject specific heterogeneous animal (bovine and porcine) vertebrae with realistic pedicle screws. They opted for smaller element sizes at the level of the screw cavity compared to the bone farer from the implant resulting in about 230,000 tetrahedral elements in the bone and 10,000 shell elements in the screw; however, no mesh refinement study was reported.…”

Section: Discussionmentioning

confidence: 99%

“…Many studies assessed the optimal fixation to treat a burst fracture by simulating with FE models a system composed of three vertebrae and two intervertebral discs implanted with different configurations of rod and screws (e.g., monolateral vs. bilateral, short segment vs. long segment) (Li et al, 2014;Elmasry et al, 2017;Su et al, 2018;Wang et al, 2019). Other studies focused on the vertebra-screws interactions and proposed FE models validated with experimental measures: FE models were found to be good predictors of pull-out strength and stiffness obtained by experimental tests better than apparent density estimated from CT images (Abbeele et al, 2018;Chevalier et al, 2018;Widmer et al, 2020). The screw size and other insertion-related parameters have been tested with linear FE models (Qi et al, 2011;Newcomb et al, 2017), with non-linear FE models (material non-linearities, contact mechanics) (Chen et al, 2003;Bianco et al, 2017Bianco et al, , 2019Molinari et al, 2021), or assuming the bone as heterogeneous material with elastic properties driven by the local bone mineral density (BMD) (Matsukawa et al, 2016(Matsukawa et al, , 2020Biswas et al, 2019;Molinari et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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

Sensale

Vendeuvre

Schilling³

et al. 2021

Front. Bioeng. Biotechnol.

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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 (R2 = 0.99). The peak stress in screws with realistic or simplified design correlated well (R2 = 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.

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“…The automatic identification and segmentation of such cases avoiding biases is one of the bottlenecks in medical images processing (Galbusera et al, 2019). However, in our group, the accelerated creation of anatomically accurate models has supported the preparation of instrumented FE models to investigate the bone-screw interface (Widmer et al, 2020b). Even if the current pipeline only accepts very specific types of deformities, it represents a first successful attempt for the automation of biomechanical analysis.…”

Section: Discussionmentioning

confidence: 99%

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

Caprara

Carrillo

Snedeker

et al. 2021

Front. Bioeng. Biotechnol.

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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.

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

Cited by 22 publications

References 48 publications

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

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

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

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

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