A novel method for assigning bone material properties to a comprehensive patient-specific pelvic finite element model using biplanar multi-energy radiographs

The increasing prevalence of adult spinal deformity requires long spino-pelvic instrumentation, but pelvic fixation faces challenges due to distal forces and reduced bone quality. Bi-planar multi-energy X-rays (BMEX) were used to develop a patient-specific finite element model (FEM) for evaluating pelvic fixation. Calibration involved 10 patients, and an 81-year-old female test case was used for FEM customization and pullout simulation validation. Calibration yielded a root mean square error of 74.7 mg/cm3 for HU. The simulation accurately replicated the experimental pullout test with a force of 565 N, highlighting the method's potential for optimizing biomechanical performance for pelvic fixation.

Predictions of thumb, hand, and arm muscle parameters derived using force measurements of varying complexity and neural networks

Subject-specific musculoskeletal models are a promising avenue for personalized healthcare. However, current methods for producing personalized models require dense, biomechanical datasets that include expensive and time-consuming physiological measurements. For personalized models to be clinically useful, we must be able to rapidly generate models from simple, easy to collect data. In this context, the objective of this paper is to evaluate if and how simple data, namely height/weight and pinch force data, can be used to achieve model personalization via machine learning. Using simulated lateral pinch force measurements from a synthetic population of 40,000 randomly generated subjects, we train neural networks to estimate four Hill-type muscle model parameters and bone density. We compare parameter estimates to the true parameters of 10,000 additional synthetic subjects. We also generate new personalized models using the parameter estimates and perform new lateral pinch simulations to compare predicted forces using these personalized models to those generated using a baseline model. We demonstrate that increasing force measurement complexity reduces the root-mean-square error in the majority of parameter estimates. Additionally, musculoskeletal models using neural network-based parameter estimates provide up to an 80% reduction in absolute error in simulated forces when compared to a generic model. Thus, easily obtained force measurements may be suitable for personalizing models of the thumb, although extending the method to more tasks and models involving other joints likely requires additional measurements.

Patient-specific finite element modeling of scoliotic curve progression using region-specific stress-modulated vertebral growth

PURPOSE

This study describes the creation of patient-specific (PS) osteo-ligamentous finite element (FE) models of the spine, ribcage, and pelvis, simulation of up to three years of region-specific, stress-modulated growth, and validation of simulated curve progression with patient clinical angle measurements.

RESEARCH QUESTION

Does the inclusion of region-specific, stress-modulated vertebral growth, in addition to scaling based on age, weight, skeletal maturity, and spine flexibility allow for clinically accurate scoliotic curve progression prediction in patient-specific FE models of the spine, ribcage, and pelvis?

METHODS

Frontal, lateral, and lateral bending X-Rays of five AIS patients were obtained for approximately three-year timespans. PS-FE models were generated by morphing a normative template FE model with landmark points obtained from patient X-rays at the initial X-ray timepoint. Vertebral growth behavior and response to stress, as well as model material properties were made patient-specific based on several prognostic factors. Spine curvature angles from the PS-FE models were compared to the corresponding X-ray measurements.

RESULTS

Average FE model errors were 6.3 ± 4.6°, 12.2 ± 6.6°, 8.9 ± 7.7°, and 5.3 ± 3.4° for thoracic Cobb, lumbar Cobb, kyphosis, and lordosis angles, respectively. Average error in prediction of vertebral wedging at the apex and adjacent levels was 3.2 ± 2.2°. Vertebral column stress ranged from 0.11 MPa in tension to 0.79 MPa in compression.

CONCLUSION

Integration of region-specific stress-modulated growth, as well as adjustment of growth and material properties based on patient-specific data yielded clinically useful prediction accuracy while maintaining physiological stress magnitudes. This framework can be further developed for PS surgical simulation.

Instrumentation of the sacroiliac joint with cylindrical threaded implants: A detailed finite element study of patient characteristics affecting fixation performance

The sacroiliac joint (SIJ) is a known pain generator that, in severe cases, may require surgical fixation to reduce intra-articular displacements and allow for arthrodesis. The objective of this computational study was to analyze how the number of implants affected SIJ stabilization with patient-specific characteristics such as the pelvic geometry and bone quality. Detailed finite element models were developed to account for three pelvises of differing anatomy. Each model was tested with a normal and low bone density (LD) under two types of loading: compression only and compression with flexion and extension moments. These models were instrumented with one to three cylindrical, threaded and fenestrated implants through a posterior oblique trajectory, requiring less muscle dissection than the more common lateral trajectory used with triangular implants. Compared with the noninstrumented pelvis, the change in range of motion (ROM) and stress distribution were used to characterize joint stabilization. Noninstrumented mobility ranged from 0.86 to 2.55 mm and from 1.37° to 6.11°. Across patient-specific characteristics, the ROM reduction with one implant varied from 3% to 21% for vertical and 15% to 47% for angular displacements. With two implants, the ROM reduction ranged from 12% to 41% for vertical and from 28% to 61% for angular displacements. Three implants, however, did not further improve the joint stability (14% to 42% for vertical and 32% to 63% for angular displacements). With respect to patient characteristics, an LD led to a decreased stabilization and a higher volume of stressed bone (>75% of yield stress). A better understanding of how patient characteristics affect the implant performance could help improve surgical planning of sacroiliac arthrodesis.

Development of a multiscale model of the human lumbar spine for investigation of tissue loads in people with and without a transtibial amputation during sit-to-stand

Quantification of lumbar spine load transfer is important for understanding low back pain, especially among persons with a lower limb amputation. Computational modeling provides a helpful solution for obtaining estimates of in vivo loads. A multiscale model was constructed by combining musculoskeletal and finite element (FE) models of the lumbar spine to determine tissue loading during daily activities. Three-dimensional kinematic and ground reaction force data were collected from participants with ([Formula: see text]) and without ([Formula: see text]) a unilateral transtibial amputation (TTA) during 5 sit-to-stand trials. We estimated tissue-level load transfer from the multiscale model by controlling the FE model with intervertebral kinematics and muscle forces predicted by the musculoskeletal model. Annulus fibrosis stress, intradiscal pressure (IDP), and facet contact forces were calculated using the FE model. Differences in whole-body kinematics, muscle forces, and tissue-level loads were found between participant groups. Notably, participants with TTA had greater axial rotation toward their intact limb ([Formula: see text]), greater abdominal muscle activity ([Formula: see text]), and greater overall tissue loading throughout sit-to-stand ([Formula: see text]) compared to able-bodied participants. Both normalized (to upright standing) and absolute estimates of L4-L5 IDP were close to in vivo values reported in the literature. The multiscale model can be used to estimate the distribution of loads within different lumbar spine tissue structures and can be adapted for use with different activities, populations, and spinal geometries.

Morphing the feature-based multi-blocks of normative/healthy vertebral geometries to scoliosis vertebral geometries: development of personalized finite element models

Personalized Finite Element (FE) models and hexahedral elements are preferred for biomechanical investigations. Feature-based multi-block methods are used to develop anatomically accurate personalized FE models with hexahedral mesh. It is tedious to manually construct multi-blocks for large number of geometries on an individual basis to develop personalized FE models. Mesh-morphing method mitigates the aforementioned tediousness in meshing personalized geometries every time, but leads to element warping and loss of geometrical data. Such issues increase in magnitude when normative spine FE model is morphed to scoliosis-affected spinal geometry. The only way to bypass the issue of hex-mesh distortion or loss of geometry as a result of morphing is to rely on manually constructing the multi-blocks for scoliosis-affected spine geometry of each individual, which is time intensive. A method to semi-automate the construction of multi-blocks on the geometry of scoliosis vertebrae from the existing multi-blocks of normative vertebrae is demonstrated in this paper. High-quality hexahedral elements were generated on the scoliosis vertebrae from the morphed multi-blocks of normative vertebrae. Time taken was 3 months to construct the multi-blocks for normative spine and less than a day for scoliosis. Efforts taken to construct multi-blocks on personalized scoliosis spinal geometries are significantly reduced by morphing existing multi-blocks.

A New Deformation Model of Biological Tissue for Surgery Simulation

A novel meshless deformation model of biological soft tissue, which is mainly based on the radial basis function point interpolation, is presented for interactive simulation applications such as virtual surgery simulators. Compared with conventional mesh models, the proposed model is particularly suitable for simulating large deformation, sucking and cutting tasks since there is no need to maintain grid information. Kelvin viscoelasticity, which represents relaxation, creep, and hysteresis of soft tissue, is integrated into the proposed model, making the simulation much more realistic than many existing meshless models. To verify the validity of the proposed model, a biomechanical test was performed on real-life biological tissue and the results show that the maximum relative error between the forces from the biomechanical test and those obtained from the model is less than 5.8%. The proposed model was also implemented on a neurosurgery simulator, which showed that the deformation of the brain tumor can be simulated in a high degree of accuracy with real-time performance. In particular, the error and distortion from the remeshing process inherited in conventional mesh models when deformation is large are avoided.

Development of an integrated CAD-FEA system for patient-specific design of spinal cages

Spinal cages are used to create a suitable mechanical environment for interbody fusion in cases of degenerative spinal instability. Due to individual variations in bone structures and pathological conditions, patient-specific cages can provide optimal biomechanical conditions for fusion, strengthening patient recovery. Finite element analysis (FEA) is a valuable tool in the biomechanical evaluation of patient-specific cage designs, but the time- and labor-intensive process of modeling limits its clinical application. In an effort to facilitate the design and analysis of patient-specific spinal cages, an integrated CAD-FEA system (CASCaDeS, comprehensive analytical spinal cage design system) was developed. This system produces a biomechanical-based patient-specific design of spinal cages and is capable of rapid implementation of finite element modeling. By comparison with commercial software, this system was validated and proven to be both accurate and efficient. CASCaDeS can be used to design patient-specific cages with a superior biomechanical performance to commercial spinal cages.

3D lumbar spine intervertebral disc segmentation and compression simulation from MRI using shape-aware models

PURPOSE

More accurate and robust image segmentations are needed for identification of spine pathologies and to assist with spine surgery planning and simulation. A framework for 3D segmentation of healthy and herniated intervertebral discs from T2-weighted magnetic resonance imaging was developed that exploits weak shape priors encoded in simplex mesh active surface models.

METHODS

Weak shape priors inherent in simplex mesh deformable models have been exploited to automatically segment intervertebral discs. An ellipsoidal simplex template mesh was initialized within the disc image boundary through affine landmark-based registration and was allowed to deform according to image gradient forces. Coarse-to-fine multi-resolution approach was adopted in conjunction with decreasing shape memory forces to accurately capture the disc boundary. User intervention is allowed to turn off the shape feature and guide model deformation when the internal simplex shape memory influence hinders detection of pathology. A resulting surface mesh was utilized for disc compression simulation under gravitational and weight loads using Simulation Open Framework Architecture. For testing, 16 healthy discs were automatically segmented, and five pathological discs were segmented with minimal supervision.

RESULTS

Segmentation results were validated against expert guided segmentation and demonstrate mean absolute shape distance error of <1 mm. Healthy intervertebral disc compression simulation resulted in a bulging disc under vertical pressure of 100 N/cm(2).

CONCLUSION

This study presents the application of a simplex active surface model featuring weak shape priors for 3D segmentation of healthy as well as herniated discs. A framework was developed that enables the application of shape priors in the healthy part of disc anatomy, with user intervention when the priors were inapplicable. The surface-mesh-based segmentation method is part of a processing pipeline for anatomical modelling to support interactive surgery simulation.

Quantification of pediatric and adult cervical vertebra-anatomical characteristics by age and gender for automotive application

OBJECTIVE

The cervical anatomy has been shown to affect injury patterns in vehicle crashes. Characterizing the spine anatomy and changes associated with growth and gender is important when assessing occupant protection. In this study, selected cervical characteristics were quantified.

METHODS

Computed tomography (CT) scans of 750 patients were selected from the University of Michigan trauma database; 314 were children and 436 were adults. Four variables were obtained: the maximum spinal canal radius, vertebral body depth, facet angles, and retroversion angles.

RESULTS

The cervical spine measurements varied with age and gender. The body depth increased nonlinearly with age. The average vertebral body depth at C4 was 9.2 ± 0.38 mm in the 0-3 age group, 15.7 ± 0.29 mm in the 18-29 age group, and 17.2 ± 0.46 mm in the 60+ age group. Pediatric and adult males had larger vertebral body depth than females overall, irrespective of vertebral level (P <.001). Compared to females, the vertebral body depth was 8-9 percent greater in male children and 13-16 percent greater in adult males. The average radius varied with gender, with male children generally having a larger radius than females irrespective of vertebral level (P <.001). Overall, spinal canal radius was smallest in the 0-3 and 60+ age groups and largest in the 18-29 age group. The C4 radius was 5.91 ± 0.17, 6.28 ± 0.14, and 6.73 ± 0.17 mm respectively. The radius was larger in the 4-7 age group than in the 0-3 age group, irrespective of vertebral level (P <.0001). There were nonsignificant radius changes between the 4-7 and 8-11 age groups and the 8-11 and age 12-17 groups, suggesting that the size of the spinal cord reaches near maturation by the age of 7. Facet angles decreased with age in children and increased with age in adults. The average facet angles were largest in the 0-3 age group (P <.1, C2-C6). Adult facet angles were greater in the 60+ age group than in the 18-29 age group (P <.0001, C2-C6). Males had larger facet angles than females overall (P <.01 at C2, C5-C7). The retroversion angles were largest at C6 and C7. They increased with age in children and decreased in the adult population; they were larger (5-22%) in the 18-29 age group than in the 60+ age group (P <.0001, C2-C6).

CONCLUSIONS

The results obtained in this study help explain variations in cervical anatomical changes associated with age and gender. The information is useful when assessing differences in injury patterns between different segments of the population. Anatomical measurements of the cervical spine should be considered for the development of models used to assess injury mechanisms for various occupant age groups.