A statistical geometrical description of the human liver for probabilistic occupant models

Approximating subject-specific brain injury models via scaling based on head-brain morphological relationships

Most human head/brain models represent a generic adult male head/brain. They may suffer in accuracy when investigating traumatic brain injury (TBI) on a subject-specific basis. Subject-specific models can be developed from neuroimages; however, neuroimages are not typically available in practice. In this study, we establish simple and elegant regression models between brain outer surface morphology and head dimensions measured from neuroimages along with age and sex information (N = 191; 141 males and 50 females with age ranging 14-25 years). The regression models are then used to approximate subject-specific brain models by scaling a generic counterpart, without using neuroimages. Model geometrical accuracy is assessed using adjusted [Formula: see text] and absolute percentage error (e.g., 0.720 and 3.09 ± 2.38%, respectively, for brain volume when incorporating tragion-to-top). For a subset of 11 subjects (from smallest to largest in brain volume), impact-induced brain strains are compared with those from "morphed models" derived from neuroimage-based mesh warping. We find that regional peak strains from the scaled subject-specific models are comparable to those of the morphed counterparts but could be considerably different from those of the generic model (e.g., linear regression slope of 1.01-1.03 for gray and white matter regions versus 1.16-1.19, or up to ~ 20% overestimation for the smallest brain studied). These results highlight the importance of incorporating brain morphological variations in impact simulation and demonstrate the feasibility of approximating subject-specific brain models without neuroimages using age, sex, and easily measurable head dimensions. The scaled models may improve subject specificity for future TBI investigations.

A parametric head geometry model accounting for variation among adolescent and young adult populations

BACKGROUND AND OBJECTIVE

Modeling the size and shape of human skull and scalp is essential for head injury assessment, design of helmets and head-borne equipment, and many other safety applications. Finite element (FE) head models are important tools to assess injury risks and design personal protective equipment. However, current FE head models are mainly developed based on the midsize male, failing to account for the significant morphological variation that exists in the skull and brain. The objective of this study was to develop a statistical head geometry model that accounts for size and shape variations among the adolescent and young adult population.

METHODS

To represent subject-specific geometry using a homologous mesh, threshold-based segmentation of head CT scans of 101 subjects between 14 and 25 years of age was performed, followed by landmarking, mesh morphing, and projection. Skull and scalp statistical geometry models were then developed as functions of age, sex, stature, BMI, head length, head breadth, and tragion-to-top of head using generalized Procrustes analysis (GPA), principal component analysis (PCA) and multivariate regression analysis.

RESULTS

The statistical geometry models account for a high percentage of morphological variations in scalp geometry (R²=0.63), outer skull geometry (R²=0.66), inner skull geometry (R²=0.55), and skull thickness (error < 1 mm) CONCLUSIONS: Skull and scalp statistical geometry models accounts for size and shape variations among the adolescent and young adult population were developed as functions of subject covariates. These models may serve as the geometric basis to develop individualized head FE models for injury assessment and design of head-borne equipment.

A statistical lumbar spine geometry model accounting for variations by Age, Sex, Stature, and body mass index

The objective of this study was to develop a statistical lumbar spine geometry model accounting for morphological variations among the adult population. Five lumber vertebrae and lumber spine curvature were collected from CT scans of 82 adult subjects through CT segmentation, landmark identification, and template mesh mapping. Generalized Procrustes Analysis (GPA), Principal Component Analysis (PCA), and multivariate regression analysis were conducted to develop the statistical lumbar spine model. Two statistical models were established to predict the vertebrae geometry and lumbar curvature respectively. Using the statistical models, a lumbar spine finite element (FE) model could be rapidly generated with a given set of age, sex, stature, and body mass index (BMI). The results showed that the lumbar spine vertebral size was significantly affected by stature, sex and age, and the lumbar spine curvature was significantly affected by stature and age. This statistical lumbar spine model could serve as the geometric basis for quantifying effects of human characteristics on lumbar spine injury risks in impact conditions.

Application of Magnetic Resonance Imaging in Liver Biomechanics: A Systematic Review

MRI-based biomechanical studies can provide a deep understanding of the mechanisms governing liver function, its mechanical performance but also liver diseases. In addition, comprehensive modeling of the liver can help improve liver disease treatment. Furthermore, such studies demonstrate the beginning of an engineering-level approach to how the liver disease affects material properties and liver function. Aimed at researchers in the field of MRI-based liver simulation, research articles pertinent to MRI-based liver modeling were identified, reviewed, and summarized systematically. Various MRI applications for liver biomechanics are highlighted, and the limitations of different viscoelastic models used in magnetic resonance elastography are addressed. The clinical application of the simulations and the diseases studied are also discussed. Based on the developed questionnaire, the papers' quality was assessed, and of the 46 reviewed papers, 32 papers were determined to be of high-quality. Due to the lack of the suitable material models for different liver diseases studied by magnetic resonance elastography, researchers may consider the effect of liver diseases on constitutive models. In the future, research groups may incorporate various aspects of machine learning (ML) into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification.

Statistical shape analysis of gravid uteri throughout pregnancy by a ray description technique

In order to study the anatomical variability of the uterus induced by pregnancy, a parametrization of gravid uterine geometry based on principal component analysis (PCA) is proposed. Corresponding meshes used for PCA are created by a ray description technique applied to a reference mesh. A smoothed voxel-based methodology is applied to determine the reference mesh from a database of 11 real shapes produced by the FEMONUM project. The ray-based correspondence technique is compared to two existing methods (He, Giessen) as well as a proposed mixed method. Principal component analysis results are based on a database of 11 existing shapes. Results of the parametrization show that 90% of the total variance of the database can be represented with four new shape parameters and that a wide spectrum of shapes can be generated. Graphical Abstract Proposed correspondence technique compared to existing methods.

Lung and fissure shape is associated with age in healthy never-smoking adults aged 20-90 years

Lung shape could hold prognostic information for age-related diseases that affect lung tissue mechanics. We sought to quantify mean lung shape, its modes of variation, and shape associations with lung size, age, sex, and Body Mass Index (BMI) in healthy subjects across a seven-decade age span. Volumetric computed tomography from 83 subjects (49 M/34 F, BMI [Formula: see text]) was used to derive two statistical shape models using a principal component analysis. One model included, and the other controlled for, lung volume. Volume made the strongest contribution to shape when it was included. Shape had a strong relationship with age but not sex when volume was controlled for, and BMI had only a small but significant association with shape. The first principal shape mode was associated with decrease in the antero-posterior dimension from base to apex. In older subjects this was rapid and obvious, whereas younger subjects had relatively more constant dimension. A shift of the fissures of both lungs in the basal direction was apparent for the older subjects, consistent with a change in tissue elasticity with age. This study suggests a quantifiable structure-function relationship for the healthy adult lung that can potentially be exploited as a normative description against which abnormal can be compared.

Development of a simplified, reproducible, parametric 3D model of the talus

Computational foot models have significant application in surgical decision making, injury and disease diagnosis and prevention, sports performance analysis and footwear engineering. However, due to the substantial time in model building and the heavy computational costs from the complexity of the models, daily clinical application of these foot models has yet to be achieved. Much of the previous research adopted a detailed-geometry approach in modeling bones that potentially contributed to the heavy computational costs. In this research, we developed a computational talus model based on CT section image data, image reconstruction and segmentation, contact surface identification, standard shape fitting, and finite element auto meshing algorithms. Modeling the bones as rigid is common, and modeling the contact surfaces only for the rigid body saves additional computational resources. Priority, therefore, in the shape fitting with optimization is given to the contact surfaces of the talus. Thirteen sets (9 males and 4 females) of CT section data were obtained. Image reconstruction, segmentation and bone labeling were conducted on each set of CT data to identify talus and its adjacent bones. Contact surfaces of the talus were then identified based on bone spatial relationships. Apart from the talar dome surface which was fitted by a 3rd-order polynomial, standard shapes such as ellipsoids and planes were used to fit the selected contact surfaces so that the geometrical parameters maintain physical significance. Based on these parameters, we automatically recreated and meshed the least-squares fitted shapes rapidly with limited elements. Last, mean major contact surfaces of the talus were obtained and fitted by standard shapes. Although the number of samples in this study was relatively small, our method provides sufficient and accurate geometric parameters of these contact surfaces to completely describe and reproduce the talus, on both a subject specific and average basis. The method for describing the talus here helps to parametrize computational models using planes and ellipsoids, improves surgical decision making and implants with a more precise and physically significant measures, and the description provides bone geometric parameters which can later be used to relate risk analysis for bone shape specific injury rates.

A Finite Element Model of a Midsize Male for Simulating Pedestrian Accidents

Pedestrians represent one of the most vulnerable road users and comprise nearly 22% the road crash-related fatalities in the world. Therefore, protection of pedestrians in car-to-pedestrian collisions (CPC) has recently generated increased attention with regulations involving three subsystem tests. The development of a finite element (FE) pedestrian model could provide a complementary component that characterizes the whole-body response of vehicle–pedestrian interactions and assesses the pedestrian injuries. The main goal of this study was to develop and to validate a simplified full body FE model corresponding to a 50th male pedestrian in standing posture (M50-PS). The FE model mesh and defined material properties are based on a 50th percentile male occupant model. The lower limb-pelvis and lumbar spine regions of the human model were validated against the postmortem human surrogate (PMHS) test data recorded in four-point lateral knee bending tests, pelvic\abdomen\shoulder\thoracic impact tests, and lumbar spine bending tests. Then, a pedestrian-to-vehicle impact simulation was performed using the whole pedestrian model, and the results were compared to corresponding PMHS tests. Overall, the simulation results showed that lower leg response is mostly within the boundaries of PMHS corridors. In addition, the model shows the capability to predict the most common lower extremity injuries observed in pedestrian accidents. Generally, the validated pedestrian model may be used by safety researchers in the design of front ends of new vehicles in order to increase pedestrian protection.

Probabilistic liver atlas construction

BACKGROUND

Anatomical atlases are 3D volumes or shapes representing an organ or structure of the human body. They contain either the prototypical shape of the object of interest together with other shapes representing its statistical variations (statistical atlas) or a probability map of belonging to the object (probabilistic atlas). Probabilistic atlases are mostly built with simple estimations only involving the data at each spatial location.

RESULTS

A new method for probabilistic atlas construction that uses a generalized linear model is proposed. This method aims to improve the estimation of the probability to be covered by the liver. Furthermore, all methods to build an atlas involve previous coregistration of the sample of shapes available. The influence of the geometrical transformation adopted for registration in the quality of the final atlas has not been sufficiently investigated. The ability of an atlas to adapt to a new case is one of the most important quality criteria that should be taken into account. The presented experiments show that some methods for atlas construction are severely affected by the previous coregistration step.

CONCLUSION

We show the good performance of the new approach. Furthermore, results suggest that extremely flexible registration methods are not always beneficial, since they can reduce the variability of the atlas and hence its ability to give sensible values of probability when used as an aid in segmentation of new cases.

A finite element model of a six-year-old child for simulating pedestrian accidents

Child pedestrian protection deserves more attention in vehicle safety design since they are the most vulnerable road users who face the highest mortality rate. Pediatric Finite Element (FE) models could be used to simulate and understand the pedestrian injury mechanisms during crashes in order to mitigate them. Thus, the objective of the study was to develop a computationally efficient (simplified) six-year-old (6YO-PS) pedestrian FE model and validate it based on the latest published pediatric data. The 6YO-PS FE model was developed by morphing the existing GHBMC adult pedestrian model. Retrospective scan data were used to locally adjust the geometry as needed for accuracy. Component test simulations focused only the lower extremities and pelvis, which are the first body regions impacted during pedestrian accidents. Three-point bending test simulations were performed on the femur and tibia with adult material properties and then updated using child material properties. Pelvis impact and knee bending tests were also simulated. Finally, a series of pediatric Car-to-Pedestrian Collision (CPC) were simulated with pre-impact velocities ranging from 20km/h up to 60km/h. The bone models assigned pediatric material properties showed lower stiffness and a good match in terms of fracture force to the test data (less than 6% error). The pelvis impact force predicted by the child model showed a similar trend with test data. The whole pedestrian model was stable during CPC simulations and predicted common pedestrian injuries. Overall, the 6YO-PS FE model developed in this study showed good biofidelity at component level (lower extremity and pelvis) and stability in CPC simulations. While more validations would improve it, the current model could be used to investigate the lower limb injury mechanisms and in the prediction of the impact parameters as specified in regulatory testing protocols.