Finite element analysis in implant dentistry: State of the art and future directions.

OBJECTIVE: To discuss the state of the art of Finite Element (FE) modeling in implant dentistry, to highlight the principal features and the current limitations, and giving recommendations to pave the way for future studies. METHODS: The articles' search was performed through PubMed, Web of Science, Scopus, Science Direct, and Google Scholar using specific keywords. The articles were selected based on the inclusion and exclusion criteria, after title, abstract and full-text evaluation. A total of 147 studies were included in this review. RESULTS: To date, the FE analysis of the bone-dental implant system has been investigated by analyzing several types of implants; modeling only a portion of bone considered as isotropic material, despite its anisotropic behavior; assuming in most cases complete osseointegration; considering compressive or oblique forces acting on the implant; neglecting muscle forces and the bone remodeling process. Finally, there is no standardized approach for FE modeling in the dentistry field. SIGNIFICANCE: FE modeling is an effective computational tool to investigate the long-term stability of implants. The ultimate aim is to transfer such technology into clinical practice to help dentists in the diagnostic and therapeutic phases. To do this, future research should deeply investigate the loading influence on the bone-implant complex at a microscale level. This is a key factor still not adequately studied. Thus, a multiscale model could be useful, allowing to account for this information through multiple length scales. It could help to obtain information about the relationship among implant design, distribution of bone stress, and bone growth. Finally, the adoption of a standardized approach will be necessary, in order to make FE modeling highly predictive of the implant's long-term stability.

Osteolytic vs. Osteoblastic Metastatic Lesion: Computational Modeling of the Mechanical Behavior in the Human Vertebra after Screws Fixation Procedure.

Metastatic lesions compromise the mechanical integrity of vertebrae, increasing the fracture risk. Screw fixation is usually performed to guarantee spinal stability and prevent dramatic fracture events. Accordingly, predicting the overall mechanical response in such conditions is critical to planning and optimizing surgical treatment. This work proposes an image-based finite element computational approach describing the mechanical behavior of a patient-specific instrumented metastatic vertebra by assessing the effect of lesion size, location, type, and shape on the fracture load and fracture patterns under physiological loading conditions. A specific constitutive model for metastasis is integrated to account for the effect of the diseased tissue on the bone material properties. Computational results demonstrate that size, location, and type of metastasis significantly affect the overall vertebral mechanical response and suggest a better way to account for these parameters in estimating the fracture risk. Combining multiple osteolytic lesions to account for the irregular shape of the overall metastatic tissue does not significantly affect the vertebra fracture load. In addition, the combination of loading mode and metastasis type is shown for the first time as a critical modeling parameter in determining fracture risk. The proposed computational approach moves toward defining a clinically integrated tool to improve the management of metastatic vertebrae and quantitatively evaluate fracture risk.

Effect of pedicle screw angles on the fracture risk of the human vertebra: A patient-specific computational model.

The assessment of a human vertebra's stability after a screws fixation procedure and its fracture risk is still an open clinical problem. The accurate evaluation of fracture risk requires that all fracture mechanical determinants such as geometry, constitutive behavior, loading modes, and screws angulation are accounted for, which requires biomechanics-based analyses. As such, in the present work we investigate the effect of pedicle screws angulation on a patient-specific model of non osteoporotic lumbar vertebra, derived from clinical CT images. We propose a novel computational approach of fracture analysis and compare the effects of fixation stability in the lumbar spine. We considered a CT-based three-dimensional FE model of bilaterally instrumented L4 vertebra virtually implanting pedicle screws according to clinical guidelines. Nine screws trajectories were selected combining three craniocaudal and mediolateral angles, thus investigated through a parametric computational analysis. Bone was modeled as an elastic material with element-wise inhomogeneous properties fine-tuned on CT data. We implemented a custom algorithm to identify the thin cortical layer correctly from CT images ensuring reliable material properties in the computational model. Physiological motion (i.e., flexion, extension, axial rotation, lateral bending) was further accomplished by simultaneously loading the vertebra and the implant. We simulated local progressive damage of the bone by using a quasi-static force-driven incremental approach and considering a stress-based fracture criterion. Ductile-like and brittle-like fractures were found. Statistical analyses show significant differences comparing screws trajectories and averaging the results among six loading modes. In particular, we identified the caudomedial trajectory as the least critical case, thus safer from a clinical perspective. Instead, medial and craniolaterally oriented screws entailed higher peak and average stresses, though no statistical evidence classified such loads as the most critical scenarios. A quantitative validation procedure will be required in the future to translate our findings into clinical practice. Besides, to apply the results to the target osteoporotic population, new studies will be needed, including a specimen from an osteoporotic patient and the effect of osteoporosis on the constitutive model of bone.

Image-based finite-element modeling of the human femur.

Fracture is considered a critical clinical endpoint in skeletal pathologies including osteoporosis and bone metastases. However, current clinical guidelines are limited with respect to identifying cases at high risk of fracture, as they do not account for many mechanical determinants that contribute to bone fracture. Improving fracture risk assessment is an important area of research with clear clinical relevance. Patient-specific numerical musculoskeletal models generated from diagnostic images are widely used in biomechanics research and may provide the foundation for clinical tools used to quantify fracture risk. However, prior to clinical translation, in vitro validation of predictions generated from such numerical models is necessary. Despite adopting radically different models, in vitro validation of image-based finite element (FE) models of the proximal femur (predicting strains and failure loads) have shown very similar, encouraging levels of accuracy. The accuracy of such in vitro models has motivated their application to clinical studies of osteoporotic and metastatic fractures. Such models have demonstrated promising but heterogeneous results, which may be explained by the lack of a uniform strategy with respect to FE modeling of the human femur. This review aims to critically discuss the state of the art of image-based femoral FE modeling strategies, highlighting principal features and differences among current approaches. Quantitative results are also reported with respect to the level of accuracy achieved from in vitro evaluations and clinical applications and are used to motivate the adoption of a standardized approach/workflow for image-based FE modeling of the femur.

Cortical bone mapping improves finite element strain prediction accuracy at the proximal femur.

Despite evidence of the biomechanical role of cortical bone, current state of the art finite element models of the proximal femur built from clinical CT data lack a subject-specific representation of the bone cortex. Our main research hypothesis is that the subject-specific modelling of cortical bone layer from CT images, through a deconvolution procedure known as Cortical Bone Mapping (CBM, validated for cortical thickness and density estimates) can improve the accuracy of CT-based FE models of the proximal femur, currently limited by partial volume artefacts. Our secondary hypothesis is that a careful choice of cortical-specific density-elasticity relationship may improve model accuracy. We therefore: (i) implemented a procedure to include subject-specific CBM estimates of both cortical thickness and density in CT-based FE models. (ii) defined alternative models that included CBM estimates and featured a cortical-specific or an independently optimised density-elasticity relationship. (iii) tested our hypotheses in terms of elastic strain estimates and failure load and location prediction, by comparing with a published cohort of 14 femurs, where strain and strength in stance and fall loading configuration were experimentally measured, and estimated through reference FE models that did not explicitly model the cortical compartment. Our findings support the main hypothesis: an explicit modelling of the proximal femur cortical bone layer including CBM estimates of cortical bone thickness and density increased the FE strains prediction, mostly by reducing peak errors (average error reduced by 30%, maximum error and 95th percentile of error distribution halved) and especially when focusing on the femoral neck locations (all error metrics at least halved). We instead rejected the secondary hypothesis: changes in cortical density-elasticity relationship could not improve validation performances. From these improved baseline strain estimates, further work is needed to achieve accurate strength predictions, as models incorporating cortical thickness and density produced worse estimates of failure load and equivalent estimates of failure location when compared to reference models. In summary, we recommend including local estimates of cortical thickness and density in FE models to estimate bone strains in physiological conditions, and especially when designing exercise studies to promote bone strength.

Mechanical behavior of metastatic femurs through patient-specific computational models accounting for bone-metastasis interaction.

This paper proposes a computational model based on a finite-element formulation for describing the mechanical behavior of femurs affected by metastatic lesions. A novel geometric/constitutive description is introduced by modelling healthy bone and metastases via a linearly poroelastic constitutive approach. A Gaussian-shaped graded transition of material properties between healthy and metastatic tissues is prescribed, in order to account for the bone-metastasis interaction. Loading-induced failure processes are simulated by implementing a progressive damage procedure, formulated via a quasi-static displacement-driven incremental approach, and considering both a stress- and a strain-based failure criterion. By addressing a real clinical case, left and right patient-specific femur models are geometrically reconstructed via an ad-hoc imaging procedure and embedding multiple distributions of metastatic lesions along femurs. Significant differences in fracture loads, fracture mechanisms, and damage patterns, are highlighted by comparing the proposed constitutive description with a purely elastic formulation, where the metastasis is treated as a pseudo-healthy tissue or as a void region. Proposed constitutive description allows to capture stress/strain localization mechanisms within the metastatic tissue, revealing the model capability in describing possible strain-induced mechano-biological stimuli driving onset and evolution of the lesion. The proposed approach opens towards the definition of effective computational strategies for supporting clinical decision and treatments regarding metastatic femurs, contributing also to overcome some limitations of actual standards and procedures.

Diffusion-Tensor Imaging Versus Digitization in Reconstructing the Masseter Architecture.

Accurate characterization of the craniomaxillofacial (CMF) skeleton using finite element (FE) modeling requires representation of complex geometries, heterogeneous material distributions, and physiological loading. Musculature in CMF FE models are often modeled with simple link elements that do not account for fiber bundles (FBs) and their differential activation. Magnetic resonance (MR) diffusion-tensor imaging (DTI) enables reconstruction of the three-dimensional (3D) FB arrangement within a muscle. However, 3D quantitative validation of DTI-generated FBs is limited. This study compares 3D FB arrangement in terms of pennation angle (PA) and fiber bundle length (FBL) generated through DTI in a human masseter to manual digitization. CT, MR-proton density, and MR-DTI images were acquired from a single cadaveric specimen. Bone and masseter surfaces were reconstructed from CT and MR-proton density images, respectively. PA and FBL were estimated from FBs reconstructed from MR-DTI images using a streamline tracking (STT) algorithm (n = 193) and FBs identified through manual digitization (n = 181) and compared using the Mann-Whitney test. DTI-derived PAs did not differ from the digitized data (p = 0.411), suggesting that MR-DTI can be used to simulate FB orientation and the directionality of transmitted forces. Conversely, a significant difference was observed in FBL (p < 0.01) which may have resulted due to the tractography stopping criterion leading to early tract termination and greater length variability. Overall, this study demonstrated that DTI can yield muscle FB orientation data suitable to representative directionality of physiologic muscle loading in patient-specific CMF FE modeling.

Can CT image deblurring improve finite element predictions at the proximal femur?

The aim of this study was to determine if a CT image deblurring algorithm can improve CT-based FE modelling accuracy at the proximal femur. Experimental data (CT scans of fourteen proximal fresh-frozen cadaveric femurs, non-destructive surface strain measurements in stance and sideways fall loading configurations on all femurs, and failure loads obtained in stance for seven specimens, in sideways fall for the other seven) were taken from a recent study (Schileo et al., 2014). An estimate of the 3D Point Spread Function for each CT scan was used within a deconvolution solver to perform the deblurring. The most proximal regions of three specimens were scanned using an HRpQCT scanner and compared to the original and deblurred CT images to quantify errors in bone contour estimates and determine correlation of intensity values within the bone contours. Subject-specific FE models of the proximal femur were generated. The accuracy of deblurred FE predictions against experimental measurements was compared to the published (non-deblurred) FE results. When compared to HRpQCT, CT deblurring led to lower mean surface distances (0.31 vs. 0.49mm) and higher CT intensity correlations with respect to the original CT. All indicators of strain prediction accuracy were significantly improved in deblurred FE models, more markedly at the femoral neck (peak error reduced by 38%). Failure load prediction, based on a simple elastic limit model, was also improved in deblurred FE models, although differently for stance and sideways fall loading conditions. In stance, correlation was unchanged, but specimen-wise errors were reduced (mean error 10% vs. 15%). In sideways fall, correlation notably increased (R(2)=0.95 vs. 0.81), despite a general overestimation of failure load. In summary, the proposed CT deblurring technique yielded moderate but significant improvements in FE predictions, and may thus be considered a first step toward the improvement of CT-based FE models of the human femur.

New and rare GJB2 alleles in patients with nonsyndromic sensorineural hearing impairment: a genotype/auditory phenotype correlation.

AIM: The aim of the study is to report the new and rare GJB2 variants identified in individuals with nonsyndromic sensorineural hearing impairment (HI) in a retrospective study based on 498 patients referred to the Otolaryngology and Medical Genetics Units of the Modena University Hospital, Italy, with the purpose of building new genotype/auditory phenotype correlations for the GJB2 gene. RESULTS: A total of eight variants identified in HI patients under study were considered rare for their frequency below 1% in the general population and in the HI databases. Of those, four (I20T, V95M, N206S, c.-22-2A>C) were in compound heterozygosity with known mutations resulting in a range of phenotypes from mild to profound, whereas four (W3R, C218Y, K221N, c.-22-6T>C) were found in simple heterozygosity (for those only in silico prediction of pathogenicity was possible due to the absence of a second GJB2 or GJB6 mutation). CONCLUSION: Based on patients' phenotype, reported frequency, and in silico prediction analysis, we suggest the prognostic value of eight rare and new GJB2 alleles, which may be of help to the clinician in counseling patients who carry such variants.

Multiple loading conditions analysis can improve the association between finite element bone strength estimates and proximal femur fractures: a preliminary study in elderly women.

This is a preliminary case-control study on osteopenic/osteoporotic elderly women, testing the association of proximal femur fracture with minimum femoral strength, as derived from finite element (FE) analysis in multiple loading conditions. Fracture cases (n=22) in acute conditions were enrolled among low-trauma fractures admitted in various hospitals in the Emilia Romagna Region, Italy. Women with no history of low-trauma fractures were enrolled as controls (n=33). Patients were imaged with DXA to obtain aBMD, and with a bilateral full femur CT scan. FE-strength was derived in stance and fall configurations: (i) as the minimum strength among those obtained for multiple loading conditions spanning a domain of plausible force directions, and (ii) as the strength associated to the most commonly used single loading conditions. The association of FE-strength and aBMD with fractures was tested with logistic regression models, deriving odds ratios (ORs) and area under the receiver operating characteristic curve (AUC). FE-strength from multiple loading conditions better classified fracture cases from controls (OR per SD change=9.6, 95% CI=3.0-31.3, AUC=0.87 in stance; OR=9.5, 95% CI=2.9-31.2, AUC=0.88 in fall) compared to aBMD (OR=3.6, 95% CI=1.6-8.2, AUC=0.79 for total femur aBMD), while FE-strength results from the most commonly used single loading conditions were similar to aBMD. Only FE-strength from multiple loading conditions remained significant in age- and aBMD-adjusted models (OR=10.5, 95% CI=1.8-61.3, AUC=0.95). In summary, we highlighted the importance of considering different loading conditions to identify bone weakness, and confirmed that femoral FE-strength estimates may add value to aBMD predictions in elderly osteopenic/osteoporotic women.

A three-generation family with terminal microdeletion involving 5p15.33-32 due to a whole-arm 5;15 chromosomal translocation with a steady phenotype of atypical cri du chat syndrome.

Cri du chat syndrome is characterized by cat-like cry, facial dysmorphisms, microcephaly, speech delay, intellectual disability and slow growth rate, which are present with variable frequency. The typical cri du chat syndrome, due to 5p15.2 deletion, includes severe intellectual disability, facial dysmorphisms, neonatal hypotonia and pre- and post-natal growth retardation, whereas more distal deletions in 5p15.3 lead to cat-like cry and speech delay and produce the clinical picture of the atypical cri du chat syndrome, with minimal or absent intellectual impairment. In this article we report a three-generation family with an unbalanced whole arm translocation between chromosome 5 and 15 and a microdeletion of 5.5 Mb involving 5p15.33-32. By reporting the smallest terminal deletion of 5p15.3 described so far and by reviewing the literature we discuss the genotype/phenotype correlations of the distal region of the cri du chat syndrome. The previously described critical region for the speech delay may be narrowed down and microcephaly, growth retardation and dysmorphic facial features can be included in the phenotypic expression of the atypical cri du chat syndrome due to 5p15.3 deletions.

Are spontaneous fractures possible? An example of clinical application for personalised, multiscale neuro-musculo-skeletal modelling.

Elderly frequently present variable degrees of osteopenia, sarcopenia, and neuromotor control degradation. Severely osteoporotic patients sometime fracture their femoral neck when falling. Is it possible that such fractures might occur without any fall, but rather spontaneously while the patient is performing normal movements such as level walking? The aim of this study was to verify if such spontaneous fractures are biomechanically possible, and in such case, which conditions of osteoporosis, sarcopenia, and neuromotor degradation could produce them. To the purpose, a probabilistic multiscale body-organ model validated against controlled experiments was used to predict the risk of spontaneous fractures in a population of 80-years old women, with normal weight and musculoskeletal anatomy, and variable degree of osteopenia, sarcopenia, and neuromotor control degradation. A multi-body inverse dynamics sub-model, coupled to a probabilistic neuromuscular sub-model, and to a femur finite element sub-model, formed the multiscale model, which was run within a Monte Carlo stochastic scheme, where the various parameters were varied randomly according to well defined distributions. The model predicted that neither extreme osteoporosis, nor extreme neuromotor degradation alone are sufficient to predict spontaneous fractures. However, when the two factors are combined an incidence of 0.4% of spontaneous fractures is predicted for the simulated population, which is consistent with clinical reports. When the model represented only severely osteoporotic patients, the incidence of spontaneous fractures increased to 29%. Thus, is biomechanically possible that spontaneous femoral neck fractures occur during level walking, due to a combination of severe osteoporosis and severe neuromotor degradation.