Virtual supersampling as post-processing step preserves the trabecular bone morphometry in human peripheral quantitative computed tomography scans.

In the clinical field of diagnosis and monitoring of bone diseases, high-resolution peripheral quantitative computed tomography (HR-pQCT) is an important imaging modality. It provides a resolution where quantitative bone morphometry can be extracted in vivo on patients. It is known that HR-pQCT provides slight differences in morphometric indices compared to the current standard approach micro-computed tomography (micro-CT). The most obvious reason for this is the restriction of the radiation dose and with this a lower image resolution. With advances in micro-CT evaluation techniques such as patient-specific remodeling simulations or dynamic bone morphometry, a higher image resolution would potentially also allow the application of such novel evaluation techniques to clinical HR-pQCT measurements. Virtual supersampling as post-processing step was considered to increase the image resolution of HR-pQCT scans. The hypothesis was that this technique preserves the structural bone morphometry. Supersampling from 82 µm to virtual 41 µm by trilinear interpolation of the grayscale values of 42 human cadaveric forearms resulted in strong correlations of structural parameters (R2: 0.96-1.00). BV/TV was slightly overestimated (4.3%, R2: 1.00) compared to the HR-pQCT resolution. Tb.N was overestimated (7.47%; R2: 0.99) and Tb.Th was slightly underestimated (-4.20%; R2: 0.98). The technique was reproducible with PE%CV between 1.96% (SMI) and 7.88% (Conn.D). In a clinical setting with 205 human forearms with or without fracture measured at 82 µm resolution HR-pQCT, the technique was sensitive to changes between groups in all parameters (p < 0.05) except trabecular thickness. In conclusion, we demonstrated that supersampling preserves the bone morphometry from HR-pQCT scans and is reproducible and sensitive to changes between groups. Supersampling can be used to investigate on the resolution dependency of HR-pQCT images and gain more insight into this imaging modality.

Computational modeling of long-term effects of prophylactic vertebroplasty on bone adaptation.

Cement augmentation in vertebrae (vertebroplasty) is usually used to restore mechanical strength after spinal fracture but could also be used as a prophylactic treatment. So far, the mechanical competence has been determined immediately post-treatment, without considering long-term effects of bone adaptation. In this work, we investigated such long-term effects of vertebroplasty on the stiffness of the augmented bone by means of computational simulation of bone adaptation. Using micro-finite element analysis, we determined sites of increased mechanical stress (stress raisers) and stress shielding and, based on the simulations, regions with increased or decreased bone loss due to augmentation. Cement volumes connecting the end plates led to increased stress shielding and bone loss. The increased stiffness due to the augmentation, however, remained constant over the simulation time of 30 years. If the intervention was performed at an earlier time point, it did lead to more bone loss, but again, it did not affect long-term stability as this loss was compensated by bone gains in other areas. In particular, around the augmentation cement, bone structures were preserved, suggesting a long-term integration of the cement in the augmented bone. We conclude that, from a biomechanical perspective, the impact of vertebroplasty on the bone at the microstructural level is less detrimental than previously thought.

Load-adaptive bone remodeling simulations reveal osteoporotic microstructural and mechanical changes in whole human vertebrae.

Osteoporosis is a major medical burden and its impact is expected to increase in our aging society. It is associated with low bone density and microstructural deterioration. Treatments are available, but the critical factor is to define individuals at risk from osteoporotic fractures. Computational simulations investigating not only changes in net bone tissue volume, but also changes in its microstructure where osteoporotic deterioration occur might help to better predict the risk of fractures. In this study, bone remodeling simulations with a mechanical feedback loop were used to predict microstructural changes due to osteoporosis and their impact on bone fragility from 50 to 80 years of age. Starting from homeostatic bone remodeling of a group of seven, mixed sex whole vertebrae, five mechanostat models mimicking different biological alterations associated with osteoporosis were developed, leading to imbalanced bone formation and resorption with a total net loss of bone tissue. A model with reduced bone formation rate and cell sensitivity led to the best match of morphometric indices compared to literature data and was chosen to predict postmenopausal osteoporotic bone loss in the whole group. Thirty years of osteoporotic bone loss were predicted with changes in morphometric indices in agreement with experimental measurements, and only showing major deviations in trabecular number and trabecular separation. In particular, although being optimized to match to the morphometric indices alone, the predicted bone loss revealed realistic changes on the organ level and on biomechanical competence. While the osteoporotic bone was able to maintain the mechanical stability to a great extent, higher fragility towards error loads was found for the osteoporotic bones.

Large-scale microstructural simulation of load-adaptive bone remodeling in whole human vertebrae.

Identification of individuals at risk of bone fractures remains challenging despite recent advances in bone strength assessment. In particular, the future degradation of the microstructure and load adaptation has been disregarded. Bone remodeling simulations have so far been restricted to small-volume samples. Here, we present a large-scale framework for predicting microstructural adaptation in whole human vertebrae. The load-adaptive bone remodeling simulations include estimations of appropriate bone loading of three load cases as boundary conditions with microfinite element analysis. Homeostatic adaptation of whole human vertebrae over a simulated period of 10 years is achieved with changes in bone volume fraction (BV/TV) of less than 5%. Evaluation on subvolumes shows that simplifying boundary conditions reduces the ability of the system to maintain trabecular structures when keeping remodeling parameters unchanged. By rotating the loading direction, adaptation toward new loading conditions could be induced. This framework shows the possibility of using large-scale bone remodeling simulations toward a more accurate prediction of microstructural changes in whole human bones.

Computational modelling of bone augmentation in the spine.

Computational models are gaining importance not only for basic science, but also for the analysis of clinical interventions and to support clinicians prior to intervention. Vertebroplasty has been used to stabilise compression fractures in the spine for years, yet there are still diverging ideas on the ideal deposition location, volume, and augmentation material. In particular, little is known about the long-term effects of the intervention on the surrounding biological tissue. This review aims to investigate computational efforts made in the field of vertebroplasty, from the augmentation procedure to strength prediction and long-term in silico bone biology in augmented human vertebrae. While there is ample work on simulating the augmentation procedure and strength prediction, simulations predicting long-term effects are lacking. Recent developments in bone remodelling simulations have the potential to show adaptation to cement augmentation and, thus, close this gap.

The Clinical Biomechanics Award 2012 - presented by the European Society of Biomechanics: large scale simulations of trabecular bone adaptation to loading and treatment.

BACKGROUND: Microstructural simulations of bone remodeling are particularly relevant in the clinical management of osteoporosis. Before a model can be applied in the clinics, a validation against controlled in vivo data is crucial. Here we present a strain-adaptive feedback algorithm for the simulation of trabecular bone remodeling in response to loading and pharmaceutical treatment and report on the results of the large-scale validation against in vivo data. METHODS: The algorithm follows the mechanostat principle and incorporates mechanical feedback, based on the local strain-energy density. For the validation, simulations of bone remodeling and adaptation in 180 osteopenic mice were performed. Permutations of the conditions for early (20th week) and late (26th week) loading of 8N or 0N, and treatments with bisphosphonates, or parathyroid hormone were simulated. Static and dynamic morphometry and local remodeling sites from in vivo and in silico studies were compared. FINDINGS: For each study an individual set of model parameters was selected. Trabecular bone volume fraction was chosen as an indicator of the accuracy of the simulations. Overall errors for this parameter were 0.1-4.5%. Other morphometric indices were simulated with errors of less than 19%. Dynamic morphometry was more difficult to predict, which resulted in significant differences from the experimental data. INTERPRETATION: We validated a new algorithm for the simulation of bone remodeling in trabecular bone. The results indicate that the simulations accurately reflect the effects of treatment and loading seen in respective experimental data, and, following adaptation to human data, could be transferred into clinics.