1,721,263 research outputs found
Predicting bone strength from CT data: Clinical applications
No full textIn this review we summarise over 15 years of research and development around the prediction of whole bones strength from Computed Tomography data, with particular reference to the prediction of the risk of hip fracture in osteoporotic patients. We briefly discuss the theoretical background, and then provide a summary of the laboratory and clinical validation of these modelling technologies. We then discuss the three current clinical applications: in clinical research, in clinical trials, and in clinical practice. On average the strength predicted with finite element models (QCT-FE) based on computed tomography is 7% more accurate that that predicted with areal bone mineral density from Dual X-ray Absorptiometry (DXA-aBMD), the current standard of care, both in term of laboratory validation on cadaver bones and in terms of stratification accuracy on clinical cohorts of fractured and non-fractured women. This improved accuracy makes QCT-FE superior to DXA-aBMD in clinical research and in clinical trials, where the its use can cut in half the number of patients to be enrolled to get the same statistical power. For routine clinical use to decide who to treat with antiresorptive drugs, QCT-FE is more accurate but less cost-effective than DXA-aBMD, at least when the decision is on first line treatment like bisphosphonates. But the ability to predict skeletal strength from medical imaging is now opening a number of other applications, for example in paediatrics and oncology
Biomechanics-based in silico medicine: The manifesto of a new science
Full text linkIn this perspective article we discuss the role of contemporary biomechanics in the light of recent applications such as the development of the so-called Virtual Physiological Human technologies for physiology-based in silico medicine. In order to build Virtual Physiological Human (VPH) models, computer models that capture and integrate the complex systemic dynamics of living organisms across radically different space–time scales, we need to re-formulate a vast body of existing biology and physiology knowledge so that it is formulated as a quantitative hypothesis, which can be expressed in mathematical terms. Once the predictive accuracy of these models is confirmed against controlled experiments and against clinical observations, we will have VPH model that can reliably predict certain quantitative changes in health status of a given patient, but also, more important, we will have a theory, in the true meaning this word has in the scientific method. In this scenario, biomechanics plays a very important role, biomechanics is one of the few areas of life sciences where we attempt to build full mechanistic explanations based on quantitative observations, in other words, we investigate living organisms like physical systems. This is in our opinion a Copernican revolution, around which the scope of biomechanics should be re-defined. Thus, we propose a new definition for our research domain “Biomechanics is the study of living organisms as mechanistic systems”
Special Issue on 'Computational Modelling in Medicine': Guest editor introduction.
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From bed to bench: how in silico medicine can help ageing research.
Full text linkDriven by the raising ethical concerns surrounding animal experimentation, there is a growing interest for non-animal methods, in vitro or in silico technologies that can be used to reduce, refine, and replace animal experimentation. In addition, animal experimentation is being critically revised in regard to its ability to predict clinical outcomes. In this manuscript we describe an initial exploration where a set of in vivo imaging based subject-specific technologies originally developed to predict the risk of femoral strength and hip fracture in osteoporotic patients, were adapted to assess the efficacy of bone drugs pre-clinically on mice. The CT2S technology we developed generates subject-specific models based on Computed Tomography that can separate fractured and non-fractured patients with an accuracy of 82%. When used in mouse experiments the use of in vivo imaging and modelling was found to improve the reproducibility of Bone Mineral Content measurements to a point where up to 63% less mice would be required to achieve the same statistical power of a conventional cross-sectional study. We also speculate about a possible approach where animal-specific and patient-specific models could be used to better translate the observation made on animal models into predictions of response in humans
Big Data, Big Knowledge: Big Data for Personalized Healthcare.
Full text linkThe idea that the purely phenomenological knowledge that we can extract by analyzing large amounts of data can be useful in healthcare seems to contradict the desire of VPH researchers to build detailed mechanistic models for individual patients. But in practice no model is ever entirely phenomenological or entirely mechanistic. We propose in this position paper that big data analytics can be successfully combined with VPH technologies to produce robust and effective in silico medicine solutions. In order to do this, big data technologies must be further developed to cope with some specific requirements that emerge from this application. Such requirements are: working with sensitive data; analytics of complex and heterogeneous data spaces, including nontextual information; distributed data management under security and performance constraints; specialized analytics to integrate bioinformatics and systems biology information with clinical observations at tissue, organ and organisms scales; and specialized analytics to define the "physiological envelope" during the daily life of each patient. These domain-specific requirements suggest a need for targeted funding, in which big data technologies for in silico medicine becomes the research priority
Finite Element Models to Predict the Risk of Aseptic Loosening in Cementless Femoral Stems: A Literature Review
Full text linkAseptic loosening is the most common failure mode for total hip arthroplasty, and the design of the implant plays a significant role in influencing the longevity and stability of the implant. Finite Element (FE) models have been demonstrated to be powerful numerical tools that allow for generating information supporting the device’s safety and/or efficacy during pre-clinical assessment. Different authors have proposed FE studies aiming to simulate the long-term stability of the femoral stem; however, multiple improvements are still necessary for translating computational methodologies into clinical practice. This paper provides a comprehensive overview of the modelling procedures for predicting aseptic loosening risk, focusing on cementless femoral stems. The main modelling assumptions, including bone and implant geometry, materials, boundary conditions, and bone–implant interface contact, were summarised and presented. The limitations of various modelling assumptions and their impact on the simulation results were also discussed. The analysis suggests that more rigorous clinical validation for osseointegration models and failure criteria used to determine loosening of the implant should be clearly defined, and efforts should be made to identify the appropriate limit of tolerable conditions
About the inevitable compromise between spatial resolution and accuracy of strain measurement for bone tissue: A 3D zero-strain study
Full text linkThe accurate measurement of local strain is necessary to study bone mechanics and to validate micro computed tomography (μCT) based finite element (FE) models at the tissue scale. Digital volume correlation (DVC) has been used to provide a volumetric estimation of local strain in trabecular bone sample with a reasonable accuracy. However, nothing has been reported so far for μCT based analysis of cortical bone. The goal of this study was to evaluate accuracy and precision of a deformable registration method for prediction of local zero-strains in bovine cortical and trabecular bone samples. The accuracy and precision were analyzed by comparing scans virtually displaced, repeated scans without any repositioning of the sample in the scanner and repeated scans with repositioning of the samples.The analysis showed that both precision and accuracy errors decrease with increasing the size of the region analyzed, by following power laws. The main source of error was found to be the intrinsic noise of the images compared to the others investigated. The results, once extrapolated for larger regions of interest that are typically used in the literature, were in most cases better than the ones previously reported. For a nodal spacing equal to 50 voxels (498. μm), the accuracy and precision ranges were 425-692. με and 202-394. με, respectively. In conclusion, it was shown that the proposed method can be used to study the local deformation of cortical and trabecular bone loaded beyond yield, if a sufficiently high nodal spacing is used
Multiscale modelling methods in biomechanics
Full text linkMore and more frequently, computational biomechanics deals with problems where the portion of
physical reality to be modelled spans over such a large range of spatial and temporal dimensions,
that it is impossible to represent it as a single space-time continuum. We are forced to consider
multiple space-time continua, each representing the phenomenon of interest at a characteristic
space-time scale. Multiscale models describe a complex process across multiple scales, and account
for how quantities transform as we move from one scale to another. This review offers a set of
definitions for this emerging field, and provides a brief summary of the most recent developments
on multiscale modelling in biomechanics. Of all possible perspectives, we chose that of the modelling
intent, which vastly affect the nature and the structure of each research activity. To the purpose we
organised all papers reviewed in three categories: さcausal confirmationざ, where multiscale models
are used as materialisations of the causation theories; さpredictive accuracyざ, where multiscale
modelling is aimed to improve the predictive accuracy; and さdetermination of effectざ, where
multiscale modelling is used to model how a change at one scale manifest in an effect at another,
radically different space-time scale. Consistently with the how the volume of computational
biomechanics research is distributed across application targets, we extensively reviewed papers
targeting the musculoskeletal and the cardiovascular system, and covered only a few exemplary
papers targeting other organ systems. The review shows a research sub-domain still in its infancy,
where causal confirmation papers remain the most common
Comments on ‘Experimental versus computational analysis of micromotions at the implant - bone interface’
Full text linkThe Virtual Physiological Human: Ten Years After
Full text linkBiomedical research and clinical practice are struggling to cope with the growing complexity that the progress of health care involves. The most challenging diseases, those with the largest socioeconomic impact (cardiovascular conditions; musculoskeletal conditions; cancer; metabolic, immunity, and neurodegenerative conditions), are all characterized by a complex genotype–phenotype interaction and by a “systemic” nature that poses a challenge to the traditional reductionist approach. In 2005 a small group of researchers discussed how the vision of computational physiology promoted by the Physiome Project could be translated into clinical practice and formally proposed the term Virtual Physiological Human. Our knowledge about these diseases is fragmentary, as it is associated with molecular and cellular processes on the one hand and with tissue and organ phenotype changes (related to clinical symptoms of disease conditions) on the other. The problem could be solved if we could capture all these fragments of knowledge into predictive models and then compose them into hypermodels that help us tame the complexity that such systemic behavior involves. In 2005 this was simply not possible—the necessary methods and technologies were not available. Now, 10 years later, it seems the right time to reflect on the original vision, the results achieved so far, and what remains to be done
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