biomedical modelling
Alejandro Frangi, Professor of Biomedical Image Computing at the Department of Mechanical Engineering department of the University of Sheffield, and Director of the INSIGNEO Institute on Biomedical Imaging and Modelling
I
am part of a collaborative project at the Institute for Biomedical Imaging and Modelling (INSIGNEO) that aims at
developing computational models of organ systems and eventually of human beings in their entirety. Essentially we are creating the Virtual Physiological Human (VPH). In order to achieve this, the models will need to show the physiological mechanisms that underlie those organ systems in a descriptive and predictive manner to aid studies such as the evolution of diseases or their course as a result of various treatment strategies. Finally, the models will need to be personalised to enable both description and prediction of subject-specific (patient-specific) response. It’s the combination of these three features which makes the VPH not only a cutting-edge research topic but also a new approach to healthcare. A multitude of biomedical data sources will be incorporated into the models, such as data from imaging examinations, physiological signals coming from body sensors, genetic information and laboratory results, in order to generate simulations of individuals that can then be interrogated on specific questions that hold diagnostic or prognostic value. Tis vision of the virtual human is a long-
term undertaking and currently we are focusing our attention on specific organ systems; namely,
NeuroApps
Elsevier has released the first in a new series of apps created for the iPad. This interactive application, dubbed NeuroApps: MRI Atlas of Human White Matter, is based on the MRI Atlas of White Matter by Kenichi Oishi, Andreia V. Faria, Peter C M van Zijl and Susumu Mori and essentially re-makes the atlas for a new generation of neuroscience researchers and clinicians. ‘Traditionally, brain atlases have comprised of a collection of 2D panels with anatomical annotations. Even the most bulky atlas book has severe limitations in the amount of panels, magnifications and information it can carry,’ explains Dr Susumi Mori, one of the creators of the atlas. ‘NeuroApps is the first brain atlas that removed this physical barrier. With NeuroApps, more than 100 brain sections, two contrasts and free magnifications are in the small iPad dimension with the sophisticated interface, which can be carried everywhere.’ Using NeuroApps: MRI Atlas of Human White
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Matter, the user is able to find, visualise and learn to identify the major pathways through the brain and their proximity to key neuroanatomical structures. The interactive tools provide the ability to compare coronal, horizontal and sagittal sections in one view, and to switch between MRI and DTI images for any location in the brain. Brain structures can be super-imposed on the MRI/DTI images – altogether there are 53 white matter structures, 38 cortical areas and 22 deep grey matter structures defined and labelled. In addition, locations of 11 white matter tracts and 36 cytoarchitectonic areas are defined. The app also features the ability to scroll through the brain, following a tract as it moves past brain structures. While the images are based upon those from the print book, they have been digitally enhanced and the resulting four-colour images are much sharper on iPads, which allow image zooming for more detailed study. It is the first app of its kind and aims to move biomedical modelling forward.
the cardiorespiratory and neuromusculoskeletal systems, which have a critical role in major current diseases. In addition to developing models of those areas, we are creating models of a number of devices that correspond to specific treatments. For example, in the cardiovascular system we are modelling prosthetic valves, cerebral aneurysm embolization devices as well as coronary stents. Te biomedical data we gather informs the models and allows clinicians to assess the performance of the devices and the expected recovery of the patient. In the case of the musculoskeletal system,
we are trying to assess the risk of bone fracture – particularly of the femur and the spine – and attempting to understand all the elements involved so that we can develop computational models displaying the risk a patient has of sustaining injury. To do this we take into account details of the bones taken from CT scans, muscle information from MRI images and measurements taken from gait to provide the dynamics. Tese three sources are then integrated through the finite element models where anatomical detail is provided and the resulting prediction reflects all these factors and offers variables that cannot be measured directly. Te models on the cellular level provide a further level of information in terms of how the bone is able to regenerate or absorb forces.
Traditionally, clinicians would do these
assessments by examining the scans and deciding what risk factors are present. We are trying to create a tool that will aid them by integrating and visualising all that information within a multi-scale model. Te difficulty is that the data we use is captured from National Health Service (NHS) information systems that scan across many different databases in a range of departments, and sometimes across a variety of formats – digital records and paper documents, for example. We therefore attempt to work within IT infrastructures to get a more seamless integration of the information, while respecting all the data privacy and ethical issues of current legislation to the best benefit of an improved diagnosis and treatment for patients. Working as part of such a broad inter-
disciplinary team is challenging as clinical researchers and those on the engineering side have very different languages and priorities. It definitely takes patience on each side to be able to understand the other’s perspective. But we are making great strides and in the future we believe we’ll have a more holistic understanding of how the different physiological systems interact and will be able to create personalised models that take biological and environmental variables into account in order to treat, and indeed prevent, disease and degradation.
NeuroApps is an interactive version of the MRI Atlas of White Matter, designed for the iPad
www.scientific-computing.com
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