Straight to the bone

Drs. Dolors Ayala and Daniela Tost, together with their research group, are studying some biomaterials in order to improve bone tissue regeneration. Understanding the morphology of bones is crucial for that goal. Here we how their group is turning computer graphics into an alternative technique to obtain information about bone quality, in particular about osteoporosis.

 

(Catalan Version)

The research group Computing in Engineering develops applications of the graphic representations

Doctors Dolors Ayala and Daniela Tost from the research group GIE, together with their research group, formed by researchers like Dr. Anna Puig and PhD students as Sergi Grau, Eduard Verges and Pascual Abellán, devoted their research to studying parametric volume modelling and applying it to the evaluation of the properties of biomaterial or the analysis of multimodal data changing with time.

At ESRF (European Synchrotron Radiation Facility)

Grenoble getting some specimen images
 Drs. Dolors i Daniela with Sergi Grau
  and two members from the ESRF.

Simulating computationally a biomedicine laboratory	Visualisation of multimodal data changing with time
We are increasingly getting used to see how computing reaches different science and society fields. We do not feel surprised when we listen to engineers like Dr. Dolors Ayala talking about histological cuts of biologic specimens. In contrast to  a Biology lab, inside GIE's rooms you won't find a microscope or any glass slides. Instead you find many computers and graphic terminals. Thanks to them and the algorithms devised by the GIE group it is possible to study bone morphology and to simulate the job of some wet laboratory's tools like a porosimetre. With equivalent results and precision... and faster. This research team studies the representation of volume data and the simulation of actions and operations applied to biomedicine (Bio-CAD). Given a three dimensional specimen, they are able to make cuts and slices as i if they were actually preparing the material to be used with a classical. But there is no real microscope to speak of, only computers. In order to generate a 3D model of an specimen you can use different capture techniques. Magnetic Resonance or Computerized Tomography (TAC) are two the of most used methodologies to build anatomic atlases. In the resulting bone geography one wants to pay special attention to the bone strength  in order to know the material's morphology. Once you have the 3D model it is possible to navigate inside it, evaluate its structural properties, etc. A very important property of bone is its porosity level. I determine the overall resistance and it gives a hint of health problems, especially in old age. Wet laboratories use tools that measure this property, called porosimetres. These instruments, however, have many practical drawbacks. For example, they require using toxic elements like mercury. Virtualizing tools The GIE group has developed a virtual porosimetre. The virtual porosimetre. It simulates the injection of a jet of mercury into the bone sample actually replicating the real world dynamics of diffusion of this element into the bone tissue and the subsequent analysis of the different volumes reached by different mercury insertion pressures. As they don´t manipulate real mercury, therefore there is no risk of intoxication. When someone studies the porosity of bones and other biomaterials the developed models by GIE allow them to represent the bone material partially or as a whole. The porosity part is usually represented by cylinder or sphere graph. It is important to know the volume of the porous and its connectivity.  Apart from studying the bones and the biomaterials it is also important to study their behaviour once they have been introduced in a broken bone, which is very important for reconstructive purposes. Dr. Ayala and her associates, are testing these procedures in real animals. The evaluation is done in a traditional way, in-vivo and also in a computing way, in-slico. The comparison between both systems generates answers, new questions and new challenges to the in-slice and BioCAD experimentation discipline. The framework for this biomedical research are two projects under the Spanish  Cicyt fund for research, where  the team of Drs. Ayala and Tost work together with a biomaterials research group at UPC and a veterinary group at  Lugo University.	One of the challenges that come from the precise knowledge of bone materials is the osteoporosis analysis. Osteoporosis is a function of bone density and also a property related to mechanic strength decrease that induces bone fractures. It is the most common bone illness in human population and it is even worse for women who are through the menopause. The interest for this illness is clear. Drs Ayala and Tost' made a big contribution with their morphologic bone material study. However, when you study an illness, it is not enough to know how the state of an affected part of the body is in a certain moment. You need to get a hint of its evolution. This is the reason why being able to work with the representation and analysisi of time-dependent data becomes essential when someone researches this type of illnesses. When data changes over time, there appear some problems: First of all, the amount of data is very big and that implies a high computational cost.  Calculations become slow. The "temporary coherence", assumes that the changes happen in a continuous way and it is a hypothesis that helps in accelerating the calculation. Secondly, there is a serious need to represent this data. Usually researchers use animated representations that go through the different studied properties. However, sometimes the user is interested in getting all the information at the same time. Therefore, this is not a trivial issue and it is necessary to consider it deeply in order to satisfy the user. Finally, knowing how a part evolves can help us knowing what is happening to the whole object. Having such information seems interesting in order to research how to get the machine to capture new more outstanding information depending on the past measures. That is how to created automated methods that "learn" to go for the discriminating data. In order to be successful we should optimize the transfer function. A transfer function is a mathematical model that delivers a system's response to an input signal.              The solution to the last two questions are some of the main research issues for the GIE research group at the LSI Department. They are studying them together with researchers from the Barcelona University, UB. On the other hand, these techniques for visualisation of multimodal data that changes with time can be applied to many other illnesses such as tumours, brain disturbances, ...etc.

GIE in other projects

This is one of the research fields for the research group GIE, however in other newsletters you could read about some other ones. For example about training before ever entering the operating-room, or how to connect back to real life through virtual reality.

Press Contact:

ilapuente@lsi.upc.edu

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