Difference between revisions of "Team:Slovenia/Model"

 
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myId.innerHTML = '<h4>Patients</h4><p>Above all, we wanted to talk to the final users of our project, the patients who could potentially be using it in the future. Since they will be the ones to actually live with it every day, their opinion is paramount as the negative attitude of the end users towards medical application of synthetic biology would make the efforts to develop applications vain. \
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According to the WHO, the number of diabetics has risen to 422 million by 2014. While we might not realize in everyday lives, diabetics are our friends, our grandparents, our uncles, our doctors, our postmen, our clerks, our hairdressers… As persons who do not suffer from a chronic disease, we cannot completely ourselves from our privileged position, as being a part of the community requires the experience of the life and hardship the members face. But we wanted to be allies to this community. Allyship is about being a humble guest in somebody else’s struggle, listening and learning from it, and doing what you can to help. For this reason we decided to get to know people living with diabetes and learn what we could from them, at the same time introducing our research efforts, not as a device that will at once end all their difficulties, but as a small beacon of hope. In the name of medical information confidentiality we omitted naming them or showing their pictures. \
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Having lived with a chronic disease for most of their lives, the patients were perfectly willing to try another method that could help. More than anything they were excited over the possibility of not having to prick themselves with a needle several times a day. While we mostly presented the potential foundational advantages of the system and explained that arriving to the final working device might take years, they were kind enough to highlight some of their concerns connected to the system and suggestions we could integrate in the design. Understandably, they were mostly interested in safety and the way the device would be integrated into the body. They wanted to know in what ways their bodies would be protected from the modified cells and in how the cells in the device would be protected, as well as how we would make sure the system is not triggered randomly. While years from a possible final device, we paid attention and tried to find the solutions to their concerns. To separate the modified cells in the device from patient’s unaltered ones, we suggest microencapsulation of cells in alginate capsule, which do not trigger the immune system and were proven to work by many researchers in their publications and also by the <a href="https://2012.igem.org/Team:Slovenia/Team">2012 Slovenian iGEM team</a>. In that project students already introduced several safety mechanisms, which still seem effective. To make sure the system is not induced randomly, by walking under a blue light at a party or being examined by ultrasound, we realized that we could use the <a href="https://2016.igem.org/Team:Slovenia/Protease_signaling/Logic">logic operations</a>, so two different inputs are needed for activation, which strongly decreases the possibility of an unwanted activation. Alternatively, one of the inputs can be used to recognize the correct type of cells or cell state and the other to recognize when it should be induced.</p>';
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<figure id = "fig1"> \
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<img class="ui medium image" src="//2016.igem.org/wiki/images/b/b5/T--Slovenia--HP-6.png" > \
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  <figcaption><b>Figure 1: Discussion with culturologists prof. Franc Mali and doc. Toni Pustovrh, involved in SynErgene on the societal implications of our project.</b><br/></figcaption> \
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</figure> </div> <p>Mostly communicating with MDs, researchers in natural science, and among ourselves, we realized we could quickly fall in the trap of having a limited view of synthetic biology and our project, living in a sort of confirmation microbubble composed of approving scientist, but excluding the general public and their opinion. In order to tackle this, we wanted to talk to people who can understand the greater impact of science on society and how that is perceived by the general public. Taking into account the societal impacts of synthetic biology allows for more dynamic, varied solutions in the project. \
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We consulted prof. dr. Franc Mali and doc. dr. Toni Pustovrh, two culturologists from the University of Ljubljana, whose field of expertise is the sociology of science. We presented our project to them and they shared with us some excellent insights. Consultations with them indeed opened our horizons –having only best intentions we did not think of the potential misuse of our system, such as bypassing the doping regulations in professional sport by enhancing one’s own cells. The conversation later shifted to the wider filed of synthetic biology and its role in ensuring social justice, which impassioned us and educated our Social Engagement and Education segment <a href = "#fig1">Figure 1</a>.  </p>';
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  <figcaption><b>Figure 1: One of our brainstorming meetings</b><br/></figcaption> \
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</figure> \
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</div> <p>iGEMers, be it students or advisors, together with researchers, form the base of our star. iGEMers are the individuals who imagine a design and make it come to life; the ones who put in the theoretical and practical work and therefore best understand the outline of their specific project, it’s unique possibilities, requirements and limitations. iGEMers do not know everything there is to know about the field and themselves only one of the impactors on the idea of the project, but can know more and be inspired trough  conversation and idea exchange with their colleagues, mentors and peers. With this in mind we decided to write down our ides and brainstorm very early in the project, after the first discussions with researchers who <a href="https://2016.igem.org/Team:Slovenia/Notebook/Proposals">inspired us</a> to work on our project <a href = "#fig2">Figure 1</a>. </p> <p style = "clear:both;"></p>';
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          <figcaption><b>Figure 1: Consultation with prof. dr. Marko Živin and Kaja Kolmarič</b><br/> </figcaption> \
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    </figure> \
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</div> \
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<p>Researchers are scientist concerned with the basic idea of the project, with the possibility of execution of it, with the proof of the concept - in short, people who advise if the effort is even feasible/worth it. They do not need to necessarily be synthetic biologists as the teams are encouraged to search among other fields as well. Medical doctors, mechanical and electrical engineers, biologists, biotechnologists, (bio)chemists, computer scientists and many others have great and important ideas and considerations to contribute to the field.  \
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With the aim of designing foundational technology that could be some day applied to treatment of disease such as the Parkinson’s disease and diabetes we searched for appropriate experts in the field. We consulted prof. dr. Marko Živin, MD who deals with damage, plasticity and regeneration of nerves and muscles and his junior researcher, Kaja Kolmarič. They were extremely receptive to our idea of threating neurological disease with release of therapeutic protein from patient’s own cells, but suggested that optogenetic approach might be too invasive for an organ as sensitive and crucial as the brain, while chemical inducers of dimerization might have many side effects. It was their own research with ultrasound that inspired us and led to a shift in the emphasis of our project and resulted in ultrasound stimulation (US) becoming the focus of it. After exposure to the ideas on the potential use of ultrasound, team members returned to the drawing board and each came up with a project idea mainly tailored to ultrasound stimulation but still incorporating our <a href="https://2016.igem.org/Team:Slovenia/Notebook/Proposals">initial idea of fast response</a> <a href = "#fig3">Figure 1</a>. </p><p style = "clear:both;"></p> ';
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<img class="ui medium image" src="//2016.igem.org/wiki/images/4/44/T--Slovenia--HP-4.png" > \
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  <figcaption><b>Figure 1: Team members in discussions with radiologist doc. dr. Katarina Šurlan Popovič.</b><br/></figcaption> \
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</figure> \
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</div> \
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<p>Whereas researchers are interested primarily on foundational advance, medical doctors who work with patients every day are more prone to search for readily applicable and patient oriented implications. \
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After deciding to focus on ultrasound stimulation we decided to consult medical experts in the field of radiology for advice and consultation. For that reason, we talked to doc. dr. Katarina Šurlan Popovič, MD, radiologist in order to present her our idea and hear her ideas. She was fascinated with potential connection of computed tomography (CT) and ultrasound (US) in order to obtain the benefit for patients. We are quoting her “I would really like to see you develop the model for US stimulation and be the first to try it!”. We took her eagerness to heart and decided to develop a model of ultrasound propagation through the tissue which could show us how in the future an individualized approach could be used. For instance, CT would be obtained for each patient and program would identify the tissue by their characteristics and position the US probes to obtain <a href="https://2016.igem.org/Team:Slovenia/Model">focused regions of high pressure on the selected part of the brain</a> <a href = "#fig4">Figure 1</a>. </p> \
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<div style = "clear: both; float:left"> \
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<figure id = "fig5"> \
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<img class="ui medium image" src="//2016.igem.org/wiki/images/f/fa/T--Slovenia--HP-5.png" > \
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  <figcaption><b>Figure 2: Team members presenting and discussing the Sonicell project with a hematologist dr. Matjaž Sever.</b><br/></figcaption> \
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</figure> \
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</div> \
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<p>By exploring further potential applications and reading the literature, asist. dr. Matjaž Sever, MD hematologist offered us help in his area of expertise. He went even a step further – by acknowledging how demanding the project is and how incredible it seems to develop it in half a year, he suggested making the list of all the potential hormones, peptides and proteins which might benefit if secreted by our quick system. Even when the iGEM competition finishes, our work does not – it is just a new beginning for more amazing findings to happen. It is not realistic to expect from us to start a project from scratch and develop something completely new in that short amount of time and optimize everything for medical usage. For that reason, our human practice investigation helped us realize how potentially beneficial our project can be in medicine and make long term partnerships and plans. If one could make a significant medical application, that person should have started from already known foundations. We did not. Instead, we are making the paradigm shift which will for sure find several applications in near future, maybe even by some future iGEM teams <a href = "#fig5">Figure 2</a>. </p><p style = "clear:both;"></p>';
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<b style = "margin-left: 12%">ultrasound propagation</b>
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                    <b>CaPTURE software</b>
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<div class="article" id="context">
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<!-- menu goes here -->
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<div class="main ui citing justified container"><h1><span class = "section colorize"> &nbsp; </span>Modeling of ultrasound propagation</h1>
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<div class = "ui segment" style = "background-color: #ebc7c7; ">
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<p><b><ul><li>We generated a model for the propagation of the ultrasound waves through tissue.
 +
<li>The source is available under GNU general public licence on <a href = "https://github.com/zigapusnik/UltrasoundPropagationModel">GitHub.</a>
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</ul></b></p>
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<div class = "ui segment">
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<h3><span id = "intro" class = "section colorize"> &nbsp; </span></h3>
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<p>Ultrasound are sound waves with frequencies higher than upper audible limit of human hearing, i.e. higher than 20 kHz.
 +
In the frequency range between 0.8 and 5 Mhz, the sound wave length is between 2 and 0.3 mm. Ultrasound is mainly used for diagnostic
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purposes. Unlike light ultrasound can easily penetrate the tissue and is at those intensities completely harmless. It is therefore used also in
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prenatal diagnostics where non-invasivness is of vital importance. Short wavelengths additionally enable us to create small regions of high intensity focused ultrasound waves at the focal point,
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which can be used for therapeutic purposes <x-ref>escoffre2016therapeutic</x-ref> for example for the tissue ablation. High intensity focused
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ultrasound has been already used in thermal ablation therapies <x-ref>escoffre2016therapeutic</x-ref>. In vital organs like brain it is particularly
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important to focus high intensity ultrasound beams at the small targeted structure in order to avoid unwanted tissue damage.
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</p>
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<p>
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Based on our improvement of the ultrasound responsiveness of the cells it would be feasible to introduce a genetic device into the target tissue and then selectively activate only specific cells by using focused ultrasound, causing a sufficient intensity of the acoustic pressure. This would for example enable the stimulation of neurons in the selected brain section to achieve non-invasive deep brain stimulation or to stimulate cells to produce different hormones.
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</p>
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<p>
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For this purpose we designed a model of the ultrasound propagation. The model can guide us in the process of the ultrasound device calibration with the potential to use multiple ultrasound probes.
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</p>
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</div>
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<!--<div>
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<h2><span id ="usesInMedicine" class = "section colorize"> &nbsp; </span>Use of high intensity focused ultrasound in medicine</h2>
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<p>
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Parkinson&#39;s disease (PD) is considered as the most frequent movement disorder. At the same time, it also represents second most common
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neurodegenerative disorder, affecting from 1 to 2% of people older than 60 years
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<x-ref>Li2016</x-ref>. According to our current understanding of the disease, it is caused by loss
 +
of dopaminergic neurons form substantia nigra pars compacta. The loss of
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neurons clinically presents with classical triad of PD symptoms: tremor, rigidity
 +
and bradikynesia <x-ref>kumar2014robbins</x-ref>.
 +
Considering PD treatment, there are two main possibilities. We can ascribe
 +
different types of pharmacological treatments to one group of treatment
 +
strategies and newly developed non-pharmacological therapeutic strategies e.g.
 +
deep brain stimulation to another <x-ref>Oertel2016, Li2016</x-ref>.
 +
Among pharmacological treatments, levodopa treatment is considered as first
 +
symptomatic and the most effective treatment of dopaminergic deficit. However,
 +
main reported problem of long term use of levodopa as intervention of PD is
 +
different types of motor complications <x-ref>Oertel2016</x-ref>.
 +
On the other hand, deep brain stimulation represents the treatment strategy for
 +
parkinsonian motor symptoms. In this procedure the electrode is placed in one
 +
of the two most hyperactive nuclei in those with PD, i.e. globus pallidus internus
 +
(GPi) or subthalamic nucleus (STN) <x-ref>Baizabal-Carvallo2016, Li2016</x-ref>. Using this
 +
approach bradykinesia and rigidity are substantially improved, more than 50% reduction of medication use in case of STN stimulation
 +
is also reported <x-ref>Oertel2016</x-ref>. On the other hand, there is significant evidence that deep brain
 +
simulation can worsen motor functioning also influencing physiological neural
 +
activity. Therefore, there is hypothesis that deep brain stimulation could be more
 +
effective when the diencephalon region is stimulated only when necessary
 +
<x-ref>Beudel2015</x-ref>.
 +
With our model, we are aiming to show the ultrasound interference in brain
 +
tissue. We additionally demonstrate how to focus ultrasound to specific point using two ultrasound
 +
probes. Using our system, one can achieve stimulation of certain population of
 +
cells only when required and so avoid unwanted side effects of deep brain
 +
stimulation.
 +
</p>
 +
</div> -->
 +
<h1 class = "ui left dividing header"><span class="section colorize">&nbsp;</span>Modeling</h1>
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<div class = "ui segment">
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<h3><span id = "mod" class = "section colorize"> &nbsp; </span>Sound modeling with wave equation</h3>
 +
<p>The code for the ultrasound propagation model is written in C++ programming language with OpenGL library. The model was parallelized using OpenMP to take advantage of multi-core processor architecture and to achieve better performance. Source code is available on <a href = "https://github.com/zigapusnik/UltrasoundPropagationModel">GitHub.</a></p>
 +
<br />
 +
<p>
 +
Sound is a vibration that propagates as a mechanical wave of pressure and displacement through the medium. The speed of its propagation also depends on the properties of the medium.
 +
This means that the speed of sound varies greatly between different types of tissues <x-ref>azhari2010basics</x-ref>. The speed of sound propagation in different tissue in comparison to its propagation through air is represented in <ref>2</ref>.
 +
</p>
 +
 +
<table class="ui fixed single collapsing line celled table" data-ref="2">
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<thead>
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<tr>
 +
<th>Name</th>
 +
<th>Speed (m/s)</th>
 +
</tr>
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</thead>
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<tbody>
 +
<tr>
 +
<td>Skin</td>
 +
<td>1730</td>
 +
</tr>
 +
<tr>
 +
<td>White matter</td>
 +
<td>1570</td>
 +
</tr>
 +
<tr>
 +
<td>Grey matter</td>
 +
<td>1570</td>
 +
</tr>
 +
<tr>
 +
<td>Skull</td>
 +
<td>4080</td>
 +
</tr>
 +
<tr>
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<td>Cerebrospinal Fluid</td>
 +
<td>1500</td>
 +
</tr>
 +
<tr>
 +
<td>Air</td>
 +
<td>343</td>
 +
</tr>
 +
</tbody>
 +
</table>
 +
<br />
 +
<br />
 +
<p>
 +
In order to achieve a realistic simulation of the sound propagation through brain an MR image represented in <ref>3</ref> was used <x-ref>mollerpocket</x-ref>. Furthermore, we performed the tissue segmentation with the aid of medical experts, i.e. our team members, students of medicine (Kosta, Samo and Nina) (<ref>4</ref>).
 +
</p>
 +
<div style = "float:left; width:50%;">
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<figure data-ref="3">
 +
<img src="//2016.igem.org/wiki/images/0/0b/T--Slovenia--Head.png">
 +
<figcaption>
 +
<b>An MR of transversal cut at the middle head area.</b>
 +
</figcaption>
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</figure>
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</div>
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<div style = "float: left; width:50%;">
 +
<figure data-ref="4">
 +
<img src="//2016.igem.org/wiki/images/f/f8/T--Slovenia--Segm_head.jpg"> </img>
 +
<figcaption><b>The segmentation of head section.</b>
 +
<p style="text-align:justify">The green color represents skin, blue color represents bone, cyan color represents the
 +
cerebrospinal fluid, dark grey color represents grey brain matter and light grey color represents white brain matter. Since the speed of sound does not vary
 +
much between dark and white grey matter it is sufficient to model only brain matter in general.</figcaption>
 +
</p>
 +
</figure>
 
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+
<img src = "//2016.igem.org/wiki/images/a/a8/T--Slovenia--GaussianBeam.jpg"> </img>
<div class="main ui citing justified container"><h1 class = "ui left dividing header"><span class="section">&nbsp;</span>Integrated Practices</h1>
+
<figcaption><b>The representation of a Gaussian beam function in two dimensions using a probe with a focus of 7 cm.</b>
<div class = "ui segment">
+
<p style="text-align:justify">Although focusing is not good, one can notice the elongation of a focused area. This is the case even in simulation with higher frequencies. This suggests that efficient focusing in the tissue requires at least two probes.</figcaption>
<p>Various extraordinary synthetic biology projects can be depicted as boats and ships, seeking the safety of a harbor in the wide ocean, their main purpose
+
</p>
finding the final destination.</p>
+
</figure>
<p>No matter how different or fascinating the boat is, its main purpose is to safely arrive to the harbor. Before there were modern GPS systems, sailors
+
</div>
had to rely on using natural events and signs. One of the main was the lodestar, the most shining star, which is always a good orientation point.</p>
+
<p>
<p>Similarly, many research projects can struggle no matter how fascinating they are. They might lose the feeling of reality and just travel for the sake of travel.</p>
+
The probes in our model are capable of emitting sound waves at frequencies ranging from 0.5 Mhz to 5 Mhz at acoustic pressure from 10 kPa to 100 kPa. The focused probes that we used have focal length of 7 cm. Besides focused probes we also modelled unfocused probes. Both types of probes have an aperture of 4.4 cm.
<p>In order to give the right coordinates, which showed to be of high importance in our case, we developed a new symbol for future iGEM teams who might apply their
+
In general propagation of sound from the focused probe can be approximated with an analytic function of a Gaussian beam (<ref>6</ref>), but this representation fails when we want to model wave interferences from multiple probes. For such cases wave equation model needs to be established.  
projects to the medical field – community oriented lodestar. No matter if the team is competing in the foundational advance or medical application section, maximization
+
</p>
of benefit to society should be the number one priority.</p>
+
<p style = "clear:left;">
 +
Acoustic wave equation is a second-order linear partial differential equation that governs the propagation of acoustic waves through the medium. The general form of the equation is:
  
<div style = "display:block; width: 100%; margin-left:auto; margin-right:auto;" align = "center">
+
\begin{equation}
<div style = "width:40%;">
+
\frac{\partial^2 p}{\partial t^2} = c^2(\nabla^2 p)
                                    <img width="100%" onresize="relativeCoordsStar();" onload="relativeCoordsStar();"
+
\end{equation}
                                        style="border-radius: 15px;"
+
 
                                        src="//2016.igem.org/wiki/images/3/30/T--Slovenia--LoadStar-v5-01.png"
+
where $c$ is speed of sound in the medium, $p$ is acoustic pressure (the deviation from ambient pressure) and $\nabla^2$ is Laplacian operator (sum of second order partial derivatives with respect to each independent variable). In two dimensional Cartesian coordinate system we get the following equation:
                                        alt="project scheme" usemap="#starMap" id="starScheme"/>
+
 
<map name="starMap">
+
\begin{equation}
                                        <area id="patients" shape="poly" coords="" alt="patients"
+
\frac{\partial^2 p}{\partial t^2} = c^2(\frac{\partial^2 p}{\partial x^2} + \frac{\partial^2 p}{\partial y^2})
                                              onmouseover="loadImage('//2016.igem.org/wiki/images/4/4b/T--Slovenia--LoadStar-v5-1-01.png', 'patients')"
+
\end{equation}
                                              onmouseout="loadImage('//2016.igem.org/wiki/images/3/30/T--Slovenia--LoadStar-v5-01.png', 'patients')" onClick = "setTekst('patients');">
+
 
                                        <area id="scientists" shape="poly" coords="" alt="scientists"
+
While wave equation cannot be solved analytically, one can approximate it with finite difference method. Let's presume we want to approximate the solution on a squared area. First, we need to discretize the area to obtain the grid of evenly distributed points $(x_{i}, y_{j})$, $i,j = 1,...,n$. The Laplacian operator can now be approximated as:
                                              onmouseover="loadImage('//2016.igem.org/wiki/images/1/14/T--Slovenia--LoadStar-v5-2-01.png', 'scientists')"
+
 
                                              onmouseout="loadImage('//2016.igem.org/wiki/images/3/30/T--Slovenia--LoadStar-v5-01.png', 'scientists')" onClick = "setTekst('scientists');">
+
\begin{equation}
                                        <area id="iGEMers" shape="poly" coords="" alt="iGEMers"
+
\nabla^2 p_{i, j} \approx \frac{1}{h^2}(p_{i + 1, j} + p_{i-1, j} + p_{i, j + 1} + p_{i, j - 1} - 4p_{i,j})
                                              onmouseover="loadImage('//2016.igem.org/wiki/images/b/b7/T--Slovenia--LoadStar-v5-3-01.png', 'iGEMers')"
+
\end{equation}
                                              onmouseout="loadImage('//2016.igem.org/wiki/images/3/30/T--Slovenia--LoadStar-v5-01.png', 'iGEMers')" onClick = "setTekst('iGEMers');">
+
 
                                        <area id="researches" shape="poly" coords="" alt="researches"
+
where $h$ is Euclidean distance between two adjacent points. Since the frequencies between 0.8 and 5 Mhz correspond to the wavelength between 2 and 0.3 mm, $h$ does not need to be smaller than 0.3 mm. We now obtain a $n*n$ system of the second order ordinary differential equations:
                                              onmouseover="loadImage('//2016.igem.org/wiki/images/e/e7/T--Slovenia--LoadStar-v5-4-01.png', 'researches')"
+
 
                                              onmouseout="loadImage('//2016.igem.org/wiki/images/3/30/T--Slovenia--LoadStar-v5-01.png', 'researches')" onClick = "setTekst('researches');">
+
\begin{equation}
                                        <area id="doctors" shape="poly" coords="" alt="doctors"
+
\ddot{p}_{i, j} = \frac{c^2}{h^2}(p_{i + 1, j} + p_{i-1, j} + p_{i, j + 1} + p_{i, j - 1} - 4p_{i,j})
                                              onmouseover="loadImage('//2016.igem.org/wiki/images/2/2d/T--Slovenia--LoadStar-v5-5-01.png', 'doctors')"
+
\end{equation} 
                                              onmouseout="loadImage('//2016.igem.org/wiki/images/3/30/T--Slovenia--LoadStar-v5-01.png', 'doctors')" onClick = "setTekst('doctors');">  
+
 
</map>
+
These equation can be simplified to the first order differential equations with the introduction of a new variable that represents the speed: $(v_{i, j} = \dot{p}_{i, j})$. The new system now has the following form:
 +
\begin{equation}
 +
\begin{aligned}
 +
\dot{p}_{i, j} = v_{i, j} \\
 +
\dot{v}_{i, j} = \frac{c^2}{h^2}(p_{i + 1, j} + p_{i-1, j} + p_{i, j + 1} + p_{i, j - 1} - 4p_{i,j})
 +
\end{aligned}
 +
\end{equation}
 +
 
 +
The dispersion of the waves is already included in the wave equation. However, the absorption of sound waves in tissue is not included. The absorption can be approximated with the introduction of the attenuation coefficient $k$. We fitted attenuation coefficient to experimental data <x-ref>sprawls1989ultrasound</x-ref> to obtain, $k = 16000$ for soft tissue and $k = 160000$ for bone tissue.
 +
The final equation now has the form:
 +
\begin{equation}
 +
\dot{v}_{i, j} = \frac{c^2}{h^2}(p_{i + 1, j} + p_{i-1, j} + p_{i, j + 1} + p_{i, j - 1} - 4p_{i,j}) - k*v_{i,j}
 +
\end{equation}
 +
</p>
 +
<div style = "float:left; width:47%">
 +
<figure data-ref="5">
 +
<img src="//2016.igem.org/wiki/images/a/ab/T--Slovenia--Scheme.png" >
 +
<figcaption>
 +
<b>A flowchart representing an iterative computation of wave equation.</b>
 +
</figcaption>
 +
</figure>
 +
</div>
 +
<p>
 +
Finally we can solve the given system with iterative numeric methods such as Euler's method or Runge-Kutta method. The most widely known method of the Runge-Kutta family is RK4, which was also used in our model.  
 +
While RK4 introduces some computational overhead it also significantly increases the numerical stability of the system in comparison to the Euler's method.
 +
The most basic steps used for the calculation of ultrasound propagation are displayed in (<ref>5</ref>).
 +
</p>
 +
<p>
 +
We model a propagation of the ultrasound waves on a 500 x 500 grid, where distances between points are exactly 0.3 cm. This translates to a stimulated area of 15 by 15 cm.  
 +
The model computes propagation of waves in 2 dimensions. While the computational complexity of calculating the solutions of wave equation in 3 dimensions is asymptotically much higher than in 2 dimensional space, it is unnecessary to demonstrate the ability to focus the ultrasound by modulation of the intensity, frequency and geometry of the ultrasound probes.  
 +
However, in 3 dimensional space the intensity in the focal point should increase, since addition of sound waves is coming from all directions not just from left and right. Three or more probes could be combined to define the focal point in 3D. In our model it is also possible to observe the main sound characteristics such as the attenuation, reflection and occlusion. Probes are modelled as the set of finite elements. The pressure of every finite element on the probe is set according to sine function with the selected amplitude and frequency, thus every finite element acts like independent source of the acoustic pressure.
 +
</p>
 +
</div>
 +
<div>
 +
<h1><span id = "res" class = "section colorize"> &nbsp; </span>Results</h1>
 +
<div class = "ui segment">
 
 
</div>
+
<p>
<div class = "ui segment">
+
Simulations computed with our model (<ref>7</ref>) clearly show that it is possible to target small regions of brain tissue. We can also observe the one dimensional cut of acoustic pressure, where focusing is even more evident (<ref>8</ref>). The probe on the right is slightly displaced due to the asymmetry of the tissue. This clearly shows that models need to be applied to calculate the optimal position of ultrasound probes.
<div id = "tekst" data = "empty"><h3 id="THEstar">For content click on THE star</h3></div>
+
Such software will include automatic tissue segmentation, modeling of propagation of ultrasound waves and will assist experts in probe positioning. Our model is a step in that direction, since it can be used as a tool for positioning the probes. In the model that we generated focused and unfocused probes can be added or removed and positioned. Additionally, probe's acoustic pressure and frequency can be set. 
</div>
+
</p>
</div>
+
<div align = "center">
+
<figure data-ref="7">
<p style = "clear:both;"><br />Consequently, if ever lost, teams should just find the shining star and orient in respect to it. By thorough discussions and careful implementation of ideas
+
<img class="playGif ui big centered image" src="//2016.igem.org/wiki/images/4/4a/T--Slovenia--USModelThumbnail.png" data-alt="//2016.igem.org/wiki/images/c/c0/T--Slovenia--Usmodel.gif">
provided by all the participants involved in dialogue, iGEM team should be able to present at the Giant Jamboree the most of the project –completely analyzed project
+
<figcaption><b>The propagation of ultrasound waves through brain tissue as computed with our model.</b>
in real life. It’s not only the idea that influences the minds and thinking of individuals involved, but the relationship is reciprocal. The people involved have a great
+
<p style="text-align:justify">One can observe the small focused area in the middle of the brain (Fornix). We can also detect green specks in the bone region, which are caused by the reflection of the sound waves. Since the speed of sound in the bone is much higher than the speed in soft tissue, the acoustic wavelengths in the bone are increased.
deal of influence over the idea itself as well. The concept will be explained on our example. While we are competing in the foundational advance track we have considered
+
</p>
many possible medical applications of our project, particularly diabetes, Parkinson’s disease and hemorrhagic diseases, since medicine is the field of study of several
+
</figcaption>
students and other students and mentors have a soft spot for this direction. .</p>
+
</figure>
+
</div>
+
</div>
+
 
</div>
 
</div>
 +
<div align = "center">
 +
<figure data-ref="8" align = "center">
 +
<img class="playGif ui big centered image" src="//2016.igem.org/wiki/images/c/cc/T--Slovenia--1dThumbnail.png" data-alt="//2016.igem.org/wiki/images/7/7b/T--Slovenia--Us1d.gif">
 +
<figcaption><b>The vertical cut of the acoustic pressure through the focal point.</b>
 +
<p style="text-align:justify">The waves that travel from the right to the left, are slightly deformed on the right side due to the wave interferences from two separate probes.
 +
</p></figcaption>
 +
</figure>
 +
</div>
 +
</div>
 +
<div>
 +
<div class = "ui segment">
 +
<h3><span id="con" class = "section colorize"> &nbsp; </span>Conclusion and outlook</h3>
 +
<p>
 +
We generated a model for the propagation of the ultrasound waves through tissue. In our case a transversal cut of the middle head area was taken. Two probes were adjusted in such a manner that the focusing on small area was obtained.
 +
With this model we can confirm the potential to use the ultrasound as a platform for therapeutic applications, but for more advanced use the software tools needs to be further developed. Further development will include automatic tissue segmentation from patient medical images, computing propagation of ultrasound waves in 3 dimensions aimed to guide the experts with the probe positioning.
 +
The low intensity ultrasound image could be used to receive the feedback of the sonogram of the tissue for each probe that could be used to drive ultrasound stimulation for cell activation in the desired area. It is likely that the specific shape of the stimulated tissue could be selected rather than just a single focal point.
 +
</p>
 +
</div>
 +
<div>
 +
<h1 class = "ui left dividing header"><span id="ref-title" class = "section colorize">&nbsp; </span>References</h1>
 +
<div class = "ui segment">
 +
<div class="citing" id="references"></div>
 +
</div>
 +
</div>
 
</div>
 
</div>
 +
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$( document ).ready( function() {
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$('.playGif').on('click', function() {
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<div>
 
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<a href="//igem.org/Main_Page">
 
<a href="//igem.org/Main_Page">
 
<img border="0" alt="iGEM" src="//2016.igem.org/wiki/images/8/84/T--Slovenia--logo_250x250.png" width="5%" style = "position: fixed; bottom:0%; right:1%;">
 
<img border="0" alt="iGEM" src="//2016.igem.org/wiki/images/8/84/T--Slovenia--logo_250x250.png" width="5%" style = "position: fixed; bottom:0%; right:1%;">
 
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Latest revision as of 14:47, 19 October 2016

Ultrasound propagation modeling

  Modeling of ultrasound propagation

  • We generated a model for the propagation of the ultrasound waves through tissue.
  • The source is available under GNU general public licence on GitHub.

 

Ultrasound are sound waves with frequencies higher than upper audible limit of human hearing, i.e. higher than 20 kHz. In the frequency range between 0.8 and 5 Mhz, the sound wave length is between 2 and 0.3 mm. Ultrasound is mainly used for diagnostic purposes. Unlike light ultrasound can easily penetrate the tissue and is at those intensities completely harmless. It is therefore used also in prenatal diagnostics where non-invasivness is of vital importance. Short wavelengths additionally enable us to create small regions of high intensity focused ultrasound waves at the focal point, which can be used for therapeutic purposes escoffre2016therapeutic for example for the tissue ablation. High intensity focused ultrasound has been already used in thermal ablation therapies escoffre2016therapeutic. In vital organs like brain it is particularly important to focus high intensity ultrasound beams at the small targeted structure in order to avoid unwanted tissue damage.

Based on our improvement of the ultrasound responsiveness of the cells it would be feasible to introduce a genetic device into the target tissue and then selectively activate only specific cells by using focused ultrasound, causing a sufficient intensity of the acoustic pressure. This would for example enable the stimulation of neurons in the selected brain section to achieve non-invasive deep brain stimulation or to stimulate cells to produce different hormones.

For this purpose we designed a model of the ultrasound propagation. The model can guide us in the process of the ultrasound device calibration with the potential to use multiple ultrasound probes.

 Modeling

  Sound modeling with wave equation

The code for the ultrasound propagation model is written in C++ programming language with OpenGL library. The model was parallelized using OpenMP to take advantage of multi-core processor architecture and to achieve better performance. Source code is available on GitHub.


Sound is a vibration that propagates as a mechanical wave of pressure and displacement through the medium. The speed of its propagation also depends on the properties of the medium. This means that the speed of sound varies greatly between different types of tissues azhari2010basics. The speed of sound propagation in different tissue in comparison to its propagation through air is represented in 2.

Name Speed (m/s)
Skin 1730
White matter 1570
Grey matter 1570
Skull 4080
Cerebrospinal Fluid 1500
Air 343


In order to achieve a realistic simulation of the sound propagation through brain an MR image represented in 3 was used mollerpocket. Furthermore, we performed the tissue segmentation with the aid of medical experts, i.e. our team members, students of medicine (Kosta, Samo and Nina) (4).

An MR of transversal cut at the middle head area.
The segmentation of head section.

The green color represents skin, blue color represents bone, cyan color represents the cerebrospinal fluid, dark grey color represents grey brain matter and light grey color represents white brain matter. Since the speed of sound does not vary much between dark and white grey matter it is sufficient to model only brain matter in general.

The representation of a Gaussian beam function in two dimensions using a probe with a focus of 7 cm.

Although focusing is not good, one can notice the elongation of a focused area. This is the case even in simulation with higher frequencies. This suggests that efficient focusing in the tissue requires at least two probes.

The probes in our model are capable of emitting sound waves at frequencies ranging from 0.5 Mhz to 5 Mhz at acoustic pressure from 10 kPa to 100 kPa. The focused probes that we used have focal length of 7 cm. Besides focused probes we also modelled unfocused probes. Both types of probes have an aperture of 4.4 cm. In general propagation of sound from the focused probe can be approximated with an analytic function of a Gaussian beam (6), but this representation fails when we want to model wave interferences from multiple probes. For such cases wave equation model needs to be established.

Acoustic wave equation is a second-order linear partial differential equation that governs the propagation of acoustic waves through the medium. The general form of the equation is: \begin{equation} \frac{\partial^2 p}{\partial t^2} = c^2(\nabla^2 p) \end{equation} where $c$ is speed of sound in the medium, $p$ is acoustic pressure (the deviation from ambient pressure) and $\nabla^2$ is Laplacian operator (sum of second order partial derivatives with respect to each independent variable). In two dimensional Cartesian coordinate system we get the following equation: \begin{equation} \frac{\partial^2 p}{\partial t^2} = c^2(\frac{\partial^2 p}{\partial x^2} + \frac{\partial^2 p}{\partial y^2}) \end{equation} While wave equation cannot be solved analytically, one can approximate it with finite difference method. Let's presume we want to approximate the solution on a squared area. First, we need to discretize the area to obtain the grid of evenly distributed points $(x_{i}, y_{j})$, $i,j = 1,...,n$. The Laplacian operator can now be approximated as: \begin{equation} \nabla^2 p_{i, j} \approx \frac{1}{h^2}(p_{i + 1, j} + p_{i-1, j} + p_{i, j + 1} + p_{i, j - 1} - 4p_{i,j}) \end{equation} where $h$ is Euclidean distance between two adjacent points. Since the frequencies between 0.8 and 5 Mhz correspond to the wavelength between 2 and 0.3 mm, $h$ does not need to be smaller than 0.3 mm. We now obtain a $n*n$ system of the second order ordinary differential equations: \begin{equation} \ddot{p}_{i, j} = \frac{c^2}{h^2}(p_{i + 1, j} + p_{i-1, j} + p_{i, j + 1} + p_{i, j - 1} - 4p_{i,j}) \end{equation} These equation can be simplified to the first order differential equations with the introduction of a new variable that represents the speed: $(v_{i, j} = \dot{p}_{i, j})$. The new system now has the following form: \begin{equation} \begin{aligned} \dot{p}_{i, j} = v_{i, j} \\ \dot{v}_{i, j} = \frac{c^2}{h^2}(p_{i + 1, j} + p_{i-1, j} + p_{i, j + 1} + p_{i, j - 1} - 4p_{i,j}) \end{aligned} \end{equation} The dispersion of the waves is already included in the wave equation. However, the absorption of sound waves in tissue is not included. The absorption can be approximated with the introduction of the attenuation coefficient $k$. We fitted attenuation coefficient to experimental data sprawls1989ultrasound to obtain, $k = 16000$ for soft tissue and $k = 160000$ for bone tissue. The final equation now has the form: \begin{equation} \dot{v}_{i, j} = \frac{c^2}{h^2}(p_{i + 1, j} + p_{i-1, j} + p_{i, j + 1} + p_{i, j - 1} - 4p_{i,j}) - k*v_{i,j} \end{equation}

A flowchart representing an iterative computation of wave equation.

Finally we can solve the given system with iterative numeric methods such as Euler's method or Runge-Kutta method. The most widely known method of the Runge-Kutta family is RK4, which was also used in our model. While RK4 introduces some computational overhead it also significantly increases the numerical stability of the system in comparison to the Euler's method. The most basic steps used for the calculation of ultrasound propagation are displayed in (5).

We model a propagation of the ultrasound waves on a 500 x 500 grid, where distances between points are exactly 0.3 cm. This translates to a stimulated area of 15 by 15 cm. The model computes propagation of waves in 2 dimensions. While the computational complexity of calculating the solutions of wave equation in 3 dimensions is asymptotically much higher than in 2 dimensional space, it is unnecessary to demonstrate the ability to focus the ultrasound by modulation of the intensity, frequency and geometry of the ultrasound probes. However, in 3 dimensional space the intensity in the focal point should increase, since addition of sound waves is coming from all directions not just from left and right. Three or more probes could be combined to define the focal point in 3D. In our model it is also possible to observe the main sound characteristics such as the attenuation, reflection and occlusion. Probes are modelled as the set of finite elements. The pressure of every finite element on the probe is set according to sine function with the selected amplitude and frequency, thus every finite element acts like independent source of the acoustic pressure.

  Results

Simulations computed with our model (7) clearly show that it is possible to target small regions of brain tissue. We can also observe the one dimensional cut of acoustic pressure, where focusing is even more evident (8). The probe on the right is slightly displaced due to the asymmetry of the tissue. This clearly shows that models need to be applied to calculate the optimal position of ultrasound probes. Such software will include automatic tissue segmentation, modeling of propagation of ultrasound waves and will assist experts in probe positioning. Our model is a step in that direction, since it can be used as a tool for positioning the probes. In the model that we generated focused and unfocused probes can be added or removed and positioned. Additionally, probe's acoustic pressure and frequency can be set.

The propagation of ultrasound waves through brain tissue as computed with our model.

One can observe the small focused area in the middle of the brain (Fornix). We can also detect green specks in the bone region, which are caused by the reflection of the sound waves. Since the speed of sound in the bone is much higher than the speed in soft tissue, the acoustic wavelengths in the bone are increased.

The vertical cut of the acoustic pressure through the focal point.

The waves that travel from the right to the left, are slightly deformed on the right side due to the wave interferences from two separate probes.

  Conclusion and outlook

We generated a model for the propagation of the ultrasound waves through tissue. In our case a transversal cut of the middle head area was taken. Two probes were adjusted in such a manner that the focusing on small area was obtained. With this model we can confirm the potential to use the ultrasound as a platform for therapeutic applications, but for more advanced use the software tools needs to be further developed. Further development will include automatic tissue segmentation from patient medical images, computing propagation of ultrasound waves in 3 dimensions aimed to guide the experts with the probe positioning. The low intensity ultrasound image could be used to receive the feedback of the sonogram of the tissue for each probe that could be used to drive ultrasound stimulation for cell activation in the desired area. It is likely that the specific shape of the stimulated tissue could be selected rather than just a single focal point.

  References