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Creating in-vitro phantoms of blood vessels to support the testing and validation of new ultrasonic blood flow imaging techniques Guillaume Pattyn Supervisors: Prof. dr. ir. Abigaïl Swillens, Prof. dr. ir. Patrick Segers Master's dissertation submitted in order to obtain the academic degree of Master of Science in de industriële wetenschappen: elektromechanica Department of Electronics and Information Systems Chair: Prof. dr. ir. Rik Van de Walle Faculty of Engineering and Architecture Academic year 2015-2016 i Creating in-vitro phantoms of blood vessels to support the testing and validation of new ultrasonic blood flow imaging techniques Guillaume Pattyn Supervisors: Prof. dr. ir. Abigaïl Swillens, Prof. dr. ir. Patrick Segers Master's dissertation submitted in order to obtain the academic degree of Master of Science in de industriële wetenschappen: elektromechanica Department of Electronics and Information Systems Chair: Prof. dr. ir. Rik Van de Walle Faculty of Engineering and Architecture Academic year 2015-2016 ii Permission The author(s) gives (give) permission to make this master dissertation available for consultation and to copy parts of this master dissertation for personal use. In the case of any other use, the copyright terms have to be respected, in particular with regard to the obligation to state expressly the source when quoting results from this master dissertation." 1-6-2016 iii Preface As a preface is often to no interest for most of the readers -if they even exist- I’ve shortly listed the people who helped me during the hatching of this thesis. Many thanks to Jurgen, Viviana, Daniela, Frank, Stefan, Patrick for the things they know they’ve helped me with. I also would like to thank prof. Swillens and prof. Segers for sincerely helping when problems occurred. The choice for a certain subject is partially based on the people you meet the moment you enter a new environment. It is unfortunate for Joris that he decided to change tracks, although it remains strange how everyone unconsciously follows the standard road. I wish him all the best, wherever on the globe he may be cycling. Lastly, I want to thank my family for their unconditional support. iv Extended Abstract Creating in-vitro phantoms of blood vessels to support the testing and validation of new ultrasonic blood flow imaging techniques Guillaume Pattyn Abstract: Ultrasound has proven to be a versatile technique, and its applications could be broadened by focussing on the visualization of perfusion throughout the microcirculatory system. This implies the use of high-frequency imaging (>15 MHz) which augments the spatial resolution needed to detect small capillaries. The main goal of this thesis is to quantify the accuracy of flow estimations when using high frequencies, with variation in depth, vessel size, flow speed and frequency itself. To do so, an experimental set-up has been made, based on the possibilities described in the literature. The first part elaborates on the attempted methods to produce such a phantom, describing what went wrong and which methods did prove to work. The second part consists of conducting experiments on the developed phantom. Theoretical flow speeds were compared to the measured ones when using a Visualsonics (16-32 MHz) echography machine, and a conventional GE Vivid 7 (5-9 MHz) apparatus. The results showed a high accuracy for spectral PW as well as Colour Doppler measurements. Further testing should be done using perfused ex-vivo tissue to investigate complex fractional structures. The third part comprises the production of a 3D model of the Circle of Willis. As this region is crucial to the perfusion of the brain, the model could simulate problematic flow inputs, and the results could be validated using 3D printed version of the geometry in an in-vitro setting. Keywords: high-frequency ultrasound, microcirculation, flow phantoms, Circle of Willis Introduction Part I: Phantom construction The ability to look inside the human body, without the need for invasive surgery has always been of great value to physicians. Many imaging techniques rely on the use of radioactivity, contrast agents or strong magnetic fields, making it perilous to utilize when severe health issues are present. One exception is ultrasound imaging which is until present considered being safe. It is also convenient to use because the machine can be brought to the patient, who doesn’t need to be sedated. But, the fairly low imaging resolution hampers the possibility to visualize microcirculation. To tackle this restriction, the frequency should be altered to higher levels (>15 MHz), which also leads to a decrease in penetration depth. This thesis focusses on the development of a flow phantom which mimics the microcirculation to a relevant precision. Afterwards, this phantom is used to check the accuracy of speed examinations by comparing the measured speed and the theoretical values. Materials and methods For the production of flow phantoms, two methods have been tested. The first method involved the use of several very thin wires (10-300 µm). Tube connectors were inserted through the opposing walls of a plastic container (96*96*62 mm) to leave an opening for the wires to be pulled through. The TMM consisted at first of a Gelatine/Agar/water mixture (resp. 8-3-89 wt.%) which is prepared by mixing the ingredients at 90 °C for the agar, and 65 °C for the gelatine, while continuously stirring. When the mixture was cooled down to somewhere around 40 °C, and all the gas bubbles had risen to the surface, it was poured into the plastic container. The box was put in the fridge for an overnight to fully solidify the TMM. Then the wires were pulled out of the TMM, hopefully resulting in hollow vessels in the TMM. The same procedure has been done using PVA (polyvinyl-alcohol, 99+ hydrolysed). A mixture of v PVA and water (10/90 wt.%) has been prepared using the same procedure as for the Gelatine/Agar, but the cooling stage consisted of putting the box into the freezer for 12h. Afterwards, it could be removed to let it thaw. The second construction was based on the use of hollow polyimide tubes, kindly donated by Microlumen® (100,155,165,178 µm). They were embedded in PVA which went through two freeze-thaw cycles. Hence optimal acoustic properties (vsound = 1535 cm/s) of the TMM could be achieved [2]. Results To fully understand what would happen when extracting the wires, the GE Vivid 7 echography machine was used to monitor the procedure (linear array transducer at 5.5 MHz, B-Mode). The PVA proved to be too flexible to keep the small vessels open. They immediately collapsed under the weight of the TMM lying above. Gelatine/Agar was rigid enough to keep the vessels down to 120 µm open, although artefacts appeared on the image. A syringe pump (Alaris Asena, pressure alarm set to maximum level = 1000 mmHg) was used to infuse the vessels, but the pressure rose until the alarm value was reached. The second design which uses the hollow tubes proved to be successful. Flow (pure water) could easily be generated. array probes (MS250 13-24 MHz, MS550S 32-56 MHz), and a GE Vivid 7 (linear array 5-9 MHz). The blood mimicking fluid was made using a mixture of nylon (Orgasol Arkema Caresse R) particles, with an average diameter of 5µm. Using a calibrated syringe pump, low flow speeds between 1-10 cm/s were generated inside the tubes. Results The measurements showed high accuracy of speed estimation in the 155 and 178 µm vessels. The proportional error on the estimation converged to zero when nearing 10 cm/s. The results at 16 MHz proved to be more consistent, whereas at 32 MHz occasional over and underestimation could be observed. The 100µm tube was problematic to infuse due to constant blockage, although the few successful measurements indicate that a stable set-up should provide accurate results. The precision of the colour Doppler was also analysed, and it proved to be less precise than spectral PW measurements. However, no aberration of factor 1.1-3.5 could be observed as described in the literature [3]. At last, the Vivid 7 was used to check the influence of imaging depth. An increase in underestimation could be observed at lower depths, probably resulting from a weaker echo signal. Discussion Discussion The vessel extraction method is by far the most adaptable way to create phantoms. But the vessel wall is prone to rupture, which causes premature blockages. Also, there is no control over the roughness of the interior of the vessels, which could have a drastic effect on the flow pattern. The hollow tubes proved to be successful. No excessive reflections arising from the polyimide tubes could be observed. Part II: Experiments Materials and methods The experiments were conducted using a flow phantom made as mentioned above (hollow tubes, PVA 2 ftc.). The experiments were done using a Visualsonics Vevo 2100 equipped with two linear The measurements have shown that down to 100µm, no problems could be observed when visualizing simple straight vessel systems. The velocity estimates proved that no challenges will arise at this level. Conclusion To fully investigate the problem, further measurements should be done on ex-vivo tissue. A microscope should be used to provide the ground truth while monitoring with the ultrasound machine. Hence, flow through complex structures comparable to the real body can be replicated, which is necessary to be conclusive on the ability of estimating perfusion at micro scale. ii List of figures ...........................................................................................................................................iii List of abbreviations .................................................................................................................................v Chapter 1. 1.1 Background knowledge ................................................................................................... 2 Ultrasound technology ............................................................................................................ 2 1.1.1 Sonar................................................................................................................................ 2 1.1.2 Ultrasound waves ............................................................................................................ 3 1.2 Echography .............................................................................................................................. 4 1.2.1 The Probe ........................................................................................................................ 4 1.2.2 Imaging modes ................................................................................................................ 5 1.2.3 Flow imaging.................................................................................................................... 6 1.2.4 Safety concerns ............................................................................................................... 8 1.3 Microcirculation ...................................................................................................................... 9 1.3.1 The human circulatory system ........................................................................................ 9 1.3.2 Special phenomena ......................................................................................................... 9 Chapter 2. Literature review ........................................................................................................... 11 2.1 Aim......................................................................................................................................... 11 2.2 Flow phantoms ...................................................................................................................... 12 2.2.1 Types.............................................................................................................................. 12 2.2.2 Tissue Mimicking Material............................................................................................. 17 2.2.3 BMF................................................................................................................................ 19 2.2.4 Pump.............................................................................................................................. 19 2.3 Chosen set-up(s) .................................................................................................................... 20 Chapter 3. 3.1 Production of the set-up ............................................................................................... 21 Set-up .................................................................................................................................... 21 3.1.1 Preparation of the TMM................................................................................................ 21 3.1.2 Blood mimicking fluid .................................................................................................... 22 3.2 Wire extraction phantom ...................................................................................................... 22 3.3 Hollow tube phantom ........................................................................................................... 23 3.4 Discussion .............................................................................................................................. 24 Chapter 4. Experiments ................................................................................................................... 26 4.1 Pressure test procedure ........................................................................................................ 26 4.2 PW flow speed measurements.............................................................................................. 27 4.2.1 Visual Sonics .................................................................................................................. 27 i 4.2.2 4.3 GE .................................................................................................................................. 31 Colour flow speed measurements ........................................................................................ 33 4.3.1 Visualsonics ................................................................................................................... 33 4.4 Flow profile monitoring ......................................................................................................... 34 4.5 Discussion .............................................................................................................................. 36 Chapter 5. 5.1 Extra: CFD ...................................................................................................................... 37 Introduction ........................................................................................................................... 37 5.1.1 Anatomical information ................................................................................................ 37 5.1.2 From images to model................................................................................................... 38 5.1.3 Real model ..................................................................................................................... 39 ii List of figures Figure 1 Active sonar relies on the emission and reception of a sound wave (Source: http://www.actus.info) ..................................................................................................................................................... 2 Figure 2 (L) longitudinal wave with zones of compression and rarefaction (R) Transverse wave moving up and down perpendicular to direction of wave [5] ............................................................................. 3 Figure 3 Reflected wave (ain=aout) and transmitted wave (ain ≠ aout) (Source: http://www.azooptics.com) .................................................................................................................... 4 Figure 4 Influence of transducer frequency on penetration depth [7] ................................................... 4 Figure 5 Schematic representation of a transducer (Source: http://www.nano-tera.ch) ...................... 5 Figure 6 (L) A-mode imaging: a peak is observed when a change in acoustic impedance is met [8] (M) B-mode image of a hollow vessel embedded in TMM. The reflective wall is represented by an elevated brightness (R) M-mode image of a moving mitral valve .......................................................... 6 Figure 7(L) Continuous wave Doppler used to monitor high flow speeds at the aortic valve [9] , (R)in A the beam and vessel are almost aligned, providing a decent frequency shift, in B and C the angle is smaller, resulting in a weaker signal and a bigger error (D) same is in A but inverted resulting in a negative speeds (Source: https://sonoworld.com) ................................................................................. 7 Figure 8 (L) Overview of the human circulatory system (Source: https://www.haikudeck.com) (R) Diameter and flow speeds of different types of vessels ......................................................................... 9 Figure 9 Formation of rouleaux [16] ..................................................................................................... 10 Figure 10 the use of clutter belts to evaluate the influence of wall motion on the Doppler shift. (L) wall and vessel are mimicked by a belt (R) vessel replicated by a hollow tube and wall motion provided by the belt [17] ....................................................................................................................... 13 Figure 11: (L) ex vivo artery made by LifeTecGroup (R) Comparison between the burst pressure of the same artery in and ex vivo (after preservation method) [18] ............................................................... 14 Figure 12 (L) .STL model (R) printed version of the circle of Willis ....................................................... 15 Figure 13 Scaffold made using two-photon polymerisation (2PP) [23] ................................................ 15 Figure 14 Solid ground curing process (Cubital), where the mask is translucent light-induced polymerisation will occur [21] ............................................................................................................... 16 Figure 15 Vertebra submerged in a TMM based on gelatine/agar [29] ............................................... 18 Figure 16: Influence of the amount of freeze-thaw cycles on (A) the attenuation (B) the speed of sound [2] The red line indicates the value of tissue, an optimum is found at 2 ftc ([30] ..................... 18 Figure 17 (A) Tensioned wires and connectors fitted through the wall, ready to pour the TMM (B) box from A filled with G/A, wires extracted and ready to perfuse .............................................................. 22 Figure 18 Rupture due to elevated pressure, initiated at the tube connector ..................................... 23 Figure 19 Final model before pouring the PVA ..................................................................................... 24 Figure 20 B-mode image of 1 longitudinal and 6 cross sections of 200µm silicon tubes. Distinct lumens can hardly be observed, and high reflections could impede precise measurements .............. 25 Figure 21 Variation of the pressure in time after setting a certain flow rate to the system. Convergence takes more than 20 minutes ........................................................................................... 26 Figure 22 Pressure test in stabilized conditions. No pulsatility can be detected. ................................. 27 Figure 23 Post-processing of a sonogram with the Vevo software package. The mean value can be traced automatically.............................................................................................................................. 28 Figure 24 Measured speeds vs. speed of infusion of a 178µm vessel .................................................. 29 iii Figure 25 Proportional error on speed measurements, both trend lines convergence to zero. .......... 30 Figure 26 Speed measurements within a 155 µm tube ........................................................................ 30 Figure 27 Proportional error on the speed measurement when infusing a 155 µm tube. At both frequencies, a convergence towards zero can be observed for higher flow speeds. ........................... 30 Figure 28 Flow speed measured through a 100 µm ID tube, a large spread in results can be observed due to clots shutting off the vessel ....................................................................................................... 31 Figure 29 Sonogram being processed using the Asklepios Matlab tool................................................ 32 Figure 30 Measured vs. True flow speed at 1.5cm (red) and 3cm (blue) ............................................. 32 Figure 31 Colour Doppler speed estimation in a 178 µm tube ............................................................. 33 Figure 32 Comparison between the flow profiles (speed vs. pixels) for different frequencies and different tube diameters ....................................................................................................................... 35 Figure 33 The colour Doppler image taken at (L) 16 MHz confines the flow quite precisely within the tube. At (R) 32 MHz a reflection of the tube can be observed. ............................................................ 35 Figure 34 Anatomical picture of the circle of Willis [1] ......................................................................... 37 Figure 35 (L) before trimming the excess branches (R) after trimming and smoothing ....................... 38 Figure 36 (up) CFD simulation of flow through the circle of Willis (down) zoomed image showing the individual vectors .................................................................................................................................. 39 iv List of abbreviations SONAR Sound navigation and ranging US Ultrasound COW Circle of Willis PRF Pulse repetition frequency B-mode Brightness mode CW/PW Continuous and pulse wave LVRej Low-velocity rejection PZT Lead (Plumbum) Zirconite Titanate OD Outer diameter PVA Polyvinyl-alcohol G/A Gelatine agar ID Inner diameter TMM Tissue mimicking material BMF Blood mimicking fluid CFD Computational fluid dynamics 2PP Two-photon polymerisation SLA Stereolithography ftc Freeze-thaw cycles CFI Color flow imaging v Introduction War can never be accepted, but it has proven to accelerate research on technologies which can be used to the military’s advantage. At the end of the interbellum, the U.S. feared the possibility of the Germans being able to produce a nuclear weapon. In the shadows, leading scientists of the 20th century theorized the first nuclear bomb, hoping to produce one before the enemy did. Although the devastating capacities of such a weapon are enormous, the fundaments of today’s nuclear energy can be traced to this project. The same applies to the use of ultrasound for object detection. Researchers made little progress until, during the First World War, the threat of submarine attacks became plausible. Huge investments were made, quickly resulting in devices such as the hydrophone and SONAR. In 1953, ultrasound made its entrance in the field of medical imaging. J.J. Wild and J. Reid visualized a 7mm thoracic tumour using their machine: “the echographe”. Since that moment, ultrasound evolved continuously. Features such as Doppler, colour Doppler, and 3D were implemented, enlarging the scope of application to a major extent. In contrast to other techniques such as MRI and CT, ultrasound is considered to be safe, and the examination can be done without moving or sedating the patient. The aim of this thesis is to study the feasibility of estimating blood flow and perfusion at a microcircular scale, using new ultrasound techniques. This could be of great use for preterm born babies who tend to suffer from cerebral lesions and need constant monitoring in the early stages of life. To validate these new techniques, flow phantoms mimicking the human microcirculation had to be designed. In the first part of this text, the fundamentals of ultrasound imaging and the human microcirculation are explained. Next, a literature review elaborates the possibilities and restrictions of flow phantoms. The second part envelopes the experimental part. Some disused setups will be discussed, explaining why they failed and to which extent they could be used. Other setups, which did work, were used to compare measured flow speeds with the actual speed. Based on these results, conclusions about the feasibility of perfusion imaging are made. The last part consists of computational models related to brain flow imaging. A CAD model of the Circle of Willis has been developed using MRI data and the Mimics software. The geometry was optimized and meshed to perform CFD calculations using Ansys Fluent. 1 Chapter 1. Background knowledge It should be stated that this introduction is by no means an exhaustive explanation of physics, nor a guide to the human anatomy. However, it should provide the reader with enough information to fully understand the challenges, techniques and solutions described in this thesis. 1.1 Ultrasound technology The term ultrasound is derived from the Latin words ‘ultra’ and ‘sonus’, which can be translated as ‘beyond the sound’. This refers to the frequency surpassing the human hearing range which is situated between 20-20000 Hz. In this section, the basic principles of sound waves will be elaborated using SONAR as an example. 1.1.1 Sonar Sonar (Sound navigation and ranging) was used by the American army since the 1930s for underwater object detection. As submarine attacks became a considerable threat, the Navy needed an instrument to scan the sea. To do so, they mounted a sender to the hull of their ships which creates a pulse (ping, Figure 1) of acoustic energy propagating through the water. When this wave reaches an object, an important amount of energy will be reflected. This reflection will be detected, thus discovering a nearby enemy. Figure 1 Active sonar relies on the emission and reception of a sound wave (Source: http://www.act-us.info) Knowing the bulk modulus K and the density ρ of (saline) water, the wave speed c can be calculated. (1) √ The sender, which often also acts as a receiver, acquires the reflected wave. The interval between the emission and reception is the amount of time (t) which the wave needs to cover twice the distance between sender and object. Hence - knowing the wave speed - the distance x between the ship and submarine can be calculated. (2) Despite being a century old technology, more complex forms of SONAR a still being used for e.g. scanning the ocean floor and creating 3D plots of the seabed. Furthermore, the intensity of the received signal provides enough information to determine the composition of the ocean floor [4]. 2 1.1.2 Ultrasound waves 1.1.2.1 Propagation When swimming in the sea, your body goes up and down following the movement of the water. This motion can be described as a transverse wave (Figure 4), which moves perpendicular to the direction of the energy transfer. A longitudinal wave is an alternation of high-pressure zones (compression) followed by low-pressure zones (rarefaction), propagating along the direction of energy transfer. Figure 2 (L) longitudinal wave with zones of compression and rarefaction (R) Transverse wave moving up and down perpendicular to direction of wave [5] The transverse part of a sound wave is known as a shear wave, and is the basis of ultrasound elastography. This fairly young technique maps the stiffness of tissue, making it possible to distinct cancerous from normal tissue [5]. However, in the scope this thesis, shear waves will be neglected because US flow imaging is based on the longitudinal wave. The longitudinal part can be mathematically described as [6]: ( with ) (3) being the pressure amplitude (4) From equation (4) we can see that the longitudinal wave is a cosine function varying with the wavenumber ( ), angular frequency ( ), place (x) and time (t). The pressure amplitude depends on the amplitude of displacement (A), the density (ρ), the frequency and the wave speed (c). 1.1.2.2 Scattering The submarine (mentioned above) can be seen because it reflects some of the energy emitted by the sender. The driving force behind reflections is the change in density and compressibility (bulk modulus) of the medium through which the waves propagate. When the wave hits the metal wall (larger than the wavelength), it reaches a boundary between two densities. Some of the energy will bounce back, leaving the surface with the same angle as the incident wave (law of reflection). This is called specular (mirror-like, Figure 3) reflection. Another portion of the energy will be transmitted through the new medium. The ratio of transmission and reflection depends on the difference in acoustic impedance of the media. This acoustic impedance Z is defined as the product of the density times the wave speed in the medium. 3 Figure 3 Reflected wave (ain=aout) and transmitted wave (ain ≠ aout) (Source: http://www.azooptics.com) The transmitted wave will pass through a material with different bulk ratio and density, resulting in an altered speed and direction of propagation. This is known as refraction. With respect to echography, a third phenomenon has to be addressed, which occurs when a wave hits an object smaller than the wavelength. Instead of being reflected, the energy is scattered in every direction. This is known as diffuse scattering. 1.1.2.3 Attenuation Lossless energy transportation is impossible, and the same applies to the propagation of a sound wave. The longitudinal wave will cause vibrations, which will partly be converted to heat. The longer the distance covered by the wave, the more energy it will have lost, thus weakening the amplitude of the received signal (Figure 4). The following formula describes the interaction between the depth z, the frequency f of the wave and the coefficient of attenuation α of the medium. ( ) (5) This thesis focusses on the visualisation of microcirculation using higher frequencies. Looking at equation 5 and Figure 4, it is clear that the influence of attenuation will have to be examined, especially when monitoring deeper structures. Figure 4 Influence of transducer frequency on penetration depth [7] 1.2 Echography 1.2.1 The Probe At the heart of the probe lie a series of piezoelectric crystals. These crystals have the special ability to deform when an electrical voltage is applied, and to generate an electrical signal due to external 4 forces. The cause of this effect can be found in the lattice structure of such a crystal, which consists of small electrical charges oriented in such a way that electrostatic equilibrium is achieved. Due to external forces, negatively and positively charged zones will be induced, generating a voltage. Mutatis mutandis, when a voltage is applied the lattice will deform to restore the equilibrium. This deformation can produce a wave. Hence, an electrical signal can be used to generate an acoustic wave and the reflection can be detected because it deforms the crystal. Nowadays, the most common material used as piezoelectric crystals is Lead Zirconate Titanate (PZT). C A B Figure 5 Schematic representation of a transducer (Source: http://www.nano-tera.ch) A specific name has been assigned to every direction in order to avoid any ambiguity. Axis A (Figure 5) is the axial direction, parallel to the trajectory of the beam. Axis B and C are respectively known as the lateral direction and elevation. 1.2.2 Imaging modes 1.2.2.1 Grayscale imaging A-mode The amplitude of the reflected wave is plotted in function of the depth. This is used for e.g. echoencephalography to detect lesions inside the brain. B-mode Brightness mode (or 2D mode) produces two-dimensional images with the brightness varying with the amplitude of the echo. M-mode Motion mode is a special form of B-mode which can be compared with a photo finish. A single scan line (Figure 6, red line) is plotted through time, hence showing the movements of the observed structure. 5 Scanline Motion on the line in time Figure 6 (L) A-mode imaging: a peak is observed when a change in acoustic impedance is met [8] (M) B-mode image of a hollow vessel embedded in TMM. The reflective wall is represented by an elevated brightness (R) M-mode image of a moving mitral valve 1.2.3 Flow imaging Flow imaging is powerful and safe, if practiced within its limits. Otherwise, these methods can be prone to misleading results. Doppler Effect When sitting on a train, speeding towards the ringing bell of a level crossing, the frequency of the observed sound will change. The pitch will be high when getting near to the crossing, and low once you passed the bell. A simple explanation for the Doppler effect, named after an Austrian physicist who was observed this when looking at the stellar motion, is the following: Suppose that at regular interval gnomes (i.e. positive amplitude peaks) are jumping off a moving truck. The speed of the truck vt is constant, and the gnomes are always running at vg towards the observer. The truck approaches the observer and gnomes are sprinting towards him. Because the gnomes are faster than the truck, the distance between the gnome and truck will increase at a rate vd equal to their difference in speed. (6) Once the truck passes the observer, gnomes are still running towards him, thus moving in the opposite direction of the truck. Hence, the distance between the truck and the gnome will increase at a rate which is the sum of both speeds. (7) The gnomes, representing the positive peak of a sound wave, will be closer together when going towards the observer, resulting in a higher frequency. When moving away, the opposite effect will occur. (8) 6 Continuous wave Doppler Blood flow can be measured applying the Doppler Effect to ultrasound waves (equation 9). One crystal of the probe continuously emits a wave, of which the frequency is known, towards the vessels. When a change in acoustic impedance is met, the wave will partly be reflected and received by another crystal, which is constantly listening. If the reflection origins from moving particles, such as red blood cells or vibrating muscles, there will be a change between the emitted and received frequency. This can be used to calculate the speed at which the particles were moving. A disadvantage of using continuous wave Doppler is the inability to determine the speed at one specified depth, as illustrated in Figure 7. The received data will always consist of all the backscattered information on the scan line. But to its advantage, CW is not bound to the restrictions of the Nyquist theorem (discussed below), making high speed measurements possible. This is why it is still being used to assess high flow speeds at cardiovascular level. (9) An important variable is the angle between the emitted wave and the vessel because this technique measures the difference in speed relative to the direction of the beam. If the beam and the vessel are not aligned, a factor cos(θ) is needed to calculate real speed of the blood flow in the direction of the vessel. Figure 7(L) Continuous wave Doppler used to monitor high flow speeds at the aortic valve [9] , (R)in A the beam and vessel are almost aligned, providing a decent frequency shift, in B and C the angle is smaller, resulting in a weaker signal and a bigger error (D) same is in A but inverted resulting in a negative speeds (Source: https://sonoworld.com) Pulsed wave imaging Pulsed wave (PW) flow imaging has often been –incorrectly- denoted as Doppler imaging. Each crystal of the transducer acts successively as a sender and receiver, firing short bursts of acoustic energy towards the tissue. Because the speed of sound through the human body is known, the moment of receiving a pulse arising from a certain depth can be calculated. Hence, the flow speed within a volume (i.e. sample volume) at a specific depth can be measured. This technique is called “time-gating”. The Doppler shift has to be sampled at least twice as frequently as the highest frequency shift measured in the volume. The frequency at which the pulses are emitted is known as the pulse 7 repetition frequency (PRF). Numerous examples of PW measurements can be found in chapter 4. Further information about the physics behind PW imaging and ultrasound in general can be found in the doctoral thesis of prof. Swillens. [10] 1.2.4 Safety concerns Ultrasound is used for imaging unborn babies because is it safe. Or isn’t it? As mentioned in 1.1.2, this technique relies on the propagation of a sound wave through the body. Travelling waves transport energy, and the way this acoustic energy dissipates or is converted to other forms of energy is crucial to the safety of ultrasound. There are two major physical effects which should be considered. First is the thermal effect of US. A wave propagating through tissue loses its energy, and this loss is converted to a certain extent into heat. The heating effect depends on the heat absorption coefficient of the tissue, and proves to be maximal in bone structures. However, it is daunting to predict the overall rise in temperature, partly due to the many variables (power, focus etc.). The heating effect of ultrasound examinations on brain tissue has been studied and showed an increase in surface temperature of 4,3 °C after 120s. Due to the dense vascular system deeper inside the brain, the increase in temperature was limited to 1,2 °C. [11]. Second is the possibility of cavitation. This is the formation of a gas bubble due to a decrease in pressure arising from a rarefaction zone. The explosion of such a bubble can cause sudden high pressures, which may be hazardous.[12] A recent study has shown to possibility the use cavitation as an alternative to the conventional lithotripsy treatment. After injection microbubbles, they could be detonated using ultrasound waves. These explosions could fracture kidney stones [13]. In the scope of ultrasound imaging, cavitation is not desirable. Older large-scale studies have found no correlation between echography imaging during pregnancy and later health problems when the child grows up. However, the power output of the newer generation of ultrasound machines is higher, which implies the need of further testing. When using higher frequencies, the possible effects should also be examined. But, higher frequencies should not be confused with higher power outputs. 8 1.3 Microcirculation The use of Doppler echography has been used extensively to visualize major arteries, quantify blood flow and to detect plaques. This can be done because the signals arising from the blood flow are noticeably differing from tissue and muscular noise. When observing microcirculation, these differences will decrease, leading to possible ambiguity. 1.3.1 The human circulatory system Our body consists of a several billion to trillion cells which can be seen as small factories. Each cell must receive enough raw materials to maintain its homeostasis, and similarly get rid of all its waste products. Blood can be seen as the medium of transportation, and it is propelled by the movement of the heart. An overview of the circulatory system can be seen in Figure 8. Aorta Common carotid artery Capillaries Diameter 2-3 cm 0.55-0.78 cm 5-300 µm Flow speed > 40 cm/s 15-25 cm/s < 3 cm/s (non-pulsatile) Figure 8 (L) Overview of the human circulatory system (Source: https://www.haikudeck.com) (R) Diameter and flow speeds of different types of vessels Deoxygenated blood (blue) arrives at the right atrium, passes through the right ventricle and enters the pulmonary artery. When blood reaches the lungs, CO2 is released and O2 is added. The oxygenated blood (red) flows back to the heart, closing the loop known as the pulmonary circulation. Then, the aortic artery leaves the heart, carrying oxygen to the organs. At this level, the flow is highly pulsatile, following the contraction and relaxation of the cardiac muscles. The aorta branches into smaller arteries and arterioles. As the heart is more remote, the pulsatile factor decreases, as well as the flow speed. The smallest roads in the human circulation are the capillaries. These tiny vessels communicate with the surrounding tissue, exchanging nutriments through the thin wall. At macrocircular scale, Doppler echography provides us with much information concerning the flow speed, vortices, valve malfunctions etc. Visualization of microcirculation could give us feedback on the perfusion of e.g. the brain tissue. 1.3.2 Special phenomena A well-known example of non-Newtonian behaviour of fluids is the “water-maize” experiment. While it is impossible to walk on water, the water/maize mixture will become “solid” when a force is 9 exerted on it. This is a result of an increasing viscosity due to a soaring shear stress. Materials behaving this way are known as shear-thickening or dilatant. Blood behaves in the opposite way, thus getting thinner (less viscous) when shear rate increases[14]. This phenomenon was first observed by the Swedish scientists Fahraeus en Lindqvist. They forced blood through a tube with a diameter of 250µm and observed the flow pattern. What they saw was the formation of a RBC free layer near the vessel wall. Because of this thin layer of plasma the “oriented” blood will have lower flow resistance than homogeneous blood. The net effect will be an overall decrease in viscosity. There are two causes which can favour a cell free layer[15]: Silberberg effect: neutrally beyond particles in a suspension tend to be pushed towards the centre of a vessel as a results of several hydrodynamic interactions Statistically, the density of RBC will be higher at the centre of the vessel Another shear thinning factor is related to the formation of red blood cell stacks, also known as “rouleaux” (Figure 9). This effect is often related to several pathologies such as sickle cell disease and malaria, but it also occurs naturally as a reversible aggregation process. When shear rates increase, these “rouleaux” tend to dissolve, leading to a less viscous fluid. [16] Figure 9 Formation of rouleaux [16] 10 Chapter 2. Literature review 2.1 Aim The ability to visualize perfusion at a microcircular scale could be a major asset to the already indispensable ultrasound technique. It would broaden its use and could be of particular interest to brain flow imaging. However, the methods which are being used to improve the sensibility and resolution will give birth to some new problems (as discussed below), which will have to be examined thoroughly. Capillaries and arterioles are unmistakably smaller than arteries, and necessitate higher spatial resolution and backscattered power to be observed. This can be achieved by enhancing the imaging frequency from 5-8 MHz, which is the current standard for flow measurements, to 15MHz and higher. Sadly, the increase of frequency comes at the cost of an exponential decrease in penetration depth (cf. 1.1.2.3). The trade-off between depth and resolution has to be quantified before any prediction can be made on the accuracy of perfusion estimates. The challenges aren’t limited to physical problems. Signal processing will also need to be reevaluated. The amount of data received from the backscattering is enormous and has to be filtered. Arterial flow differs significantly from tissue motion and vibrations induced by the operator’s hand, making a velocity based rejection of clutter signals possible. If the same rejection methods were to be applied when observing low flow rates in capillaries, the data of interest would be rejected because the speed of scatterers and clutter signals overlap. Hence, new filters have to be designed. Furthermore, the blood flow in capillaries can’t be translated as a downscaling of the flow in e.g. the aortic artery. As mentioned in 1.3.2(“special phenomena”), red blood cells will form stacks which can cause moderate reflections at one moment and almost none in the next frame. To address these problems, a multiphysics model has been designed. One facet of this model focusses on the simulation of ultrasound echoes using a virtual transducer (Matlab). The other facet calculates the flow pattern within the structure, depending on boundary conditions applied to the model (ANSYS Fluent). Combining these two, scatterers can be moved along the flow lines (derived from the CFD), and their echoes can be visualized. However, computational models always suffer from (over)simplification of complex fluid behaviour, as well as geometrical imperfection. And to be conclusive, their accuracy has to be validated against a realistic set-up. Hence, the need for a flow phantom arises. This literature review attempts to list the possibilities for making a model mimicking the properties microcirculation to a relevant precision. 11 2.2 Flow phantoms In its simplest form, a flow phantom is a hollow geometry through which flow is sent. In contrast to in-vivo or ex-vivo (i.e. on real tissue) measurements, in-vitro (i.e. model) gives the researcher full control over the flow speed, pressure, geometry etc. The way such a phantom will be made strongly depends on the system which needs to be replicated, and what needs to be measured. Our phantom should meet the following criteria: - Mimic capillaries and arterioles - Diameter between 5-300 µm - Low flow speeds 0.1-10 cm/s - US compatible -> echogenic material - Low budget - Different set-ups possible When going through the published literature, it became clear that numerous methods exist to produce phantoms for macro scale. However, can these be translated to microcirculation? Depending on the design, blood and tissue will need to be mimicked using a blood mimicking fluid (BMF) and tissue mimicking material (TMM). The next section will cover the different types of flow phantoms which have been made until present, and how TMM and BMF can be incorporated to mimic an in-vivo setting. 2.2.1 Types String and belt phantoms When thinking of flow phantoms, the necessity of using a fluid is the first element that comes to the mind. However, a moving solid can create a similar echo (to a certain extent, as discussed below).As the name suggests, a string or belt is submerged in a fluid and connected to an electric motor. The string is covered with scattering particles to provide a strong echo. The wave speed through the fluid must be near 1540 m/s (speed in human tissue) to minimize errors. These phantoms (fig 1) have been successfully used to assess the influence of wall and tissue motion - known as clutter - on the Doppler shift.[17] 12 Figure 10 the use of clutter belts to evaluate the influence of wall motion on the Doppler shift. (L) wall and vessel are mimicked by a belt (R) vessel replicated by a hollow tube and wall motion provided by the belt [17] This kind of phantom fails to replicate the parabolic flow pattern which can be observed in-vivo because the inner structure of the belt moves at the same speed as the outer regions. + A good option when solely quantifying flow speeds - No fluid dynamics to analyse - No control over scatterer concentration in time Ex-vivo material It is possible to use excised (Figure 11) arteries instead of trying to replicate them. This can be of utmost importance when the elastic properties of the tissue have a big influence. However, it is a very cumbersome procedure. Donor tissues have to be found and treated for storage. Otherwise, the material’s properties will deteriorate fast, making it almost impossible to do exhaustive measurements. Even if the tissue is kept at optimal conditions, the elastic properties could change. Figure 2 shows the difference in burst pressure of an epigastric vein, in vivo and ex vivo (fused invivo). A significant difference in burst pressure can be seen. [18] Muscle Vessel Blood Density (kg/m³) 1041 1066 ± 10 1060 Velocity ( m/s) 1595 ± 20 1616 ± 23 1587 ± 3 Attenuation (dB cm-1 MHz-n) 1.47 1.026 0.17 Table 1 : In vivo characteristics of different types of human tissues [19] Reperfusion of capillary ex-vivo networks has been done before, and flow could easily be observed. [20] However, it is daunting to assess which volume is passing through each individual capillary when infusing at artery level. But, the combination of assessing the speed using ultrasound and an optical microscope to watch the particles travel through the system could be the ground truth solution. 13 + Good elastic properties + Perfect geometry and attenuation - Biological degradation after short time - Poor control on speed in individual capillaries Figure 11: (L) ex vivo artery made by LifeTecGroup (R) Comparison between the burst pressure of the same artery in and ex vivo (after preservation method) [18] Tubing Hollow tubes can be used to replicate vessels, but the design will be limited to straight lines without branching [3]. To be representative as a microcirculation mimic, the tubes must have an internal diameter (ID) between 50-300µm. Moreover, they must be made from a material which has good echogenic properties. Common silicon or PTFE tubing can rarely be found with an ID smaller than 0.4 mm, which is at least the double of what is needed. Smaller dimensions can be found when looking at Tygon-based tubes, but the ID still hovers around 0.25 mm. The thinnest tubes are used for gas chromatography, with ID’s as low as 0.06 mm. But, they come at a very high cost, with the uncertainty if they are echogenic. To save expenses, different tube manufacturing companies will be addressed to ask if samples can be donated for research purposes. + Widely available and economic + Several set-ups are easily produced - No complex geometries with continuous cavity 3D printing Rapid prototyping has been booming since the beginning of the 21st century. New machines and methods made it possible to print in a variety of materials. A 3D model, based on CT or MRI images, can be made easily using mimics software. The generated STL file (Figure 12) can be post-processed and directly send to the printer, resulting in an almost perfect duplicate of the region of interest. 14 Figure 12 (L) .STL model (R) printed version of the circle of Willis Stereolithography (SLA) and fused deposition modelling (FDM) are two common technologies within the rapid prototyping industry. They are used for making prototypes at early stages of the developing process. Hence, faults and design flaws can be detected by visually inspecting a real model. Sadly, the precision required for making a microcirculation phantom is beyond the capabilities of these technologies.[21] Two-photon polymerisation (2PP) is a state of the art technology, which could be used to create objects to nanometre precision. It uses very powerful lasers (up to 200 GW) to induce polymerisation in photosensitive materials. In contrast to normal polymerization, 2PP uses near infrared light which can travel through the photosensitive material. This makes printing in 3D possible, instead of using a layer-by-layer approach. Because 2PP is still in the experimental phase, this method can’t be applied to this thesis. [22, 23] + Perfect geometry and different materials - Technological limits to precision Figure 13 Scaffold made using two-photon polymerisation (2PP) [23] 15 Dialysis cartridges Cartridges have been used as capillary flow phantoms to evaluate the behaviour of contrast agents at low flow speeds. A cartridge is a bundle of several thousands of hollow tubes with an internal diameter in the range of 200 µm. It could be used to evaluate averaged flow speeds in a dense network. But because the slightest dimensional error can cause higher or lower flow resistance, it can’t be used as a reliable indicator of flow speeds in individual vessels (cf. reperfusion of tissue). [24] + Dense network of fibres and easy to attach to circuit - Poor control of flow speed Microfluidic systems This technique is used to make tiny vessels, down to 50-100 µm. To produce the vessels, photopolymers are used which cure when exposed to light (Figure 14). Starting from a 3D CAD model, a mask is manufactured for each layer of the curing process. Hence, where the mask is transparent, polymerization can take place. The resulting product which has the positive geometry is known as the “master”. This can be used to create the negative geometry in PDMS (poly(dimethylsiloxane)).[25] [26] Figure 14 Solid ground curing process (Cubital), where the mask is translucent light-induced polymerisation will occur [21] These models have many applications in the field of medicine and biochemistry. + Ultra high precision + Perfect geometry - Expensive 16 2.2.2 Tissue Mimicking Material The system has to be embedded in a tissue-like material, referred to as the Tissue Mimicking Material (TMM). To estimate perfusion, the attenuation coefficient and the speed of sound through the TMM will be important. The average speed of sound in human tissue is 1540 m/s, and this value is also set in the echography machine. When differing significantly from this value, the resulting image will have a dimensional distortion. (cf. equation 2) The attenuation in the TMM is an important variable when monitoring deeper structures. If it is too low, the received echo from the phantom will be higher than would be the case with in vivo material. These results could be rescaled using equation 5, if the attenuation coefficient of the material is known. However, it is preferred to start with a material which has acoustic properties close to human tissue. Table 2 Characteristics of TMM candidates. The velocity should be near 1540 m/s to replicate the properties of in vivo tissue [19] Gelatine/agar Gelatine and agar are ingredients which are used to make gel-like structures for nutritional purposes. Because a mixture of both materials with water has good acoustic properties, it has been used for several tissue mimic applications, of which some will be discussed. Gelatine/agar was used as a wall mimic, to make carotid flow phantoms for strain imaging research.[27] The fabrication started with a metal rod which was centred in a cylindrical mould. Then, the liquid gelatine/agar (resp. 8%/3%) mix was poured around the rod. After putting it in the fridge for 12h, the rod was extracted. Hence, a hollow carotid remained with a wall thickness of 5mm. This mixture can also be used as a tissue surrounding ex vivo or artificial structures such as vertebra (Figure 15) [27] or catheters[3]. A third possibility is to let the TMM act as wall and tissue mimic [28]. These phantoms are known as “wall-less”. 17 Figure 15 Vertebra submerged in a TMM based on gelatine/agar [29] Gelatine melts at 60 °C and agar at 93 °C, and they are both easily available. This makes them accessible to use. But, biological degradation can occur fast if no anti-bacterial agents are added. Jia Wei Li et al. reported the use of chlorhexidine as an anti-bacterial agent. PVA Polyvinyl-alcohol (PVA) is a material with unique properties. When dissolved in water, it forms a gel with varying degree of cross-linkage (crystallinity) depending on the number of freeze-thaw cycles (ftc). As can be seen in fig. 5, the amount of ftc will alter the attenuation and speed of sound. When comparing the acoustic properties of human tissue, as listed in Table 1, with Figure 17, it can be seen that two freeze-thaw cycles give the TMM an optimal speed of sound[2]. No predictions can be made on the attenuation because the frequency used during the measurements will be far greater than the values mentioned in Figure 17. As mentioned above, gelatine agar can be used to mimic different structures. The same design can be made using PVA. However, PVA is much more tedious to process due to its difficulty to dissolve in water, and the time consuming freeze-thaw cycles A B Figure 16: Influence of the amount of freeze-thaw cycles on (A) the attenuation (B) the speed of sound [2] The red line indicates the value of tissue, an optimum is found at 2 ftc ([30] 18 2.2.3 BMF Doppler flow imaging in vivo relies on the detection of moving red blood cells. To replicate these echoes in artificial blood, particles have to be added to the fluid. Most BMF’s are water based, however, oil based emulsions have also been reported [31]. Real blood can also be used, but as with ex vivo material, there are many complications. Blood will only be representative for in vivo blood when it is heated to 37°C. The red blood cells are easily damaged, and there is always a biohazard risk (i.e. infection by pathogens in the blood). Hence, it is preferred to use alternatives. The BMF needed for this thesis should meet following criteria: - Particle size: smaller than 30 µm - Density: neutrally buoyant - Concentration: high enough to be normally distributed (central limit theorem) - Viscosity: around 4 mPa.s When observing flow patterns or wall shear stress, the viscosity of the BMF must be similar to real blood viscosity. This value can be altered by adding glycerol to the mixture.[32] Table 3 Properties of the most common particles used as scatterers in a BMF preparation [19] Nylon particles are ideal due to their low dimensions and appropriate density. But, as with the other particles, they have to be filtered. Otherwise, contaminants or bigger particles could block or distort the flow. Table 2 omits starch as a BMF candidate. It has a density of 1.5 g/cm³ and the particle size varies between 2 µm (rice starch) to 100µm (potato starch) [33]. 2.2.4 Pump When accidentally cutting in your finger blood won’t gush out, but a drop of blood will steadily grow. This is because the heart is remote compared to the capillary system, and the attenuating effect of arteries, resulting in almost no pulsatility in the blood flow. 19 The pump propelling the fluid has to be able to deliver very low and linear flow rates with high precision. This can be achieved by placing a reservoir at a certain height, and measuring the mass of the outlet flow in a measured time frame. A second possibility is using a syringe pump. This device is designed to administrate a precise flow rate of medicinal drugs. A third option is by using a roller pump designed for handling small volumes with high precision. Camfermann et al. report that high friction between plunger and wall when using a plastic syringe can be problematic. Instead moving linearly, the pressure in the syringe increases until the friction can be overcome, resulting in a flow/pressure peak. Hence, a glass syringe is preferred.[3] 2.3 Chosen set-up(s) The feasibility of making wall-less flow phantoms with micrometre range lumens will be checked because solid wires can be found in the almost every dimension. Hence, models could be made fast and cheap, which is useful when tiny changes have to be made. If unsuccessful, tubing will be used. These have the disadvantage of being a lot more expensive and a lot less adaptive in the scope of available diameters. As for the TMM, both Gelatine/agar and PVA will be tested. The preparation of PVA is timeconsuming, but the acoustic properties are far superior to these of Gelatine/agar. PVA is also less prone to biological degradation. However, a homogenous solution of G/A is easier to make due to the low melting point of both components. The initial BMF will consist of starch particles because it is safe to use. When the set-up is in its final stage, ready for the decisive experiments, the starch will be replaced by orgasol (nylon) particles. Not only are they smaller, but the consistency of particle size is superior compared to starch. The propelling apparatus will be either a syringe pump or a roller pump. This way, the displaced volume, as well as the flow speed can be determined with high precision. 20 Chapter 3. Production of the set-up The literature provided some techniques to make flow phantoms. Because many of these methods are applied for the production of larger vessels, it remains uncertain if downscaling to a microcirculation level will be possible. Hence, the experimental part can be seen as a feasibility “study” within the feasibility study of monitoring perfusion. 3.1 Set-up In this section, every component of the flow phantom will be discussed. Due to failure, many designs have been tested and changes have been made accordingly. However, they all rely on the same TMM and BMF. This is why these will firstly be explained in general. Afterwards, every flow phantom design will be covered separately, in detail. 3.1.1 Preparation of the TMM Ultrasound waves can’t travel through air. This is why some material is needed between the flow vessel and the transducer. It is preferred that the acoustic properties of this material match those of the human tissue. Hence, dimensional distortion of the image and excessive attenuation of the signals can be avoided. The literature review revealed two valuable substances to use as a TMM, being PVA and a mixture of Gelatine and Agar. The following paragraph embodies the preparation of these materials. PVA The optimal acoustic characteristics of polyvinyl-alcohol are achieved when (Table 1) using a 90/10 (wt. %) mixture of H2O and PVA-grains (Aldrich chemistry, 99%+ hydrolysed). The mixture was slowly heated to 95 °C for at least 40 minutes while continuously stirring to avoid any burning at the bottom of the glass beaker. During this step, a lot of water evaporates, which will need to be compensated for by adding extra water until the initial concentration is restored. Once the solution got translucent, meaning the PVA was fully dissolved, it was left to cool to ambient temperature. During the cooling stage, the container must be covered to prevent excessive evaporation to occur, which could alter the initial concentration of PVA. After waiting at least 30 minutes, a skin will form on the cooled solution. This needs to be removed before pouring the mixture into the box. When no more gas bubbles could be seen inside the phantom, it was put in the freezer for at least 12h. After letting it thaw, the wires were removed thus forming a cavity inside of the TMM. Note: if the dimensions must remain unaltered, it is preferable to use a mixture of glycol and H2O (resp. 40/60 wt.%) instead of only using H2O. The addition of glycol lowers the melting point which results in less distortion during the freezing stage. Preparing the Gelatine/Agar A similar procedure was used to prepare the Gelatine/Agar TMM. A mixture of 356 g water and 12 g agar (Agar Agar, Vahiné) was heated to 90 °C until a homogeneous melt was obtained. Afterwards, the temperature was lowered to 60 °C before adding 32 g of gelatine (Dr Oetker). Once the gelatine was fully dissolved, it was cooled to ambient temperature using the same procedure as described in the PVA section. However, no freezing stage was involved. The sample was put in a fridge overnight before using it. A summary of the composition of both PVA and G/A can be found in Table 4. 21 PVA phantom PVA Water Glycol Wt. % 10 90 (54*) (36*) Gelatine Agar Gelatine Agar Water Wt. % 8 3 89 Table 4 Composition the used TMM, * values when using a Glycol/Water mixture 3.1.2 Blood mimicking fluid If water were to be sent through the vessel, only a few echoes would be generated by the echography machine. To amplify the backscattered power little particles, known as scatterers, have to be added to the fluid. Potato starch was used during the initial testing. These ovoid particles have a diameter ranging from 30 to 100 µm, and a density of 1.55 g/mL. Using a magnetic stirring bar, starch can easily be homogeneously dispersed in water. However, due its relatively high density compared to water, the particles tend to sink after a few minutes. This is no problem when using a closed circuit with high flow rates gushing through the vessels, because little turbulence will propel the particles back into suspension. However, when a syringe pump was used to administer very low flow rates (< 10 mL/h), the particles quickly sank to the bottom of the syringe. This caused fade out of the echoes after some minutes of measuring, because the scatterers remained in the syringe. Furthermore, individual potato starch particles are too big to be used in capillary vessels (<200µm), not mentioning the fact that they tend to agglomerate and form bigger clumps. For making the final measurements, orgasol nylon particles were used (Orgasol (R) Caresse). The density of orgasol is 200-500 kg/m³, which is a lot less dense than water, hence the need for a wetting procedure as described in [32]. 3.2 Wire extraction phantom Knowing how the BMF and TMM can be made, the design of the phantom itself should be addressed. The first technique that will be explained relies on the extraction of wires which are embedded inside the TMM. After letting it solidify, the wires would be removed, thus leaving vessel-like cavities inside the phantom. The advantages of this technique are the lower cost of solid wires compared to hollow tubes, and the broad spectrum of available dimensions. But this design, simple as it may look, proved to be daunting to produce. Tube connector Tube connector Figure 17 (A) Tensioned wires and connectors fitted through the wall, ready to pour the TMM (B) box from A filled with G/A, wires extracted and ready to perfuse 22 A simple plastic box (Figure 17, 96x96x64mm) was used as a TMM container. Small holes were made in the opposing walls using a needle (diameter of 0.81mm and 0.56mm), making it possible to embed the wires within the sample volume. To provide a flow inlet, a tube connector was inserted in the hole. Then the wires were tensioned, and the edges between the connectors and the box were glued to assure no TMM could leak. However, the holes of the connectors would still allow the TMM to leak out of the box. An attempt was made to seal the aperture with glue or silicone, sadly resulting in clotted vessels due to remaining residue when pulling the wires out. The most efficient solution was forcing a toothpick through the connector, making care to not break the tensioned wires. The wires were removed while observing with the GE vivid 7 ultrasound. It was clear that the cavities of the 52µm and 180µm collapsed immediately after the extraction, in PVA as well as in G/A. The two other vessels measuring 300µm and 700µm remained seemingly intact. However, after one minute of perfusion, the 300µm also closed. To find the cause, the phantom was cut open along the direction of the closed vessel. No visible problems could be seen. Although, when manually purging one of the connectors, a small amount of TMM came out of the cavity which could have led to the blockage. During an attempt to expulse the clot through the vessel with higher pressure (by setting the syringe pump to its maximal level = 1000 mmHg), the TMM ruptured (Figure 18). Figure 18 Rupture due to elevated pressure, initiated at the tube connector 3.3 Hollow tube phantom The use of hollow tubes eliminates problems such as wall roughness, TMM-tear and vessel collapse. But, they can’t be found in a variety of dimensions as solid wire. Furthermore, they come at a high cost. Luckily, 20 samples of polyimide tubes were donated by Microlumen®. The geometry of phantom should meet the challenges faced when observing complex and small vascular networks. In contrast to carotid imaging, there is no clear distinction between the strong signal arising from the artery, and the negligible signals arising from smaller arterioles and capillaries. Hence, following influences should be examined at different flow rates: - Depth Angle Tube diameter 23 - Crossing patterns A box (similar to 3.1.3) was used to make a phantom with a depth of 4 cm. The tubes were put through holes (made with a syringe). After tensioning the tubes, the aperture between the vessel and the box were filled using glue. The ends of the tubes were inserted in a larger silicon vessel (ID = 200µm), because no needle could be found thin enough to fit inside the tubes lumen. The silicon tube can be infused using an ultra-fine stent needle. Figure 19 Final model before pouring the PVA Figure 19 shows the final phantom before the TMM (PVA , 2 ftc) was inserted. It basically consists of 5 parallel tubes (100,155,165,178,200µm) inserted under an angle of 25 degrees. It should provide enough space to measure at depths ranging from 5-30 mm. The perfusion of this system proved to be straightforward, as will be discussed in chapter 4. 3.4 Discussion The problems of making flow phantoms for microcirculation lie in the attempt to reconcile both the simplicity of the design (“low-cost”) and the high-precision needed at such low dimensions. The wire extraction method proves to be useful when mimicking structures at the level of arterioles or bigger (>300µm). When going smaller, the structural properties such as rigidity and strength of the TMM (both PVA and Gelatine/Agar) are insufficient to generate a reliable set-up resulting in blocked or collapsed vessels. The biggest problem proved to be the opening of the tube connector. To prevent the TMM from leaking, it has to be shut when pouring the liquid PVA or G/A inside the container. But once the tissue mimic has solidified, it has to be reopened, to make perfusion possible. It became clear that the substance used to seal the aperture (glue, wax etc.) is prone to granulate and cause obstructions when perfusion is started. 24 Hollow tubes can be embedded in a TMM and purged to simulate flow through smaller vessels. However capillary tubing comes at a high cost and the range of dimensions is limited. Depending on the material that is used, high reflections arising from the vessel wall could be detrimental for the measurements. This could clearly be observed when embedding a close-packed 3*3 matrix of 200µm silicon tubes. The reflections of the superficial tubes could be noticed through the image down to the lowest tubes. Nonetheless, flow through vessels down to 100µm can be replicated, making a parametrical study possible. Reflections Figure 20 B-mode image of 1 longitudinal and 6 cross sections of 200µm silicon tubes. Distinct lumens can hardly be observed, and high reflections could impede precise measurements 25 Chapter 4. Experiments In this chapter, the experiments will be discussed. As with the build of the phantom, many complications occurred in the early stages of testing, which created the necessity of doing some extra tests. The first section describes the response of the set-up to changing the infusion speed. Next, the accuracy of the flow speed measurements, at different depths and through various tubes, will be tested. By recording the CFI and PW data, a comparison between the two can be made. 4.1 Pressure test procedure During the early stages of testing, it became clear that any manipulation (e.g. increasing the speed) on the flow had a long term effect on the measurements. This paragraph describes a pressure test which has been done to quantify the time needed for the flow to stabilize (after being altered). Firstly, the basics of a syringe pump will be discussed. A syringe pump is the perfect machine to deliver a fluid at a precise flow rate. As it was produced to administer medicinal drugs, it works with high precision. The driving element is a stepper motor, which turns a ball screw mechanism to achieve “pseudo-linear” movement of the plunger. The word “stepper” refers to the way this electrical motor works. In contrast to other electrical motors, where a slightly varying torque is applied to the rotor at almost any instance, the rotor of a stepper motor jumps from one angle to another. Depending on its design and the speed at which it turns, this movement can look quite smooth. But, some oscillation of the fluid’s speed and pressure can’t be excluded. Hence, a test was done to investigate if a pulsatile factor could be observed. The second reason to conduct the test is to quantify the time needed for the pressure to stabilize. The syringe pump (Alaris GH carefusion, calibrated) was connected to a 200µm hollow tube, embedded in the final phantom. A Y-shaped connector was inserted between the phantom inlet and the syringe, to connect a pressure measurement tool. Figure 21 show the results of the test, but it should be mentioned that connecting the system generated in initial pressure, leading to an offset from the origin at the start of the test. Variation of pressure in time Pressure (mmHg) 60 40 20 0 0 200 400 600 800 1000 1200 1400 Time (s) Figure 21 Variation of the pressure in time after setting a certain flow rate to the system. Convergence takes more than 20 minutes 26 Pressure (mmHg) Stabilized pressure in time 40 20 0 0 20 40 60 80 100 Time (s) Figure 22 Pressure test in stabilized conditions. No pulsatility can be detected. The time needed for the pressure to stabilize is substantial ( > 1200s) because of the relatively large dimension (radius of 10mm, longer than 10 cm) of the branch connecting the pressure measurement tool to the circuit, compared with the flow phantom vessel, and the low flow rate (4mL/h). An approximation of the time needed for the pressure to stabilize is done using volume proportions of the capillary vessel and the “measurement circuit”. ( ) ( ) It can be assumed that constant pressure results in a constant flow speed (when keeping the flow resistance constant). This simplified calculation shows that the pressure should converge to the final value when waiting for at least 30s. Figure 22 shows the absence of any variation in pressure once it has reached its final value. 4.2 PW flow speed measurements The goal of the experiment described in this section is to see if the frequency, flow speed and vessel diameter have an influence on the accuracy of pulsed wave speed estimation. The first tests were performed with the Visualsonics high-frequency echography machine. Afterwards, a similar procedure has been performed on a “traditional” machine. 4.2.1 Visual Sonics 4.2.1.1 Testing procedure Figure 19 shows the phantom that has been used for the measurements. It basically consists of five parallel tubes (internal diameter of 100,155,165,178 and 200µm) embedded under a moderate angle (around 25°) inside PVA (2ftc). The syringe pump was used to infuse the BMF at flow rates ranging 27 from 1 to 10 mL/h. The scattering function was provided by Orgasol particles, which have been filtered extensively with a 40µm filter to avoid clotting. The echography machine used is a Visualsonics Vevo 2100, equipped with the MS250 (13-24 MHz) and MS550S (32-56 MHz) linear array transducers. Sadly, due to technical limitations of the transducer, flow measurements with beam angle steering could only be made at one frequency for each transducer, being 16 and 32 MHz. Before testing, all the air bubbles remaining in the system had to be removed. To do so, the phantom (the specific tube) was perfused at high flow rates (>15 mL/h), for at least 5 minutes. Afterwards, the machine was paused until the flow ceased. At this stage, the syringe pump could be set at any desired flow rate to start testing. In section 4.1 we addressed the danger of measuring too fast after changing the flow variables. To prevent collecting data from a set-up in a transient state, the recordings were done after waiting at least two minutes after every manipulation. And, to avoid any signal arising from movements when measuring, the probe was fixed inside a mount. The flow speeds were calculated using following formula: (with Q being the flow rate, A the surface of the tubes lumen, and the flow speed) 4.2.1.2 Data processing The Visualsonics machine has its own proprietary post-processing software package (Figure 23). This can be used for measuring distances or angles, or changing the contrast and brightness of the image. But, it can also be used to calculate the mean speed based on the sonogram, which proved to be very useful for this test. However, it should be stated that the identification of this mean value is based on a sensitivity scale1, which has to be determined intuitively. Sample volume Ultrasound beam with angle adjustment Automatically tracked mean Figure 23 Post-processing of a sonogram with the Vevo software package. The mean value can be traced automatically. 1 By lowering the sensitivity scale, the software will look for clear echoes only. If the sonogram is discontinuous or has ambiguous regions, they will be neglected resulting in a local zero speed estimation. A higher sensitivity value will also take the faintest echoes into account, and cancel the obscure regions by interpolating the strong echoes confining this zone. 28 4.2.1.3 Test results Figure 24 shows the results of PW speed estimations on a 178µm ID tube at 32 MHz (blue) and 16 MHz (red), and the theoretical value (black line). The speeds were calculated using the Vevo software mentioned above, with an optimal sensitivity setting chosen for each recording. An overestimation of the speeds can be observed at 32 MHz as well as at 16 MHz. Both the trend lines have a R² value close to one. This means that the difference between the theoretical value and the measured values won’t be a consequence of design flaws leading to inconsistent results. The overestimation could be caused by a poorly chosen angle correction, because -as mentioned before- the measured speed has to be corrected to the real speed using the angle between the US beam and the flow direction. This calculation is based on following equation: ( ) The angle correction can be changed in steps of 5 degrees which implies that if the angle would be set to 65°, instead of the real 67°, an error of 10% will be generated. Note: the difference between using 60° and 65° for results in an aberration of 18,3 %, whereas the difference between 40° and 45° is only 8.3%. This is why the angle should always be minimized, preferably below 60° when doing measurements in-vivo and in-vitro [34]. Measured vs true flow speed, 178 µm Measured speed (cm/s) 10 R² = 0,9926 8 R² = 0,9992 6 4 2 0 0 2 4 6 infusion speed (cm/s) Linear (16 MHz) Linear (std) 8 10 Linear (32 MHz) Figure 24 Measured speeds vs. speed of infusion of a 178µm vessel Figure 25 shows the trend lines of the proportional error calculated by: A convergence towards the theoretical value can be observed at higher speeds for both frequencies. But, because many variables can cause a certain offset in the results (e.g. angle correction), it can be stated that the consistency between the measurements is crucial, rather than the absolute value of the estimation. At 16 MHz, the results are more accurate than at 32 MHz, and this also applies to the 155µm tube. 29 Proportional error on speed measurement error (%) 120 90 60 30 0 0 2 4 6 8 infusion speed (cm/s) Log. (16 MHz) Expon. (32 MHz) Figure 25 Proportional error on speed measurements, both trend lines convergence to zero. Figure 26 shows almost perfect estimations at 32MHz, whereas at 16 MHz there is a small offset of 0.4481 cm/s ( ). Again, a convergence towards zero can be observed with higher infusion rates (Figure 27). Measured vs true flow speed, 155 µm Measured speed (cm/s) 10 R² = 0,9947 8 R² = 0,9894 6 4 2 0 0 2 4 6 8 10 infusion speed (cm/s) Linear (std) Linear (16 MHz) Linear (32 MHz) Figure 26 Speed measurements within a 155 µm tube Proportional error on speed measurement (155µm) error (%) 100 0 0 2 4 6 8 10 -100 -200 infusion speed (cm/s) 16 MHz 32 MHz Figure 27 Proportional error on the speed measurement when infusing a 155 µm tube. At both frequencies, a convergence towards zero can be observed for higher flow speeds. 30 Figure 28 shows the results acquired from the 100 µm tube. Although the results look decent, the results can be denoted as untrustworthy. The first reason is the very frequent obstructions faced while doing the test. Narrow as the lumen is, only a few large BMF particles have to coagulate to create a clump big enough to close the vessel. Second, the system responded slowly to changing the settings of the pump. To visualize these problems, the logarithmic trend line has been plotted, showing a good fit between the continuous measurements done from 4-10 mL/h. Furthermore, the resistance of the vessel was so high that even when observing stable laminar flow, the syringe pump went into alarm (> 1000 mmHg at highest setting). This could possibly be solved by filtering the BMF in the 8-20 µm range, and by keeping the tube as short as possible. Nonetheless, the sonograms of these measurements showed no hiatuses or any apparent lack of backscattered information necessary to track the mean value. Measured speed (cm/s) Measured vs true flow speed, 100 µm 12 R² = 0,9463 10 8 6 4 2 0 -2 0 2 4 6 8 10 12 infusion speed (cm/s) 32 MHz Linear (32 MHz) Linear (std) Figure 28 Flow speed measured through a 100 µm ID tube, a large spread in results can be observed due to clots shutting off the vessel To be conclusive on the influence of diminishing diameter sizes, even thinner tubes should be acquired to perform the same experiments on. However the results are showing no complications on the level of speed measurements in a simple setup. 4.2.2 GE The influence of varying depth could not be measured with the Visualsonics because the transducers are optimised for imaging superficial (5-15 mm) structures in rodents. The imaging depth is also limited due to the high frequency and consequently high attenuation. Hence, a similar experiment as mentioned above has been done using the GE Vivid 7, equipped with a linear array transducer (5-9 MHz), but with a certain variation of depth. 4.2.2.1 Data processing In contrast to the Visualsonics, there was no software package available for post-processing data acquired with the Vivid 7. A Matlab tool (Asklepios) that had been written in the context ultrasound research was used to estimate the velocity on a sonogram. The working of this program is based on estimating where the white zone of the sonogram (i.e. “stronger” echoes) stops (Figure 29). The distance between this endpoint and the baseline can be multiplied with the scale (contained in the dicom header tags), which results in a single speed estimation. Repeating this procedure for every point of the contour will provide a good approximation of the maximum speed. However, the true 31 averaged speed lies within the centre of the white band, and can’t be approximated by using the peak values. This is why, for this experiment, the lower contour was added to the upper contour, and divided by two. Upper contour (white dots) Averaged speed Lower contour Figure 29 Sonogram being processed using the Asklepios Matlab tool Figure 30 shows an underestimation of flow speeds when observing deeper structures. This can be expected owing to the fact that the attenuation will increase exponentially when going deeper inside the TMM. As the intensity of the backscattered signal drops, the upper and lower contours are likely to drop because the echoes won’t be detected unambiguously. Changing the sensitivity could address this problem because weaker signals won’t be neglected. But, this will generate many erroneous interpretations, making the measurement unreliable. Measured vs. true flow speed at 2 depths 10 Measured speed (cm/s) R² = 0,9887 8 6 R² = 0,9586 4 2 0 0 2 4 6 8 10 infusion speed (cm/s) Figure 30 Measured vs. True flow speed at 1.5cm (red) and 3cm (blue) 32 4.3 Colour flow speed measurements 4.3.1 Visualsonics The extraction of flow speeds starting from colour Doppler images is quite cumbersome. There was to my knowledge- no software which could directly relate images to flow speeds. The procedure for extracting the data is explained below. 4.3.1.1 Data processing Studies saved on the Visualsonics are stored in a proprietary file type. These can be read by the Vevo software package, and they can be exported to .dicom files. This is a standard file type developed specifically for “digital imaging and communications in medicine” (DICOM). Once the images are converted to .dicom, they can be read into Matlab. The first part of a dicom file consists of several attributes which refer to the imaging settings (frequency, flow scale etc.) and some general information (time and date, patient’s name etc.). The second part contains the pixel data, stored in an m*n*3 matrix, respectively being the number of rows and columns, and the red, green and blue values of each pixel. When looking closely at a colour flow image, it is clear that the intensity of the flow (and colour) is directly related to the green value (for arterial = red and venous = blue flow). A piece of Matlab code was written which relates the green values of every pixel to the colour scale. The GE machine has a linear scale which makes a linear interpolation quite precise. The Visualsonics has a discontinuous parabolic scale, thus making linear interpolation imprecise. This is why the measurements below have been calculated manually by linking the green value to the parabolic scale designated by the machine. The true speed can be calculated using following formula: ( ) with being the average green value of a cross section divided by the maximum green value (= 255), and s being the flow speed scale factor. Theoretical speed vs Color doppler estimation Measured speed (cm/s) 12 R² = 0,9935 10 8 6 4 2 0 0 2 32MHz 4 6 8 10 12 Theoretical speed (cm/s) Linear (std) Linear (32MHz) Figure 31 Colour Doppler speed estimation in a 178 µm tube 33 As can be seen in Figure 31, the results are surprisingly accurate even at low speeds. This corresponds to the results obtained in a previous study done by Carolus J.P.M. Teirlinck and Peter R. Hoskins d [35], who noticed an overestimation of only a factor 1.0 to 1.25 at 2.5 MHz. However, a more recent study showed there was an overestimation with a factor 1.5-3 [3]. These results can’t be confirmed by the measurements done in this thesis. Lower flow speeds were not measured because the lower boundaries of the flow speed scale were already reached, resulting in almost no colour data (cf. [36]). 4.4 Flow profile monitoring The collected CFI data could be used to estimate the flow profile within the tube. If this proves to be accurate, problematic flow patterns within the smallest arterioles could be analysed. Ideally, the flow pattern should be parabolic. However, the information the transducer acquires is based on the momentary distribution of scatterers (in vivo = red blood cells) which could deviate from the parabolic pattern. To draw the flow profile of one single cross-sectional line, the average of 15 frames has been calculated using the same methods as described in 4.3. The results are shown in Figure 32. The profiles based on the 16 MHz images approach the parabolic shape although a minor plateau can be seen, which arises from an artefact in the image. The 32 MHz profiles display a different pattern differing a lot from the parabolic form. The explanation for this phenomenon can be seen in Figure 33. At 32 MHz, the reflections are high, leading to a falsely observed flow outside of the vessel. This problem doesn’t exist at 16 MHz, or for the 100 µm tube. Having accurate flow estimates within a small sample volume (cf. 4.2.1.3) doesn’t necessarily prove that erroneous flow patterns can be detected. But, combined with the knowledge that the measured distribution of speeds across the tube is corresponds to the theoretical profile; more information could be gathered about the flow pattern of the blood. This could be useful for e.g. making surface plots of the blood flow through of narrow site. 34 32 MHz 100 µm 16 MHz 32 MHz reflection 155µm 178 µm Figure 32 Comparison between the flow profiles (speed vs. pixels) for different frequencies and different tube diameters Reflection Figure 33 The colour Doppler image taken at (L) 16 MHz confines the flow quite precisely within the tube. At (R) 32 MHz a reflection of the tube can be observed. 35 4.5 Discussion Because this discussion embodies several aspects of the measurements, they will be addressed separately. Set-up The set-up showed to be reliable up to 155µm. The flow was easily controllable without generating resistance which exceeded the syringe pumps maximal value. The scatterers remained in suspension throughout the entire measurement procedure and provided an echo strong enough to be detected. It was feared that the polyimide tubing could cause strong reflections, but they demonstrated a decent echogenicity. When testing the 100µm tube, several problems emerged. The filtering of the orgasol with a 70µm filter was insufficient to prevent blockage of the vessel. This caused periodical pressure build-ups, followed by high flow speeds until the system stabilized. Furthermore, the resistance generated by this short tube was high enough to push the syringe pump into alarm. This made continuous measurements arduous. Measurements Both the measurements at 32 MHz and 16 MHz showed to be accurate for estimating “high” and low (1 cm/s) flow speeds through vessels down to 155µm. It is expected that the same trend will be observed when downscaling to 100µm, but the phantom reached its boundaries making it impossible to produce conclusive data at this level. It should be noted that the sonogram gets ambiguous when observing speeds lower than 3 cm/s due to two reasons. The first being the weak signal received from such slow fluid movement consequently producing a vague sonogram. Second, it is all but optimal to estimate values which are closely packed around the baseline, even when the scale is minimized. Optimal set-up It will be extremely hard to incorporate the additional difficulties such as smaller vessels (<100µm), muscle movement en complex patterns into a model as produced. Nonetheless, these challenges will be decisive to the question If perfusion at microcircular scale is feasible or not. A better solution would be the perfusion of an embalmed ex-vivo structure. Such a set-up comprises the fractional nature of a complex network of crossing vessels. As stated in the literature review, it can be difficult the asses which volume is passing through each capillary, but this can be solved using a microscope to track the moving particles while performing US measurements. Hence, a comparison can be made between the ultrasound imaging and the ground truth. 36 Chapter 5. Extra: CFD 5.1 Introduction Preterm born babies are prone to develop cerebral strokes within the first weeks after birth. There are many techniques to detect abnormalities, which could be an indication of cerebral lesions. But, they all impose a high burden on the patient. Most of these imaging techniques rely on the use of contrast agents or radioactivity, and often the patient has to be transported to the machine and sedated to acquire decent images. It won’t be surprising to state that the toll of similar examinations will be too high for preterm born babies. If high-frequency ultrasound proves to estimate brain perfusion accurately, it could be used as a bed-side tool to monitor the brain circulation of preterm born babies on a regular basis. Hence, any indication of an upcoming problem could be detected at an early stage which would minimize the possibly detrimental outcome of e.g. a stroke. The experiments which have been conducted on the parametrical model (cf. chapter 4) are not sufficient to state that high-frequency ultrasound is ready for clinical use. Before doing so, exhaustive testing should be done on an in-vivo mimicking model, which could replicate the flow with high precision. The difference between this set-up and the parametrical model would be the complexity of the geometry and flow pattern. If possible, low frequency (5-36 Hz) clutter noise should be introduced to replicate muscle vibrations throughout the tissue [37]. The geometry of choice is the Circle of Willis (CoW) because it is of utmost importance to the perfusion of the cerebral vascular system. In this chapter, the importance of the CoW will be briefly explained by showing the basic anatomy. Next, the basics of the model acquisition and meshing procedure will be covered, as well as its possible uses to further research. 5.1.1 Anatomical information The human brain is the most crucial part of the body because it is the centralized computer powering every mechanical, physiological and chemical process necessary to live. It is fuelled by a complex circulatory system with a built-in safety feature, known as the Circle of Willis. If one of the major arteries supplying the brain with oxygenated blood becomes narrow or gets blocked, the other arteries can still provide enough blood to avoid severe health issues (e.g. ischemia) by using alternative pathways. This set of linkages between vessels (anastomosis) is known as the Circle of Willis. A peculiar aspect of the CoW is its design, which strongly varies from person to person. Only 20-25% of the population possesses a fully develop system.[38] Figure 34 Anatomical picture of the circle of Willis [1] 37 5.1.2 From images to model The production of a 3D model can be a cumbersome procedure involving many different challenges. In this section a short overview of the basic steps will be given. Exhaustive guides can be found online. An MRI-TOF (=time of flight) dataset was used as the basis of the model. Such an examination consists of making many thin slices, each representing a cross-sectional image of the head. Based on several phenomena which will not be addressed in the scope of this thesis, the internal structures can be clearly distinguished in each image. When loading this data into the Materialise Mimics software, the Circle of Willis can be delimited in each slice. Doing this for many images, an approximation of the regions of interest its contour can be calculated. This results in a rough model with many artefacts and defects. Further cleaning can be done by either erasing some pixels on each slice, or by using smoothing and triangle reduction algorithms implemented in the Magics ® postprocessing software. The first is preferred because solving the problem at its roots proves to be timesaving and better results will be achieved afterwards. For finalizing, the post-processing software can be used. To prevent the model from being too complicated as can be seen in Figure 35, it is beneficial for the CFD results to eliminate the smallest vessels and to concentrate on the larger arteries. The next step involves the generation of a mesh using ICEM. Depending on the application, the mesh can be made out of 1D, 2D (thinshell) or 3D elements. In the context of fluid simulations, a 3D mesh will be required. Figure 35 (L) before trimming the excess branches (R) after trimming and smoothing To start the CFD calculations, there should be enough data on the flow speeds through the afferent vessels. The outlet flow can be set to “velocity outlet” and based on the proportional surface areas; approximations of the volume distribution through each separate efferent vessel can be made. Test solutions, based on parameters found in the literature [39] showed good convergence behaviour, with very low residuals. Figure 36 shows a solution on which the vectors are depicted, and their magnitude is related to a colourscale. By making such a visual representation of flow data, problems can easily be seen and communicated to non-technical staff. 38 Figure 36 (up) CFD simulation of flow through the circle of Willis (down) zoomed image showing the individual vectors By combining the design possibilities of Magics with the CFD power of Fluent, many interesting pathologies could be created and simulated, on general models and on patient specific data. 5.1.3 Real model The .STL file shown in Figure 35 has been 3D printed; the result can be seen in Figure 12. 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