Abdominal aortic wall thickness and compliance The possibilities to measure and the effect of variation in the analysis of aneurysms

Writer Master University Company

Karel van den Hengel Medical Engineering University of Technology Eindhoven University Medical Centre Maastricht

Professor Daily supervisors

Frans van de Vosse Lambert Speelman & Marielle Bosboom

Date Assignment BMT Number

April 2008 – September 2008 Internship Master Program BMTE 08.47

Index Chapter 1: Introduction .................................................................................................................... - 3 Chapter 2: Overview of the aorta wall............................................................................................. - 5 Variation in wall thickness in healthy AA and AAA’s.................................................................... - 6 MRI & CT........................................................................................................................................ - 7 Detection method MRI ................................................................................................................. - 8 Detection method CT ................................................................................................................... - 9 Chapter 3: Finite Element Method................................................................................................. - 10 Segmentation and Mesh Creation .................................................................................................. - 10 Wall thickness variation................................................................................................................. - 10 Finite element analysis................................................................................................................... - 12 Wall stresses results by different wall variations........................................................................... - 13 Chapter 4: Wall detection ultrasound............................................................................................ - 15 Introduction.................................................................................................................................... - 15 Method ........................................................................................................................................... - 16 ART.LAB .................................................................................................................................... - 16 Material parameters .................................................................................................................. - 17 Results............................................................................................................................................ - 18 Wave analyses aortic wall.......................................................................................................... - 18 Conclusion ..................................................................................................................................... - 21 Chapter 5: Discussion & Recommendations ................................................................................. - 22 Appendix ........................................................................................................................................... - 24 Appendix 1: Table of export file ART.LAB.................................................................................. - 24 Appendix 2: Principle of MRI, and TFE and Black blood sequences. .......................................... - 25 Appendix 3: Meshplots all subjects and wall thickness variations ................................................ - 27 Appendix 4: Distention 7 ............................................................................................................... - 29 Appendix 5: Graphs wall velocity and distention .......................................................................... - 30 References ......................................................................................................................................... - 33 -

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Chapter 1: Introduction An aneurysm in the abdominal aorta is a common disease. An aneurysm is a localized dilation of a blood vessel. Every year, 150.000 new patients are diagnosed (Ouriel, Green et al. 1992; Bengtsson, Sonesson et al. 1996). In most cases, an abdominal aortic aneurysm (AAA) causes no symptoms or illness to the patient, so it is often detected coincidently. The aneurysms grow progressively and may eventually rupture. If it ruptures it causes death 9 out of 10 times. The only therapeutic option for patients with (ruptured) AAA is open or endovascular surgery. The criterion for elective a surgery is a maximum AAA diameter of 5.5 cm. However, about 60% of the aneurysms with a diameter over 5,5 cm never ruptures, so an operation takes unnecessary surgery risk (Vorp 2007). On the other hand, small AAAs can rupture too (Choksy, Wilmink et al. 1999). Over the last couple of years an increasing amount of screening programs have been developed for research. In these programs the only criterion ‘diameter’ is replaced by more patient specific criterions. Biomechanically, rupture of the AAA wall will occur when the stress acting on the wall due to the blood pressure, exceeds the strength of the wall. Many studies have focused on patient-specific wall stress analyses (Fillinger, Raghavan et al. 2002; Truijers, Pol et al. 2007). With a computer-based method, the Finite element method (FEM), for solving complex structural problems, the stress values can be calculated. The calculations are based on the 3D geometry of the AAA, material parameters and the blood pressure. The geometrical shape of the AAA is in most cases determined from Computed Topographic Angiography (CT). In research on the material parameters of the AAA wall and healthy abdominal aortas large variations have been found. Using standard values for these parameters just led to a maximum error less than 5 %(Vorp 2007). Vorp purpose, it is obvious the differences in AAA wall stresses between patients are driven more by the differences in surface geometry than the differences in material properties (Vorp 2007). Also the wall thickness of the abdominal aorta is taken uniform in the computer models. Intravascular research of wall thickness in the neck of the aorta by AAA is done by Arko et al (Arko, Murphy et al. 2007). A difference in wall thickness, 2.3 + 0.6 anterior and posterior and 1.2 + 0.3 lateral (mean + SD), was found in 25 patients. Where the wall experiences more stresses, a thicker aortic wall was found (Yamada and Hasegawa 2006). Therefore in vivo research is advisable to measure the wall thickness for stress analysis models. With Magnetic resonance imaging (MRI) and CT the wall thickness of the aorta is yet hardly discernible. Besides these imaging methods, ultrasound is also a common used medical imaging method. In previous research wall thickness by ultrasound measurements was done on some arteries, for example the carotid artery. The carotid artery lies close to the skin, so a high ultrasound frequency can be used to image this artery. The high frequency results in high resolution images, with excellent analysis possibilities.(Haller, Schulz et al. 2007) Research on the wall thickness of the abdominal aortic is scarce and more complex. The abdominal aortic is located dorsal, anterior to the spinal column. Because of the properties of ultrasound, bones make it impossible to image the anatomy behind it. Therefore it is impossible to image the abdominal aortic from the backside of the patient. When imaging a patient from the front side, the distance to the abdominal aorta is larger than for the carotid artery. This requires a lower frequency for a deeper penetration of the ultrasound waves. A lower frequency consequently leads to results with a lower resolution.(Hill 2004)

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The aim of this study is to evaluate the possibilities to measure the wall thickness of the abdominal aorta, to evaluate the potential to measure and calculate the elasticity of the abdominal aorta and to study the effect of the wall thickness on the wall stress analyses. In chapter 2 first an overview of the structure of the aortic wall is given, also a short view on the methods MRI and CT is discussed. In chapter 3 the effects of wall thickness variation in stress analyses will be discussed. In chapter 4 the focus lies on the ultrasound research, wall thickness measurement and wall velocity measurement. First healthy people will be measured to define and evaluate the measurement protocol. Finally in chapter 5 the discussion and recommendations for the future are shown.

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Chapter 2: Overview of the aorta wall The wall of the aorta can be differentiated in 3 parts; from the lumen to the outside, the intima, the media and the adventitia (figure 1).

Figure 1: Schematic the aortic wall.

The intima is the most inner and the thinnest layer of the aortic wall. The first monolayer is the endothelium. This prevents interaction, like the inflammatory. The largest part of the intima is the subendothelial, existing of connective tissue elements, only 20 to 40 collagen elements and elastin. This layer grows with age by proliferation. The last layer of the intima is the internal elastic membrane. This membrane is circumferentially oriented and uninterrupted. The average thickness of the intima is about 130 µm for adult.(Lindsay 1979; Restrepo, Strong et al. 1979) The media has an average thickness of 1 mm for an adult. The functional tissues in this layer are elastin fibers and smooth muscle cells, absorbing the pressure waves of the heartbeat. Elastin fibers lay ordered circumferentially in the media. These ligaments are intermediate by collagen and smooth muscle cells, which are positioned longitudinally and anchored to the elastic fibers. The elastin in this layer leads to the elastic properties of the artery. The amount of elastic ligaments is related to the diameter of the aorta. After the age of 50, the amount of the elastic fibers decreases and the amount of collagen increases. This results in a loss of elasticity and an increased stiffness of the aortic wall (Lindsay 1979).

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Figure 2: Schematic the aortic wall.

The adventitia has an insignificant effect on the structural stability of the aorta. It mainly contains connective tissue, like fibroblasts (figure 2). The adventitia is the only one of the three layers that can becomes thinner throughout life. Because of the thickness of the aortic wall, blood supply by diffusion from the lumen is not enough. Small arteries and veins lay in the adventitia, which is the vasa vasorum.

Variation in wall thickness in healthy AA and AAA’s. Abdominal aorta (AA) wall thickness measurements were done on healthy subjects in multiple studies. Åstrand (2005) used B-mode ultrasonography in his study to determine the lumen diameter and intimamedia thickness (IMT) in the AA. In total 111 healthy subjects were involved in the study. An intimamedia wall thickness (mean + SD) of 0.73 mm + 0.15 was found for men and an intima-media wall thickness (mean + SD) of 0.73 mm + 0.16 for woman (Åstrand, 2005). In 1979 Restrepo published an article about intimal thickness of the aortic wall. Restrepo found intima wall thickness of the AA of 0.10 mm for males and 0.09 mm for females. This research measured the aortic intima thickness microsopically on samples collected during the first year of the International Atherosclerosis Project and includes information of subjects from all over the world. The population consisted of 2,472 healthy subjects aged 15 to 64. Samples included were free of atherosclerosis. (Restrepo, Strong et al. 1979) Beside healthy, also abdominal aortic aneurysms (AAA) were measured. On human abdominal aortic aneurysms that are surgically removed, wall thickness measurements were done. Raghavan -6-

explored the regional distribution of wall thickness and failure properties in human AAA’s. Three unruptured and one ruptured AAA were collected for the study. Thickness was measured at about every 1.5 cm2 wall surface area each AAA. With a total of 100 measurements for every AAA, a thickness (intima, media and adventitia) in a range of 0.23 mm to 4.26 mm with a median of 1.48 mm were found.(Raghavan, Kratzberg et al. 2006) Thubrikar studied five surgically removed abdominal aortic aneurysms. A variation in wall thickness was found circumferential. The wall thickness results were from posterior region 2.73 + 0.46 mm (mean + SD) to lateral region 2.52 + 0.67 mm (mean + SD) to anterior 2.09 + 0.51 mm (mean + SD) region (Thubrikar, Labrosse et al. 2001).

Figure 3: Aortic wall will the different tunica (left) and endothelia, elastin and smooth muscle cells (right).

MRI & CT For FEM analyses patient specific values of wall thickness leads to more realistic and accurate models. Earlier wall thickness research of AA is only done on surgically removed tissue. In this pilot research we look at the possibilities to measure the wall thickness noninvasively. For noninvasively and local wall thickness measurements, CT and MRI are the possible methods. With the analysis of the data, the variation in one patient and between patients will be researched. The technical explanation of MRI and the used sequences are explained in appendix 2.

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Detection method MRI The available MRI sequences of multiple AAA patients were 3DBTFE, 2DBTFE and Black Blood (figure 4 A, B & C). On MRI it is hard to differentiate the aortic wall from surrounding tissue. In the TFE 2D and 3D sequence the aorta is surrounded by a black border. However, this is not the aortic wall. This black border is caused by the chemical shift artefact. This artefact is caused by a transition of water and fat protons. The resonance frequency of these protons differ from each other, which leads to a spatially misregistration. Because of this artefact a black or white border appears on the image on the tissue transition. (Campus_Medica 2007) The aortic wall is invisible due to the black border. A benefit of this border is its good boundary detection for the shape and position of the aorta. On the other sequence is the black blood MR, what can be used to detect the aortic wall thickness. However, a disadvantage of this sequence is the fact that the aortic wall and thrombosis tissue can not be discriminated. To research wall thickness variation in patients, slices without thrombosis must be taken to measure the wall thickness. To select these slices the TFE 2D and 3D sequence can be used. In these slices of the black blood MR lines from de centre of the aorta to the outer side of the aorta can be made. On these lines a line spectrum can be made. To determine the wall thickness, a 50 percentile value of the maximum wall pixel blackness is taken as a transition to the surrounding tissue. To measure the aortic wall thickness posterior, anterior and lateral in different slices, the variation in and between patients can be researched. For this research, MRI images of AAA patients from Catharina Hospital Eindhoven and Academic Hospital Maastricht are used. However, the results of the measurements are not adequate, because the values have a large variation. The cause of this is the quite large pixel size of 0.34 mm by black blood and 0.59 mm by TFE 2D and 3D. In comparison with the expected wall thickness of about 2 mm, this is a too low resolution for the detection. Therefore the quality of the MRI measurements used for this project was insufficient.

A

B

C

D

Figure 4: Image sample of the MRI sequences 2DBTFE (A), 3DBTFE (B) and Black Blood (C), and a CT image sample (D).

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Detection method CT CT measurement is another possible imaging technique (figure 4D). In CT the aortic wall can not be discriminated from surrounding tissue. In the images calcification in the wall is visible by CT. Disappointing is an inhomogeneous deposit against the wall. Another disadvantage is the large pixel size of CT (0.7x0.7x2 mm), similar to the MRI techniques.

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Chapter 3: Finite Element Method Research studies to analyze the risk on rupture have focused on patient-specific wall stress analyses. In the mesh of the abdominal aortic aneurysm (AAA) in these studies the wall thickness is a constant factor. To study the effect of the variation in wall thickness, meshes with varying wall thickness are made and used as input for the stress computing. This will answer the question what the effect of wall thickness variation on the wall stress of an AAA is.

Segmentation and Mesh Creation Software developed by Philips Medical Systems (Best, the Netherlands) is used to automatically segment the AAA from the CT scan (Breeuwer, de Putter et al. 2008).The user-input is selecting a starting point proximal to the AAA and an endpoint, proximal to the aortic bifurcation. The aortic bifurcation is excluded from the segmentation in this study. A standard mesh is placed over the centreline and fixed on both endpoints. A 3D active object (3DAO), based on the centreline, is used to automatically detect the edges of the lumen and the AAA wall (figure 5). The 3DAO implementation method is based on work by Delingette (Delingette 1994) and the segmentation of the AAA wall is used as input for the AAA wall stress simulations. A standard mesh typically consists of approximately 6.000 quadratic 27-node hexahedral elements.

A

B

C

Figure 5: Mesh creation, with the centre line (A), the lumen (B) and the aortic wall (C).

Wall thickness variation The wall thickness in the 3D models of the AAA (meshes) is normally uniform and set to 2 mm. To see the effect of variation of the wall thickness, a Matlab script is written to change the wall coordinates. In the standard cylinder mesh the numbers of the mesh points that lay in one line, in the same angle and in the same height were found. The meshes used for this analyzes were built with 1 layer of elements in the thickness, this means 3 position coordinates in the thickness. This is only possible when the mesh is built with hexahedral elements. The middle point of the three found mesh

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points is the middle line of the wall. The other two points were translated to an increase or decrease distance to the middle point (figure 6).

a

Figure 6: Repositioning mesh points.

To research the effects of variation, 5 different meshes were made for 3 different AAA meshes. The first variation in wall thickness is a decreased wall thickness when the diameter of the mesh is larger. The second variation is a decrease of wall thickness along the aorta. In the superior level a wall thickness of 2 mm and a lineair decrease to 1,6 mm at the inferior level. The third variation is a combination of the first and second variations. The fourth variation is the wall thickness measured by Thubrikar (Thubrikar, Labrosse et al. 2001). Lastly a mesh with the standard 2 mm wall thickness is added (variation 0) (figure 7). Each variation expects influence on the stress values. In the first variation the wall is thinner where the diameter is higher. To caught the force by the wall by a higher diameter, the stress will be higher each vessel. When the diameter is doubled, the thickness is halved, so the stress will be doubled too. In the second variation the wall thickness is maximal decreased by 20 % and the peak pressure will not be in the end and begin of the mesh, the stresses will maximal increase by 25 %. In the third variation, a combination will happen and will lead to the highest stress results. By Thubrikar mesh the stresses will decrease, because the wall is thicker.

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Variation 1

Variation 2

Variation 3

Variation 4

2

2

2

2

1.4

1.87

1.2

2

1

1.73

0.8

2

2

1.7

1.6

Variation 5 P 2.73 L 2.52 A 2.09

1.4

Figure 7: Wall thickness variation in different slices applies on the meshes. Wall thickness is written in each slice. In variation 5 all slices have the same wall thickness variation.

Finite element analysis The finite element software Sepran (Sepra, Delft, the Netherlands) was used to calculate the AAA wall stresses, using the segmented AAA wall. The variations in wall thickness were used and a realistic hyper-elastic material model (shear modulus of 0.9 MPa) was used for the AAA wall. A systolic blood pressure of 120 mmHg is applied to the inner wall of the finite element model. The most distal and proximal planes are constrained in all directions as essential boundary conditions. Local stresses, strains and displacements were calculated. In each node, maximum principal stress is computed as a single stress measure. The equations used in the finite element models are based on the momentum equation, with the conservation of mass. The outcome is position points, stress, strain and displacements of the mesh points. Final results are the stresses which act on the wall. To analyze the effect of the variation the outcome of the calculation will be compared. The maximal, 99 percentile and the 95 percentile stress is estimated. Because of the high sensitivity by the peak wall stress (Speelman), we will focus on the 99 and 95 percentile values. In this way the extreme peaks values can exclude. Also the change in stress distribution on the wall will be analyzed.

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Wall stresses results by different wall variations In the table below the maximal, 99 percentile and the 95 percentile stresses of subject P03, P06 and P10 are shown. P03

Var 0

Var 1

Var 2

Var 3

Var 4

Max stress

618

874

41%

668

8%

998

61%

522

-16%

99 percentile

305

468

53%

368

20%

553

81%

248

-19%

95 percentile

227

386

70%

265

16%

458

102%

183

-19%

P06 Max stress 99 percentile

Var 0 479 230

95 percentile

182

P10 Max stress 99 percentile 95 percentile

Var 0 301 229 202

Var 1 594 24% 303 32%

Var 2 586 22% 259 12%

Var 3 721 51% 346 51%

Var 4 377 -21% 185 -20%

255

208

299

147

40%

Var 1 468 415 378

55% 81% 87%

14%

Var 2 348 263 235

15% 15% 16%

65%

Var 3 555 497 446

84% 117% 121%

-19%

Var 4 264 191 166

-12% -17% -18%

Table 1: Results of max stress, 99 percentile stresses and 95 percentile stresses by all subjects and all wall thickness variations. The values are in kPa. Also the percentage change compare to the Variation 0 is shown behind the stress values.

The results in the stresses acting on the outer wall of the aorta are quite different by all wall thickness variations applied on the meshes before the stress calculations. The stress distribution over the meshes of all subjects and variation is shown in appendix 3. The colour changes display the stress changes between the variations. In subject P03 a spot in the middle of the mesh is visible. This spot indicates local high stresses. In wall variation 1 and 3 this area has expanded a little, so there is more local stress on the aortic wall. In P10 a similar spot is found on the mesh. In contrast to subject P03, the spot shows less stresses by wall variation 1 and 3. Although subject P03 and P06 shows no big changes in stress distribution results between the wall variations, the results of subject P10 shows a much larger increase in stresses on the inferior part of the AAA mesh. Geometry and fluid streams must be the cause of these different results. In table 1 the shown results between the subjects in wall variation 2 and 4 is almost none. Variation 4 results in decreased stresses. In the variations 1 and 3 P06 shows the smallest changes and P10 the biggest changes in wall stresses. The maximal stress shows overall the smallest changes and the 95 percentile the biggest changes compared with variation 0.

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Figure 8: Mesh plot of subject P10 with wall thickness variation 3 and the wall stresses acting on the mesh wall.

Subject P10 shows with variation 3 the biggest change in the stress values, the same as the stress distribution. This could be explained with local anatomic tissue structure, but this is not investigated. Furthermore the diameter of this subject is the largest of all subject what results in the smallest wall thickness, and this leads to the highest wall stresses. Overall the variations show effect in the distribution and stress values, which pleads for the importance of wall thickness by AAA. These differences imply that wall thickness is an important parameter for the stress calculation and thus crucial for the analysis of the AAA.

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Chapter 4: Wall detection ultrasound Ultrasound (US) is a used technique by ex vivo human research. It is a technique with much potential and is possibly a good solution when doing measurements on wall thickness on the abdominal aortic aneurysm (AAA).

Introduction Ultrasound is a high frequency sound (it definite ranges between 2 MHz and 20 MHz), which is higher than the range of our hearing system. In a medical ultrasound system the application used is the echo of the US waves. The ultrasound is generated by a piezoelectric transducer. Electric pulses administered to the transducer generate a wave, the ultrasound. The reflection of the sent sound waves caused by a density transition will be received and measured. The transducer is fixed in a probe. The returned signal is caught with the same probe. The sound wave vibrates the transducer, and the transducer translates the vibration into an electric signal. This signal will convert from an analogue into a digital Radio Frequency signal (RF-signal) (figure 9). This is the basic signal that is used in medical research. In clinical settings this signal is directly translated into a digital image for real-time analyze (Cobbold 2007).

Figure 9: Rf-signal

The returned signal gives information about the anatomy in the line of the sent wave. Changes in density of tissue cause a reflection; the fraction of reflection depends on the size of density change. With a 2D image of different wave lines anatomic structures can be recognized.(Hill 2004) Ultrasound use different frequencies, the temporal sample frequency, the spatial sample frequency and the frequency of the sound. The frequency of the sound defines the images resolution and the penetration depth. Higher frequencies have a smaller wavelength, thus giving smaller details. Reflections of two points close behind each other can best be differentiated with a small wavelength. The negative effect of a high frequency is a high attenuation, which means that the sound will not reach the depth of a low frequency. Because the aorta lies relatively deep in the body, usually a low ultrasound around 3.5 MHz will be used. We used a frequency of 3.5 MHz, which gave a wavelength of 0.44 mm and an axial resolution of 0.22 mm. The temporal frequency of the ultrasound machine is the pulse frequency of the machine. The scanner sends 1 pulse (1 pulse contain three sound waves) and first receives all reflected information before sending the next pulse. This time is determined by the penetration depth. The signal travels away and returns with the speed of sound, so the more depth the longer the travel time. We used a temporal sample frequency of 1020 Hz. - 15 -

The spatial sample frequency we used was 33 MHz. This is the sample frequency of the reflected signal, and is much higher than the ultrasound frequency. So the resolution is not limited by the detection, because one sample captures the information of a smaller distance in the tissue than the resolution definite by the frequency of the sound.

Method Ultrasound measurements were performed on 3 healthy persons. 5 measurements perpendicular to the belly (the normal), 5 measurements around 30 degree negative lateral to the normal and 5 measurements around 30 degree positive lateral to the normal were done (figure 10).

Belly

30°

Aorta Figure 10: Measurement angles on the belly.

First the abdominal aorta will be displayed in B-mode in the machine screen and focused in the middle. The B-mode is a 2D image of the anatomic structure, using several beam lines. When the aorta is in the middle and has enough reflection on the anterior and posterior wall the machine is switched to M-mode. The M-mode displays just one beam line rf-signal towards the time. This signal is the export of the ultrasound machine during the measurements.

ART.LAB ART.LAB is a program for analyzing ultrasound data. The program uses the RF-signal, measured by the ultrasound machine. Data can be imported during and after measurements. During the measurements on the patient, all basic data without processing will be exported in a zrf-file. This file can also be imported in ART.LAB for data analysis later on. During five heart beats the subject will be measured. In ART.LAB the average values and SD (standard deviation) of the diameter and the IMT are calculated. When the data later on will be analyzed, some setting can be changed to get better detection (figure 11). First the program Distention 7 is used for afterwards research (Appendix 4). The manual input in Distention 7 was more as in ART.LAB. This leads to large variations in the results caused by user interpretation input. To exclude this, ART.LAB is finally used for analysis. With the M-mode signal displayed, different thicknesses can be measured. Thickness values interesting for this research are total diameter and intima-media thickness. These values can be detected automatically based on mathematics and input parameters, for example the centre of the aorta. The change of the media to the adventitia gave a maximal reflection compared to the surrounding tissue. The reflection of the lumen to the intima is less, but can be detect because of the phase change caused by the tunica transition of the lumen to the intima. The other transitions of tunica gave nearly no reflection. This tunica transition can be detected if there are not much artefacts, but enough reflection power (Brands, Hoeks et al. 1997; Hoeks, Willekes et al. 1997; Meinders, Brands et al.

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2001). Mirror artefact is sound that is reflected several times before it reaches the probe (Softways 2008) .

Figure 11: User window ART.LAB

All detected results can be exported from ART.LAB in a DSP-headers file. In the table in Appendix 1 the exported data lines can be seen (Brands 2003) .

Material parameters The DSP-headers imported in matlab give many possibilities to analyze the data. When the signal is cut in separate heart beats, the signal can be compared by beat and average all beats. The wall velocity can be integrated to get the average wall distention. With the wall thickness, distention, diameter and the systolic and diastolic blood pressure, the elastic modulus, also called the Young modulus (e-modulus) of the aorta can be calculated. For a homogeneous linear elastic walled tube with constant wall thickness, the formula for the e-modules is Ε=

σ ε

with σ the applied force and ε the stretch. With ε ZZ = ∆L / L0 =

1 Ε UR σ ZZ , σ φφ = Ε 1 − µ 2 A0

and

σ zz = µσ φφ leads to 2π ∗ a 03 1 − µ 2 h ∂A / ∂p with a0 the diastole radius, h the wall thickness, µ the Poisson ratio, ∂A the cross area change and ∂p the systole, diastole pressure difference. Ε=

Also the diameter with SD, distention with SD, IMT with SD and delta IMT with SD can be calculated for each subject.

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Results The measurements gave a good image of a part of the aorta. For most measurements the aorta had good reflection at the posterior and anterior wall. Despite the good reflections of the walls, there was also a signal received from the lumen. This signal has been caused by the mirror artifact, and it leads to wrong interpretation. Because the mirror artifact and hardly any reflection of the lumen intima transition, data measured by the ultrasound machine was not of enough quality to determine the IMT. The ART.LAB system had problems to find the IMT, in most measurements no lumen intima transition was found. In Distention 7 the manual input to determine the wall gave an indefinite uncertainty. Because the transition between the lumen en intima is more difficult to see, the placement of the markers is arbitrary. The placement of the markers for the anterior and posterior wall can be quite good by using the rf-signal window (figure 10 & 11). Because of the low quantity, no results and conclusion can be created of the IMT by the ultrasound measurements.

Wave analyses aortic wall When analyzing, the wall velocity appeared to be quite good to analyze. In figure 12A the wall velocity of all heartbeats of 1 measurement for 1 subject can be found. The velocity wave for one heartbeat can be very coarse, this is caused by the bad imaging quality of the ultrasound machine. Averaging of the heartbeat gave a nice smooth heartbeat (figure 12B). When integrating the velocity the wall distention can be found (figure 12C). All plots are in appendix 5. B

A

C

Aorta wall velocity - subject subject LL Aorta wall velocity - subject subject LL 50

50

40

40

30

30

Distention - subject subject LL 1.8 1.6 1.4

10

20

[mm]

[mm/s]

[mm/s]

1.2

20

10

1 0.8 0.6

0

0

-10

-10

-20

-20

0.4 0.2 0

0

0.1

0.2

0.3

0.4

0.5

0.6

→ One beat

0.7

0.8

0.9

1

0

0.25

0.5

→ One beat

0.75

1

-0.2

0

0.25

0.5

→ One beat

0.75

1

[s]

Figuur 12: Aortic wall velocity each heartbeat (A), the average aortic wall velocity with STD box (B) and the aortic wall distention with STD box (C) of subject LL 0 degrees. The figures of the all subjects in all degrees are shown in appendix 5.

In table 2 the results of the ultrasound measurements are shown. The compliance and E modulus are calculated as written in the methods.

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0 Degree Aortic diastole pressure (Pa) Aortic systole pressure (Pa) Distention (mm) Mean STD Distention Diameter (mm) Compliance (m/Pa) Total heartbeats Total measurements E modulus (Pa) Minus 30 Degree Aortic diastole pressure (Pa) Aortic systole pressure (Pa) Distention (mm) Mean STD Distention Diameter (mm) Compliance (m/Pa) Total heartbeats Total measurements E modulus (Pa) Plus 30 Degree Aortic diastole pressure (Pa) Aortic systole pressure (Pa) Distention (mm) Mean STD Distention Diameter (mm) Compliance (m/Pa) Total heartbeats Total measurements E modulus (Pa)

TK 0 ° 7.6 E+03 17.0 E+03 1.01 0.05 15.6 2.7E-09 16 4

LL 0 ° 9.7 E+03 17.1 E+03 1.46 0.09 18.3 5.9E-09 16 4

KH 0 ° 6.7E+03 15.9 E+03 1.78 0.09 14.6 4.7E-09 3 1

4.2E+05

3.1E+05

2.0E+05

TK -30 ° no results no results no results no results no results no results no results no results

LL -30 ° 8.4 E+03 20.9 E+03 1.53 0.08 14.9 3.0E-09 20 5

KH -30 ° 8.8 E+03 19.9 E+03 1.58 0.15 13.6 3.2E-09 2 1

#VALUE!

3.3E+05

2.3E+05

TK 30 ° 7.2 E+03 16.1 E+03 0.81 0.10 14.6 2.1E-09 6 2

LL 30 ° 7.2 E+03 19.1 E+03 1.58 0.07 14.6 3.2E-09 20 5

KH 30 ° 7.2 E+03 15.6 E+03 1.96 0.11 15.9 6.2E-09 11 4

4.4E+05

2.9E+05

1.9E+05

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Mean Aortic diastole pressure (Pa) Aortic systole pressure (Pa) Distention (mm) Diameter (mm) Compliance (m/Pa) Total heartbeats Total measurements

Mean E modulus (Pa)

Mean TK 7.4E+03 16.6E+03 0.91 15.1 2.4E-09 22 6

Mean LL 8.4E+03 19.0E+03 1.52 15.9 4.0E-09 56 14

Mean KH 7.6E+03 17.2E+03 1.77 14.7 4.7E-09 16 6

4.3E+05

3.1E+05

2.1E+05

Table 2: Results of Aortic diastole pressure, Aortic systole pressure, Distention, Mean STD Distention, Diameter, Compliance, Total heartbeats, Total measurements and E modulus of each subject by a degree of 0, minus 30 and plus 30. TK minus 30 degree show no results

The tables show similar results in subjects for the different angles. The bold values in the table are results that were corrected afterwards. These results were inaccurately calculated, by including artefacts in the evaluated data in the calculation. For the subject ‘TK’ by an angle of minus 30 degree all the measurements gave insufficient data. The data was inadequate to make an analysis. KH 0 degrees and KH minus 30 had just one good measurement and TK plus 30 only two good measurements. Scatterplot by Level Code (X 10000) 44

E modulus

39 34 29 24 19 KH

LL

TK

Subject Figure 13: Scatter plot of the measurement results of the E modulus (Pa) of each subject.

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The results of the E modulus in the different angles give quite the same values (figure 13). The variation between the subjects is larger as inter by a subject between the different angles. Differences by one subject can be caused by a not fully circular aorta. The subject KH shows a high distention, which results in a lower E modulus, and subject TK shows a lower distention, resulting in a high E modulus shown in table 2. The results evaluated with the ANOVA test leads to a p < 0.0002. This means de results are subject specific.

Conclusion The wall velocity measurements with ultrasound show stable results. It is possible to measure statistically significant different between subjects. With these measurements more vascular research on the transferring functions between the aorta and other arteries is possible. Also patient specific material parameters can be measured to include in the AAA analysis models.

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Chapter 5: Discussion & Recommendations The surgery criterion for patients with an abdominal aortic aneurysm (AAA) is a diameter 5.5 cm. Studies evaluate the prognoses of rupture change of the AAA by wall stresses instead of the diameter (Fillinger, Raghavan et al. 2002; Truijers, Pol et al. 2007). In wall stress studies a constant wall thickness is used. The aim of this study was to see the effect of the wall thickness on in wall stress analyses, to evaluate the possibilities to measure the wall thickness of the abdominal aorta and to evaluate the potential to measure and calculate the elasticity of the abdominal aortic. First we evaluated the effect of wall thickness variations on wall stresses computed by finite element model. The applied wall thickness (WT) variations (WT decrease by diameter increase, WT decrease along the aorta, a combination and literature values (Thubrikar P 2.73, L 2.52, A 2.09)) resulted in different stress results. The stress results of the 99 percentile could be doubled between the different wall thickness variations. The variation of Thubribar had a larger wall thickness and led to lower stresses, but the other wall thickness variations led to higher stresses. Although the stress distribution over the abdominal aortic aneurysm (AAA) showed just little changes, the peak stress points were still in the same position. Overall, these results show that the wall thickness variation over the aorta influences the stresses in the Finite Element Models (FEM). As local wall thickness can strongly influence the wall stress, local wall thickness measurements are required. To measure ex vivo the local wall thickness of the aorta, CT and MRI are possible medical imaging techniques. With different sequences of MRI (Black Blood, TFE 2D and TFE 3D) and the CT images, no wall thickness could be determined. Reasons why the aortic wall was not traceable are that there was no differentiation between wall and surrounding tissue and artifacts. Furthermore the pixel size of the CT images was inadequate. The expected wall thickness exists of around 3 pixels, which is insufficient for sub millimeter wall thickness assessment. Therefore these methods were not suitable for the measurement of the local wall thickness of the aorta. Another imaging method was ultrasound, although with this method, the wall thickness cannot be measured at every location on the aorta. Nevertheless ultrasound can be used to measure the wall thickness at multiple locations. Because of secondary reflections and noise, the lumen intima transition (inner side of the wall) was not detectable. So this method was not suitable for the measurement of the wall thickness. Lastly we looked at the compliance and E modulus of the aorta, which are important material parameters. Ultrasound is used for measuring wall position over time, by detecting the media adventitia transition. Measurements were done on 3 healthy volunteers. Each measurement existed of 5 times 5 seconds recording in 3 different circumferential angles. With measuring the position of the aortic wall and the blood pressure over time, the compliance and the E modulus could be computed. The results of the E modulus that we found were 430 kPa (range: 420-440), 310 kPa (range: 290-330) and 210 kPa (range: 190-230). Variation between and within subjects resulted in an AVOVA test to p < .01. The mean E modulus is 3 times the values found in literature (Long, 2004). These differences could be explained by the diameter measurements, which were done based on the adventitia layer and not the intima layer. As the diameter influences the E modulus with a power of 3, this can have a significant effect on the resulting E modulus. Limitations of this study were an assumption of a wall thickness of 2 mm in the calculation of the E modulus and small sample size: 3 volunteers are not population representative. Although the measurement was done at only 3 subjects, it gave constant outcomes within subject for material parameter research.

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In the healthy subjects we used in this research the diameter of the aorta was around the 1.5 cm, which gives no problems with the record window of 4 cm in the system used in this research. For the future a new computer system behind the ultrasound systems is required that is capable of processing data for more than 4 cm ultrasound information, which is necessary for a patient with an AAA with a diameter larger than 4 cm. For future research of the wall thickness of the aortic wall, the focus must be on the new developments of the imaging methods. Ultrasound is rapidly undergoing developments, and more stable and less noisy images could give higher resolution images and better details of the wall in deeply located structures. For AAA patients this is necessary in any case, because the patients are often obese, in contrast to the healthy subjects used in this research. Another opportunity is to measure the wall thickness with CT images by visualizing the calcification of the aortic wall. Hereby it is assumed that the size of the calcified parts is the same as the whole aortic wall thickness. Also, different MRI and CT sequences may be combined to visualize the aortic wall. Future ultrasound research can be done on wall velocity measurements. For the population representative values larger sample sizes are required. Beside this, research can be done to compare the stiffness between arteries. This can give insight in relations in blood pressure between arteries. An overall local wall thickness variation measurement is needed by the analysis of the risk of an AAA, because the results of the variation wall thickness meshes evaluate in the FEM models. Although the available detection methods were not sufficient to measure the aortic wall thickness, the ultrasound measurements were suitable to compute the E modulus, a material property of the aortic wall. The ultrasound E modulus measurements show statistically significant differences between the subjects. Future technical developments might generate higher resolution and less noisy images to calculate wall thickness of the aorta.

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Appendix Appendix 1: Table of export file ART.LAB General DSP result label 16 w (16): L0

(16) :

RfLine

RF-line number (position in frame)

L1

(16) :

FrNr

Frame number

L2

(16) :

ScanMode (1 Bm, 2 FBm, 16 Mm, 32 Dm)

Scan mode

L3

(16) :

DspTrigBit

Trigger bits (low active)

L4 L5

(16) : (16) :

NrRfRow NrRfCol

Number of RF samples in depth Number of RF lines in one frame

L6

(16) :

Skip

Delay (skip) [RF sp]

L7

(16) :

RefCh0

Pressure channel.

L8

(16) :

RefCh1

Reference channel 1.

D16

(32) :

esys_tsint

echo system temporal sample interval [

D17

(32) : rf_ssint

RF-signal spatial sample interval [

m]

D18

(32) : bm_tsint

B-mode temporal sample interval [

s]

D19

(32) : fm_tsint

Fast B-mode temporal sample interval [

D20

(32):

mm_tsint

M-mode temporal sample interval [

s]

D21

(32):

dm_tsint

D-mode temporal sample interval [

s]

D22

(32):

rf_ssint

RF-signal spatial sample interval [ nm ]

D23

(32):

probe_pitch

Probe pitch [ nm ]

W32

(16) :

ant_pos

Anterior wall position [ RF sp ]

W33

(16) : pos_pos

Posterior wall position [ RF sp ]

W34

(16) : lum_pos

Blood vessel lumen position [ RF sp ]

W35

(16) : drop_out

W36

(16):

Dimensions 32 w (8): s]

s]

Vessel wall contour 16 w (16):

Drop out indicator [ Flag ] Diam

Blood vessel diameter [

m]

Vessel wall thickness information 16 w (16): I48

(16) : MedPos

Media position anterior wall [RF sp]

I49

(16) : IntPos

Intima position anterior wall [RF sp]

I50

(16) : PImt

Intima media thickness [um]

E64

(16) : Dist_int

Displacement integration [ Bool ]

E65

(16) : Dant

Displacement anterior wall [nm]

E66

(16) : Dpos

Displacement posterior wall [nm]

E67

(16) : IDant

Distension anterior wall [

E68

(16) : IDpos

Displacement posterior wall [

Tissue velocity information 16 w (16):

m e-1] m e-1]

Position device 16 w (16): P80

(16):

Lum_angle

Lumen angle [ deg ]

P81

(16):

exp_imtr

Expected IMT range [RF sp]

P82

(16) : Line1

Region line1 (l1 < l2) [RF line]

P83

(16) : Line2

Region line2 (l2 < Ncol) [RF line]

P84

(16) : Wf_line

Waveform line ( l1