Home Medicine Development of a skull phantom for the assessment of implant X-ray visibility
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Development of a skull phantom for the assessment of implant X-ray visibility

  • Thomas Hoffmann EMAIL logo , Fabian Klink , Axel Boese , Karin Fischer , Oliver Beuing and Georg Rose
Published/Copyright: September 30, 2016
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Current Directions in Biomedical Engineering
From the journal Current Directions in Biomedical Engineering Volume 2 Issue 1

Abstract

The paper presents the development and test of a skull phantom, which can be used for the assessment of the radiographic visibility of neurovascular implants. State of the art methods are based on specimens of the human skull. These are highly individual and not suitable for comparison of different radiographic data sets. The development process of the skull phantom is described from data generation to image processing, design and manufacturing using 3D printing. An experimental setup is recommended to generate reproducible data sets for implant visibility assessment with bone mimicking structures of the phantom. The model is evaluated by qualitative comparison with equivalent data sets of the original human skull model. The results show, that contrast characteristics of the phantom and the human skull model are similar. X-ray attenuation of the human bone is higher than the polymeric phantom material. The introduced phantom allows the determination of X-ray attenuation characteristics of different neurovascular implants for medical approval and testing processes.

Keywords: medical approval; phantom; radiopacity; skull; stent; testing; X-ray

1 Introduction

The X-ray visibility of neurovascular implants like stents or coils is a crucial factor for the success of an intervention. The thin stent structures are hardly recognizable under fluoroscopy, which makes exact placement and judgment of wall apposition difficult [1], [2]. For medical approval processes of such implants, radiopacity has to be proven. This is done by quantitative [3] or qualitative X-ray radiographies. For qualitative assessment, the implant is placed in different regions of a human skull specimen. Following the implant is imaged by radiography with clinical parameters. The visual appearance of the implant is compared to a benchmark.

Disadvantage of this method is, that the visibility strongly depends on the region of interest and the thickness and density of the used bones. Thus, images of implants from different sites are not comparable with each other.

The aim of this work was to overcome this problem by using a reproducible artificial model of the skull in a defined field of view. Following the development process of the model is described and an assessment of the model is done by comparing the radiographic data sets of the original and phantom in an implant trial.

2 Material and methods

2.1 Preparation and image generation

In cooperation with the anatomical institute, the skull of a female body donor was selected for image generation. The jawbone of the skull was removed and the calvaria was cut for preparation processes.

A cone beam computed tomography (CT) data set of the skull was acquired with a Siemens Artis zeego (Siemens Healthcare GmbH, Erlangen, Germany) flat panel angiography system (see Figure 1). The data set was 3D reconstructed with an isotropic voxel size of 0.5 mm.

Figure 1 Experimental setup. (A) Siemens Artis zeego flat panel 3D-angiography system. (B) Patient table. (C) Skull.
Figure 1

Experimental setup. (A) Siemens Artis zeego flat panel 3D-angiography system. (B) Patient table. (C) Skull.

2.2 Image processing

To define a realistic projection plane of the skull, neurointerventions of patients undergoing device implantation were analysed. The results were verified by experienced neuroradiologists. From the chosen projection plane, a region of interest (ROI) was selected. Structures affecting the visibility, like the temporal bone as an area with high attenuation and the opposing skullbones along the projection axis, were included in the ROI (see Figure 2). The CT dataset was processed with Mevislab (MeVis Medical Solutions AG, Bremen, Germany). A thresholding filter was used to separate bones in the ROI from patient table and imaging artifacts. The segmentation process was finished by using a region growing algorithm to segment only connected areas of the temporal bone and skullcap.

Figure 2 Image processing steps. (A) Radiography of the skull in realistic angulation of projection and selected ROI (white square). (B) ROI along the projection axis (white arrow) in 3D CT dataset.
Figure 2

Image processing steps. (A) Radiography of the skull in realistic angulation of projection and selected ROI (white square). (B) ROI along the projection axis (white arrow) in 3D CT dataset.

2.3 Design process

For an efficient manufacturing process the distance between skullcap and temporal bone was decreased, as changes of this distance don’t induce relevant deviations from realistic projection images (Figure 3A and B).

For connecting upper and lower bone structures in the desired orientation of the physical model, four rods were modeled in the data set (see Figure 3C).

The post processed image data was triangulated to create a standard tessellation language (STL) data type which can be printed via rapid prototyping systems. The volume model was smoothed to decrease the step effects of the voxel surface.

Figure 3 Design process of the phantom. (A) Segmented bone structures with temporal bone (up) and skullcap (down). (B) Decreased distance between both structures to save time and material in the manufacturing process. (C) Integrated rods for the spatial orientation of the physical model.
Figure 3

Design process of the phantom. (A) Segmented bone structures with temporal bone (up) and skullcap (down). (B) Decreased distance between both structures to save time and material in the manufacturing process. (C) Integrated rods for the spatial orientation of the physical model.

2.4 Rapid prototyping - techniques and materials

Requirements for the design of a realistic head phantom are similar X-ray attenuation properties as real bone and that identical structures are visible. The attenuation is described by the Hounsfield Units (HU) which vary from 50–3000 for different bones [4]. In the skull specimen, the cortical bone had a density of ∼2300 HU, whereas the trabecular bone had lower values of ∼800 HU. The HU values were calculated from a volume data set of the human specimen, which was generated at 70 kV with a Siemens SOMATOM Definition AS+ (Siemens Healthcare GmbH, Erlangen, Germany) CT system.

Figure 4 Investigated rapid prototyping materials. (A) Photography of the different material cubes. (B) Image of a dynaCT data set of the materials. Materials 8 and 12 show the lowest attenuation (dark), samples 10, 11, 13 the highest.
Figure 4

Investigated rapid prototyping materials. (A) Photography of the different material cubes. (B) Image of a dynaCT data set of the materials. Materials 8 and 12 show the lowest attenuation (dark), samples 10, 11, 13 the highest.

Table 1

Hounsfield unit (HU) values of the investigated materials. Wax materials show the lowest attenuation, powder the highest. UV curing polymers with a light wavelength of 354.6 nm (sample 10 and 11) show a higher attenuation than UV curing materials with a wavelength of 405 nm (sample 1–5, 6–8).

No.LabelMaterialHU (70 kV)
1Black resinpolymer54
2Clear resinpolymer63
3Flexible resinpolymer46
4Tough resinpolymer64
5White resinpolymer69
6PlasGRAYpolymer96
7PlasPINKpolymer71
8SuperWAXpolymer−98
9SuperCASTpolymer42
10VisiJet® SL clearpolymer415
11VisiJet® SL toughpolymer512
12Thermo neutralwax−121
13ZP102 (cyanoacrylate infiltration)powder795
14Fullcure 720polymer71
15Paperpaper/glue17
Figure 5 Qualitative comparison between the datasets of the original skull specimen and the manufactured phantom (A, A.1, A.2). The radiography of the real bones (B) with visible filigree bone structures. Those are not distinguishable in the radiography of the skull phantom (C). Both datasets show similar gray intensity changes. The windowing levels are not comparable to each other (B: 983/1044, C: 1894/1044), caused by different measuring setups and X-ray system properties. Images B.1–B.4 show different planes in the 3D data. Compared to C.1–C.4 there are different dense bone structures with smaller cavities visible. Those were not depicted in the manufactured model or are filled with liquid polymer.
Figure 5

Qualitative comparison between the datasets of the original skull specimen and the manufactured phantom (A, A.1, A.2). The radiography of the real bones (B) with visible filigree bone structures. Those are not distinguishable in the radiography of the skull phantom (C). Both datasets show similar gray intensity changes. The windowing levels are not comparable to each other (B: 983/1044, C: 1894/1044), caused by different measuring setups and X-ray system properties. Images B.1–B.4 show different planes in the 3D data. Compared to C.1–C.4 there are different dense bone structures with smaller cavities visible. Those were not depicted in the manufactured model or are filled with liquid polymer.

Attenuation and depiction of the structures highly depend on the chosen manufacturing process and material. In a first step, the attenuation properties of different rapid prototyping (RP) materials were checked. Therefore, a cube of 1 × 1 × 1 cm3 was designed and stored as a surface triangulated file format. The cube was manufactured in different materials with the following RP machines: ProJet 6000, ZPrinter 310 Plus, Thermojet (all 3D Systems Ltd., Rock Hill, South Carolina, USA), EDEN 330 (Objet Geometries Inc, Rehovot, Israel), Freeform Pico (ASIGA Pty Ltd, St Peters, Australia), Form 1+ (Formlabs Inc., Somerville, Massachusetts, United States), LOM 2030 (Helisys Inc., Michigan, U.S.). A CT scan of each sample was performed (see Figure 4) and their arithmetic mean gray values were calculated (see Table 1). Powder material showed bone-like attenuation values, but it is limited by the manufacturing process. With the underlying 3d printing (3DP) process cavities cannot be created without remnants of powder. This increases attenuation compared to normal temporal bones, in which such cavities are filled with air. Sample 10 and 11 showed values in the range of 415 HU to 512 HU, which are less than human cortical bone but are still in the range of expected gray values. The material was chosen as a feasible compromise between imaging and manufacturing properties.

After the manufacturing process, the model was cleaned, support structures removed and fully cured in a UV light system.

3 Results

3.1 Comparison of characteristic structures

The phantom was imaged with a 2D radiography and 3D volume CT. The acquired images were compared with those of the human skull specimen regarding characteristic structures (see Figure 5). Radiographic images show similarities in the gray scale characteristics, but 2D tomographic images show differences in filigree bone structures. The reason is that the cavities of the phantom temporal bone still contain liquid polymer, which has a similar attenuation as solid polymer.

3.2 Implant trial

A measurement setup was created in accordance to Schmidt et al. [3] based on a polymethyl methacrylate (PMMA) block of 200 mm × 200 mm × 150 mm (l × b × h) as scattering body. The bone phantom was positioned in the center of the block. A field of view of 200 mm × 200 mm was used for radiography. As usual done in clinical neurovascular interventions, the tube voltage was adjusted to 70 kV. A representative stent was positioned in the ROI. The auditory canal was used for defined alignment. A second data set of the original skull with the identical implant and orientation was acquired for a qualitative comparison. Figure 6 shows the image data with equal windowing properties (2006/1720). As expected, human bone has higher attenuation which can be determined in higher contrast values of the skull structures. In both images stent markers are distinguishable. In the phantom data set, stent struts are visible, though only barely.

Figure 6 Radiography of the phantom (A) and human skull specimen (B). A neurovascular stent was placed in the region of the auditory passage. Stent markers are visible in both images (white circles). The phantom model shows a lower attenuation. Thus stent struts are slightly noticeable in the left image.
Figure 6

Radiography of the phantom (A) and human skull specimen (B). A neurovascular stent was placed in the region of the auditory passage. Stent markers are visible in both images (white circles). The phantom model shows a lower attenuation. Thus stent struts are slightly noticeable in the left image.

4 Conclusion

The developed skull phantom showed similar attenuation distribution as a human skull. Attenuation of the chosen rapid prototyping material is lower than that of real bone. This results in lower contrast values of phantom data sets. However, no other of the tested polymeric RP materials showed attenuation properties like cortical bone. Furthermore, the varying density of bones cannot be imitated with the investigated rapid prototyping methods.

However, the presented setup can be used for generating reproducible datasets for comparison of implant visibility. Beside the qualitative testing of the radiopacity, this method can be used for generating data for medical approval processes or product benchmark.

Author’s Statement

Research funding: This work was partly funded by the Federal Ministry of Education and Research in Germany within the Research Campus STIMULATE under grant number 03FO16102A. Conflict of interest: Authors state no conflict of interest. Material and Methods: Informed consent: Informed consent has been obtained from all individuals included in this study. Ethical approval: The research related to human use complies with all the relevant national regulations, institutional policies and was performed in accordance with the tenets of the Helsinki Declaration, and has been approved by the authors’ institutional review board or equivalent committee.

References

[1] Lu X, Chen T, Comaniciu D. Robust discriminative wire structure modeling with application to stent enhancement in fluoroscopy. In Computer Vision and Pattern Recognition (CVPR). 2011:1121–7.10.1109/CVPR.2011.5995714Search in Google Scholar

[2] Boese A, Rose G, Friebe M, Hoffmann T, Serowy S, Skalej M, et al. Increasing the visibility of thin NITINOL vascular implants. Current Directions in Biomedical Engineering. 2015;1:503–6.10.1515/cdbme-2015-0120Search in Google Scholar

[3] Schmidt W, Behrens P, Kamke F, Schmitz KP. Measurement of radiopacity of vascular implants. Biomedical Engineering-Biomedizinische Technik. 2014;59:S1216–9.Search in Google Scholar

[4] Lehmann T, Oberschelp W, Pelikan E, Repges R. Bildverarbeitung für die Medizin: Grundlagen, Modelle, Methoden, Anwendungen. Springer-Verlag: 2013.Search in Google Scholar

Published Online: 2016-9-30
Published in Print: 2016-9-1

©2016 Thomas Hoffmann et al., licensee De Gruyter.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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https://doi.org/10.1515/cdbme-2016-0078
Keywords for this article
medical approval; phantom; radiopacity; skull; stent; testing; X-ray
Creative Commons
BY-NC-ND 4.0

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  91. Regularization of EIT reconstruction based on multi-scales wavelet transforms
  92. Assessing MRI susceptibility artefact through an indicator of image distortion
  93. EyeGuidance – a computer controlled system to guide eye movements
  94. A framework for feedback-based segmentation of 3D image stacks
  95. Doppler optical coherence tomography as a promising tool for detecting fluid in the human middle ear
  96. 3D Local in vivo Environment (LivE) imaging for single cell protein analysis of bone tissue
  97. Inside-Out access strategy using new trans-vascular catheter approach
  98. US/MRI fusion with new optical tracking and marker approach for interventional procedures inside the MRI suite
  99. Impact of different registration methods in MEG source analysis
  100. 3D segmentation of thyroid ultrasound images using active contours
  101. Designing a compact MRI motion phantom
  102. Cerebral cortex classification by conditional random fields applied to intraoperative thermal imaging
  103. Classification of indirect immunofluorescence images using thresholded local binary count features
  104. Analysis of muscle fatigue conditions using time-frequency images and GLCM features
  105. Numerical evaluation of image parameters of ETR-1
  106. Fabrication of a compliant phantom of the human aortic arch for use in Particle Image Velocimetry (PIV) experimentation
  107. Effect of the number of electrodes on the reconstructed lung shape in electrical impedance tomography
  108. Hardware dependencies of GPU-accelerated beamformer performances for microwave breast cancer detection
  109. Computer assisted assessment of progressing osteoradionecrosis of the jaw for clinical diagnosis and treatment
  110. Evaluation of reconstruction parameters of electrical impedance tomography on aorta detection during saline bolus injection
  111. Evaluation of open-source software for the lung segmentation
  112. Automatic determination of lung features of CF patients in CT scans
  113. Image analysis of self-organized multicellular patterns
  114. Effect of key parameters on synthesis of superparamagnetic nanoparticles (SPIONs)
  115. Radiopacity assessment of neurovascular implants
  116. Development of a desiccant based dielectric for monitoring humidity conditions in miniaturized hermetic implantable packages
  117. Development of an artifact-free aneurysm clip
  118. Enhancing the regeneration of bone defects by alkalizing the peri-implant zone – an in vitro approach
  119. Rapid prototyping of replica knee implants for in vitro testing
  120. Protecting ultra- and hyperhydrophilic implant surfaces in dry state from loss of wettability
  121. Advanced wettability analysis of implant surfaces
  122. Patient-specific hip prostheses designed by surgeons
  123. Plasma treatment on novel carbon fiber reinforced PEEK cages to enhance bioactivity
  124. Wear of a total intervertebral disc prosthesis
  125. Digital health and digital biomarkers – enabling value chains on health data
  126. Usability in the lifecycle of medical software development
  127. Influence of different test gases in a non-destructive 100% quality control system for medical devices
  128. Device development guided by user satisfaction survey on auricular vagus nerve stimulation
  129. Empirical assessment of the time course of innovation in biomedical engineering: first results of a comparative approach
  130. Effect of left atrial hypertrophy on P-wave morphology in a computational model
  131. Simulation of intracardiac electrograms around acute ablation lesions
  132. Parametrization of activation based cardiac electrophysiology models using bidomain model simulations
  133. Assessment of nasal resistance using computational fluid dynamics
  134. Resistance in a non-linear autoregressive model of pulmonary mechanics
  135. Inspiratory and expiratory elastance in a non-linear autoregressive model of pulmonary mechanics
  136. Determination of regional lung function in cystic fibrosis using electrical impedance tomography
  137. Development of parietal bone surrogates for parietal graft lift training
  138. Numerical simulation of mechanically stimulated bone remodelling
  139. Conversion of engineering stresses to Cauchy stresses in tensile and compression tests of thermoplastic polymers
  140. Numerical examinations of simplified spondylodesis models concerning energy absorption in magnetic resonance imaging
  141. Principle study on the signal connection at transabdominal fetal pulse oximetry
  142. Influence of Siluron® insertion on model drug distribution in the simulated vitreous body
  143. Evaluating different approaches to identify a three parameter gas exchange model
  144. Effects of fibrosis on the extracellular potential based on 3D reconstructions from histological sections of heart tissue
  145. From imaging to hemodynamics – how reconstruction kernels influence the blood flow predictions in intracranial aneurysms
  146. Flow optimised design of a novel point-of-care diagnostic device for the detection of disease specific biomarkers
  147. Improved FPGA controlled artificial vascular system for plethysmographic measurements
  148. Minimally spaced electrode positions for multi-functional chest sensors: ECG and respiratory signal estimation
  149. Automated detection of alveolar arches for nasoalveolar molding in cleft lip and palate treatment
  150. Control scheme selection in human-machine- interfaces by analysis of activity signals
  151. Event-based sampling for reducing communication load in realtime human motion analysis by wireless inertial sensor networks
  152. Automatic pairing of inertial sensors to lower limb segments – a plug-and-play approach
  153. Contactless respiratory monitoring system for magnetic resonance imaging applications using a laser range sensor
  154. Interactive monitoring system for visual respiratory biofeedback
  155. Development of a low-cost senor based aid for visually impaired people
  156. Patient assistive system for the shoulder joint
  157. A passive beating heart setup for interventional cardiology training
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