Loading [MathJax]/jax/output/CommonHTML/jax.js
Home A macrophage model of osseointegration
Article Open Access

A macrophage model of osseointegration

  • Herbert P. Jennissen EMAIL logo
Published/Copyright: September 30, 2016

Abstract

The mechanisms of peri-implant de novo bone formation and contact osteogenesis are still largely unknown. In 1984 Donath et al. showed that macrophages were the first cells to colonize a titanium implant. Recently it was shown that that there are inflammatory (M1) and healing macrophages (M2), the latter of which can secrete BMP 2. In the context of data from a gap healing experiment a macrophage model of osseointegration is suggested.

1 Introduction

Peri-implant healing by de novo bone formation (increase in bone volume) involves two principal pathways, namely contact osteogenesis and distance osteogenesis as originally reported by Osborn 1979 [1]. In contact osteogenesis (osteoconduction), predominant in trabecular bone, bone forms first on the implant surface by recruitment and migration of osteogenic cells so the implant surface, followed by bone formation in apposition to the implant surface [2]. In distance osteogenesis, predominant in cortical bone, autochtonous new bone is formed on the surface of old bone, instead of on the implant, and approximates the implant surface from the periphery [2]. An important factor influencing contact osteogenesis appears to be the hydrophilicity and microtopography of an implant surface (for reviews see Ref. [3], [4]). The histology of the first stages of peri-implant healing on a titanium plasma sprayed surface (TPS) was reported in 1984 by Donath et al. [5]. However, how de novo bone formation occurs on an inert metallic surface such as titanium is unclear. Here a model is proposed for nanostructured, hyperhydrophilic titanium surfaces (see [6]).

2 Material and methods

Methods for the preparation of hyperhydrophilic titanium plasma sprayed surfaces are described in Ref. [6]. The methods involved in gap healing experiments in vivo have been described for osteoinductive TPS-surfaces (BMP-2) in sheep [7] and for nanostructured hyperhydrophilic TPS surfaces preliminarily in minipigs [8]. The hyperhydrophilic nanostructured TPS-implant surfaces were conserved in the dry state by an exsiccation layer of salt [9]. They were implanted in this dry state being wetted intra operationem with blood. The de novo bone formation is defined as the ratio between the area (mm2) of new bone and the total defined area (reference region of interest) in percent. Bone ongrowth i.e. bone implant contact (BIC) via histological slide (1D) is defined as the ratio between the length (mm) of the bone-implant contact and the total defined unit length (reference, region of interest) in percent.

3 Results

As has been shown by others [4] and in Ref. [9], [10] ultra- and hyperhydrophilic titanium surfaces can lead to an increase in bone volume (osteoinduction) and bone ongrowth i.e. BIC (osteoconduction). This is illustrated in Table 1.

Table 1:

Bone volume increase and bone ongrowth increase on nanostructured surface in minipig femur (see [8]).

TPS-control super-hydrophobicTPS-CSA hyper-hydrophilicp-Value
No nanostructureNanostructure
4 Weeks
 Osteoid volume (%)1.79 ± 0.333.78 ± 0.34<0.001
8 Weeks
 Bone ongrowth (%)0.073 ± 1.416.68 ± 1.48<0.030
12 Weeks
 Osteoid ongrowth (%)0.40 ± 1.107.53 ± 1.01<0.004

a100% = 6.5 mm, ˉx ± SD, n = 15.

Titanium TPS surfaces are originally super- or hyperhydrophobic. A wettability shift by acid etching makes the surfaces hyperhydrophilic. In experiments on nanostructured hyperhydrophilic TPS surfaces (Table 1) 4 weeks after implantation in minipigs [8] osteoid volume increases two-fold corresponding to induced de novo bone. Bone ongrowth (i.e. BIC) after 8 weeks increases nearly by two orders of magnitude and osteoid ongrowth (BIC) after 12 weeks nearly 20-fold.

The question is, how can these increases in peri-implant bone volume and bone implant contact be explained?

4 Discussion

4.1 Macrophages are the first cells to colonize a titanium implant

In 1984 Donath et al. [5] first described mononuclear histiocytes, today known as stationary form of connective tissue macrophages [11], on the surface of TPS coated titanium cylinders 3 days after implantation in the rat femur (Figure 1). Between 5 and 56 postoperative days foreign body giant cells (multinucleate macrophages) on the implant surface were observed. Two populations could be distinguished cytoplasm-rich “acid-phosphatase-positive giant cells” and smaller “acid-phophatase-negative giant cells” [5]. In contrast osteoclasts and osteoblastswere observed on bone spicules and trabeculae [5] but not on the Ti-implant. The above results are in agreement with the recent conclusion that specific osteal macrophages (“osteomacs”) exist in bone and that osteal macrophages and osteoclast precursor cells are cytologically different after having diverged from a common progenitor cell [12]. Thus the observations of Donath et al. strongly indicate the importance of macrophages for peri-implant endosseous healing.

Figure 1: Multinucleated giant cells (arrows) on titanium plasma sprayed (TPS) implant surface (Ti). Two types giant cells were first reported as (i) acid-phosphatase positive and (ii) acid phosphates negative cells. The former correspond to osteoclasts and the latter may be derived from wound-healing osteal macrophages (from: Donath et al. [5]).
Figure 1:

Multinucleated giant cells (arrows) on titanium plasma sprayed (TPS) implant surface (Ti). Two types giant cells were first reported as (i) acid-phosphatase positive and (ii) acid phosphates negative cells. The former correspond to osteoclasts and the latter may be derived from wound-healing osteal macrophages (from: Donath et al. [5]).

Peri-implant healing by de novo bone formation involves two principal pathways, namely contact osteogenesis and distance osteogenesis as originally reported by Osborn 1979 [1]. Of prime importance for bone bonding to the biomaterial surface is a structure called “cement line” an initial secretion of non-collagenous proteins followed by mineral nucleation and crystal growth [2], [13].

Of key importance appear to be the physico-chemical properties of the hyperhydrophilic CSA-TPS implant surface as previously described [6], [14]. Together with the high wettability expressed in imaginary contact angles of ΘAR = 10.9i°/13.5i°, and an extremely high wetting and spreading rate on hyperhydrophilic surfaces appear optimal for the immediate deposition of a fibrin matrix [2] together with blood platelets [15]. Platelet-rich plasma contains a variety of growth factors supporting bone repair [15], which may also play an important initial role on the first day. However, very soon afterwards macrophages move in [5]. Recently the connective tissue macrophages of the bone, i.e. histiocytes, discovered on the third postoperative day on implants together with the fused form of macrophages (i.e. foreign body giant cells) on the fifth day by Donath et al. [5] (Figure 1), have become of prime interest. Bone tissue specific macrophages have beentermed “osteal macrophages” [12], which can secrete a large number of cytokines, chemokines and growth factors [16].

4.2 M2-macrophages synthesize BMP-2

An important discovery was the polarization of macrophages into two phenotypes i.e. destructive inflammatory M1 and reparative wound healing M2 macrophages [17]. Crucial growth factors of such reparative macrophages for bone growth are VEGF [18] and surprisingly also of BMP-2 [19], [20]. Therefore the findings of oseoconductivity can be interpreted on this pathophysiological and biochemical basis. BMP-2 in concentrations of 50–300 pg/ml can be secreted into the cell culture medium by macrophage cell lines such as J774A.1 and RAW264.1 cells [19], [20]. In sum these findings can be interpreted as a new pathophysiological and biochemical basis of osteoconductivity.

4.3 Nanostructures on implant surface stimulate synthesis of BMP-2

Recently Sun et al. [20] reported that TiO2 nanotube layers stimulate RAW 264.7 macrophages to secrete BMP-2 in contrast to smooth surfaces. A nanostructure with tubes of 30 nm in diameter begins to stimulate BMP-2 secretion versus a smooth surface. BMP-2 secretion by RAW 264.7 macrophages then increases two-fold up to 300 pg/ml as the diameter is increased to 120 nm. Since the hyperhydropilic TPS surfaces (e.g. in Table 1) are nanostructured [7], it is conceivable that the osteal macrophages are optimally stimulated by the nanostructured TPS surface to secrete BMP-2, explaining the osteoinductive and osteoconductive properties of this surface (Table 1). In contrast the super hydrophobic TPS controls, which lack high wettability, high wetting and spreading rates as well as the macrophage stimulating nanostructure, show practically neither osteoinductivity nor osteoconductivity. Given these results, hyperhydrophilic nanostructured implants may display a great potential in a variety of orthopedic and trauma surgery applications.

4.4 Macrophage model of osseointegration

A novel model of surface contact osteogenesis can be proposed on the above observations. The new insights indicate that the osteoconductive efficiency of hyperhydrophilic micro- and nanostructured surfaces can be tested in vitro [20]. The putative mononuclear osteal macrophages arriving on day 3 on the implant surface as histiocytes [5] (Figure 2A) differentiate further into M2 wound healing macrophages putatively secreting BMP-2 (Figure 2B) for recruiting osteoblasts to the implant surface by chemotaxis. Donath et al. [5] in addition clearly describe multinuclear giant cells on day 5 (Figure 1). Thus the “cytoplasm-rich acid-phosphatase-positive and smaller acid-phophatase-negative giant cells [5], are in agreement with osteal macrophages and osteoclast precursor cells having diverged from a common progenitor cell [12]. Recently it was shown that interleukin 4 converts mononuclear macrophages into multinuclear giant cells [21] (Figure 2C). At present it is unclear, how BMP-2 in concentrations of 50–300 pg/ml stimulate bone growth, when the affinity of BMP-2 receptors on bone precursor cells and osteoblasts is two to three orders of magnitude lower [22], [23]. However, this might be explained by a juxtacrine secretion model [24] or other unconventional secretory processes [25].

Figure 2: Model of the development of macrophage types M1, M2 and osteoclasts in bone and peri-implant bone healing. Uncommitted macrophages differntiate into M1 and M2 macrophages and into osteoclasts. Wound-healing M2 macrophages secrete BMP-2 and VEGF. Nanostructures on the biomaterial enhance BMP-2 secretion.
Figure 2:

Model of the development of macrophage types M1, M2 and osteoclasts in bone and peri-implant bone healing. Uncommitted macrophages differntiate into M1 and M2 macrophages and into osteoclasts. Wound-healing M2 macrophages secrete BMP-2 and VEGF. Nanostructures on the biomaterial enhance BMP-2 secretion.

In the model (Figure 2) it is proposed that MGCs not only secrete BMP-2 for recruiting osteoblasts to the implant surface by chemotaxis (Figure 2), but also VEGF for angiogenesis initiating osteoinduction. BMP-2 secretion is stimulated further by nanostructures offering an innovative approach to synthesizing bioactive implant surfaces. A stimulation of VEGF secretion by nanostructures has however, not yet been shown.


Corresponding author: Prof. Dr. Herbert P. Jennissen, Institut für Physiologische Chemie, Universität Duisburg-Essen, Universitätsklinikum Essen, Hufelandstr. 55, D-45122 Essen, Germany

Author’s Statement

Research funding: The author state no funding involved. Conflict of interest: Authors state no conflict of interest. Material and Methods: Informed consent: Informed consent is not applicable. Ethical approval: The conducted research is not related to either human or animal use.

References

[1] Osborn JF. [Biomaterials and their application to implantation] Biowerkstoffe und ihre Anwendung bei Implantaten. SSO. Schweiz. Monatsschr. Zahnheilkd. 1979;89:1138–9.Search in Google Scholar

[2] Davies JE. Understanding peri-implant endosseous healing. J Dent Educ. 2003;67:932–49.10.1002/j.0022-0337.2003.67.8.tb03681.xSearch in Google Scholar

[3] Jennissen HP. Ultra-hydrophilic transition metals as histophilic biomaterials. Macromol Symp. 2005;225:43–69.10.1002/masy.200550705Search in Google Scholar

[4] Schwarz F, Wieland M, Schwartz Z, Zhao G, Rupp F, Geis-Gerstorfer J, et al. Potential of chemically modified hydrophilic surface characteristics to support tissue integration of titanium dental implants. J Biomed Mater Res B Appl Biomater. 2009;88:544–57.10.1002/jbm.b.31233Search in Google Scholar PubMed

[5] Donath K, Kirsch A, Osborn JF. Zelluläre Dynamik um enossale Titanimplantate. Fortschr Zahnärztl Implantol. 1984;1:55–8.Search in Google Scholar

[6] Jennissen HP. Hyperhydrophilic rough surfaces and imaginary contact angles. Materialwiss Werkstofftech. (Mater Sci Eng Technol). 2012;43:743–50.10.1002/mawe.201200961Search in Google Scholar

[7] Chatzinikolaidou M, Lichtinger TK, Müller RT, Jennissen HP. Peri-implant reactivity and osteoinductive potential of immobilized rhBMP-2 on titanium carriers. Acta Biomater. 2010;6:4405–21.10.1016/j.actbio.2010.06.009Search in Google Scholar PubMed

[8] Lüers S, Lehmann L, Laub M, Schwarz M, Obertacke U, Jennissen HP. The inverse lotus effect as a means of increasing osseointegration of titanium implants in a gap model. Bionanomaterials (formerly: Biomaterialien). 2011;12:34.Search in Google Scholar

[9] Jennissen HP. Stabilizing ultra-hydrophilic surfaces by an exsiccation layer of salts and implications of the hofmeister effect. Materialwiss Werkstofftech. (Mater Sci Eng Technol). 2010;41:1035–9.10.1002/mawe.201000705Search in Google Scholar

[10] Becker J, Kirsch A, Schwarz F, Chatzinikolaidou M, Rothamel D. Lekovic V, et al. Bone apposition to titanium implants biocoated with recombinant human bone morphogenetic protein-2 (rhBMP-2). A Pilot Study in dogs. Clin Oral Investig. 2006;10:217–4.10.1007/s00784-006-0049-0Search in Google Scholar PubMed PubMed Central

[11] Galli SJ, Borregaard N, Wynn TA. Phenotypic and functional plasticity of cells of innate immunity: macrophages, mast cells and neutrophils. Nat Immunol. 2011;12:1035–44.10.1038/ni.2109Search in Google Scholar PubMed PubMed Central

[12] Alexander KA, Chang MK, Maylin ER, Kohler T, Muller R, Wu AC, et al. Osteal macrophages promote in vivo intramembranous bone healing in a mouse tibial injury model. J. Bone Miner Res. 2011;26:1517–32.10.1002/jbmr.354Search in Google Scholar PubMed

[13] Davies JE. Bone bonding at natural and biomaterial surfaces. Biomaterials. 2007;28:5058–67.10.1016/j.biomaterials.2007.07.049Search in Google Scholar PubMed

[14] Lattner D, Jennissen HP. Preparation and properties of ultra-hydrophilic surfaces on titanium and steel. Materialwiss Werkstofftech. (Mater Sci Eng Technol). 2009;40:109–16.10.1002/mawe.200800416Search in Google Scholar

[15] El-Sharkawy H, Kantarci A, Deady J, Hasturk H, Liu H, Alshahat M, et al. Platelet-rich plasma: growth factors and pro- and anti-inflammatory properties. J Periodontol. 2007;78:661–9.10.1902/jop.2007.060302Search in Google Scholar PubMed

[16] Arango DG, Descoteaux A. Macrophage cytokines: involvement in immunity and infectious diseases. Front Immunol. 2014;5:491.10.3389/fimmu.2014.00491Search in Google Scholar

[17] Mills CD. Anatomy of a discovery: m1 and m2 macrophages. Front Immunol. 2015;6:212.10.3389/fimmu.2015.00212Search in Google Scholar

[18] Dohle E, Bischoff I, Bose T, Marsano A, Banfi A, Unger RE, et al. Macrophage-mediated angiogenic activation of outgrowth endothelial cells in co-culture with primary osteoblasts. Eur Cell Mater. 2014;27:149–64.10.22203/eCM.v027a12Search in Google Scholar

[19] Champagne CM, Takebe J, Offenbacher S, Cooper LF. Macrophage cell lines produce osteoinductive signals that include bone morphogenetic protein-2. Bone. 2002;30:26–31.10.1016/S8756-3282(01)00638-XSearch in Google Scholar

[20] Sun SJ, Yu WQ, Zhang YL, Jiang XQ, Zhang FQ. Effects of TiO2 nanotube layers on RAW 264.7 macrophage behaviour and bone morphogenetic protein-2 expression. Cell Prolif. 2013;46:685–94.10.1111/cpr.12072Search in Google Scholar PubMed PubMed Central

[21] Binder F, Hayakawa M, Choo MK, Sano Y, Park JM. Interleukin-4-induced beta-catenin regulates the conversion of macrophages to multinucleated giant cells. Mol Immunol. 2013;54:157–63.10.1016/j.molimm.2012.12.004Search in Google Scholar PubMed PubMed Central

[22] Wiemann M, Rumpf HM, Bingmann D, Jennissen HP. The binding of rhBMP-2 to the receptors of viable MC3T3 cells and the question of cooperativity. Materialwiss Werkstofftech. (Mat Sci Engineer Technol). 2001;32:931–6.10.1002/1521-4052(200112)32:12<931::AID-MAWE931>3.0.CO;2-HSearch in Google Scholar

[23] Laub M, Chatzinikolaidou M, Jennissen HP. Aspects of BMP-2 binding to receptors and collagen: influence of cell senescence on receptor binding and absence of high-affinity stoichiometric binding to collagen. Materialwiss Werkstofftech. (Mat Sci Engineer Technol). 2007;38:1020–6.10.1002/mawe.200700238Search in Google Scholar

[24] Jennissen HP. Accelerated and improved osteointegration of implants biocoated with bone morphogenetic protein 2 (BMP-2). Annals N Y Acad Sci. 2002;961:139–42.10.1111/j.1749-6632.2002.tb03067.xSearch in Google Scholar PubMed

[25] La VG, Zeitler M, Steringer JP, Muller HM, Nickel W. The startling properties of fibroblast growth factor 2: how to exit mammalian cells without a signal peptide at hand. J Biol Chem. 2015;290:27015–20.10.1074/jbc.R115.689257Search in Google Scholar PubMed PubMed Central

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

©2016 Herbert P. Jennissen, licensee De Gruyter.

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

Articles in the same Issue

  1. Synthesis and characterization of PIL/pNIPAAm hybrid hydrogels
  2. Novel blood protein based scaffolds for cardiovascular tissue engineering
  3. Cell adhesion and viability of human endothelial cells on electrospun polymer scaffolds
  4. Effects of heat treatment and welding process on superelastic behaviour and microstructure of micro electron beam welded NiTi
  5. Long-term stable modifications of silicone elastomer for improved hemocompatibility
  6. The effect of thermal treatment on the mechanical properties of PLLA tubular specimens
  7. Biocompatible wear-resistant thick ceramic coating
  8. Protection of active implant electronics with organosilicon open air plasma coating for plastic overmolding
  9. Examination of dielectric strength of thin Parylene C films under various conditions
  10. Open air plasma deposited antimicrobial SiOx/TiOx composite films for biomedical applications
  11. Systemic analysis about residual chloroform in PLLA films
  12. A macrophage model of osseointegration
  13. Towards in silico prognosis using big data
  14. Technical concept and evaluation of a novel shoulder simulator with adaptive muscle force generation and free motion
  15. Usability evaluation of a locomotor therapy device considering different strategies
  16. Hypoxia-on-a-chip
  17. Integration of a semi-automatic in-vitro RFA procedure into an experimental setup
  18. Fabrication of MEMS-based 3D-μECoG-MEAs
  19. High speed digital interfacing for a neural data acquisition system
  20. Bionic forceps for the handling of sensitive tissue
  21. Experimental studies on 3D printing of barium titanate ceramics for medical applications
  22. Patient specific root-analogue dental implants – additive manufacturing and finite element analysis
  23. 3D printing – a key technology for tailored biomedical cell culture lab ware
  24. 3D printing of hydrogels in a temperature controlled environment with high spatial resolution
  25. Biocompatibility of photopolymers for additive manufacturing
  26. Biochemical piezoresistive sensors based on pH- and glucose-sensitive hydrogels for medical applications
  27. Novel wireless measurement system of pressure dedicated to in vivo studies
  28. Portable auricular device for real-time swallow and chew detection
  29. Detection of miRNA using a surface plasmon resonance biosensor and antibody amplification
  30. Simulation and evaluation of stimulation scenarios for targeted vestibular nerve excitation
  31. Deep brain stimulation: increasing efficiency by alternative waveforms
  32. Prediction of immediately occurring microsleep events from brain electric signals
  33. Determining cardiac vagal threshold from short term heart rate complexity
  34. Classification of cardiac excitation patterns during atrial fibrillation
  35. An algorithm to automatically determine the cycle length coverage to identify rotational activity during atrial fibrillation – a simulation study
  36. Deriving respiration from high resolution 12-channel-ECG during cycling exercise
  37. Reducing of gradient induced artifacts on the ECG signal during MRI examinations using Wilcoxon filter
  38. Automatic detection and mapping of double potentials in intracardiac electrograms
  39. Modeling the pelvic region for non-invasive pelvic intraoperative neuromonitoring
  40. Postprocessing algorithm for automated analysis of pelvic intraoperative neuromonitoring signals
  41. Best practice: surgeon driven application in pelvic operations
  42. Vasomotor assessment by camera-based photoplethysmography
  43. Classification of morphologic changes in photoplethysmographic waveforms
  44. Novel computation of pulse transit time from multi-channel PPG signals by wavelet transform
  45. Efficient design of FIR filter based low-pass differentiators for biomedical signal processing
  46. Nonlinear causal influences assessed by mutual compression entropy
  47. Comparative study of methods for solving the correspondence problem in EMD applications
  48. fNIRS for future use in auditory diagnostics
  49. Semi-automated detection of fractional shortening in zebrafish embryo heart videos
  50. Blood pressure measurement on the cheek
  51. Derivation of the respiratory rate from directly and indirectly measured respiratory signals using autocorrelation
  52. Left cardiac atrioventricular delay and inter-ventricular delay in cardiac resynchronization therapy responder and non-responder
  53. An automatic systolic peak detector of blood pressure waveforms using 4th order cumulants
  54. Real-time QRS detection using integrated variance for ECG gated cardiac MRI
  55. Preprocessing of unipolar signals acquired by a novel intracardiac mapping system
  56. In-vitro experiments to characterize ventricular electromechanics
  57. Continuous non-invasive monitoring of blood pressure in the operating room: a cuffless optical technology at the fingertip
  58. Application of microwave sensor technology in cardiovascular disease for plaque detection
  59. Artificial blood circulatory and special Ultrasound Doppler probes for detecting and sizing gaseous embolism
  60. Detection of microsleep events in a car driving simulation study using electrocardiographic features
  61. A method to determine the kink resistance of stents and stent delivery systems according to international standards
  62. Comparison of stented bifurcation and straight vessel 3D-simulation with a prior simulated velocity profile inlet
  63. Transient Euler-Lagrange/DEM simulation of stent thrombosis
  64. Automated control of the laser welding process of heart valve scaffolds
  65. Automation of a test bench for accessing the bendability of electrospun vascular grafts
  66. Influence of storage conditions on the release of growth factors in platelet-rich blood derivatives
  67. Cryopreservation of cells using defined serum-free cryoprotective agents
  68. New bioreactor vessel for tissue engineering of human nasal septal chondrocytes
  69. Determination of the membrane hydraulic permeability of MSCs
  70. Climate retainment in carbon dioxide incubators
  71. Multiple factors influencing OR ventilation system effectiveness
  72. Evaluation of an app-based stress protocol
  73. Medication process in Styrian hospitals
  74. Control tower to surgical theater
  75. Development of a skull phantom for the assessment of implant X-ray visibility
  76. Surgical navigation with QR codes
  77. Investigation of the pressure gradient of embolic protection devices
  78. Computer assistance in femoral derotation osteotomy: a bottom-up approach
  79. Automatic depth scanning system for 3D infrared thermography
  80. A service for monitoring the quality of intraoperative cone beam CT images
  81. Resectoscope with an easy to use twist mechanism for improved handling
  82. In vitro simulation of distribution processes following intramuscular injection
  83. Adjusting inkjet printhead parameters to deposit drugs into micro-sized reservoirs
  84. A flexible standalone system with integrated sensor feedback for multi-pad electrode FES of the hand
  85. Smart control for functional electrical stimulation with optimal pulse intensity
  86. Tactile display on the remaining hand for unilateral hand amputees
  87. Effects of sustained electrical stimulation on spasticity assessed by the pendulum test
  88. An improved tracking framework for ultrasound probe localization in image-guided radiosurgery
  89. Improvement of a subviral particle tracker by the use of a LAP-Kalman-algorithm
  90. Learning discriminative classification models for grading anal intraepithelial neoplasia
  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
Downloaded on 3.7.2025 from https://www.degruyterbrill.com/document/doi/10.1515/cdbme-2016-0015/html
Scroll to top button