Micro-computed tomography characterization of tissue engineering scaffolds: effects of pixel size and rotation step

  • Ibrahim Fatih Cengiz
  • Joaquim Miguel Oliveira
  • Rui L. Reis
Biomaterials Synthesis and Characterization Original Research
Part of the following topical collections:
  1. Biomaterials Synthesis and Characterization


Quantitative assessment of micro-structure of materials is of key importance in many fields including tissue engineering, biology, and dentistry. Micro-computed tomography (µ-CT) is an intensively used non-destructive technique. However, the acquisition parameters such as pixel size and rotation step may have significant effects on the obtained results. In this study, a set of tissue engineering scaffolds including examples of natural and synthetic polymers, and ceramics were analyzed. We comprehensively compared the quantitative results of µ-CT characterization using 15 acquisition scenarios that differ in the combination of the pixel size and rotation step. The results showed that the acquisition parameters could statistically significantly affect the quantified mean porosity, mean pore size, and mean wall thickness of the scaffolds. The effects are also practically important since the differences can be as high as 24% regarding the mean porosity in average, and 19.5 h and 166 GB regarding the characterization time and data storage per sample with a relatively small volume. This study showed in a quantitative manner the effects of such a wide range of acquisition scenarios on the final data, as well as the characterization time and data storage per sample. Herein, a clear picture of the effects of the pixel size and rotation step on the results is provided which can notably be useful to refine the practice of µ-CT characterization of scaffolds and economize the related resources.

Graphical Abstract

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This article is a result of the project FROnTHERA (NORTE-01-0145-FEDER-000023), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). IFC thanks the Portuguese Foundation for Science and Technology (FCT) for the Ph.D. scholarship (SFRH/BD/99555/2014). JMO also thanks the FCT for the funds provided under the program Investigador FCT 2012 and 2015 (IF/00423/2012 and IF/01285/2015).

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Conflict of interest

The authors declare that they have no competing interests.

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  1. 1.
    Flannery BP, Deckman HW, Roberge WG, D’Amico KL. Three-dimensional X-ray microtomography. Science. 1987;237(4821):1439–44.CrossRefGoogle Scholar
  2. 2.
    Landis EN, Keane DT. X-ray microtomography. Mater Charact. 2010;61(12):1305–16.CrossRefGoogle Scholar
  3. 3.
    Mizutani R, Suzuki Y. X-ray microtomography in biology. Micron. 2012;43(2):104–15.CrossRefGoogle Scholar
  4. 4.
    Ritman EL. Micro-computed tomography - current status and developments. Annu Rev Biomed Eng. 2004;6:185–208.CrossRefGoogle Scholar
  5. 5.
    Sasov A, Van Dyck D. Desktop X-ray microscopy and microtomography. Journal Microsc. 1998;191(2):151–8.CrossRefGoogle Scholar
  6. 6.
    Ho ST, Hutmacher DW. A comparison of micro-CT with other techniques used in the characterization of scaffolds. Biomaterials. 2006;27(8):1362–76.CrossRefGoogle Scholar
  7. 7.
    Müller R, Matter S, Neuenschwander P, Suter U, Rüegsegger P editors. 3D micro-tomographic imaging and quantitative morphometry for the nondestructive evaluation of porous biomaterials. MRS Proceedings; 1996: Cambridge Univ Press.Google Scholar
  8. 8.
    Cnudde V, Boone MN. High-resolution X-ray computed tomography in geosciences: a review of the current technology and applications. Earth-Sci Rev. 2013;123:1–17.CrossRefGoogle Scholar
  9. 9.
    Zhu W, Gaetani GA, Fusseis F, Montési LG, De Carlo F. Microtomography of partially molten rocks: three-dimensional melt distribution in mantle peridotite. Science. 2011;332(6025):88–91.CrossRefGoogle Scholar
  10. 10.
    Hindelang F, Zurbach R, Roggo Y. Micro-computer tomography for medical device and pharmaceutical packaging analysis. J Pharm Biomed Anal. 2015;108:38–48.CrossRefGoogle Scholar
  11. 11.
    Wise LD, Winkelmann CT, Dogdas B, Bagchi A. Micro‐computed tomography imaging and analysis in developmental biology and toxicology. Birth Defects Res Part C: Embryo Today: Rev. 2013;99(2):71–82.CrossRefGoogle Scholar
  12. 12.
    Swain MV, Xue J. State of the art of Micro-CT applications in dental research. Int J Oral Sci. 2009;1(4):177.CrossRefGoogle Scholar
  13. 13.
    Thimm BW, Wechsler O, Bohner M, Müller R, Hofmann S. In vitro ceramic scaffold mineralization: Comparison between histological and micro-computed tomographical analysis. Ann Biomed Eng. 2013;41(12):2666–75.CrossRefGoogle Scholar
  14. 14.
    van Lenthe GH, Hagenmüller H, Bohner M, Hollister SJ, Meinel L, Müller R. Nondestructive micro-computed tomography for biological imaging and quantification of scaffold–bone interaction in vivo. Biomaterials. 2007;28(15):2479–90.CrossRefGoogle Scholar
  15. 15.
    Gao X, Tay FR,oGutmann JL, Fan W, Xu T, Fan B. Micro-CT evaluation of apical delta morphologies in human teeth. Sci Rep. 2016;6:36501. doi: 10.1038/srep36501.
  16. 16.
    Hildebrand T, Laib A, Müller R, Dequeker J, Rüegsegger P. Direct three‐dimensional morphometric analysis of human cancellous bone: microstructural data from spine, femur, iliac crest, and calcaneus. J bone Mineral Res. 1999;14(7):1167–74.CrossRefGoogle Scholar
  17. 17.
    Müller R, Van Campenhout H, Van Damme B, Van der Perre G, Dequeker J, Hildebrand T, et al. Morphometric analysis of human bone biopsies: a quantitative structural comparison of histological sections and micro-computed tomography. Bone. 1998;23(1):59–66.CrossRefGoogle Scholar
  18. 18.
    Pereira H, Caridade S, Frias A, Silva-Correia J, Pereira D, Cengiz I, et al. Biomechanical and cellular segmental characterization of human meniscus: Building the basis for tissue engineering therapies. Osteoarthr Cartil. 2014;22(9):1271–81.CrossRefGoogle Scholar
  19. 19.
    Zhu S, Zhu Q, Liu X, Yang W, Jian Y, Zhou X et al. Three-dimensional reconstruction of the microstructure of human acellular nerve allograft. Sci Rep. 2016;6:30694. doi: 10.1038/srep30694.
  20. 20.
    Schambach SJ, Bag S, Schilling L, Groden C, Brockmann MA. Application of micro-CT in small animal imaging. Methods. 2010;50(1):2–13.CrossRefGoogle Scholar
  21. 21.
    Tremoleda JL, Khalil M, Gompels LL, Wylezinska-Arridge M, Vincent T, Gsell W. Imaging technologies for preclinical models of bone and joint disorders. EJNMMI Res. 2011;1(1):1.CrossRefGoogle Scholar
  22. 22.
    Cox TR, Rumney RM, Schoof EM, Perryman L, Høye AM, Agrawal A, et al. The hypoxic cancer secretome induces pre-metastatic bone lesions through lysyl oxidase. Nature. 2015;522(7554):106–10.CrossRefGoogle Scholar
  23. 23.
    Gibson AL, Mingalone CKH, Foote AT, Uchimura T, Zhang M, Zeng L. Wnt7a inhibits IL-1β induced catabolic gene expression and prevents articular cartilage damage in experimental osteoarthritis. Sci Rep. 2017;7:41823. doi: 10.1038/srep41823.
  24. 24.
    Hu C-H, Sui B-D, Du F-Y, Shuai Y, Zheng C-X, Zhao P, et al. miR-21 deficiency inhibits osteoclast function and prevents bone loss in mice. Sci Rep. 2017;7:43191.CrossRefGoogle Scholar
  25. 25.
    Kusumbe AP, Ramasamy SK, Adams RH. Coupling of angiogenesis and osteogenesis by a specific vessel subtype in bone. Nature. 2014;507(7492):323–8.CrossRefGoogle Scholar
  26. 26.
    Vermeij W, Dollé M, Reiling E, Jaarsma D, Payan-Gomez C, Bombardieri C, et al. Restricted diet delays accelerated ageing and genomic stress in DNA-repair-deficient mice. Nature. 2016;537(7620):427–31.CrossRefGoogle Scholar
  27. 27.
    Boyd SK, Davison P, Müller R, Gasser JA. Monitoring individual morphological changes over time in ovariectomized rats by in vivo micro-computed tomography. Bone. 2006;39(4):854–62.CrossRefGoogle Scholar
  28. 28.
    Geng H, Todd NM, Devlin-Mullin A, Poologasundarampillai G, Kim TB, Madi K, et al. A correlative imaging based methodology for accurate quantitative assessment of bone formation in additive manufactured implants. J Mater Sci: Mater Med. 2016;27(6):1–9.Google Scholar
  29. 29.
    Xu L, Lv K, Zhang W, Zhang X, Jiang X, Zhang F. The healing of critical-size calvarial bone defects in rat with rhPDGF-BB, BMSCs, and β-TCP scaffolds. J Mater Sci: Mater Med. 2012;23(4):1073–84.Google Scholar
  30. 30.
    Wongsupa N, Nuntanaranont T, Kamolmattayakul S, Thuaksuban N. Assessment of bone regeneration of a tissue-engineered bone complex using human dental pulp stem cells/poly (ε-caprolactone)-biphasic calcium phosphate scaffold constructs in rabbit calvarial defects. J Mater Sci: Mater Med. 2017;28(5):77.Google Scholar
  31. 31.
    Liu G, Zhao L, Zhang W, Cui L, Liu W, Cao Y. Repair of goat tibial defects with bone marrow stromal cells and β-tricalcium phosphate. J Mater Sci: Mater Med. 2008;19(6):2367–76.Google Scholar
  32. 32.
    Fajardo R, Müller R. Three‐dimensional analysis of nonhuman primate trabecular architecture using micro‐computed tomography. Am J Phys Anthropol. 2001;115(4):327–36.CrossRefGoogle Scholar
  33. 33.
    Cardeira J, Gavaia PJ, Fernández I, Cengiz IF, Moreira-Silva J, Oliveira JM, et al. Quantitative assessment of the regenerative and mineralogenic performances of the zebrafish caudal fin. Sci Rep. 2016;6:39191.CrossRefGoogle Scholar
  34. 34.
    Claes JM, Dean MN, Nilsson D-E, Hart NS, Mallefet J. A deepwater fish with ‘lightsabers’–dorsal spine-associated luminescence in a counterilluminating lanternshark. Sci Rep. 2013;3:1308.CrossRefGoogle Scholar
  35. 35.
    Webb SJ, Tu J, Cory E, Morgan V, Sah RL, Deheyn DD et al. Stress physiology and weapon integrity of intertidal mantis shrimp under future ocean conditions. Sci Rep. 2016;6:38637. doi: 10.1038/srep38637.
  36. 36.
    Lee SC, Kim JH, Lee SJ. Floating of the lobes of mosquito (Aedes togoi) larva for respiration. Sci Rep. 2017;7:43050. doi: 10.1038/srep43050.
  37. 37.
    Smith DB, Bernhardt G, Raine NE, Abel RL, Sykes D, Ahmed F et al. Exploring miniature insect brains using micro-CT scanning techniques. Sci Rep. 2016;6:21768. doi: 10.1038/srep21768.
  38. 38.
    van de Kamp T, Vagovič P, Baumbach T, Riedel A. A biological screw in a beetle’s leg. Science. 2011;333(6038):52-.CrossRefGoogle Scholar
  39. 39.
    Cleveland RO, McAteer JA, Müller R. Time-lapse nondestructive assessment of shock wave damage to kidney stones in vitro using micro-computed tomography. J Acoust Soc Am. 2001;110(4):1733–6.CrossRefGoogle Scholar
  40. 40.
    Scherer K, Braig E, Willer K, Willner M, Fingerle AA, Chabior M, et al. Non-invasive differentiation of kidney stone types using X-ray dark-field radiography. Sci Rep. 2015;5:9527.CrossRefGoogle Scholar
  41. 41.
    Dumbravă MD, Rothschild BM, Weishampel DB, Csiki-Sava Z, Andrei RA, Acheson KA et al. A dinosaurian facial deformity and the first occurrence of ameloblastoma in the fossil record. Sci Rep. 2016;6:29271. doi: 10.1038/srep29271.
  42. 42.
    Eriksson ME, Parry LA, Rudkin DM. Earth’s oldest ‘Bobbit worm’–gigantism in a Devonian eunicidan polychaete. Sci Rep. 2017;7:43061. doi: 10.1038/srep43061.
  43. 43.
    Liu Y, Scholtz G, Hou X. When a 520 million-year-old Chengjiang fossil meets a modern micro-CT--a case study. Sci Rep. 2014;5:12802.CrossRefGoogle Scholar
  44. 44.
    Hollister SJ. Porous scaffold design for tissue engineering. Nat Mater. 2005;4(7):518–24.CrossRefGoogle Scholar
  45. 45.
    Indolfi L, Baker AB, Edelman ER. The role of scaffold microarchitecture in engineering endothelial cell immunomodulation. Biomaterials. 2012;33(29):7019–27.CrossRefGoogle Scholar
  46. 46.
    Karageorgiou V, Kaplan D. Porosity of 3D biomaterial scaffolds and osteogenesis. Biomaterials. 2005;26(27):5474–91.CrossRefGoogle Scholar
  47. 47.
    Karande TS, Ong JL, Agrawal CM. Diffusion in musculoskeletal tissue engineering scaffolds: design issues related to porosity, permeability, architecture, and nutrient mixing. Ann Biomed Eng. 2004;32(12):1728–43.CrossRefGoogle Scholar
  48. 48.
    Mastrogiacomo M, Scaglione S, Martinetti R, Dolcini L, Beltrame F, Cancedda R, et al. Role of scaffold internal structure on in vivo bone formation in macroporous calcium phosphate bioceramics. Biomaterials. 2006;27(17):3230–7.CrossRefGoogle Scholar
  49. 49.
    Yang S, Leong K-F, Du Z, Chua C-K. The design of scaffolds for use in tissue engineering. Part I. Traditional factors. Tissue Eng. 2001;7(6):679–89.CrossRefGoogle Scholar
  50. 50.
    Zeltinger J, Sherwood JK, Graham DA, Müeller R, Griffith LG. Effect of pore size and void fraction on cellular adhesion, proliferation, and matrix deposition. Tissue Eng. 2001;7(5):557–72.CrossRefGoogle Scholar
  51. 51.
    Christen P, Schulte FA, Zwahlen A, Van Rietbergen B, Boutroy S, Melton LJ, et al. Voxel size dependency, reproducibility and sensitivity of an in vivo bone loading estimation algorithm. J R Soc Interface. 2016;13(114):20150991.CrossRefGoogle Scholar
  52. 52.
    Cioffi M, Boschetti F, Raimondi MT, Dubini G. Modeling evaluation of the fluid‐dynamic microenvironment in tissue‐engineered constructs: a micro‐CT based model. Biotechnol Bioeng. 2006;93(3):500–10.CrossRefGoogle Scholar
  53. 53.
    Porter B, Zauel R, Stockman H, Guldberg R, Fyhrie D. 3-D computational modeling of media flow through scaffolds in a perfusion bioreactor. J Biomech. 2005;38(3):543–9.CrossRefGoogle Scholar
  54. 54.
    Zermatten E, Vetsch J, Ruffoni D, Hofmann Boss S, Müller R, Steinfeld A. Micro-computed tomography based modeling of shear stresses in perfused regular and irregular scaffolds. Ann Biomed Eng. 2014;42(5):1085.CrossRefGoogle Scholar
  55. 55.
    Rockwood DN, Preda RC, Yücel T, Wang X, Lovett ML, Kaplan DL. Materials fabrication from Bombyx mori silk fibroin. Nat Protoc. 2011;6(10):1612–31.CrossRefGoogle Scholar
  56. 56.
    Yan L-P, Oliveira JM, Oliveira AL, Caridade SG, Mano JF, Reis RL. Macro/microporous silk fibroin scaffolds with potential for articular cartilage and meniscus tissue engineering applications. Acta Biomater. 2012;8(1):289–301.CrossRefGoogle Scholar
  57. 57.
    Oliveira JM, Silva SS, Malafaya PB, Rodrigues MT, Kotobuki N, Hirose M, et al. Macroporous hydroxyapatite scaffolds for bone tissue engineering applications: physicochemical characterization and assessment of rat bone marrow stromal cell viability. J Biomed Mater Res Part A. 2009;91(1):175–86.CrossRefGoogle Scholar
  58. 58.
    Bouxsein ML, Boyd SK, Christiansen BA, Guldberg RE, Jepsen KJ, Müller R. Guidelines for assessment of bone microstructure in rodents using micro–computed tomography. J Bone Mineral Res. 2010;25(7):1468–86.CrossRefGoogle Scholar
  59. 59.
    Cooper D, Turinsky A, Sensen C, Hallgrimsson B. Effect of voxel size on 3D micro-CT analysis of cortical bone porosity. Calcif Tissue Int. 2007;80(3):211–9.CrossRefGoogle Scholar
  60. 60.
    Kim D-G, Christopherson GT, Dong XN, Fyhrie DP, Yeni YN. The effect of microcomputed tomography scanning and reconstruction voxel size on the accuracy of stereological measurements in human cancellous bone. Bone. 2004;35(6):1375–82.CrossRefGoogle Scholar
  61. 61.
    Longo AB, Salmon PL, Ward WE. Comparison of ex vivo and in vivo micro‐computed tomography of rat tibia at different scanning settings. J Orthop Res. 2016. (Epub ahead of print). doi: 10.1002/jor.23435
  62. 62.
    Morris DE, Mather ML, Simon CG, Crowe JA. Time‐optimized X‐ray micro‐CT imaging of polymer based scaffolds. J Biomed Mater Res Part B: Appl Biomater. 2012;100(2):360–7.CrossRefGoogle Scholar
  63. 63.
    Müller R, Koller B, Hildebrand T, Laib A, Gianolini S, Rüegsegger P. Resolution dependency of microstructural properties of cancellous bone based on three-dimensional mu-tomography. Technol Health Care. 1996;4(1):113–9.Google Scholar
  64. 64.
    Peng S, Hu Q, Dultz S, Zhang M. Using X-ray computed tomography in pore structure characterization for a Berea sandstone: resolution effect. Journal Hydrol. 2012;472:254–61.CrossRefGoogle Scholar
  65. 65.
    Peyrin F, Salome M, Cloetens P, Laval‐Jeantet A, Ritman E, Rüegsegger P. Micro‐CT examinations of trabecular bone samples at different resolutions: 14, 7 and 2 micron level. Technol Health Care. 1998;6(5, 6):391–401.Google Scholar
  66. 66.
    Pyka G, Kerckhofs G, Schrooten J, Wevers M. The effect of spatial micro-CT image resolution and surface complexity on the morphological 3D analysis of open porous structures. Mater Charact. 2014;87:104–15.CrossRefGoogle Scholar
  67. 67.
    Cohen J. Statistical power analysis for the behavioral sciences. 2nd edn. Hillsdale, NJ: Lawrence Erlbaum Associates; 1988.Google Scholar
  68. 68.
    Ellis PD. The essential guide to effect sizes: statistical power, meta-analysis, and the interpretation of research results. UK: Cambridge University Press; 2010.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Ibrahim Fatih Cengiz
    • 1
    • 2
  • Joaquim Miguel Oliveira
    • 1
    • 2
  • Rui L. Reis
    • 1
    • 2
  1. 1.3B’s Research Group–Biomaterials, Biodegradables and Biomimetics, University of Minho, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, AvePark, Parque de Ciência e TecnologiaZona Industrial da GandraGuimarãesPortugal
  2. 2.ICVS/3B’s–PT Government Associate LaboratoryBraga/GuimarãesPortugal

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