Magnetic resonance imaging as a tool for quality control in extrusion-based bioprinting.
bioprinting
image analysis
magnetic resonance imaging (MRI)
quality control
reproducibility
Journal
Biotechnology journal
ISSN: 1860-7314
Titre abrégé: Biotechnol J
Pays: Germany
ID NLM: 101265833
Informations de publication
Date de publication:
May 2022
May 2022
Historique:
revised:
24
11
2021
received:
05
07
2021
accepted:
10
02
2022
pubmed:
3
3
2022
medline:
11
5
2022
entrez:
2
3
2022
Statut:
ppublish
Résumé
Bioprinting is gaining importance for the manufacturing of tailor-made hydrogel scaffolds in tissue engineering, pharmaceutical research and cell therapy. However, structure fidelity and geometric deviations of printed objects heavily influence mass transport and process reproducibility. Fast, three-dimensional and nondestructive quality control methods will be decisive for the approval in larger studies or industry. Magnetic resonance imaging (MRI) meets these requirements for characterizing heterogeneous soft materials with different properties. Complementary to the idea of decentralized 3D printing, magnetic resonance tomography is common in medicine, and image data processing tools can be transferred system-independently. In this study, a MRI measurement and image analysis protocol was evaluated to jointly assess the reproducibility of three different hydrogels and a reference material. Critical parameters for object quality, namely porosity, hole areas and deviations along the height of the scaffolds are discussed. Geometric deviations could be correlated to specific process parameters, anomalies of the ink or changes of ambient conditions. This strategy allows the systematic investigation of complex 3D objects as well as an implementation as a process control tool. Combined with the monitoring of metadata this approach might pave the way for future industrial applications of 3D printing in the field of biopharmaceutics.
Identifiants
pubmed: 35235239
doi: 10.1002/biot.202100336
doi:
Substances chimiques
Hydrogels
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e2100336Subventions
Organisme : German Federal Ministry of Education and Research
Informations de copyright
© 2022 The Authors. Biotechnology Journal published by Wiley-VCH GmbH.
Références
Gretzinger, S., Beckert, N., Gleadall, A., Lee-Thedieck, C., & Hubbuch, J. (2018). 3D bioprinting - Flow cytometry as analytical strategy for 3D cell structures. Bioprinting, 11, e00023.
Bernhardt, A., Wehrl, M., Paul, B., Hochmuth, T., Schumacher, M., Schuetz, K., & Gelinsky, M. (2015). Improved sterilization of sensitive biomaterials with supercritical carbon dioxide at low temperature. Plos One, 10(6), e0129205.
Cidonio, G., Alcala-Orozco, C. R., Lim, K. S., Glinka, M., Mutreja, I., Kim, Y.-H., Dawson, J. I., Woodfield, T. B. F., & Oreffo, R. O. C. (2019). Osteogenic and angiogenic tissue formation in high fidelity nanocomposite Laponite-gelatin bioinks. Biofabrication, 11(3), 035027. https://doi.org/10.1088/1758-5090/ab19fd.
Di Prima, M., Coburn, J., Hwang, D., Kelly, J., Khairuzzaman, A., & Ricles, L. (2016). Additively manufactured medical products - The FDA perspective. 3D Printing in Medicine, 2, 1.
Wehrle, M., Koch, F., Zimmermann, S., Koltay, P., Zengerle, R., Stark, G. B., Strassburg, S., & Finkenzeller, G. (2019). Examination of hydrogels and mesenchymal stem cell sources for bioprinting of artificial osteogenic tissues. Cellular and Molecular Bioengineering, 12, 583-597.
Straub, J. (2015). Initial work on the characterization of additive manufacturing (3D printing) using software image analysis. Machines, 3, 55-71.
Eggert, S., & Hutmacher, D. W. (2019). In vitro disease models 4.0 via automation and high-throughput processing. Biofabrication, 11, 43002.
Radtke, C. P., Hillebrandt, N., & Hubbuch, J. (2018). The Biomaker: an entry-level bioprinting device for biotechnological applications. Journal of Chemical Technology and Biotechnology, 93, 792-799. https://doi.org/10.1002/jctb.5429.
Armstrong, A. A., Alleyne, A. G., & Johnson, A. J. W. (2020). 1D and 2D error assessment and correction for extrusion-based bioprinting using process sensing and control strategies. Biofabrication, 12, 45023.
Fahmy, A. R., Becker, T., & Jekle, M. (2020). 3D printing and additive manufacturing of cereal-based materials: Quality analysis of starch-based systems using a camera-based morphological approach. Innovative Food Science & Emerging Technologies, 63, 102384.
Petsiuk, A. L., & Pearce, J. M. (2020). Open source computer vision-based layer-wise 3D printing analysis. Additive Manufacturing, 36, 101473.
Strauß, S., Meutelet, R., Radosevic, L., Gretzinger, S., & Hubbuch, J. (2021). Image analysis as PAT-Tool for use in extrusion-based bioprinting. Bioprinting, 21, e00112.
Alonzo, M., Dominguez, E., Alvarez-Primo, F., Quinonez, A., Munoz, E., Puebla, J., Barron, A., Aguirre, L., Vargas, A., Ramirez, J. M., & Joddar, B. (2020). A comparative study in the printability of a bioink and 3D models across two bioprinting platforms. Materials Letters, 264, 127382.
Ribeiro, A., Blokzijl, M. M., Levato, R., Visser, C. W., Castilho, M., Hennink, W. E., Vermonden, T., & Malda, J. (2018). Assessing bioink shape fidelity to aid material development in 3D bioprinting. Biofabrication, 10(1), 014102.
Wang, L., Xu, M., Zhang, L., Zhou, Q., & Luo, L. (2016). Automated quantitative assessment of three-dimensional bioprinted hydrogel scaffolds using optical coherence tomography. Biomedical Optics Express, 7(3), 894-910. https://doi.org/10.1364/BOE.7.000894.
Cahuana-Bartra, P., Cahuana-Cárdenas, A., Brunet-Llobet, L., et al. (2020). The use of 3D additive manufacturing technology in autogenous dental transplantation. 3D Printing in Medicine, 6, 16. https://doi.org/10.1186/s41205-020-00070-9.
Filippou, V., & Tsoumpas, C. (2018). Recent advances on the development of phantoms using 3D printing for imaging with CT, MRI, PET, SPECT, and ultrasound. Medical Physics, 45, e740-e760.
Wiese, M., Benders, S., Blümich, B., & Wessling, M. (2018). 3D MRI velocimetry of non-transparent 3D-printed staggered herringbone mixers. Chemical Engineering Journal, 343, 54-60.
Flood, P., Page, H., Reynaud, E. G. (2016). Using hydrogels in microscopy: A tutorial. Micron, 86, 7-16. https://doi.org/10.1016/j.micron.2016.02.002.
Chimene, D., Kaunas, R., & Gaharwar, A. K. (2020). Hydrogel bioink reinforcement for additive manufacturing: A focused review of emerging strategies. Advanced Materials, 32.
Wenger, L., Radtke, C. P., Goepper, J., Woerner, M., & Hubbuch, J. (2020). 3D-printable and enzymatically active composite materials based on hydrogel-filled high internal phase emulsions. Frontiers in Bioengineering and Biotechnology, 8, 713. https://doi.org/10.3389/fbioe.2020.00713.
Han, B., Yun, G. Y., Boley, J. W., Kim, S. H., Hwang, J. Y., & Chiu, G. T.-C., & Park, K. (2016). Dropwise gelation-dehydration kinetics during drop-on-demand printing of hydrogel-based materials. International Journal of Heat & Mass Transfer, 97, 15-25.
Tummala, G. K., Felde, N., Gustafsson, S., Bubholz, A., Schoeder, S., & Mihranyan, A. (2017). Light scattering in poly(vinyl alcohol) hydrogels reinforced with nanocellulose for ophthalmic use. Optical Materials Express, 7(8), 2824-2837. https://doi.org/10.1364/OME.7.002824.
Teo, M. Y., Kee, S., RaviChandran, N., Stuart, L., Aw, K. C., & Stringer, J. (2020). Enabling Free-Standing 3D Hydrogel Microstructures with Microreactive Inkjet Printing. ACS applied materials & interfaces, 12, 1832-1839.
Arndt, F., Schuhmann, S., Guthausen, G., Schuetz, S., & Nirschl, H. (2017). In situ MRI of alginate fouling and flow in ceramic hollow fiber membranes. Journal of Membrane Science, 524, 691-699. https://doi.org/10.1016/j.memsci.2016.11.079.
Bastawrous, S., Wake, N., Levin, D., & Ripley, B. (2018). Principles of three-dimensional printing and clinical applications within the abdomen and pelvis. Abdominal Radiology (New York), 43, 2809-2822.
Busato, A., Fumene Feruglio, P., Parnigotto, P. P., Marzola, P., & Sbarbati, A. (2016). In vivo imaging techniques: A new era for histochemical analysis. European Journal of Histochemistry, 60, 273-279.
Estelrich, J., Sanchez-Martin, M. J., & Busquets, M. A. (2015). Nanoparticles in magnetic resonance imaging: From simple to dual contrast agents. International Journal of Nanomedicine, 10, 1727-1741.
Tondera, C., Hauser, S., Krüger-Genge, A., Jung, F., Neffe, A. T., Lendlein, A., Klopfleisch, R., Steinbach, J., Neuber, C., & Pietzsch, J. (2016). Gelatin-based hydrogel degradation and tissue interaction in vivo: Insights from multimodal preclinical imaging in immunocompetent nude mice. Theranostics, 6, 2114-2128.
Mancha Sánchez, E., Gómez-Blanco, J. C., López Nieto, E., Casado, J. G., Macías-García, A., Díaz Díez, M. A., Carrasco-Amador, J. P., Torrejón Martín, D., Sánchez-Margallo, F. M., & Pagador, J. B. (2020). Hydrogels for bioprinting: A systematic review of hydrogels synthesis, bioprinting parameters, and bioprinted structures behavior. Frontiers in Bioengineering and Biotechnology, 8, 776.
Mandrycky, C., Wang, Z., Kim, K., & Kim, D.-H. (2016). 3D bioprinting for engineering complex tissues. Biotechnology Advances, 34, 422-434.
Otsu, N. (1979). A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 9, 62-66.
Janmaleki, M., Liu, J., Kamkar, M., Azarmanesh, M., Sundararaj, U., & Nezhad, A. S. (2021). Role of temperature on bio-printability of gelatin methacryloyl bioink in two-step cross-linking strategy for tissue engineering applications. Biomedical Materials, 16, 015021. https://doi.org/10.1088/1748-605X/abbcc9.
Ottone, M. L., Peirotti, M. B., & Deiber, J. A. (2009). Rheokinetic model to characterize the maturation process of gelatin solutions under shear flow. Food Hydrocolloids, 23, 1342-1350.
Ruiz-Cantu, L., Gleadall, A., Faris, C., Segal, J., Shakesheff, K., & Yang, J. (2020). Multi-material 3D bioprinting of porous constructs for cartilage regeneration. Materials science & engineering. C, Materials for biological applications, 109, 110578.
Schmieg, B., Nguyen, M., & Franzreb, M. (2020). Simulative minimization of mass transfer limitations within hydrogel-based 3D-printed enzyme carriers. Frontiers in Bioengineering and Biotechnology, 8, 365.
Xu, Y., & Wang, X. (2015). Fluid and cell behaviors along a 3D printed alginate/gelatin/fibrin channel. Biotechnology and Bioengineering, 112, 1683-1695.
Schmideder, S., Barthel, L., Mueller, H., Meyer, V., & Briesen, H. (2019). From three-dimensional morphology to effective diffusivity in filamentous fungal pellets. Biotechnology and Bioengineering, 116, 3360-3371.
Maier, M., Radtke, C. P., Hubbuch, J., Niemeyer, C. M., & Rabe, K. S. (2018). On-demand production of flow-reactor cartridges by 3D printing of thermostable enzymes. Angewandte Chemie International Edition, 57, 5539-5543.
Schmieg, B., Doebber, J., Kirschhoefer, F., Pohl, M., & Franzreb, M. (2019). Advantages of hydrogel-based 3D-printed enzyme reactors and their limitations for biocatalysis. Frontiers in Bioengineering and Biotechnology, 6, 211. https://doi.org/10.3389/fbioe.2018.00211.
Fisch, P., Holub, M., & Zenobi-Wong, M. (2021). Improved accuracy and precision of bioprinting through progressive cavity pump-controlled extrusion. Biofabrication, 13, 15012.
Matamoros, M., Gómez-Blanco, J. C., Sánchez, Á. J., Mancha, E., Marcos, A. C., Carrasco-Amador, J. P., & Pagador, J. B. (2020). Temperature and humidity PID controller for a bioprinter atmospheric enclosure system. Micromachines, 11, 999.