From Imaging Data to Cranioplasty Implant Designs

  • Talitha Asmaria National Research and Innovation Agency (BRIN)
  • Andi Justike Mahatmala Zain Department of Physics, University of Indonesia, Depok, Indonesia
  • Arindha Reni Pramesti Cluster of Medical Technology, Indonesian Medical Education and Research Institute (IMERI), Central Jakarta, Indonesia
  • Azwien Niezam Hawalie Marzuki Cluster of Medical Technology, Indonesian Medical Education and Research Institute (IMERI), Central Jakarta, Indonesia
  • Muhammad Satrio Utomo Department of Biomedical Engineering, University of Melbourne, Victoria, Australia
Keywords: Computed Tomography Image;, Image Processing; Three-Dimensional Printing; Cranioplasty Procedures; Implant Designs;

Abstract

The cranioplasty procedure is starting from removal the skull bone defects and replacing them with any biocompatible material, such as polymer, ceramic, or titanium alloy. The complication of the surgery as well as the high cost from several material selection required a simulation. Besides that, the case of cranial defects sometimes required a customized design. The presence of three-dimensional (3D) printing technology would be a promising tool to improve the success rate. Prior to 3D printing, the model needs to be corrected from the initial patient’s imaging data to the intended implant design. However, previous related literatures were almost not informing the specific image processing steps to gain the models, while not all operators could understand this sophisticated technique.  The study aims to design an implant bone for cranioplasty purpose. The data were processed through the very clear step-by-step image processing stages, three-dimensional (3D) printing, and its evaluation through biomechanical simulation. Quantitatively, the designed cranioplasty implant could deal with the load in the actual application. Qualitatively, the prototypes have matched if applied to the host of cranium bone. In conclusion, although image processing and refinements are the most complicated process, the whole explanation indicate that the provided precise methodology could be a major reference to the similar procedure.

Downloads

Download data is not yet available.

References

A. Alkhaibary, A. Alharbi, N. Alnefaie, A. Oqalaa Almubarak, A. Aloraidi, and S. Khairy, “Cranioplasty: A Comprehensive Review of the History, Materials, Surgical Aspects, and Complications,” World Neurosurg., vol. 139, pp. 445–452, Jul. 2020, doi: 10.1016/j.wneu.2020.04.211.

M. Belzberg et al., “Cranioplasty Outcomes From 500 Consecutive Neuroplastic Surgery Patients,” J. Craniofac. Surg., vol. 33, no. 6, pp. 1648–1654, Sep. 2022, doi: 10.1097/SCS.0000000000008546.

H. Mee et al., “Cranioplasty: A Multidisciplinary Approach,” Front. Surg., vol. 9, May 2022, doi: 10.3389/fsurg.2022.864385.

J. Thimukonda Jegadeesan, M. Baldia, and B. Basu, “Next-generation personalized cranioplasty treatment,” Acta Biomater., vol. 154, pp. 63–82, Dec. 2022, doi: 10.1016/j.actbio.2022.10.030.

W. Czyżewski et al., “Low-Cost Cranioplasty—A Systematic Review of 3D Printing in Medicine,” Materials (Basel)., vol. 15, no. 14, p. 4731, Jul. 2022, doi: 10.3390/ma15144731.

J. Yang, T. Sun, Y. Yuan, X. Li, H. Yu, and J. Guan, “Evaluation of titanium cranioplasty and polyetheretherketone cranioplasty after decompressive craniectomy for traumatic brain injury,” Medicine (Baltimore)., vol. 99, no. 30, p. e21251, Jul. 2020, doi: 10.1097/MD.0000000000021251.

T. Apriawan et al., “Polylactic Acid Implant for Cranioplasty with 3-dimensional Printing Customization: A Case Report,” Open Access Maced. J. Med. Sci., vol. 8, no. C, pp. 151–155, Nov. 2020, doi: 10.3889/oamjms.2020.5156.

A. Aimar, A. Palermo, and B. Innocenti, “The Role of 3D Printing in Medical Applications: A State of the Art,” J. Healthc. Eng., vol. 2019, pp. 1–10, Mar. 2019, doi: 10.1155/2019/5340616.

Q. Wu and K. R. Castleman, “Image Segmentation,” in Microscope Image Processing, Elsevier, 2023, pp. 119–152.

Y. Qi, A. Zhang, H. Wang, and X. Li, “An efficient FCM-based method for image refinement segmentation,” Vis. Comput., vol. 38, no. 7, pp. 2499–2514, Jul. 2022, doi: 10.1007/s00371-021-02126-1.

I. L. Putri, T. R. Aditra, T. Apriawan, D. Kuswanto, F. R. Dhafin, and M. R. Hutagalung, “A Case Report on Lateral Proboscis: A Rare Congenital Anomaly,” Cleft Palate-Craniofacial J., p. 105566562110664, Dec. 2021, doi: 10.1177/10556656211066434.

D. Annur et al., “Material Selection Based on Finite Element Method in Customized Iliac Implant,” Mater. Sci. Forum, vol. 1000, pp. 82–89, Jul. 2020, doi: 10.4028/www.scientific.net/MSF.1000.82.

A. Ridwan-Pramana, P. Marcián, L. Borák, N. Narra, T. Forouzanfar, and J. Wolff, “Structural and mechanical implications of PMMA implant shape and interface geometry in cranioplasty – A finite element study,” J. Cranio-Maxillofacial Surg., vol. 44, no. 1, pp. 34–44, Jan. 2016, doi: 10.1016/j.jcms.2015.10.014.

Y. Guo and W. Guo, “Study and numerical analysis of Von Mises stress of a new tumor-type distal femoral prosthesis comprising a peek composite reinforced with carbon fibers: finite element analysis,” Comput. Methods Biomech. Biomed. Engin., vol. 25, no. 15, pp. 1663–1677, Nov. 2022, doi: 10.1080/10255842.2022.2032681.

D. Haak, C. E. Page, K. Kabino, and T. M. Deserno, “Evaluation of DICOM viewer software for workflow integration in clinical trials,” Mar. 2015, p. 94180O, doi: 10.1117/12.2082051.

D. Haak, C.-E. Page, and T. M. Deserno, “A Survey of DICOM Viewer Software to Integrate Clinical Research and Medical Imaging,” J. Digit. Imaging, vol. 29, no. 2, pp. 206–215, Apr. 2016, doi: 10.1007/s10278-015-9833-1.

P. S. Dewi, N. N. Ratini, and N. L. P. Trisnawati, “Effect of x-ray tube voltage variation to value of contrast to noise ratio (CNR) on computed tomography (CT) Scan at RSUD Bali Mandara,” Int. J. Phys. Sci. Eng., vol. 6, no. 2, pp. 82–90, Jun. 2022, doi: 10.53730/ijpse.v6n2.9656.

D. A. Garzón-Alvarado, A. González, and M. L. Gutiérrez, “Growth of the flat bones of the membranous neurocranium: A computational model,” Comput. Methods Programs Biomed., vol. 112, no. 3, pp. 655–664, Dec. 2013, doi: 10.1016/j.cmpb.2013.07.027.

Z. Li, J. Wang, J. Wang, J. Wang, C. Ji, and G. Wang, “Experimental and numerical study on the mechanical properties of cortical and spongy cranial bone of 8-week-old porcines at different strain rates,” Biomech. Model. Mechanobiol., vol. 19, no. 5, pp. 1797–1808, Oct. 2020, doi: 10.1007/s10237-020-01309-4.

A. T. Davis, A. L. Palmer, S. Pani, and A. Nisbet, “Assessment of the variation in CT scanner performance (image quality and Hounsfield units) with scan parameters, for image optimisation in radiotherapy treatment planning,” Phys. Medica, vol. 45, pp. 59–64, Jan. 2018, doi: 10.1016/j.ejmp.2017.11.036.

S. Park, E.-K. Park, K.-W. Shim, and D.-S. Kim, “Modified Cranioplasty Technique Using 3-Dimensional Printed Implants in Preventing Temporalis Muscle Hollowing,” World Neurosurg., vol. 126, pp. e1160–e1168, Jun. 2019, doi: 10.1016/j.wneu.2019.02.221.

R. De Santis, T. Russo, J. V. Rau, I. Papallo, M. Martorelli, and A. Gloria, “Design of 3D Additively Manufactured Hybrid Structures for Cranioplasty,” Materials (Basel)., vol. 14, no. 1, p. 181, Jan. 2021, doi: 10.3390/ma14010181.

J. Li et al., “Automatic skull defect restoration and cranial implant generation for cranioplasty,” Med. Image Anal., vol. 73, p. 102171, Oct. 2021, doi: 10.1016/j.media.2021.102171.

M. A. Sabrina et al., “Simulated Analysis Ti-6Al-4V Plate and Screw as Transverse Diaphyseal Fracture Implant for Ulna Bone,” J. Biomimetics, Biomater. Biomed. Eng., vol. 55, pp. 35–45, Mar. 2022, doi: 10.4028/p-63a93r.

M. S. Utomo, M. I. Amal, S. Supriadi, D. Malau, D. Annur, and A. W. Pramono, “Design of modular femoral implant based on anthropometry of eastern asian,” AIP Conf. Proc., vol. 2088, 2019, doi: 10.1063/1.5095285.

J. P. Pöppe, M. Spendel, C. Schwartz, P. A. Winkler, and J. Wittig, “The ‘springform’ technique in cranioplasty: custom made 3D-printed templates for intraoperative modelling of polymethylmethacrylate cranial implants,” Acta Neurochir. (Wien)., vol. 164, no. 3, pp. 679–688, Mar. 2022, doi: 10.1007/s00701-021-05077-7.

T. Zegers, D. Koper, B. Lethaus, P. Kessler, and M. ter Laak-Poort, “Computer-Aided-Design/Computer-Aided-Manufacturing Titanium Cranioplasty in a Child,” J. Craniofac. Surg., vol. 31, no. 1, pp. 237–240, 2020, doi: 10.1097/SCS.0000000000005948.

Published
2023-07-08
How to Cite
[1]
T. Asmaria, A. J. M. Zain, A. R. Pramesti, A. N. H. Marzuki, and M. S. Utomo, “From Imaging Data to Cranioplasty Implant Designs”, j.electron.electromedical.eng.med.inform, vol. 5, no. 3, pp. 125-133, Jul. 2023.
Section
Electronics