Multi-hole spherical CT scan method to characterize large quantities of bones in rats

  • Neng Nenden Mulyaningsih Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia; Department of Physics Education, Faculty of Mathematics and Natural Sciences, Universitas Indraprasta PGRI, Jakarta, Indonesia https://orcid.org/0000-0003-4474-6261
  • Ariadne Lakshmidevi Juwono Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia
  • Djarwani Soeharso Soejoko Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia
  • Dewi Apri Astuti Department of Nutrition and Feed Technology, Faculty of Animal Sciences, Institut Pertanian Bogor, Bogor, Indonesia
DOI: https://doi.org/10.13181/mji.oa.215452
Keywords: bone quality, CT scan, multi-hole spherical model, osteoporosis, ovariectomy
Abstract viewed: 827 times
PDF downloaded: 487 times
HTML downloaded: 198 times
EPUB downloaded: 248 times

Abstract

BACKGROUND New therapeutic options are often explored in in vivo studies using animals like rats. Since rats are small, it is difficult to examine them in a computed tomography (CT) scan. This study aimed to introduce a multi-hole spherical model CT scan method as a new, fast, economical, and reliable method to characterize large quantities of rat bones at once in estimating the timing of osteoporosis in ovariectomized white rats.

METHODS 50 female white rats (12 weeks old) were treated as the control group, and 40 rats of the same age were ovariectomized to establish the osteoporosis model. Sham rats were sacrificed at 13, 15, 17, 19, and 21 weeks old, while the ovariectomized rats were sacrificed at 15, 17, 19, and 21 weeks old. Afterward, tibia bones were removed, placed in the multi-hole spherical model, and characterized using a CT scan. Their characteristics were compared using a scanning electron microscope (SEM), transmission electron microscopy (TEM), and X-ray diffraction (XRD).

RESULTS The Hounsfield unit scores resulted from the multi-hole spherical model CT scan method of tibia bones of rats were consistent with the percentage of the osteocyte cavities, canalicular diameters, and crystal size. The multi-hole spherical model CT scan method could produce 50 times more data than the SEM, TEM, or XRD.

CONCLUSIONS Multi-hole spherical model CT scan was considered good and reliable in assessing bone quality parameters in rat samples simultaneously.

References

  1. Pennington Z, Ehresman J, Lubelski D, Cottrill E, Schilling A, Ahmed AK, et al. Assessing underlying bone quality in spine surgery patients: a narrative review of dual-energy X-rayabsorptiometry (DXA) and alternatives. Spine J. 2021;21(2):321-31. https://doi.org/10.1016/j.spinee.2020.08.020

  2. Manns M, Basbasse YE, Freund N, Ocklenburg S. Paw preferences in mice and rats: meta-analysis. Neurosci Biobehav Rev. 2021;127:593-606. https://doi.org/10.1016/j.neubiorev.2021.05.011

  3. Zolocinska A, Siennicka K, Debski T, Gut G, Mazur S, Gajewska M, et al. Comparison of mouse, rat and rabbit models for adipose - Derived stem cells (ASC) research. Curr Res Transl Med. 2020;68(4):205-10. https://doi.org/10.1016/j.retram.2020.07.001

  4. Parker CC, Chen H, Flagel SB, Geurts AM, Richards JB, Robinson TE, et al. Rats are the smart choice: rationale for a renewed focus on rats in behavioral genetics. Neuropharmacology. 2014;76 Pt B(0 0):250-8. https://doi.org/10.1016/j.neuropharm.2013.05.047

  5. Mitić Ž, Stolić A, Stojanović S, Najman S, Ignjatović N, Nikolić G, et al. Instrumental methods and techniques for structural and physicochemical characterization of biomaterials and bone tissue: a review. Mat Sci Eng C Mater Biol Appl. 2017;79:930-49. https://doi.org/10.1016/j.msec.2017.05.127

  6. Ramahwati MN, Juwono AL, Soejoko DS, Mulyaningsih NN. Analysis of morphology and absorption of calcium and magnesium for calcium phosphate Ca3(PO4)2 in rat's spine. IOP Conf Ser Mater Sci Eng. 2019;496:012039. https://doi.org/10.1088/1757-899X/496/1/012039

  7. Doria S, Valeri F, Lasagni L, Sanguineti V, Ragonesi R, Akbar MU, et al. Addressing signal alterations induced in CT images by deep learning processing: a preliminary phantom study. Phys Med. 2021;83:88-100. https://doi.org/10.1016/j.ejmp.2021.02.022

  8. Hembrick-Hollomana V, Samuel T, Mohammeda Z, Jeelani S, Rangari VK. Ecofriendly production of bioactive tissue engineering scaffolds derived from egg- and sea-shells. J Mater Res Technol. 2020;9(6):13729-39. https://doi.org/10.1016/j.jmrt.2020.09.093

  9. Mulyaningsih NN, Juwono AL, Soejoko DS, Astuti DA. Morphology of proximal cortical epiphysis bone of ovariectomized Rattus Norvegicus. Turk J Osteporos. 2020;26:169-74. https://doi.org/10.4274/tod.galenos.2020.36002

  10. Okumura T, Shoji M, Hisada A, Ominami Y, Ito S, Ushiki T, et al. Electron tomography of whole cultured cells using novel transmission electron imaging technique. Micron. 2018;104:21-5. https://doi.org/10.1016/j.micron.2017.10.006

  11. Falsafi SR, Rostamabadi H, Assadpour E, Jafari SM. Morphology and microstructural analysis of bioactive-loaded micro/nanocarriers via microscopy techniques; CLSM/SEM/TEM/AFM. Adv Colloid Interface Sci. 2020;280:102166. https://doi.org/10.1016/j.cis.2020.102166

  12. Ismail NA, Abdullah N, Mohamad Noor MH, Lai PS, Shafie MS, Nor FM. Accuracy and reliability of virtual femur measurement from CT scan. J Forensic Legal Med. 2019;63:11-7. https://doi.org/10.1016/j.jflm.2019.02.010

  13. Carew RM, Viner MD, Conlogue G, Márquez-Grant N, Beckett S. Accuracy of computed radiography in osteometry: a comparison of digital imaging techniques and the effect of magnification. J Forensic Radiol Imaging. 2019;19:100348. https://doi.org/10.1016/j.jofri.2019.100348

  14. Yoshida Y, Yanagawa M, Hata A, Sato Y, Tsubamoto M, Doi S, et al. Quantitative volumetry of ground-glass nodules on high-spatial-resolution CT with 0.25-mm section thickness and 1024 matrix: phantom and clinical studies. Eur J Radiol Open. 2021;8:100362. https://doi.org/10.1016/j.ejro.2021.100362

  15. Racine D, Becce F, Viry A, Monnin P, Thomsen B, Verdun FR, et al. Task-based characterization of a deep learning image reconstruction and comparison with filtered back-projection and a partial model-based iterative reconstruction in abdominal CT: a phantom study. Phys Med. 2020;76:28-37. https://doi.org/10.1016/j.ejmp.2020.06.004

  16. Narayanan A, Cai A, Xi Y, Maalouf NM, Rubin C, Chhabra A. CT bone density analysis of low-impact proximal femur fractures using Hounsfield units. Clin Imaging. 2019;57:15-20. https://doi.org/10.1016/j.clinimag.2019.04.009

  17. Londoño-Restrepo SM, Herrera-Lara M, Bernal-Alvarez LR, Rivera-Muñoz EM, Rodriguez-García ME. In-situ XRD study of the crystal size transition of hydroxyapatite from swine bone. Ceram Int. 2020;46(15):24454-61. https://doi.org/10.1016/j.ceramint.2020.06.230

  18. Castillo-Paz AM, Londoño-Restrepo SM, Tirado-Mejía L, Mondragón MA, Rodríguez-García ME. Nano to micro size transition of hydroxyapatite in porcine bone during heat treatment with low heating rates. Prog Nat Sci Mater. 2020;30(4): 494-501. https://doi.org/10.1016/j.pnsc.2020.06.005

  19. McNerny EMB, Buening DT, Aref MW, Chen NX, Moe SM, Allen MR. Time course of rapid bone loss and cortical porosity formation observed by longitudinal μCT in a rat model of CKD. Bone. 2019;125:16-24. https://doi.org/10.1016/j.bone.2019.05.002

  20. Booz C, Noeske J, Albrecht MH, Lenga L, Martin SS, Yel I, et al. Diagnostic accuracy of quantitative dual-energy CT-based bone mineral density assessment in comparison to Hounsfield unit measurements using dual x-ray absorptiometry as standard of reference. European J Radiol. 2020;132:109321. https://doi.org/10.1016/j.ejrad.2020.109321

  21. Shevroja E, Lamy O, Kohlmeier L, Koromani F, Rivadeneira F, Hans D. Use of trabecular bone score (TBS) as a complementary approach to dual-energy X-ray absorptiometry (DXA) for fracture risk assessment in clinical practice. J Clin Densitom. 2017;20(3):334-45. https://doi.org/10.1016/j.jocd.2017.06.019

  22. Hunt HB, Donnelly E. Bone quality assessment techniques: geometric, compositional, and mechanical characterization from macroscale to nanoscale. Clinic Rev Bone Miner Metab. 2016;14(3):133-49. https://doi.org/10.1007/s12018-016-9222-4

Published
2021-10-01
How to Cite
1.
Mulyaningsih NN, Juwono AL, Soejoko DS, Astuti DA. Multi-hole spherical CT scan method to characterize large quantities of bones in rats. Med J Indones [Internet]. 2021Oct.1 [cited 2024Apr.26];30(3):182-90. Available from: http://mji.ui.ac.id/journal/index.php/mji/article/view/5452
Issue
Vol. 30 No. 3 (2021): September
Section
Basic Medical Research

Copyright (c) 2021 Neng Nenden Mulyaningsih, Ariadne Lakshmidevi Juwono, Djarwani Soeharso Soejoko , Dewi Apri Astuti

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Authors who publish with Medical Journal of Indonesia agree to the following terms:

  1. Authors retain copyright and grant Medical Journal of Indonesia right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial License that allows others to remix, adapt, build upon the work non-commercially with an acknowledgment of the work’s authorship and initial publication in Medical Journal of Indonesia.
  2. Authors are permitted to copy and redistribute the journal's published version of the work non-commercially (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in Medical Journal of Indonesia.

Most read articles by the same author(s)