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CT imaging parameters for precision models using additive manufacturing

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Abstract

Additive manufacturing (AM), generally known as 3D Printing, is one of the manufacturing methods to develop medical models. The AM physical medical models are manufactured by virtual Computer-Aided Design (CAD) models. These CAD models are generated using medical scan data such as, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), etc. In the process of CT data acquisition and transformation from CT to CAD data, dimensional and volumetric errors occur. In this work, the influence of several CT image reconstruction parameters on the 3D CAD model was evaluated experimentally. The dry mandible has been considered as a phantom from construction of a 3D CAD model. The linear dimensional and volumetric errors in the CT image reconstruction were compared from the dry mandible to the 3D CAD model of the CT images. Further, the CT image reconstruction parameters are optimized by Taguchi and Gray relational analysis methods. The optimized parameter of a 3D CAD model was used to develop STereo Lithography (STL) file and Fused Deposition Modeling (FDM) model by AM process. The scaling factor of each axis is determined by considering the ratio of STL to FDM model linear dimensions. Finally, the scaled STL model was manufactured by FDM technique and investigated that the dimensional error of the FDM model was minimized.

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References

  • Asaumi J, Kawai N, Honda Y, Shigehara H, Wakasa T, Kishi K (2001) Comparison of three-dimensional computed tomography with rapid prototype models in the management of coronoid hyperplasia. Dentomaxillofac Radiol 30:330–335

    Article  Google Scholar 

  • Broeck JV, Vereecke E, Speetjens RW, Sloten JV (2014) Segmentation accuracy of long bones. Med Eng Phys 36:949–953

    Article  Google Scholar 

  • Choi JY, Choi JH, Kim NK, Kim Y, Lee JK (2002) Analysis of errors in medical rapid prototyping models. Int J Oral Maxillofac Surg 31:23–32

    Article  Google Scholar 

  • Deng J (1989) Introduction to gray system theory. J Gray Syst 1:1–24

    MATH  Google Scholar 

  • El-Katatny I, Masood SH, Morsi YS (2010) Error analysis of FDM fabricated medical replicas. Rapid Prototyp J 16:36–43

    Article  Google Scholar 

  • Gelaude F, Sloten JV, Lauwers B (2008) Accuracy assessment of CT-based outer surface femur meshes. Comput Aided Surg 13:188–199

    Article  Google Scholar 

  • Gibson I, Cheung LK, Chow SP, Cheung WL, Beh SL, Savalani M, Lee SH (2006) The use of rapid prototyping to assist medical applications. Rapid Prototyp J 12:53–58

    Article  Google Scholar 

  • Goiato MC, Santos MR, Pesqueira AA, Moreno A, Santos DM, Haddad MF (2011) Prototyping for surgical and prosthetic treatment. J Craniofac Surg 22:914–917

    Article  Google Scholar 

  • Goldman LW (2007) Principles of CT and CT technology. J Nucl Med Technol 35:115–128

    Article  Google Scholar 

  • Huang MW, Liu SM, Zheng L, Shi Y, Zhang J, Sheng LY, Yan YUG, Zhang JG (2012) A digital model individual template and CT-guided 125I seed implants for malignant tumors of the head and neck. J Radiat Res 53:973–977

    Article  Google Scholar 

  • Hughes William S (2005) Archimedes revisited: a faster, better, cheaper method of accurately measuring the volume of small objects. Phys Educ 40:468–474

    Article  Google Scholar 

  • Kamrani AK, Azimi M (2011) Geometrical modeling of H&N cancer tumor. Rapid Prototyp J 17:55–63

    Article  Google Scholar 

  • Krishna LSR, Manmadhachary A, Reddy PB, Venkatesh S (2011) Development of optimum preplanning for maxillofacial surgery using selective laser sintering. Int J Eng Sci Technol 3:185–196

    Google Scholar 

  • Lee BK (2011) Computational fluid dynamics in cardiovascular disease. Korean Soc Cardiol 41:423–430

    Google Scholar 

  • Mallepree T, Bergers D (2009) Accuracy of medical RP models. Rapid Prototyp J 15:325–332

    Article  Google Scholar 

  • Manmadhachary A, Ravi Kumar Y, Krishnanand L (2016) Finding of correction factor and dimensional error in bio-AM model by FDM technique. J Inst Eng (India) 99:293–300

    Google Scholar 

  • Manmadhachary A, Kumar YR, Krishnanand L (2017) Effect of CT acquisition parameters of spiral CT on image quality and radiation dose. Measurement 103:18–26

    Article  Google Scholar 

  • Meurer MI, Souza KP, Wangenheim AV, Abdala DD, Nobre LFS, Meurer E, Silva JVL (2013) Influence of tomographic slice thickness and field of view variation on the reproduction of thin bone structures for rapid prototyping purposes—an in vitro study. Open J Radiol 3:12–25

    Article  Google Scholar 

  • Murugesan K, Anandapandian PA, Sharma SK, Kumar MV (2012) Comparative evaluation of dimension and surface detail accuracy of models produced by three different rapid prototype techniques. J Indian Prosthodont Soc 12:16–20

    Article  Google Scholar 

  • Plessis A, Roux SG, Els J, Booysen G, Blaine DC (2015) Application of microCT to the non-destructive testing of an additive manufactured titanium component. Case Stud Nondestruct Test Evaluation 4:1–7

    Article  Google Scholar 

  • Rathnayaka K, Momot KI, Noser H, Volp A, Schuetz MA, Sahama T, Schmutz B (2012) Quantification of the accuracy of MRI generated 3D models of long bones compared to CT generated 3D models. Med Eng Phys 34:357–363

    Article  Google Scholar 

  • Salmi M, Paloheimo K, Tuomi J, Wolff J, Salmi AM, Paloheimo K, Tuomi J, Wolff J, Makitie A (2013) Accuracy of medical models made by additive manufacturing (rapid manufacturing). J Craniomaxillofac Surg 41:603–609

    Article  Google Scholar 

  • Seeram E (1994) Computed tomography: physical principles, clinical applications and quality control. WB Saunders Co., Philadelphia

    Google Scholar 

  • Selepchi ED, Duliu OGR (2007) Image processing and data analysis in computed tomography. J Phys 52:667–675

    Google Scholar 

  • Silva DN, Oliveira MGD, Meurer E, Meurer M, Silva JVLD, Rbara AS (2008) Dimensional error in selective laser sintering and 3D-printing of models for craniomaxillary anatomy reconstruction. J Cranio-Maxillofac Surg 36:443–449

    Article  Google Scholar 

  • Stull KE, Tise ML, Ali Z, Fowler DR (2014) Accuracy and reliability of measurements obtained from computed tomography 3D volume rendered images. Forensic Sci Int 238:133–140

    Article  Google Scholar 

  • Taguchi G (1990) Introduction to quality engineering. Asian Product Org, Tokyo

    Google Scholar 

  • Varghese S, Kailasam V, Padmanabhan S, Vikraman B, Chithranjan A (2010) Evaluation of the accuracy of linear measurements on spiral computed tomography-derived three-dimensional images and its comparison with digital cephalometric radiography. Dentomaxillofac Radiol 39:216–223

    Article  Google Scholar 

  • Wang M, Qu X, Cao M, Wang D, Zhang C (2013) Biomechanical three-dimensional finite element analysis of prostheses retained with/without zygoma implants in maxillectomy patients. J Biomech 46:1155–1161

    Article  Google Scholar 

  • Winder J, Bibb R (2005) Medical rapid prototyping technologies: state of the art and current limitations for application in oral and maxillofacial surgery. Am J Oral Maxillofac Surg 63:1006–1015

    Article  Google Scholar 

  • Wohler TT (2013) Additive manufacturing and 3D printing state of the industry. Annual Worldwide Progress Report. Wohlers Associates, Colorado

    Google Scholar 

  • Yang N, Quan Z, Zhang D, Tian Y (2014) Multi-morphology transition hybridization CAD design of minimal surface porous structures for use in tissue engineering. Comput Aided Des 56:11–21

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Mechanical Engineering, IcfaiTech, IFHE University, Hyderabad, Telangana, India

    A. Manmadhachary

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  1. A. Manmadhachary
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Correspondence to A. Manmadhachary.

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Manmadhachary, A. CT imaging parameters for precision models using additive manufacturing. Multiscale and Multidiscip. Model. Exp. and Des. 2, 209–220 (2019). https://doi.org/10.1007/s41939-019-00046-1

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  • DOI: https://doi.org/10.1007/s41939-019-00046-1

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