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Open AccessArticle

Cumulative Inaccuracies in Implementation of Additive Manufacturing Through Medical Imaging, 3D Thresholding, and 3D Modeling: A Case Study for an End-Use Implant

1
Department of Mechanical Engineering, Aalto University, Otakaari 4, 02150 Espoo, Finland
2
MIKES-National Metrology Institute of Finland, VTT Technical Research Centre of Finland, Tekniikantie 1, 02150 Espoo, Finland
3
Department of Radiology, Medical Imaging Center, University of Helsinki and Helsinki University Hospital, P.O.Box 263, HUS, 00029 Helsinki, Finland
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(8), 2968; https://doi.org/10.3390/app10082968
Received: 25 March 2020 / Revised: 13 April 2020 / Accepted: 21 April 2020 / Published: 24 April 2020
(This article belongs to the Special Issue 3D Printing of Bioactive Medical Device)
In craniomaxillofacial surgical procedures, an emerging practice adopts the preoperative virtual planning that uses medical imaging (computed tomography), 3D thresholding (segmentation), 3D modeling (digital design), and additive manufacturing (3D printing) for the procurement of an end-use implant. The objective of this case study was to evaluate the cumulative spatial inaccuracies arising from each step of the process chain when various computed tomography protocols and thresholding values were independently changed. A custom-made quality assurance instrument (Phantom) was used to evaluate the medical imaging error. A sus domesticus (domestic pig) head was analyzed to determine the 3D thresholding error. The 3D modeling error was estimated from the computer-aided design software. Finally, the end-use implant was used to evaluate the additive manufacturing error. The results were verified using accurate measurement instruments and techniques. A worst-case cumulative error of 1.7 mm (3.0%) was estimated for one boundary condition and 2.3 mm (4.1%) for two boundary conditions considering the maximum length (56.9 mm) of the end-use implant. Uncertainty from the clinical imaging to the end-use implant was 0.8 mm (1.4%). This study helps practitioners establish and corroborate surgical practices that are within the bounds of an appropriate accuracy for clinical treatment and restoration. View Full-Text
Keywords: 3D printing; craniomaxillofacial surgery; medical imaging; computed tomography (CT); segmentation; digital design; CAD; implants; cumulative error; error propagation; standard uncertainty; spatial accuracy; quality control; quality assurance 3D printing; craniomaxillofacial surgery; medical imaging; computed tomography (CT); segmentation; digital design; CAD; implants; cumulative error; error propagation; standard uncertainty; spatial accuracy; quality control; quality assurance
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  • Externally hosted supplementary file 1
    Doi: 10.17632/d9j2chwdz8.1
    Link: http://dx.doi.org/10.17632/d9j2chwdz8.1
    Description: Medical CT-images of the sus domesticus acquired using the Siemens Somatom Definition Edge CT system
MDPI and ACS Style

Akmal, J.S.; Salmi, M.; Hemming, B.; Teir, L.; Suomalainen, A.; Kortesniemi, M.; Partanen, J.; Lassila, A. Cumulative Inaccuracies in Implementation of Additive Manufacturing Through Medical Imaging, 3D Thresholding, and 3D Modeling: A Case Study for an End-Use Implant. Appl. Sci. 2020, 10, 2968.

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