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    Quantitative and qualitative comparison of low- and high-cost 3D-printed heart models

    74939.pdf (946.1Kb)
    Access Status
    Open access
    Authors
    Lau, I.
    Wong, Y.
    Yeong, C.
    Abdul Aziz, Y.
    Md Sari, N.
    Hashim, S.
    Sun, Zhonghua
    Date
    2019
    Type
    Journal Article
    
    Metadata
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    Citation
    Lau, I. and Wong, Y. and Yeong, C. and Abdul Aziz, Y. and Md Sari, N. and Hashim, S. and Sun, Z. 2019. Quantitative and qualitative comparison of low- and high-cost 3D-printed heart models. Quantitative Imaging in Medicine and Surgery. 9 (1): pp. 107-114.
    Source Title
    Quantitative Imaging in Medicine and Surgery
    DOI
    10.21037/qims.2019.01.02
    ISSN
    2223-4292
    School
    School of Molecular and Life Sciences (MLS)
    URI
    http://hdl.handle.net/20.500.11937/74654
    Collection
    • Curtin Research Publications
    Abstract

    Current visualization techniques of complex congenital heart disease (CHD) are unable to provide comprehensive visualization of the anomalous cardiac anatomy as the medical datasets can essentially only be viewed from a flat, two-dimensional (2D) screen. Three-dimensional (3D) printing has therefore been used to replicate patient-specific hearts in 3D views based on medical imaging datasets. This technique has been shown to have a positive impact on the preoperative planning of corrective surgery, patient-doctor communication, and the learning experience of medical students. However, 3D printing is often costly, and this impedes the routine application of this technology in clinical practice. This technical note aims to investigate whether reducing 3D printing costs can have any impact on the clinical value of the 3D-printed heart models. Low-cost and a high-cost 3D-printed models based on a selected case of CHD were generated with materials of differing cost. Quantitative assessment of dimensional accuracy of the cardiac anatomy and pathology was compared between the 3D-printed models and the original cardiac computed tomography (CT) images with excellent correlation (r=0.99). Qualitative evaluation of model usefulness showed no difference between the two models in medical applications

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