Anatomic modeling using 3D printing: quality assurance and optimization

3D Printing in Medicine, Apr 2017

Background The purpose of this study is to provide a framework for the development of a quality assurance (QA) program for use in medical 3D printing applications. An interdisciplinary QA team was built with expertise from all aspects of 3D printing. A systematic QA approach was established to assess the accuracy and precision of each step during the 3D printing process, including: image data acquisition, segmentation and processing, and 3D printing and cleaning. Validation of printed models was performed by qualitative inspection and quantitative measurement. The latter was achieved by scanning the printed model with a high resolution CT scanner to obtain images of the printed model, which were registered to the original patient images and the distance between them was calculated on a point-by-point basis. Results A phantom-based QA process, with two QA phantoms, was also developed. The phantoms went through the same 3D printing process as that of the patient models to generate printed QA models. Physical measurement, fit tests, and image based measurements were performed to compare the printed 3D model to the original QA phantom, with its known size and shape, providing an end-to-end assessment of errors involved in the complete 3D printing process. Measured differences between the printed model and the original QA phantom ranged from -0.32 mm to 0.13 mm for the line pair pattern. For a radial-ulna patient model, the mean distance between the original data set and the scanned printed model was -0.12 mm (ranging from -0.57 to 0.34 mm), with a standard deviation of 0.17 mm. Conclusions A comprehensive QA process from image acquisition to completed model has been developed. Such a program is essential to ensure the required accuracy of 3D printed models for medical applications.

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Anatomic modeling using 3D printing: quality assurance and optimization

D Printing in Medicine Anatomic modeling using 3D printing: quality assurance and optimization Shuai Leng 0 Kiaran McGee 0 Jonathan Morris 0 Amy Alexander 0 Joel Kuhlmann 1 Thomas Vrieze 0 Cynthia H. McCollough 0 Jane Matsumoto 0 0 Department of Radiology , 200 First Street SW , Mayo Clinic , Rochester 55901, MN , USA 1 Division of Engineering , 200 First Street SW , Mayo Clinic , Rochester 55901, MN , USA Background: The purpose of this study is to provide a framework for the development of a quality assurance (QA) program for use in medical 3D printing applications. An interdisciplinary QA team was built with expertise from all aspects of 3D printing. A systematic QA approach was established to assess the accuracy and precision of each step during the 3D printing process, including: image data acquisition, segmentation and processing, and 3D printing and cleaning. Validation of printed models was performed by qualitative inspection and quantitative measurement. The latter was achieved by scanning the printed model with a high resolution CT scanner to obtain images of the printed model, which were registered to the original patient images and the distance between them was calculated on a point-by-point basis. Results: A phantom-based QA process, with two QA phantoms, was also developed. The phantoms went through the same 3D printing process as that of the patient models to generate printed QA models. Physical measurement, fit tests, and image based measurements were performed to compare the printed 3D model to the original QA phantom, with its known size and shape, providing an end-to-end assessment of errors involved in the complete 3D printing process. Measured differences between the printed model and the original QA phantom ranged from -0.32 mm to 0.13 mm for the line pair pattern. For a radial-ulna patient model, the mean distance between the original data set and the scanned printed model was -0.12 mm (ranging from -0.57 to 0.34 mm), with a standard deviation of 0.17 mm. Conclusions: A comprehensive QA process from image acquisition to completed model has been developed. Such a program is essential to ensure the required accuracy of 3D printed models for medical applications. Quality assurance; 3D printing; Imaging; Segmentation; Phantom; Computed tomography (CT) - Background First used in manufacturing, medical applications of 3D printing or additive manufacturing have been rapidly developing. Using a patient’s own medical image data, 3D printing can be used to create individualized, life-size patient-specific models. These models are increasingly being used as aids in surgical planning for complex cases [1–11]. 3D models can contribute to surgical procedures by providing surgeons with an accurate life size physical reproduction of the anatomy of interest. In addition, models offer unique educational opportunities, including simulation for resident training [12, 13]. Research applications include patient-specific imaging and therapeutic phantoms used for advancing imaging techniques, reducing radiation dose, and conducting treatment planning and dose verification in radiation therapy [14–21]. Additional applications include the development of patient specific surgical guides and the reproduction of forensic models. 3D printing offers advantages over conventional manufacturing technologies. Individualized single models can be created as needed in a clinical setting with relatively low cost in a fairly short time frame. Depending on the type of 3D printing technology used, models can be printed with varying material types, colors, and mechanical properties with potential for sterilization. 3D printing is more efficient and less costly than standard manufacturing technologies and is uniquely suited to contribute to individualized patient care. While the role of 3D printing in medicine is rapidly expanding and will certainly be a part of medical care © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. going into the future, it is important that quality assurance (QA) programs are in place as part of the development and maintenance of a 3D printing program. To develop a QA program, it is important to identify the steps involved in generating a 3D model. There are essentially three steps involved in 3D printing in medicine: (1) Step one involves the acquisition of 3D volumetric images of the patient. (2) Step two is to separate out the anatomy of interest from surrounding structures and output the segmented virtual models as stereolithography (STL) files. This step also includes the editing of the original segmented objects, such (...truncated)


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Shuai Leng, Kiaran McGee, Jonathan Morris, Amy Alexander, Joel Kuhlmann, Thomas Vrieze, Cynthia H. McCollough, Jane Matsumoto. Anatomic modeling using 3D printing: quality assurance and optimization, 3D Printing in Medicine, 2017, pp. 6, Volume 3, Issue 1, DOI: 10.1186/s41205-017-0014-3