Anatomic modeling using 3D printing: quality assurance and optimization
Abstract 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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2017-04-01
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| Series: | 3D Printing in Medicine |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s41205-017-0014-3 |
| _version_ | 1818234187808768000 |
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| author | Shuai Leng Kiaran McGee Jonathan Morris Amy Alexander Joel Kuhlmann Thomas Vrieze Cynthia H. McCollough Jane Matsumoto |
| author_facet | Shuai Leng Kiaran McGee Jonathan Morris Amy Alexander Joel Kuhlmann Thomas Vrieze Cynthia H. McCollough Jane Matsumoto |
| author_sort | Shuai Leng |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-12T11:34:06Z |
| format | Article |
| id | doaj.art-3b8db68a680c407d9547cee71ca9fb09 |
| institution | Directory Open Access Journal |
| issn | 2365-6271 |
| language | English |
| last_indexed | 2024-12-12T11:34:06Z |
| publishDate | 2017-04-01 |
| publisher | BMC |
| record_format | Article |
| series | 3D Printing in Medicine |
| spelling | doaj.art-3b8db68a680c407d9547cee71ca9fb092022-12-22T00:25:42ZengBMC3D Printing in Medicine2365-62712017-04-013111410.1186/s41205-017-0014-3Anatomic modeling using 3D printing: quality assurance and optimizationShuai Leng0Kiaran McGee1Jonathan Morris2Amy Alexander3Joel Kuhlmann4Thomas Vrieze5Cynthia H. McCollough6Jane Matsumoto7Department of RadiologyDepartment of RadiologyDepartment of RadiologyDepartment of RadiologyDivision of EngineeringDepartment of RadiologyDepartment of RadiologyDepartment of RadiologyAbstract 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.http://link.springer.com/article/10.1186/s41205-017-0014-3Quality assurance3D printingImagingSegmentationPhantomComputed tomography (CT) |
| spellingShingle | 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 Quality assurance 3D printing Imaging Segmentation Phantom Computed tomography (CT) |
| title | Anatomic modeling using 3D printing: quality assurance and optimization |
| title_full | Anatomic modeling using 3D printing: quality assurance and optimization |
| title_fullStr | Anatomic modeling using 3D printing: quality assurance and optimization |
| title_full_unstemmed | Anatomic modeling using 3D printing: quality assurance and optimization |
| title_short | Anatomic modeling using 3D printing: quality assurance and optimization |
| title_sort | anatomic modeling using 3d printing quality assurance and optimization |
| topic | Quality assurance 3D printing Imaging Segmentation Phantom Computed tomography (CT) |
| url | http://link.springer.com/article/10.1186/s41205-017-0014-3 |
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