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Anatomic Modeling Using 3D Printing: Quality Assurance and Optimization

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Anatomic Modeling Using 3D Printing: Quality Assurance and Optimization Leng et al. 3D Printing in Medicine (2017) 3:6 DOI 10.1186/s41205-017-0014-3 RESEARCH Open Access Anatomic modeling using 3D printing: quality assurance and optimization Shuai Leng1*, Kiaran McGee1, Jonathan Morris1, Amy Alexander1, Joel Kuhlmann2, Thomas Vrieze1, Cynthia H. McCollough1 and Jane Matsumoto1 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 wasachievedbyscanningtheprintedmodelwithahighresolution 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. Keywords: Quality assurance, 3D printing, Imaging, Segmentation, Phantom, Computed tomography (CT) Background phantoms used for advancing imaging techniques, reducing First used in manufacturing, medical applications of 3D radiation dose, and conducting treatment planning and printing or additive manufacturing have been rapidly de- dose verification in radiation therapy [14–21]. Additional veloping. Using a patient’s own medical image data, 3D applications include the development of patient specific printing can be used to create individualized, life-size surgical guides and the reproduction of forensic models. patient-specific models. These models are increasingly 3D printing offers advantages over conventional manu- being used as aids in surgical planning for complex cases facturing technologies. Individualized single models can be [1–11]. 3D models can contribute to surgical procedures created as needed in a clinical setting with relatively low by providing surgeons with an accurate life size physical cost in a fairly short time frame. Depending on the type of reproduction of the anatomy of interest. In addition, 3D printing technology used, models can be printed with models offer unique educational opportunities, including varying material types, colors, and mechanical properties simulation for resident training [12, 13]. Research appli- with potential for sterilization. 3D printing is more efficient cations include patient-specific imaging and therapeutic and less costly than standard manufacturing technologies and is uniquely suited to contribute to individualized * Correspondence: [email protected] patient care. 1Department of Radiology, 200 First Street SW, Mayo Clinic, Rochester 55901, MN, USA While the role of 3D printing in medicine is rapidly Full list of author information is available at the end of the article 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. Leng et al. 3D Printing in Medicine (2017) 3:6 Page 2 of 14 going into the future, it is important that quality assur- Methods ance (QA) programs are in place as part of the develop- We have developed a systematic approach that involves ment and maintenance of a 3D printing program. To QA for each of the major steps of 3D printing: imaging, develop a QA program, it is important to identify the segmentation and processing, and printing. In the fol- steps involved in generating a 3D model. There are es- lowing subsections, we will discuss the appropriate QA sentially three steps involved in 3D printing in medicine: process for each of these three major steps. (1) Step one involves the acquisition of 3D volumetric images of the patient. (2) Step two is to separate out the QA and optimization of image acquisition anatomy of interest from surrounding structures and The first step of anatomic modeling is to acquire volu- output the segmented virtual models as stereolithog- metric image data of the patient. The quality of the raphy (STL) files. This step also includes the editing of image data (i.e. spatial resolution, signal-to-noise ratio, the original segmented objects, such as wrapping and artifacts) has a direct impact on the accuracy and effi- smoothing. (3) Step three is to print the physical models ciency of the following steps, e.g. segmentation, process- and clean them. While the accuracy of medical imaging ing, and printing. Therefore, thorough control of the is a critical first step in 3D printing, the additional ele- quality of the acquired image data plays a critical role as ments of segmentation and processing of imaging data it directly affects the quality of the final model. and the technical aspects of the 3D printing process can CT and MRI are the most common imaging modalities all affect the accuracy of the final 3D printed model. used to generate 3D volumetric data for the purpose of Each of these production steps should be individually anatomical modeling. At most institutions, CT and MRI evaluated, analyzed and optimized. Medical confidence scanners are accredited by an accreditation organization, in the accurate representation of patient anatomy and such as American College of Radiology (ACR). As part pathology is a necessary component of medical 3D print- of the accreditation, a QA program is required that in- ing applications. cludes the performance of routine tests for all scanners. A successful QA program requires input from all Tests are performed on a daily, monthly and annual stakeholders involved in the 3D printing process. As basis depending on the requirements specified by the such, it is critical to build an interdisciplinary QA team. accreditation organization. During the QA process, geo- Typical stakeholders include: 1) Surgeons or physicians metric accuracy and spatial resolution are routinely who order the model know the clinical need, and are the checked [22, 23]. end users of the model; 2) Interpreting radiologists who As scan and reconstruction parameters directly affect possess expertise in acquiring and interpreting the im- image quality, imaging protocols need to be optimized aging study; 3) Medical physicists who are experts in the to meet the needs of 3D modeling. For example, lower imaging technology and ensure exams are performed tube potential (kV) can be used in CT to increase the with optimized scanning and reconstruction techniques; enhancement of iodine contrast when building vascular they also have extensive experience and leadership roles models [24]. Contrast injection and bolus timing can be for the QA programs in a radiology department; 4) Tech- adjusted to separate arterial and venous phases of the nologists who perform the imaging and segmentation; 5) contrast enhancement. Image slice thickness and recon- Engineers and operators who do variable amounts of struction kernel are important factors influencing the segmentation, model design and printer maintenance. An spatial resolution and image noise. Thick images can essential component of a successful QA program is effect- generate discontinuous, stair-step like boundaries on the ive communication between these team members to en- segmented model (Fig. 1). The reconstruction kernel im- sure creation of a high quality model. pacts both spatial resolution and image noise, which A QA program with validation, verification, and docu- need to be balanced based on particular applications. mentation to assure accuracy and quality is therefore a For models with fine structures, such as the temporal key component of 3D printing. Fortunately, radiology bone, a sharp kernel is more appropriate to get the best departments have significant expertise in the development spatial resolution (Fig. 2). Conversely, for models with of QA programs and this experience can be adapted to moderate to large size, low contrast objects, such as liver medical 3D printing. Expansion of QA programs to in- lesions, a smooth kernel is more appropriate to control clude evaluation of the unique characteristics of 3D print- image noise (Fig. 2). ing technology and segmentation processes forms the Novel imaging techniques should be adopted to assist basis of a medical 3D printing QA program. The purpose the process of 3D printing to improve accuracy and effi- of this paper is to give an overview of the QA program ciency. For example, both bone and iodine-enhanced that has been developed at our institution to assess vessels have high CT numbers and show up as bright the accuracy and precision of each step of the 3D structures in regular CT images. It can be challenging to printing process. separate such bones and vessels. Dual-energy CT, which Leng et al.
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