A robust, autonomous, volumetric quality assurance method for 3D printed porous scaffolds.
A robust, autonomous, volumetric quality assurance method for 3D printed porous scaffolds.
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DOI：
10.1186/s41205-022-00135-x
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发表时间：
2022-04-06
影响因子：
3.7
通讯作者：
Grayson WL
中科院分区：
文献类型：
--
作者：
Zhang N;Singh S;Liu S;Zbijewski W;Grayson WL
旨在治疗临界尺寸颅面缺陷的骨组织工程策略通常利用新型生物材料和支架。使用 3D 打印策略快速制造缺陷匹配的几何形状是治疗颅面骨丢失以改善美观和再生结果的一种有前途的策略。为了验证制造质量，如果要将多孔支架从实验室转移到临床环境，则需要强大的三维质量保证管道来提供打印质量的客观定量指标。先前发表的评估支架打印质量的方法使用一维和二维测量（例如，支柱宽度、孔隙宽度和孔隙面积），或者在某些情况下，假设单个模型的打印质量代表所有后续打印的质量。解剖形状之间更稳健的体积相关性已经实现；然而，在具有挑战性的情况下，例如骨支架等多孔物体，它需要用户手动校正。在这里，我们设计了具有同质或异质多孔结构的多孔、符合解剖学形状的支架。我们使用丙烯腈丁二烯苯乙烯 (ABS) 3D 打印设计，并使用锥形束计算机断层扫描 (CBCT) 来获得 3D 图像重建。我们应用迭代最近点算法将计算支架设计与 CBCT 图像叠加以获得 3D 体积重叠。为了避免在使用体积相关的自主工作流程时出现错误收敛，我们使用 MATLAB® 开发了一种独立的迭代最近点 (I-ICP10) 算法，该算法对 CBCT 图像相对于原始设计的空间方向应用了 10 个初始条件。成功关联后，可以在体积的任何部分的亚体素尺度上量化和可视化支架质量。
Bone tissue engineering strategies aimed at treating critical-sized craniofacial defects often utilize novel biomaterials and scaffolding. Rapid manufacturing of defect-matching geometries using 3D-printing strategies is a promising strategy to treat craniofacial bone loss to improve aesthetic and regenerative outcomes. To validate manufacturing quality, a robust, three-dimensional quality assurance pipeline is needed to provide an objective, quantitative metric of print quality if porous scaffolds are to be translated from laboratory to clinical settings. Previously published methods of assessing scaffold print quality utilized one- and two-dimensional measurements (e.g., strut widths, pore widths, and pore area) or, in some cases, the print quality of a single phantom is assumed to be representative of the quality of all subsequent prints. More robust volume correlation between anatomic shapes has been accomplished; however, it requires manual user correction in challenging cases such as porous objects like bone scaffolds. Here, we designed porous, anatomically-shaped scaffolds with homogenous or heterogenous porous structures. We 3D-printed the designs with acrylonitrile butadiene styrene (ABS) and used cone-beam computed tomography (CBCT) to obtain 3D image reconstructions. We applied the iterative closest point algorithm to superimpose the computational scaffold designs with the CBCT images to obtain a 3D volumetric overlap. In order to avoid false convergences while using an autonomous workflow for volumetric correlation, we developed an independent iterative closest point (I-ICP10) algorithm using MATLAB®, which applied ten initial conditions for the spatial orientation of the CBCT images relative to the original design. Following successful correlation, scaffold quality can be quantified and visualized on a sub-voxel scale for any part of the volume.
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DOI：
10.1073/pnas.1001208107
发表时间：
2010-07-27
影响因子：
11.1
作者：
Sutradhar, Alok;Paulino, Glaucio H.;Nguyen, Tam H.
通讯作者：
Nguyen, Tam H.
影响因子：
4.9
作者：
Temple, Joshua P.;Hutton, Daphne L.;Grayson, Warren L.
通讯作者：
Grayson, Warren L.
DOI：
10.3390/s18051641
发表时间：
2018-05-21
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Cheng L;Chen S;Liu X;Xu H;Wu Y;Li M;Chen Y
通讯作者：
Chen Y
DOI：
10.1109/34.121791
发表时间：
1992-02-01
影响因子：
23.6
作者：
BESL, PJ;MCKAY, ND
通讯作者：
MCKAY, ND
影响因子：
9
作者：
Guo T;Holzberg TR;Lim CG;Gao F;Gargava A;Trachtenberg JE;Mikos AG;Fisher JP
通讯作者：
Fisher JP