Haefner Matthias Felix, Giesel Frederik Lars, Mattke Matthias, Rath Daniel, Wade Moritz, Kuypers Jacob, Preuss Alan, Kauczor Hans-Ulrich, Schenk Jens-Peter, Debus Juergen, Sterzing Florian, Unterhinninghofen Roland
Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany.
National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), 69120 Heidelberg, Germany.
Oncotarget. 2018 Jan 8;9(5):6490-6498. doi: 10.18632/oncotarget.24032. eCollection 2018 Jan 19.
We developed a new approach to produce individual immobilization devices for the head based on MRI data and 3D printing technologies. The purpose of this study was to determine positioning accuracy with healthy volunteers. 3D MRI data of the head were acquired for 8 volunteers. In-house developed software processed the image data to generate a surface mesh model of the immobilization mask. After adding an interface for the couch, the fixation setup was materialized using a 3D printer with acrylonitrile butadiene styrene (ABS). Repeated MRI datasets (n=10) were acquired for all volunteers wearing their masks thus simulating a setup for multiple fractions. Using automatic image-to-image registration, displacements of the head were calculated relative to the first dataset (6 degrees of freedom). The production process has been described in detail. The absolute lateral (x), vertical (y) and longitudinal (z) translations ranged between -0.7 and 0.5 mm, -1.8 and 1.4 mm, and -1.6 and 2.4 mm, respectively. The absolute rotations for pitch (x), yaw (y) and roll (z) ranged between -0.9 and 0.8°, -0.5 and 1.1°, and -0.6 and 0.8°, respectively. The mean 3D displacement was 0.9 mm with a standard deviation (SD) of the systematic and random error of 0.2 mm and 0.5 mm, respectively. In conclusion, an almost entirely automated production process of 3D printed immobilization masks for the head derived from MRI data was established. A high level of setup accuracy was demonstrated in a volunteer cohort. Future research will have to focus on workflow optimization and clinical evaluation.
我们基于MRI数据和3D打印技术开发了一种用于制作头部个性化固定装置的新方法。本研究的目的是确定健康志愿者的定位准确性。为8名志愿者采集了头部的3D MRI数据。内部开发的软件对图像数据进行处理,以生成固定面罩的表面网格模型。在添加了用于治疗床的接口后,使用3D打印机和丙烯腈丁二烯苯乙烯(ABS)实现了固定装置。为所有佩戴面罩的志愿者采集了重复的MRI数据集(n = 10),从而模拟多次分割的设置。使用自动图像到图像配准,计算头部相对于第一个数据集的位移(6个自由度)。详细描述了生产过程。绝对横向(x)、纵向(y)和纵向(z)平移分别在-0.7至0.5 mm、-1.8至1.4 mm和-1.6至2.4 mm之间。俯仰(x)、偏航(y)和滚动(z)的绝对旋转分别在-0.9至0.8°、-0.5至1.1°和-0.6至0.8°之间。平均3D位移为0.9 mm,系统误差和随机误差的标准差(SD)分别为0.2 mm和0.5 mm。总之,建立了一种几乎完全自动化的从MRI数据制作3D打印头部固定面罩的生产过程。在志愿者队列中证明了高水平的设置准确性。未来的研究将不得不专注于工作流程优化和临床评估。