Annals of Anatomy ( IF 2.2 ) Pub Date : 2020-11-01 , DOI: 10.1016/j.aanat.2020.151629 Mark Kaschwich 1 , Marco Horn 2 , Sarah Matthiensen 3 , Erik Stahlberg 4 , Christian-Alexander Behrendt 5 , Florian Matysiak 3 , Juljan Bouchagiar 3 , Annika Dell 3 , David Ellebrecht 6 , Andreas Bayer 7 , Markus Kleemann 8
Introduction
3D printing has a wide range of applications in medicine. In surgery, this technique can be used for preoperative planning of complex procedures, production of patient specific implants, as well as training. However, accuracy evaluations of 3D vascular models are rare.
Objectives
Aim of this study was to investigate the accuracy of patient-specific 3D-printed aortic anatomies.
Methods
Patients suffering from aorto-iliac aneurysms and with indication for treatment were selected on the basis of different anatomy and localization of the aneurysm in the period from January 1st 2014 to May 27th 2016. Six patients with aorto-iliac aneurysms were selected out of the database for 3D-printing. Subsequently, computed tomography (CT) images of the printed 3D-models were compared with the original CT data sets.
Results
The mean deviation of the six 3D-vascular models ranged between −0.73 mm and 0.14 mm compared to the original CT-data. The relative deviation of the measured values showed no significant difference between the 3D-vascular and the original patient CT-data.
Conclusion
Our results showed that 3D printing has the potential to produce patient-specific 3D vascular models with reliable accuracy. This enables the use of such models for the development of new endovascular procedures and devices.
中文翻译:
患者特定 3D 打印主动脉解剖结构的准确性评估
介绍
3D打印在医学领域有着广泛的应用。在外科手术中,该技术可用于复杂程序的术前计划、患者特定植入物的生产以及培训。然而,3D 血管模型的准确性评估很少见。
目标
本研究的目的是调查患者特定的 3D 打印主动脉解剖结构的准确性。
方法
2014年1月1日至2016年5月27日期间,根据动脉瘤的不同解剖结构和定位选择具有治疗指征的主髂动脉瘤患者。从数据库中选出6名主髂动脉瘤患者用于 3D 打印。随后,将打印的 3D 模型的计算机断层扫描 (CT) 图像与原始 CT 数据集进行比较。
结果
与原始 CT 数据相比,六个 3D 血管模型的平均偏差介于 -0.73 毫米和 0.14 毫米之间。测量值的相对偏差表明 3D 血管和原始患者 CT 数据之间没有显着差异。
结论
我们的结果表明,3D 打印有可能以可靠的精度生产特定于患者的 3D 血管模型。这使得能够使用此类模型来开发新的血管内手术和设备。