Shepard Lauren, Sommer Kelsey, Izzo Richard, Podgorsak Alexander, Wilson Michael, Said Zaid, Rybicki Frank J, Mitsouras Dimitrios, Rudin Stephen, Angel Erin, Ionita Ciprian N
University Dept. of Biomedical Engineering, University at Buffalo, Buffalo, NY.
Toshiba Stroke and Vascular Research Center, Buffalo, NY.
Proc SPIE Int Soc Opt Eng. 2017 Feb 11;10138. doi: 10.1117/12.2253889. Epub 2017 Mar 13.
Accurate patient-specific phantoms for device testing or endovascular treatment planning can be 3D printed. We expand the applicability of this approach for cardiovascular disease, in particular, for CT-geometry derived benchtop measurements of Fractional Flow Reserve, the reference standard for determination of significant individual coronary artery atherosclerotic lesions.
Coronary CT Angiography (CTA) images during a single heartbeat were acquired with a 320×0.5mm detector row scanner (Toshiba Aquilion ONE). These coronary CTA images were used to create 4 patient-specific cardiovascular models with various grades of stenosis: severe, <75% (n=1); moderate, 50-70% (n=1); and mild, <50% (n=2). DICOM volumetric images were segmented using a 3D workstation (Vitrea, Vital Images); the output was used to generate STL files (using AutoDesk Meshmixer), and further processed to create 3D printable geometries for flow experiments. Multi-material printed models (Stratasys Connex3) were connected to a programmable pulsatile pump, and the pressure was measured proximal and distal to the stenosis using pressure transducers. Compliance chambers were used before and after the model to modulate the pressure wave. A flow sensor was used to ensure flow rates within physiological reported values.
3D model based FFR measurements correlated well with stenosis severity. FFR measurements for each stenosis grade were: 0.8 severe, 0.7 moderate and 0.88 mild.
3D printed models of patient-specific coronary arteries allows for accurate benchtop diagnosis of FFR. This approach can be used as a future diagnostic tool or for testing CT image-based FFR methods.
可通过3D打印获得用于设备测试或血管内治疗规划的精确患者特异性体模。我们扩展了这种方法在心血管疾病中的适用性,特别是用于基于CT几何结构的血流储备分数(FFR)的台式测量,FFR是确定个体冠状动脉显著动脉粥样硬化病变的参考标准。
使用320×0.5mm探测器排CT扫描仪(东芝Aquilion ONE)采集单次心跳期间的冠状动脉CT血管造影(CTA)图像。这些冠状动脉CTA图像用于创建4个具有不同狭窄程度的患者特异性心血管模型:重度,<75%(n = 1);中度,50 - 70%(n = 1);轻度,<50%(n = 2)。使用3D工作站(Vitrea,Vital Images)对DICOM体积图像进行分割;输出结果用于生成STL文件(使用AutoDesk Meshmixer),并进一步处理以创建用于血流实验的3D可打印几何模型。多材料打印模型(Stratasys Connex3)连接到可编程搏动泵,并使用压力传感器测量狭窄近端和远端的压力。在模型前后使用顺应性腔室调节压力波。使用流量传感器确保流速在生理报告值范围内。
基于3D模型的FFR测量与狭窄严重程度密切相关。每个狭窄等级的FFR测量值分别为:重度0.8、中度0.7、轻度0.88。
患者特异性冠状动脉的3D打印模型可实现FFR的精确台式诊断。这种方法可作为未来的诊断工具或用于测试基于CT图像的FFR方法。