Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
Sci Rep. 2023 Oct 15;13(1):17495. doi: 10.1038/s41598-023-44602-9.
The objective of this study is to create patient-specific phantoms for computed tomography (CT) that possess accurate densities and exhibit visually realistic image textures. These qualities are crucial for evaluating CT performance in clinical settings. The study builds upon a previously presented 3D printing method (PixelPrint) by incorporating soft tissue and bone structures. We converted patient DICOM images directly into 3D printer instructions using PixelPrint and utilized calcium-doped filament to increase the Hounsfield unit (HU) range. Density was modeled by controlling printing speed according to volumetric filament ratio to emulate attenuation profiles. We designed micro-CT phantoms to demonstrate the reproducibility, and to determine mapping between filament ratios and HU values on clinical CT systems. Patient phantoms based on clinical cervical spine and knee examinations were manufactured and scanned with a clinical spectral CT scanner. The CT images of the patient-based phantom closely resembled original CT images in visual texture and contrast. Micro-CT analysis revealed minimal variations between prints, with an overall deviation of ± 0.8% in filament line spacing and ± 0.022 mm in line width. Measured differences between patient and phantom were less than 12 HU for soft tissue and 15 HU for bone marrow, and 514 HU for cortical bone. The calcium-doped filament accurately represented bony tissue structures across different X-ray energies in spectral CT (RMSE ranging from ± 3 to ± 28 HU, compared to 400 mg/ml hydroxyapatite). In conclusion, this study demonstrated the possibility of extending 3D-printed patient-based phantoms to soft tissue and bone structures while maintaining accurate organ geometry, image texture, and attenuation profiles.
本研究旨在为计算机断层扫描(CT)创建具有准确密度且呈现逼真视觉纹理的患者特定体模。这些特性对于评估临床环境中的 CT 性能至关重要。本研究基于之前提出的 3D 打印方法(PixelPrint),纳入软组织和骨结构。我们使用 PixelPrint 将患者的 DICOM 图像直接转换为 3D 打印机指令,并利用钙掺杂长丝来增加亨氏单位(HU)范围。通过根据体积长丝比控制打印速度来模拟衰减曲线来模拟密度。我们设计了微 CT 体模以证明重复性,并确定临床 CT 系统中长丝比和 HU 值之间的映射关系。基于临床颈椎和膝关节检查的患者体模已制造并使用临床光谱 CT 扫描仪进行扫描。基于患者的体模 CT 图像在视觉纹理和对比度上与原始 CT 图像非常相似。微 CT 分析显示打印之间的差异很小,长丝线间距的总偏差为±0.8%,线宽的总偏差为±0.022 毫米。软组织的患者和体模之间的测量差异小于 12 HU,骨髓的测量差异小于 15 HU,皮质骨的测量差异小于 514 HU。钙掺杂长丝在光谱 CT 中准确地代表了不同 X 射线能量下的骨组织结构(RMSE 范围为±3 至±28 HU,与 400 mg/ml 羟磷灰石相比)。总之,本研究证明了将 3D 打印的基于患者的体模扩展到软组织和骨结构的同时,保持器官几何形状、图像纹理和衰减曲线的准确性是可能的。