目的:这项研究确定了关键特征,以帮助构建用于影像组学协调的物理肝脏计算机断层扫描(CT)体模;特别是,高阶纹理度量。
方法:放射组学体模的CT扫描包括18个新颖的3D打印插件,尺寸不同,形状,和材料组合在64层CT扫描仪(华晨64,飞利浦医疗)上获得。这些图像是在120kV下采集的,250mAs,CTDIvol为16.36mGy,2mm切片厚度,和迭代降噪重建(iDose,飞利浦医疗保健,安多佛,MA).使用癌症成像现象组学工具包(CaPTk)进行影像组学分析,在18个插入物的3D感兴趣区域(ROI)的自动分割之后。将研究结果与拟人化肝脏体模获得的三个额外ROI进行比较,病人的肝脏CT扫描,和一个水幻影,在可比的成像设置。体模和组织之间的影像组学度量值的百分比差异用于评估生物学等效性,<10%用于声称等效性。
结果:来自体模的所有18个ROI的HU范围为-30至120,在临床观察到的肝脏HU范围内,显示我们的体模材料(T3-6B)代表了生物CT组织密度(肝脏),其中>50%的影像组学特征与肝脏组织的差异<10%。基于对邻域灰度音调差矩阵(NGTDM)度量的评估,很明显,与来自体模的ROI相比,水体模ROI示出极值。该结果可以进一步加强诸如水HU值的无结构量与肝脏中发现的组织HU值之间的差异。
结论:构建的影像组学体模的3-D打印图案覆盖了CT图像中可见的肝脏组织纹理。利用我们的结果,纹理指标可以有选择地协调,以建立临床相关和可靠的影像组学面板。
OBJECTIVE: This study identifies key characteristics to help build a physical liver computed tomography (CT) phantom for radiomics harmonization; particularly, the higher-order texture metrics.
METHODS: CT scans of a radiomics phantom comprising of 18 novel 3D printed inserts with varying size, shape, and material combinations were acquired on a 64-slice CT scanner (Brilliance 64, Philips Healthcare). The images were acquired at 120 kV, 250 mAs, CTDIvol of 16.36 mGy, 2 mm slice thickness, and iterative noise-reduction reconstruction (iDose, Philips Healthcare, Andover, MA). Radiomics analysis was performed using the Cancer Imaging Phenomics Toolkit (CaPTk), following automated segmentation of 3D regions of interest (ROI) of the 18 inserts. The findings were compared to three additional ROI obtained of an anthropomorphic liver phantom, a patient liver CT scan, and a water phantom, at comparable imaging settings. Percentage difference in radiomic metrics values between phantom and tissue was used to assess the biological equivalency and <10% was used to claim equivalent.
RESULTS: The HU for all 18 ROI from the phantom ranged from -30 to 120 which is within clinically observed HU range of the liver, showing that our phantom material (T3-6B) is representative of biological CT tissue densities (liver) with >50% radiomic features having <10% difference from liver tissue. Based on the assessment of the Neighborhood Gray Tone Difference Matrix (NGTDM) metrics it is evident that the water phantom ROI show extreme values compared to the ROIs from the phantom. This result may further reinforce the difference between a structureless quantity such as water HU values and tissue HU values found in liver.
CONCLUSIONS: The 3-D printed patterns of the constructed radiomics phantom cover a wide span of liver tissue textures seen in CT images. Using our results, texture metrics can be selectively harmonized to establish clinically relevant and reliable radiomics panels.