Bogowicz M, Riesterer O, Bundschuh R A, Veit-Haibach P, Hüllner M, Studer G, Stieb S, Glatz S, Pruschy M, Guckenberger M, Tanadini-Lang S
Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Rämistrasse 100, 8091 Zürich, Switzerland.
Phys Med Biol. 2016 Dec 21;61(24):8736-8749. doi: 10.1088/1361-6560/61/24/8736. Epub 2016 Nov 28.
This study aimed to identify a set of stable radiomic parameters in CT perfusion (CTP) maps with respect to CTP calculation factors and image discretization, as an input for future prognostic models for local tumor response to chemo-radiotherapy. Pre-treatment CTP images of eleven patients with oropharyngeal carcinoma and eleven patients with non-small cell lung cancer (NSCLC) were analyzed. 315 radiomic parameters were studied per perfusion map (blood volume, blood flow and mean transit time). Radiomics robustness was investigated regarding the potentially standardizable (image discretization method, Hounsfield unit (HU) threshold, voxel size and temporal resolution) and non-standardizable (artery contouring and noise threshold) perfusion calculation factors using the intraclass correlation (ICC). To gain added value for our model radiomic parameters correlated with tumor volume, a well-known predictive factor for local tumor response to chemo-radiotherapy, were excluded from the analysis. The remaining stable radiomic parameters were grouped according to inter-parameter Spearman correlations and for each group the parameter with the highest ICC was included in the final set. The acceptance level was 0.9 and 0.7 for the ICC and correlation, respectively. The image discretization method using fixed number of bins or fixed intervals gave a similar number of stable radiomic parameters (around 40%). The potentially standardizable factors introduced more variability into radiomic parameters than the non-standardizable ones with 56-98% and 43-58% instability rates, respectively. The highest variability was observed for voxel size (instability rate >97% for both patient cohorts). Without standardization of CTP calculation factors none of the studied radiomic parameters were stable. After standardization with respect to non-standardizable factors ten radiomic parameters were stable for both patient cohorts after correction for inter-parameter correlations. Voxel size, image discretization, HU threshold and temporal resolution have to be standardized to build a reliable predictive model based on CTP radiomics analysis.
本研究旨在确定CT灌注（CTP）图中相对于CTP计算因素和图像离散化的一组稳定的放射组学参数，作为未来局部肿瘤对放化疗反应的预后模型的输入。分析了11例口咽癌患者和11例非小细胞肺癌（NSCLC）患者的治疗前CTP图像。每个灌注图（血容量、血流和平均通过时间）研究了315个放射组学参数。使用组内相关系数（ICC）研究了放射组学关于潜在可标准化（图像离散化方法、亨氏单位（HU）阈值、体素大小和时间分辨率）和不可标准化（动脉轮廓勾画和噪声阈值）灌注计算因素的稳健性。为了给我们的模型增加价值，与肿瘤体积相关的放射组学参数（局部肿瘤对放化疗反应的一个众所周知的预测因素）被排除在分析之外。其余稳定的放射组学参数根据参数间的斯皮尔曼相关性进行分组，并且对于每组，将具有最高ICC的参数纳入最终集合。ICC和相关性的接受水平分别为0.9和0.7。使用固定箱数或固定间隔的图像离散化方法产生的稳定放射组学参数数量相似（约40%）。潜在可标准化因素比不可标准化因素在放射组学参数中引入了更多变异性，其不稳定率分别为56 - 98%和43 - 58%。体素大小观察到的变异性最高（两个患者队列的不稳定率均>97%）。如果不标准化CTP计算因素，所研究的放射组学参数没有一个是稳定的。在针对不可标准化因素进行标准化后，在校正参数间相关性后，两个患者队列均有10个放射组学参数是稳定的。为了基于CTP放射组学分析建立可靠的预测模型，体素大小、图像离散化、HU阈值和时间分辨率必须进行标准化。
