Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands;
Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
J Nucl Med. 2022 Jun;63(6):919-924. doi: 10.2967/jnumed.121.262660. Epub 2021 Dec 21.
PET radiomics applied to oncology allow the measurement of intratumoral heterogeneity. This quantification can be affected by image protocols; hence, there is an increased interest in understanding how radiomic expression on PET images is affected by different imaging conditions. To address that interest, this study explored how radiomic features are affected by changes in F-FDG uptake time, image reconstruction, lesion delineation, and radiomic binning settings. Ten non-small cell lung cancer patients underwent F-FDG PET on 2 consecutive days. On each day, scans were obtained at 60 and 90 min after injection and reconstructed following EARL version 1 and with point-spread-function resolution modeling (PSF-EARL2). Lesions were delineated with an SUV threshold of 4.0, with 40% of SUV, and with a contrast-based isocontour. PET image intensity was discretized with both a fixed bin width (FBW) and a fixed bin number before the calculation of the radiomic features. Repeatability of features was measured with the intraclass correlation coefficient, and the change in feature value over time was calculated as a function of its repeatability. Features were then classified into use-case scenarios based on their repeatability and susceptibility to tracer uptake time. With PSF-EARL2 reconstruction, 40% of SUV lesion delineation, and FBW intensity discretization, most features (94%) were repeatable at both uptake times (intraclass correlation coefficient > 0.9), 35% being classified for dual-time-point use cases as being sensitive to changes in uptake time, 39% were classified for cross-sectional studies with an unclear dependency on time, 20% were classified for cross-sectional use while being robust to uptake time changes, and 6% were discarded for poor repeatability. EARL version 1 images had 1 fewer repeatable feature (neighborhood gray-level different matrix coarseness) than PSF-EARL2; the contrast-based delineation had the poorest repeatability of the delineation methods, with 45% of features being discarded; and fixed bin number resulted in lower repeatability than FBW (45% and 6% of features were discarded, respectively). Repeatability was maximized with PSF-EARL2 reconstruction, lesion delineation at 40% of SUV, and FBW intensity discretization. On the basis of their susceptibility to uptake time, radiomic features were classified into specific non-small cell lung cancer PET radiomics use cases.
PET 放射组学在肿瘤学中的应用可以测量肿瘤内异质性。这种定量可能会受到图像协议的影响；因此，人们越来越感兴趣于了解 PET 图像上的放射组学表达如何受到不同成像条件的影响。为了解决这一兴趣，本研究探讨了放射性特征如何受到 F-FDG 摄取时间、图像重建、病变勾画和放射组学分箱设置变化的影响。 10 名非小细胞肺癌患者在连续两天进行 F-FDG PET 检查。在每一天，分别在注射后 60 分钟和 90 分钟获得扫描，并按照 EARL 版本 1 和点扩散函数分辨率建模 (PSF-EARL2) 进行重建。病变采用 SUV 阈值为 4.0、SUV 的 40%和基于对比的等浓度曲线进行勾画。在计算放射组学特征之前，通过固定的 bin 宽度 (FBW) 和固定的 bin 数量对 PET 图像强度进行离散化。使用组内相关系数测量特征的重复性，根据其重复性计算特征值随时间的变化。然后根据其重复性和对示踪剂摄取时间的敏感性，将特征分类到用例场景中。 使用 PSF-EARL2 重建、40%的 SUV 病变勾画和 FBW 强度离散化，在两种摄取时间下，大多数特征（94%）均具有可重复性（组内相关系数>0.9），35%被归类为双时间点用例，对摄取时间变化敏感，39%被归类为横断面研究，与时间无明显依赖性，20%被归类为横断面用例，对摄取时间变化具有鲁棒性，6%因重复性差而被丢弃。与 PSF-EARL2 相比，EARL 版本 1 图像的可重复性特征少 1 个（邻域灰度差矩阵粗糙度）；基于对比的勾画方法的重复性最差，45%的特征被丢弃；与 FBW 相比，固定 bin 数导致的重复性更低（分别有 45%和 6%的特征被丢弃）。 使用 PSF-EARL2 重建、40%的 SUV 病变勾画和 FBW 强度离散化可最大程度地提高重复性。基于对摄取时间的敏感性，将放射组学特征分类为特定的非小细胞肺癌 PET 放射组学用例。
