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基于 PET 的多中心放射组学研究的后重建协调方法。

A Postreconstruction Harmonization Method for Multicenter Radiomic Studies in PET.

机构信息

Imagerie Moléculaire In Vivo, CEA-SHFJ, INSERM, CNRS, Université Paris-Sud, Université Paris-Saclay, Orsay, France

Imagerie Moléculaire In Vivo, CEA-SHFJ, INSERM, CNRS, Université Paris-Sud, Université Paris-Saclay, Orsay, France.

出版信息

J Nucl Med. 2018 Aug;59(8):1321-1328. doi: 10.2967/jnumed.117.199935. Epub 2018 Jan 4.

Abstract

Several reports have shown that radiomic features are affected by acquisition and reconstruction parameters, thus hampering multicenter studies. We propose a method that, by removing the center effect while preserving patient-specific effects, standardizes features measured from PET images obtained using different imaging protocols. Pretreatment F-FDG PET images of patients with breast cancer were included. In one nuclear medicine department (department A), 63 patients were scanned on a time-of-flight PET/CT scanner, and 16 lesions were triple-negative (TN). In another nuclear medicine department (department B), 74 patients underwent PET/CT on a different brand of scanner and a different reconstruction protocol, and 15 lesions were TN. The images from department A were smoothed using a gaussian filter to mimic data from a third department (department A-S). The primary lesion was segmented to obtain a lesion volume of interest (VOI), and a spheric VOI was set in healthy liver tissue. Three SUVs and 6 textural features were computed in all VOIs. A harmonization method initially described for genomic data was used to estimate the department effect based on the observed feature values. Feature distributions in each department were compared before and after harmonization. In healthy liver tissue, the distributions significantly differed for 4 of 9 features between departments A and B and for 6 of 9 between departments A and A-S ( < 0.05, Wilcoxon test). After harmonization, none of the 9 feature distributions significantly differed between 2 departments ( > 0.1). The same trend was observed in lesions, with a realignment of feature distributions between the departments after harmonization. Identification of TN lesions was largely enhanced after harmonization when the cutoffs were determined on data from one department and applied to data from the other department. The proposed harmonization method is efficient at removing the multicenter effect for textural features and SUVs. The method is easy to use, retains biologic variations not related to a center effect, and does not require any feature recalculation. Such harmonization allows for multicenter studies and for external validation of radiomic models or cutoffs and should facilitate the use of radiomic models in clinical practice.

摘要

已有多项报告表明,放射组学特征会受到采集和重建参数的影响,从而阻碍多中心研究。我们提出了一种方法,通过去除中心效应同时保留患者特异性效应,使使用不同成像方案获得的 PET 图像的特征标准化。

纳入了乳腺癌患者的预处理 F-FDG PET 图像。在一个核医学部门(A 部门),对 63 名患者在飞行时间 PET/CT 扫描仪上进行了扫描,其中 16 个病灶为三阴性(TN)。在另一个核医学部门(B 部门),对 74 名患者在另一台扫描仪和不同重建方案上进行了 PET/CT 检查,其中 15 个病灶为 TN。A 部门的图像使用高斯滤波器进行平滑处理,以模拟第三个部门(A-S)的数据。对主要病变进行分割以获得病变感兴趣体积(VOI),并在健康肝组织中设置球形 VOI。在所有 VOI 中计算了 3 个 SUV 和 6 个纹理特征。最初用于基因组数据的协调方法用于根据观察到的特征值来估计部门效应。在协调前后比较了每个部门的特征分布。

在健康肝组织中,A 和 B 部门之间有 4 个特征的分布和 A 和 A-S 部门之间有 6 个特征的分布在统计学上存在显著差异(<0.05,Wilcoxon 检验)。协调后,两个部门之间的 9 个特征分布没有一个在统计学上存在显著差异(>0.1)。在病变中也观察到了相同的趋势,协调后特征分布在各部门之间得到了重新调整。当在一个部门的数据中确定截断值并将其应用于另一个部门的数据时,TN 病变的识别在协调后得到了极大的增强。

所提出的协调方法在去除纹理特征和 SUV 的多中心效应方面非常有效。该方法易于使用,保留了与中心效应无关的生物学变异,并且不需要任何特征重新计算。这种协调允许进行多中心研究,并对放射组学模型或截断值进行外部验证,应该有助于放射组学模型在临床实践中的应用。

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