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. Methods: Pretreatment ¹⁸F-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. Results: 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 (P < 0.05, Wilcoxon test). After harmonization, none of the 9 feature distributions significantly differed between 2 departments (P > 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. Conclusion: 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.

几份报告表明，放射学特征受采集和重建参数的影响，从而妨碍了多中心研究。我们提出了一种方法，该方法通过消除中心效应，同时保留患者特有的效应，从而标准化从使用不同成像协议获得的PET图像测量的特征。方法：预处理¹⁸包括乳腺癌患者的F-FDG PET图像。在一个核医学部门（A部门），在飞行时间PET / CT扫描仪上扫描了63位患者，其中16处病变为三阴性（TN）。在另一个核医学科（B部门），有74名患者在不同品牌的扫描仪和不同的重建方案下进行了PET / CT检查，其中15个病变为TN。使用高斯滤波器对来自部门A的图像进行平滑处理，以模仿来自第三部门（部门AS）的数据。分割原发病变以获得目标病变体积（VOI），并在健康的肝组织中设置球形VOI。在所有VOI中计算了3辆SUV和6个纹理特征。最初针对基因组数据描述的协调方法用于根据观察到的特征值估算部门效应。结果：在健康的肝组织中，A部门和B部门之间9个特征中的4个特征以及A和AS部门之间9个特征中的6个特征的分布存在显着差异（P <0.05，Wilcoxon检验）。协调后，两个部门之间的9个特征分布均无显着差异（P > 0.1）。在病变中观察到相同的趋势，协调后各科室之间的特征分布发生了重新排列。当根据一个部门的数据确定临界值并将其应用于另一部门的数据时，统一后TN病变的识别将大大增强。结论：所提出的协调方法可以有效地消除纹理特征和SUV的多中心效应。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，并可以对放射模型或临界值进行外部验证，并应促进放射模型在临床实践中的使用。