Radiomics features can reveal hidden patterns in a tumor but usually lack an underlying biologic rationale. In this work, we aimed to investigate whether there is a correlation between radiomics features extracted from [¹⁸F]FDG PET images and histologic expression patterns of a glycolytic marker, monocarboxylate transporter-4 (MCT4), in pancreatic cancer. Methods: A cohort of pancreatic ductal adenocarcinoma patients (n = 29) for whom both tumor cross sections and [¹⁸F]FDG PET/CT scans were available was used to develop an [¹⁸F]FDG PET radiomics signature. By using immunohistochemistry for MCT4, we computed density maps of MCT4 expression and extracted pathomics features. Cluster analysis identified 2 subgroups with distinct MCT4 expression patterns. From corresponding [¹⁸F]FDG PET scans, radiomics features that associate with the predefined MCT4 subgroups were identified. Results: Complex heat map visualization showed that the MCT4-high/heterogeneous subgroup was correlating with a higher MCT4 expression level and local variation. This pattern linked to a specific [¹⁸F]FDG PET signature, characterized by a higher SUV_mean and SUV_max and second-order radiomics features, correlating with local variation. This MCT4-based [¹⁸F]FDG PET signature of 7 radiomics features demonstrated prognostic value in an independent cohort of pancreatic cancer patients (n = 71) and identified patients with worse survival. Conclusion: Our cross-modal pipeline allows the development of PET scan signatures based on immunohistochemical analysis of markers of a particular biologic feature, here demonstrated on pancreatic cancer using intratumoral MCT4 expression levels to select [¹⁸F]FDG PET radiomics features. This study demonstrated the potential of radiomics scores to noninvasively capture intratumoral marker heterogeneity and identify a subset of pancreatic ductal adenocarcinoma patients with a poor prognosis.

放射组学特征可以揭示肿瘤中隐藏的模式，但通常缺乏潜在的生物学原理。在这项工作中，我们旨在研究胰腺癌中从 [ ¹⁸ F]FDG PET 图像提取的放射组学特征与糖酵解标记物单羧酸转运蛋白 4 (MCT4) 的组织学表达模式之间是否存在相关性。方法：一组胰腺导管腺癌患者 ( n = 29) 具有肿瘤横截面和 [ ¹⁸ F]FDG PET/CT 扫描，用于开发 [ ¹⁸ F]FDG PET 放射组学特征。通过使用 MCT4 的免疫组织化学，我们计算了 MCT4 表达的密度图并提取了病理学特征。聚类分析确定了 2 个具有不同 MCT4 表达模式的亚组。从相应的 [ ¹⁸ F]FDG PET 扫描中，识别出与预定义的 MCT4 亚组相关的放射组学特征。结果：复杂的热图可视化显示 MCT4 高/异质亚组与较高的 MCT4 表达水平和局部变异相关。该模式与特定的 [ ¹⁸ F]FDG PET 特征相关，其特征是较高的 SUV_平均值和 SUV_最大值以及二阶放射组学特征，与局部变异相关。这种基于 MCT4 的 7 个放射组学特征的 [ ¹⁸ F]FDG PET 特征在独立的胰腺癌患者队列 ( n = 71) 中证明了预后价值，并确定了生存率较差的患者。 结论：我们的跨模式流程允许基于特定生物学特征标记物的免疫组织化学分析来开发 PET 扫描特征，此处在胰腺癌上使用肿瘤内 MCT4 表达水平来选择 [ ¹⁸ F]FDG PET 放射组学特征进行了演示。这项研究证明了放射组学评分在非侵入性捕获肿瘤内标志物异质性和识别预后不良的胰腺导管腺癌患者子集方面的潜力。