Histology-Based Radiomics for [<sup>18</sup>F]FDG PET Identifies Tissue Heterogeneity in Pancreatic Cancer.

Smeets, Esther M M; Trajkovic-Arsic, Marija; Geijs, Daan; Karakaya, Sinan; van Zanten, Monica; Brosens, Lodewijk A A; Feuerecker, Benedikt; Gotthardt, Martin et al. · J Nucl Med · 2024

Where this comes from

Abstract

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 [<sup>18</sup>F]FDG PET images and histologic expression patterns of a glycolytic marker, monocarboxylate transporter-4 (MCT4), in pancreatic cancer. <b>Methods:</b> A cohort of pancreatic ductal adenocarcinoma patients (<i>n</i> = 29) for whom both tumor cross sections and [<sup>18</sup>F]FDG PET/CT scans were available was used to develop an [<sup>18</sup>F]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 [<sup>18</sup>F]FDG PET scans, radiomics features that associate with the predefined MCT4 subgroups were identified. <b>Results:</b> 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 [<sup>18</sup>F]FDG PET signature, characterized by a higher SUV<sub>mean</sub> and SUV<sub>max</sub> and second-order radiomics features, correlating with local variation. This MCT4-based [<sup>18</sup>F]FDG PET signature of 7 radiomics features demonstrated prognostic value in an independent cohort of pancreatic cancer patients (<i>n</i> = 71) and identified patients with worse survival. <b>Conclusion:</b> 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 [<sup>18</sup>F]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.

Medical subject headings