Spatial correlation between in vivo imaging and immunohistochemical biomarkers: A methodological study

In this study, we present a method that enables voxel-by-voxel comparison of in vivo imaging to immunohistochemistry (IHC) biomarkers. As a proof of concept, we investigated the spatial correlation between dynamic contrast enhanced (DCE-)CT parameters and IHC biomarkers Ki-67 (proliferation), HIF-1α (hypoxia), and CD45 (immune cells). 54 whole-mount tumor slices of 15 laryngeal and hypopharyngeal carcinomas were immunohistochemically stained and digitized. Heatmaps of biomarker positivity were created and registered to DCE-CT parameter maps. The adiabatic approximation to the tissue homogeneity model was used to fit the following DCE parameters: K^trans (transfer constant), V_e (extravascular and extracellular space), and V_i (intravascular space). Both IHC and DCE maps were downsampled to 4 × 4 × 3 mm[3] voxels. The mean values per tumor were used to calculate the between-subject correlations between parameters. For the within-subject (spatial) correlation, values of all voxels within a tumor were compared using the repeated measures correlation (r_rm). No between-subject correlations were found between IHC biomarkers and DCE parameters, whereas we found multiple significant within-subject correlations: V_e and Ki-67 (r_rm = -0.17, P < .001), V_e and HIF-1α (r_rm = -0.12, P < .001), K^trans and CD45 (r_rm = 0.13, P < .001), V_i and CD45 (r_rm = 0.16, P < .001), and V_i and Ki-67 (r_rm = 0.08, P = .003). The strongest correlation was found between IHC biomarkers Ki-67 and HIF-1α (r_rm = 0.35, P < .001). This study shows the technical feasibility of determining the 3 dimensional spatial correlation between histopathological biomarker heatmaps and in vivo imaging. It also shows that between-subject correlations do not reflect within-subject correlations of parameters.