Robust segmentation-free stain quality concordance metrics in the SpaceIQ™ multi-omic analysis platform

Background: Spatial imaging outputs continue to grow in scale and complexity. While brightfield IHC and H&E remain the qualitative gold standard for antibody-based assessment, mIF offers quantitative protein measurement on a single slide. However, challenges such as non-specific binding, imaging artifacts, and variability across sites and operators limit confidence in mIF reproducibility. A quantitative, robust method is needed to assess concordance between IHC and mIF stains. Methods: Using a pan-cancer dataset with a 4-plex mIF panel and matched IHC sections from consecutive slides, we first co-registered images into a shared coordinate space with Valis, applying global rigid and non-rigid transformations from feature matches. IHC stain channels were isolated via stain-matrix-based deconvolution. A tissue mask was generated on the mIF image using Otsu thresholding and morphology operations and then projected onto the IHC slide.Tissue was divided into tiles whose size accounted for section-to-section distance, registration error, and biological variability. Within each tile, random windows were sampled to perform two tests: (1) identify whether the tile contains high stain intensity and (2) determine whether the corresponding IHC and mIF tiles exhibit statistically concordant staining. This approach yields both a DICE score for high-stain region overlap and a stain concordance metric capturing agreement across high- and low-stain regions. Tile-level results and heatmaps are visualized in SpaceIQ™. Results: Concordance between mIF and IHC varied substantially across markers, with CD8 showing the highest and FoxP3 the lowest agreement, a trend consistent across samples. Concordance heatmaps also revealed strong spatial effects, with some tissue regions highly concordant and others clearly discordant. Expert visual review matched these quantitative findings. Conclusions: This segmentation-free framework identifies substantial marker- and region-specific variation in concordance between mIF and IHC staining. Because the method is marker-agnostic and compensates for registration error and inter-section biological differences, it provides a generalized, quantitative approach for evaluating agreement between paired mIF and IHC slides across platforms.