Sam Border’s new perspective paper, “Computational Pathology Fusing Spatial Technologies,” in the Clinical Journal of the American Society of Nephrology (CJASN) showcases the potential of spatial tissue imaging to transform histopathologic interpretation by generating large datasets and visual clues that may augment existing gold-standard histopathologic interpretation.
New advancements in spatial tissue imaging allow for the generation of large datasets that anchor transcriptomic and proteomic expression on histology with high granularity. These highly multiplexed cellular and molecular data provide researchers with an entirely new way to interpret tissue morphology and generate visual clues that may augment existing gold-standard histopathologic interpretation. To best interpret these multimodal data, artificial intelligence methods are indispensable to fuse bright-field histology with diverse spatial -omics methods, including spatial transcriptomics; multiplex fluorescence imaging, including codetection by indexing (CODEX); imaging mass spectrometry; miFISH; and imaging mass cytometry.
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