Multiplexed tissue imaging facilitates the diagnosis and understanding of complex disease traits. However, the analysis of such digital images heavily relies on the experience of anatomical pathologists for the review, annotation and description of tissue features. In addition, the wider use of data from tissue atlases in basic and translational research and in classrooms would benefit from software that facilitates the easy visualization and sharing of the images and the results of their analyses. In this Perspective, we describe the ecosystem of software available for the analysis of tissue images and discuss the need for interactive online guides that help histopathologists make complex images comprehensible to non-specialists. We illustrate this idea via a software interface (Minerva), accessible via web browsers, that integrates multi-omic and tissue-atlas features. We argue that such interactive narrative guides can effectively disseminate digital histology data and aid their interpretation.
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Spatial omics technologies at multimodal and single cell/subcellular level
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This work was funded by NIH grants U54-CA225088 to P.K.S. and S.S., and by the Ludwig Center at Harvard. The Dana-Farber/Harvard Cancer Center is supported in part by NCI Cancer Center Support Grant P30-CA06516.
P.K.S. is a member of the SAB and BOD member of Applied Biomath, RareCyte Inc., and Glencoe Software, which distributes a commercial version of the OMERO database. P.K.S. is also a member of the NanoString SAB. In the past 5 years, the Sorger Laboratory has received research funding from Novartis and Merck. P.K.S. declares that none of these relationships have influenced the content of this manuscript. S.S. is a consultant for RareCyte Inc. The remaining authors declare no competing interests.
Peer review information Nature Biomedical Engineering thanks the anonymous reviewers for their contribution to the peer review of this work.
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Rashid, R., Chen, YA., Hoffer, J. et al. Narrative online guides for the interpretation of digital-pathology images and tissue-atlas data. Nat. Biomed. Eng 6, 515–526 (2022). https://doi.org/10.1038/s41551-021-00789-8
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