ReviewNature biomedical engineering2022
Narrative online guides for the interpretation of digital-pathology images and tissue-atlas data.
Review in Nature biomedical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- 3D multi-omics tumour atlases: from technology to biology and clinical translation.Nature reviews. Cancer · 2026Review
- Clinical responses to trastuzumab deruxtecan in molecularly defined ependymoma.NPJ precision oncology · 2026Article
- Development and validation of radiopathomics models for predicting molecular subtypes and WHO grades in adult-type diffuse gliomas: a multicenter study.Journal of translational medicine · 2025Article
- Spatial multiomics of acute myocardial infarction reveals immune cell infiltration through the endocardium.Nature cardiovascular research · 2025Article
- Article
- Advancing open-source visual analytics in digital pathology: A systematic review of tools, trends, and clinical applications.Journal of pathology informatics · 2025Review
- TissueViewer: a web-based multiplexed image viewer.Bioinformatics (Oxford, England) · 2025Article
- psudo: Exploring Multi-Channel Biomedical Image Data with Spatially and Perceptually Optimized Pseudocoloring.Computer graphics forum : journal of the European Association for Computer Graphics · 2024Article
- Residency Octree: A Hybrid Approach for Scalable Web-Based Multi-Volume Rendering.IEEE transactions on visualization and computer graphics · 2024Article
- An AI based, open access screening tool for early diagnosis of Burkitt lymphoma.Frontiers in medicine · 2024Article
- Lymphocyte networks are dynamic cellular communities in the immunoregulatory landscape of lung adenocarcinoma.Cancer cell · 2023Article
- Article
- Spatial omics technologies at multimodal and single cell/subcellular level.Genome biology · 2022Review
- HistoML, a markup language for representation and exchange of histopathological features in pathology images.Scientific data · 2022Article
- Integrated Analytical System for Clinical Single-Cell Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
- The Spatial Landscape of Progression and Immunoediting in Primary Melanoma at Single-Cell Resolution.Cancer discovery · 2022Article
- Temporal and spatial topography of cell proliferation in cancer.Nature cell biology · 2022Article
- Minerva: a light-weight, narrative image browser for multiplexed tissue images.Journal of open source software · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
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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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.