{"doi":"10.1093/cvr/cvaf222","title":"Mapping myocarditis in three dimensions","abstract":"This editorial refers to ‘Whole-heart 3D reconstruction of mouse CVB3 myocarditis reveals spatial and transcriptomic heterogeneity of immune foci’ by A. Daoud et al., https://doi.org/10.1093/cvr/cvaf209. Myocarditis remains one of the most enigmatic inflammatory diseases of the heart.1 Despite decades of research, clinicians continue to face major challenges in its diagnosis, risk stratification, and treatment.1–5 The clinical spectrum ranges from fulminant presentations with high early mortality to insidious progression towards dilated cardiomyopathy (DCM).1,4 Myocarditis continues to be one of the most common causes of sudden cardiac death.6 While cardiac imaging has advanced our ability to detect myocardial inflammation, and endomyocardial biopsy (EMB) remains the diagnostic gold standard, both approaches suffer from critical limitations (Figure 1).3 EMB in particular is hampered by a variable diagnostic yield, in part due to the focal distribution of inflammatory lesions.3 Current tools available to assess myocarditis. Of the many tools that are currently available to assess myocardial inflammation, the novel method presented here combines immunohistochemistry (IHC) with artificial intelligence (AI)-directed spatial transcriptomics to provide three-dimensional data about the molecular drivers of myocarditis with the potential to transform our understanding of disease. Created in BioRender. Fairweather, D. (2025) https://BioRender.com/0d8ft6o. Against this backdrop, the work of Daoud and colleagues, published in this issue of Cardiovascular Research, represents an important methodological and conceptual advance.7 The authors apply a novel AI-assisted workflow for histological reconstruction—CODA—to generate whole-heart three-dimensional reconstructions of acute Coxsackievirus B3 (CVB3) myocarditis in mice, integrating immunohistochemistry and spatial transcriptomics. This method offers several advantages over traditional mapping using single-cell transcriptomics8 by providing detailed spatial relationships. This study not only establishes a new standard for whole-organ spatial immunology but also yields insights that challenge long-standing assumptions about the nature of myocarditis lesions. Daoud et al. demonstrate that acute viral myocarditis does not consist of diffuse, uniformly distributed immune infiltrates. Instead, the disease is dominated by a relatively small number of large, elongated, and highly branched inflammatory foci. Importantly, these foci preferentially occupy the free left ventricular wall, a region rarely sampled by routine EMB, which typically targets the interventricular septum for safety reasons. This anatomic distribution provides a compelling explanation for the historically poor sensitivity of EMB in suspected myocarditis. Equally striking is the discovery of spatial immunological heterogeneity within and between foci. Using CD3 and CD64 staining in combination with spatial transcriptomics, the investigators reveal distinct immune niches: T cell–rich hotspots localizing predominantly to anterior regions of the heart, and macrophage-rich areas in posterior regions. At higher resolution, T cell hotspots are shown to coincide with zones of high vascularization, suggesting that vascular access may shape immune cell recruitment and retention. Moreover, transcriptomic analyses reveal that anterior, T cell–rich foci upregulate chemokines such as Cxcl10, Ccl7, and Ccl8, along with type I collagen, while surrounding homogeneous foci preferentially express adhesion and retention molecules including Cd93, Adgre5, and S1pr4. These findings are not only internally validated by flow cytometry and quantitative PCR across a larger cohort of mice but also supported by human data. Explanted hearts from patients with inflammatory DCM exhibited a similar anterior–posterior gradient in T cell vs. macrophage content, underscoring the translational relevance of the mouse model. Several implications arise from this stu","journal":"Cardiovascular Research","year":2025,"id":586791,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9513,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":248042,"name":"DeLisa Fairweather","orcid":"0000-0003-3093-1810","position":1,"is_corresponding":false},{"id":88821,"name":"Bettina Heidecker","orcid":"0000-0002-3811-7920","position":0,"is_corresponding":true}],"reference_count":11,"raw_metadata":null,"created_at":"2026-07-19T02:59:32.191237Z","pmid":"41424378","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}