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This study sought to quantitatively assess cardiomyocyte morphometry and its relationship with clinical phenotypes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>We developed MyoSAM, a deep learning framework for quantitative morphometric characterization of H&amp;E-stained whole-slide images (N = 334 patients). Cardiomyocyte size was quantified using the myocyte maximum inscribed circle (MMIC) radius, along with measures of nuclear size and perinuclear-halo size, interstitial and macrodomain stromal fractions. Independent associations between these histological features and clinical variables were assessed using multivariable regression and patient-level linear mixed-effects models to account for clustering of cellular measurements within individuals. MMIC radius was the strongest histological predictor of left ventricular mass index (LVMI; P &amp;lt; 0.001) and was positively correlated with clinical HF (Pearson\u2019s r = 0.77, P &amp;lt; 0.001). In severe coronary artery disease, the association between LVMI and MMIC radius was significantly attenuated (P = 0.001), indicating that myocyte hypertrophy was diminished despite increased mass; instead, remodelling shifted towards greater interstitial stromal expansion (P = 0.025). Males exhibited larger MMIC radii than females (fold-changes 1.08, P = 0.003). Distinct aetiology-specific signatures emerged: anthracycline-treated hearts showed large MMIC radii and perinuclear halos with minimal stroma, while non-ischaemic cardiomyopathy exhibited the greatest nuclear enlargement and stromal macrodomain expansion.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Computational pathology enables high-resolution characterization of myocardial remodelling, revealing distinct microstructural phenotypes across sex, coronary disease burden, and HF aetiology that may improve cardiac phenotyping and risk stratification.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/cvr\/cvag166","type":"journal-article","created":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T11:14:27Z","timestamp":1785323667000},"page":"1964-1977","source":"Crossref","is-referenced-by-count":0,"title":["Differential cardiac remodelling: patterns of cardiomyocyte morphometry in multiple patient conditions"],"prefix":"10.1093","volume":"122","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7323-0339","authenticated-orcid":false,"given":"Sandeep","family":"Manandhar","sequence":"first","affiliation":[{"name":"Wallace H. 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