ArticleHemaSphere2026
Deep cytomorphology identifies erythroid skewing and monocytic morphology to predict TKI sensitivity in CML patients.
Article in HemaSphere, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
24 authors.
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Abstract
The cellular composition of the chronic myeloid leukemia (CML) bone marrow (BM) beyond granulocyte enrichment remains poorly understood. We analyzed 1548 routinely stained BM aspirate slides from 598 patients across seven sites using deep learning-based image analysis to identify cytomorphological markers predictive of major molecular response. Erythroid precursor enrichment, monocyte nuclear lobulation, and low peripheral leukocyte count were associated with improved tyrosine kinase inhibitor (TKI) response. These features were validated both visually and computationally in two independent cohorts. We developed a Morphoclinical model integrating these image-derived and clinical variables, outperforming (area under the receiver-operating curve [AUROC] 0.76) the clinically used EUTOS long-term survival score (AUROC 0.53) and
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Registered trials
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