Deep cytomorphology identifies erythroid skewing and monocytic morphology to predict TKI sensitivity in CML patients

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 <i>BCR::ABL1</i> halving time (AUROC 0.61). Notably, poor-risk patients treated with second-generation TKIs achieved outcomes similar to favorable-risk patients on imatinib. These results underline the overlooked prognostic value of BM cytomorphology to refine risk stratification and support more personalized frontline therapy in CML.

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Publication Details

Journal
HemaSphere
Published
2026-02-01
DOI
https://doi.org/10.1002/hem3.70319
Primary Topic
Chronic Myeloid Leukemia Treatments
Type
article
Field-Weighted Citation Impact
0.00
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article

Deep cytomorphology identifies erythroid skewing and monocytic morphology to predict TKI sensitivity in CML patients

Signe Danielsson, Stina Söderlund, Sanna Siitonen, Mikko Purhonen et al.
HemaSphere
Chronic Myeloid Leukemia Treatments
article

Deep cytomorphology identifies erythroid skewing and monocytic morphology to predict TKI sensitivity in CML patients

Signe Danielsson, Stina Söderlund, Sanna Siitonen, Mikko Purhonen, Perttu Koskenvesa, Naranie Shanmuganathan, Kevin Hung, Anna Lempiäinen, Takashi Kumagai, Johanna Heikkinen, Satu Mustjoki, Mikael Tatun, Oda Tafjord, Katariina Luukkainen, Oscar Brück, Shinya Kimura, Henrik Hjorth‐Hansen, Ulla Olsson‐Strömberg, Anni Dohlen, Coral Bryce, Shady Adnan‐Awad, David M. Ross, Lotta Joutsi‐Korhonen, Henri Sundquist
article en

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 <i>BCR::ABL1</i> halving time (AUROC 0.61). Notably, poor-risk patients treated with second-generation TKIs achieved outcomes similar to favorable-risk patients on imatinib. These results underline the overlooked prognostic value of BM cytomorphology to refine risk stratification and support more personalized frontline therapy in CML.

HemaSphereVol. 10(2)
Toho University (JP), Royal Adelaide Hospital (AU), University of Helsinki (FI), Uppsala University Hospital (SE), Flinders University (AU), Saga University (JP), Norwegian University of Science and Technology (NO), Örebro University (SE), Helsinki University Hospital (FI), Flinders Medical Centre (AU), Toho University Omori Medical Center (JP), St Olav's University Hospital (NO), MRC Weatherall Institute of Molecular Medicine (GB), MRC Human Immunology Unit (GB), South Australian Health and Medical Research Institute (AU), Oxford BioMedica (United Kingdom) (GB), Cancer Society of Finland (FI), National Heart Institute (EG)
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Openalex Percentile: Top 56%
Chronic Myeloid Leukemia Treatments
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