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Artificial intelligence in bone marrow cytomorphology: Morphogo and Scopio


Authors: D. Starostka 1;  R. Doležílek 2;  K. Chasáková 1;  P. Miczková 1;  P. Kováč 2
Authors‘ workplace: Laboratoř hematoonkologie a klinické bio chemie, Nemocnice Havířov, p. o. 1;  Oddělení patologie, Nemocnice Havířov, p. o. 2
Published in: Transfuze Hematol. dnes,30, 2024, No. 1, p. 49-52.
Category: Letters to Editor
doi: https://doi.org/10.48095/cctahd2024prolekare.cz6


Sources

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2. Zini G, Barbagallo O, Scavone F, Béné MC. Digital morphology in hematology diagnosis and education: The experience of the European LeukemiaNet WP10. Int J Lab Hematol. 2022; 44 (Suppl 1): 37–44. doi: 10.1111/ijlh.13908.

3. Xing Y, Liu X, Dai J, et al. Artificial intelligence of digital morphology analyzers improves the efficiency of manual leukocyte differentiation of peripheral blood. BMC Med Inform Decis Mak. 2023; 23 (1): 50. doi: 10.1186/s12911-023-02153-z.

4. Kratz A, Lee SH, Zini G, Riedl JA, Hur M, Machin S. International Council for Standardization in Haematology. Digital morphology analyzers in hematology: ICSH review and recommendations. Int J Lab Hematol. 2019; 41 (4): 437–447. doi: 10.1111/ijlh.13042.

5. Jin H, Fu X, Cao X, et al. Developing and preliminary validating an automatic cell classification system for bone marrow smears: a pilot study. J Med Syst. 2020; 44 (10): 184. doi: 10.1007/s10916-020-01654-y.

6. Walter W, Haferlach C, Nadarajah N, et al. How artificial intelligence might disrupt diagnostics in hematology in the near future. Oncogene. 2021; 40 (25): 4271–4280. doi: 10.1038/s41388-021-0 1861-y.

7. Lin E, Fuda F, Luu HS, et al. Digital pathology and artificial intelligence as the next chapter in diagnostic hematopathology. Semin Diagn Pathol. 2023; 40 (2): 88–94. doi: 10.1053/j.semdp.2023.02.001.

8. Starostka D, Kriegova E, Kudelka M, et al. Quantitative assessment of informative immunophenotypic markers increases the diagnostic value of immunophenotyping in mature CD5-positive B-cell neoplasms. Cytometry B Clin Cytom. 2018; 94 (4): 576–587. doi: 10.1002/cyto.b. 21607.

9. Bazinet A, Wang A, Li X, et al. Automated quantification of measurable residual disease in chronic lymphocytic leukemia using an artificial intelligence-assisted workflow. Cytometry B Clin Cytom. 2023. Published on-line: February 23. doi: 10.1002/cyto.b.22116.

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11. Lv Z, Cao X, Jin X, Xu S, Deng H. High-accuracy morphological identification of bone marrow cells using deep learning-based Morphogo system. Sci Rep. 2023; 13 (1): 13364. doi: 10.1038/s41598-023-40424-x.

12. Wang X, Wang Y, Qi C, et al. The application of Morphogo in the detection of megakaryocytes from bone marrow digital images with convolutional neural networks. Technol Cancer Res Treat. 2023; 22: 15330338221150069. doi: 10.1177/15330338221150069.

13. Chen P, Chen Xu R, Chen N, et al. Detection of metastatic tumor cells in the bone marrow aspirate smears by artificial intelligence (AI) -based Morphogo system. Front Oncol. 2021; 11: 742395. doi: 10.3389/fonc.2021.742395.

14. Tang G, Fu X, Wang Z, Chen M. A Machine learning tool using digital microscopy (Morphogo) for the identification of abnormal lymphocytes in the bone marrow. Acta Cytol. 2021; 65 (4): 354–357. doi: 10.1159/000518382.

15. Katz B-Z, Feldman MD, Tessema M, et al. Evaluation of Scopio Labs X100 Full Field PBS: The first high-resolution full field viewing of peripheral blood specimens combined with artificial intelligence-based morphological analysis. Int J Lab Hematol. 2021; 43 (6): 1408–1416. doi: 10.1111/ijlh.13681.

PODÍL AUTORŮ NA PŘÍPRAVĚ RUKOPISU

DS, RD – příprava rukopisu
KCH, PM – revize rukopisu
PK – příprava obrazové dokumentace

ČESTNÉ PROHLÁŠENÍ

Autoři práce prohlašují, že v souvislosti s tématem, vznikem a publikací tohoto článku nejsou ve střetu zájmů a vznik ani publikace článku nebyly podpořeny žádnou farmaceutickou firmou.

Do redakce doručeno dne: 27. 9. 2023.
Přijato po recenzi dne: 24. 10. 2023.

MUDr. David Starostka, Ph.D.
Laboratoř hematoonkologie a klinické biochemie
Nemocnice s poliklinikou Havířov, p. o.
Dělnická 1132/24
736 01 Havířov
e-mail: david.starostka@nemhav.cz

Labels
Haematology Internal medicine Clinical oncology

Article was published in

Transfusion and Haematology Today

Issue 1

2024 Issue 1

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