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Advancements in bone marrow biopsy: the role of omics and artificial intelligence in hematologic diagnostics

Frontiers in MedicineResearch Authors: Maryam Alwahaibi, Nasar AlwahaibiAIIM Authors: Nischay Pothineni, Ahmad IslambouliApproved by President Reda RiffiPublication Date: 3/23/2026

Comprehensive Summary

The current study reviews changes that have taken place in the diagnostic field of bone marrow biopsies due to the introduction of new technologies including multi-omics and AI. The traditional approaches include the evaluation of morphology, immunohistochemistry, flow cytometry, and cytogenetics; however, such methods suffer from limitations related to subjectivity and inability to fully characterize disease biology. According to the paper, multi-omic testing, including genomics, transcriptomics, epigenomics, proteomics, metabolomics, lipidomics, and microbiomics provides a possibility of identifying molecular profiles, clonal mutations, pathway alterations, and the interaction between the cell and its microenvironment that would not be otherwise possible. Similarly, AI algorithms have shown a promising potential for the analysis of the biopsy using digital pathology, such as the quantification of fibrosis, classification of hematopoietic cells, detection of dysplasia, morphological changes related to mutations, and more accurate and reproducible histological and cytomorphological reviews. Overall, multi-omics and AI can turn bone marrow biopsy into a powerful hematological precision medicine tool. Despite the potential advantages of multi-omics and AI algorithms in hematological diagnostics, there are a number of challenges.

Outcomes and Implications

The implications of these advances are enormous, especially for hematological cancers like leukemia, lymphoma, myelodysplastic syndrome, myeloproliferative disorders, and plasma cell diseases. Multi-omic analyses can enhance risk stratification, monitor residual cancer cells, find new treatment targets, and even resolve uncertain cases by conventional pathology. AI can also cut down the time needed for diagnosis, make up for any lack of hematopathologists, and bring about consistency in interpretation among different institutions. This might have profound effects in less privileged countries where specialists are hard to find. With more research, it may even be possible in the coming years to tailor treatment regimens depending on the morphologic and molecular pattern of patients instead of relying solely on classifications. It may come to pass that bone marrow examination will not just remain a diagnostic method but a prognostic one as well that would predict disease progression, response to therapy, and guide treatment decisions.

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