Flow Cytometry Applications in Hematologic Malignancies: Current Advances and Clinical Implications for Laboratory Medicine
DOI:
https://doi.org/10.63332/joph.v5i1.3145Keywords:
flow cytometry, hematologic malignancies, minimal residual disease, immunophenotyping, leukemia, lymphoma, multiparameter analysis, spectral flow cytometry, clinical laboratory, quality assuranceAbstract
Flow cytometry has revolutionized the diagnosis, classification, and monitoring of hematologic malignancies, emerging as an indispensable tool in modern clinical laboratories. This comprehensive review examines the current applications of multiparameter flow cytometry (MFC) in the diagnosis and management of leukemias, lymphomas, and plasma cell disorders. The study explores the technical principles underlying flow cytometric analysis, including antibody panel design, gating strategies, and data interpretation protocols. Recent technological advances, including spectral flow cytometry and artificial intelligence integration, have expanded diagnostic capabilities and improved analytical precision. Minimal residual disease (MRD) monitoring represents a critical application, providing prognostic information and treatment guidance across various hematologic malignancies. Multiparameter flow cytometry (MPF) is an essential component of the diagnostic workup of hematologic malignancies, with standardized protocols ensuring reproducible results across laboratories. Quality assurance measures, including appropriate controls, standardization protocols, and proficiency testing, are essential for maintaining analytical excellence. This review addresses current challenges in flow cytometric analysis, including specimen handling, data interpretation complexity, and the need for specialized expertise. Emerging applications in germline predisposition screening and immunophenotypic monitoring of novel therapeutic interventions demonstrate the evolving role of flow cytometry in hematologic oncology. The integration of flow cytometry with complementary techniques such as cytogenetics and molecular diagnostics enhances diagnostic accuracy and provides comprehensive patient assessment. Future directions include expanded spectral capabilities, enhanced automation, and improved artificial intelligence applications for result interpretation and quality control.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
CC Attribution-NonCommercial-NoDerivatives 4.0
The works in this journal is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
