An interview with Dr Konstantinos Dimopoulos
Dr Konstantinos Dimopoulos, a specialist in Clinical Biochemistry at Bispebjerg Hospital in Denmark, shares his insights on the implementation and benefits of FlowDiff, a novel flow cytometry-based method for differential counts, in this exclusive interview.
The need for a better approach
Traditional manual differentials are time-consuming, require highly trained staff, and are prone to inter-observer variability. ‘We needed a more accessible, accurate, and automated alternative’, explains Dr Dimopoulos. Flow cytometry emerged as the ideal solution due to its ability to classify abnormal leukocyte populations based on immunophenotype, its high precision (analysing 10,000-100,000 cells), and its alignment with the technology already used in automated cell counters.
Implementing FlowDiff at Bispebjerg Hospital
Bispebjerg Hospital sought to standardise and simplify the use of flow cytometry for differential counts. They developed FlowDiff, a novel method involving a single antibody panel, standardised instrument settings based on Euroflow Consortium recommendations, an optimised staining protocol, and predefined analysis gates for simplified interpretation. Using the Sysmex XF-1600, FlowDiff demonstrated high correlation with both Sysmex XN cell counters and manual differentials, along with 100% diagnostic sensitivity for acute leukemias and B-cell lymphomas.
Benefits and future plans
FlowDiff significantly reduces turnaround time and eliminates the need for manual morphology assessment, even in complex cases. Dr Dimopoulos envisions a fully automated solution with a Sysmex PS-10 sample preparation station and automated gating on the XF-1600, achieving a turnaround time of under an hour.
Impact and user feedback
The implementation of FlowDiff has been well-received by laboratory staff and physicians at Bispebjerg Hospital. It reduces workload, improves efficiency, and allows for faster diagnosis and treatment of critical conditions.
Looking ahead
Dr Dimopoulos believes FlowDiff represents a significant advancement in differential counts, offering a more accurate, efficient, and accessible solution compared to traditional methods and other emerging technologies. He sees a bright future for FlowDiff, with the potential for further automation and AI-driven analysis to optimise patient care.
