The dynamic and complex challenges faced by the medical diagnostics laboratories have played a pivotal role in evolution of clinical hematology and blood cell counting methods. The modern-day hematology analyzers are well equipped to collect more information about the cell characteristics, and subsequently detecting the diseases more accurately. The advanced systems can classify multiple cell types, including five mature WBC types, and additionally the immature granulocytes (IG). Automated and accurate IG count has significantly reduced the manual review rates; the result including the presence and concentration of IGs is made available within a minute and can be reported along with the routine CBC and differential counts.
The modern hematology cell-counter systems can very well detect atypical parameters, which are of utmost importance in diagnosing or monitoring the progression of a blood disorder under investigation like NRBCs, reticulated RBCs/PLTs, fragmented RBCs, reticulated hemoglobin equivalent (RET-HE), immature reticulocyte fractions (IRFs), and immature platelet fractions (IRFs), neutrophil reactivity and granularity intensity (NEUT-RI and GI). Furthermore, these hematology analyzers can also detect atypical results, and can improve measurable parameters, such as red cell distribution width (RDW), platelet distribution, etc.
Data fusion is a diverse collection of techniques, which are used to combine multiple sensor measurements and/or information from related sources to improve accuracy, and draw more specific conclusions than would have been possible by using a single source. The data fusion technology has helped to recognize the presence of giant platelets using the information generated from PLT and NRBC modules. This clue can be used by the WBC algorithm to correlate with any interference detected, leading to the automated WBC count correction, if needed. Hence, it has established the bridge between the various measurement channels of the analyzer, leading to a highly dependable result and high-quality data interpretation.
Automation of hematology diagnostic process has reduced the turnaround time, and accelerated the overall treatment regimen with improved accuracy and elimination of human errors. It is evident that automation will shape the ultra-modern laboratories of the future and boost the growth of hematology testing market in the forthcoming years. To summarize, the technological advances integrated in modern hematology analyzers are providing the clinicians a plethora of information that was not available earlier with routine CBC differential counts. We all are advancing to such a future where the hematology cell counters have ability to identify and monitor clinically significant cellular transformations, and evolve as a powerful tool for management of any medical condition which impacts blood cells. It is evident and well accepted that the advanced and efficient systems are adding indispensable clinical value to modern laboratory practices. However, the value delivered by these systems demands a fair economical support for further advancements and sustainability!