Currently, the leukocyte formula, or differential leukocyte count (RDL), together with the measurement of the other basic hematological parameters (cell and hemoglobin concentration, hematocrit value and mean corpuscular volume, among others) is part of the so-called blood test or hemogram (Figure 1).
However, the concept of hemogram has evolved in parallel with the progress of diagnostic technology in hematology up to the current one. Thus, the concepts of hemogram and blood differential have been intertwined during a historical process that begins with the development of the two basic pillars of hematology; the microscope and staining methods, and ends with the advent of automation.
The first steps of the leukocyte formula
The true beginning of this process dates back to 1674 when Anton van Leeuwenhoek observed blood cells using a rudimentary microscope (Figure 2), which was perfected a century later by Wiliam Hewson (Figure 3).
Morphological analysis of blood cells was not possible until 1891, when Paul Ehrlich, a bacteriologist specializing in the use of dyes for cell staining, first described the existence of two major subpopulations of leukocytes: granulocytes and mononucleates (1). This marked the beginning of what we know today as the leukocyte formula, and at the same time marked the birth of hematology as a science dedicated to the study and diagnosis of blood diseases.
From this point on, the improvement of blood cell staining procedures was very rapid and in a very short time methods of universal use were obtained. For example, the May Grunwald-Giemsa (MGG) stain, the gold standard for the morphological study of blood cells (2).
A research carried out by different scientists
In addition to Ehrich, in the development of this first morphological stage of hematology, a very large number of distinguished scientists have contributed, including: Hayem, Pappenheim, Arneth, Schilling, Naegeli, Custer, Maximov, Ferrata, Turk, Bloom, Doan, Diggs, Mas y Magro, Forteza Bover, Guasch and Vives Mañé. Among them, J. Arneth in 1904, after studying a large number of patients with infectious processes, established a classification of neutrophilic granulocytes in subgroups according to the number of lobulations or nuclear segments which he called hemogram (3).
In Arneth’s hemogram, granulocytes with fewer lobulations or without lobulations were located on the left, and those with more lobulations on the right. In 1933, the pathologist J. Schilling simplified Arneth’s hemogram by denominating bands to juvenile neutrophils without nuclear segmentation and to their increased left deviation. He also established a procedure for individualized counting of the different leukocyte subpopulations called Schilling’s hemogram (Figure 4).
The impact of automation on the hemogram
Until the advent of automation in the 1970s, the Schilling CBC was synonymous with the leukocyte formula and for many years, it has been the only reliable procedure. Both for the diagnosis of left shift, present in many pathological processes in human clinical practice, and for the diagnosis of the right shift characteristic of pernicious anemia due to vitamin B12 deficiency (5).
With the emergence of automation in hematology, the concept of hemogram and leukocyte formula have been markedly influenced. The same applies to conceptual, structural and management changes in the hematology laboratory.
In fact, at the beginning of automation, in the 1970s, the independent performance of the CBC and the blood differential caused some terminological confusion. Especially in those professionals who remembered that the CBC was synonymous with the blood differential. For hematologists, however, who had always considered the morphological examination of the smear as the only procedure for performing the blood differential, it seemed inconceivable and even unacceptable that a machine could replace the experienced professional.
This circumstance explains why the first automated blood differential analyzers used analysis systems based on the digitization of images of blood cells stained on a slide by the conventional method. However, it did not take long to realize that this new methodology, despite its sophistication, had all the limitations of the manual method. It had none of the advantages of automation: slowness (counting at 100 elements), low reliability and high cost. Moreover, until the use of automated hematology analyzers was definitively consolidated during the 1980s, the hemogram continued to be synonymous with the leukocyte formula, as defined by Schilling in 1933.
The new system that changed everything
The real revolution took place during the 1990s, when automated analyzers appeared which, using a completely different philosophy to image digitalization such as flow cytometry, offered, together with the classic blood count values (hemoglobin and cell concentration, hematocrit value and MCV), the automated blood differential formula. This new system, due to its greater speed, reliability and lower cost, quickly replaced the previous one, especially when the number of blood counts to be performed per day was incompatible with the manual performance of the blood differential formula.
Nowadays, practically all automated hematology analyzers offer a very complete and detailed report of the state of the blood. In addition to the basic hematological parameters, it includes the blood differential formula, and is known as an automated blood count. Sometimes it also includes the reticulocyte count.
It should not be forgotten that a morphological examination of the blood by an experienced observer is a fundamental diagnostic tool in hematology. This is because the reliability of the results of the automated leukocyte formula depends on the morphological alterations that the blood cells may present.
The advantages of the new system
Modern automated hematology analyzers, even the most sophisticated ones, do not use morphology as a system of analysis and the results of the blood differential formula are only reliable when the blood samples analyzed do not show significant morphological alterations. These teams merely report warnings that investigate the origin by morphological examination of the smear. Overlooking this detail can lead to significant diagnostic errors. Despite this limitation, these devices have proven to be crucial in laboratories with a high volume of care, since they ensure the screening of all normal samples and identify, by means of alarms, those samples that require morphological examination of the smear. But the impact of automation has gone even further. Its widespread implementation has contributed to improve the knowledge of blood cells and also the methods of their study, always on the basis that the conventional morphological examination is still the gold standard for the diagnosis of any blood pathology.