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Hematology

Differential Analyzers

The evolution of hematology instrumentation has moved beyond simple cell counting to sophisticated morphological profiling. Modern automated analyzers utilize advanced data visualization techniques to sort and identify cell populations. The laboratory scientist must be competent in interpreting these graphical representations - Histograms and Scatter Plots - to validate results, detect interferences, and identify pathological states. Furthermore, the integration of Digital Imaging systems has standardized the manual review process, bridging the gap between automated flagging and human morphological assessment

Histograms (Frequency Distribution Curves)

Histograms are one-dimensional graphs primarily generated by Electrical Impedance technology. They represent the frequency distribution of cell populations based on a single characteristic: Size (Volume). On the graph, the X-axis represents the cell size in femtoliters (fL), and the Y-axis represents the relative number of cells found at that size. These curves provide the data necessary for calculation of the RDW (RBC distribution width) and the PDW (Platelet distribution width), and they serve as the basis for the 3-Part WBC differential

  • RBC Histogram
    • Normal Distribution: A symmetrical “Gaussian” bell curve peaking between 80 and 100 fL (the MCV)
    • Discriminators: The analyzer places electronic gates (typically at 36 fL and 250 fL) to exclude platelets and coincidence artifacts
    • Shifts: A shift to the left indicates Microcytosis (e.g., Iron Deficiency); a shift to the right indicates Macrocytosis (e.g., B12 Deficiency). A Bimodal (double-peaked) curve indicates two distinct populations, commonly seen after blood transfusions or in sideroblastic anemia
  • Platelet Histogram
    • Normal Distribution: A right-skewed curve located between 2 and 20 fL. Because platelets overlap with debris and small RBCs, the analyzer uses a mathematical “log-normal” fit to smooth the curve
    • Interferences: An elevation at the far left (<2 fL) suggests electronic noise or debris. An elevation at the far right (>20 fL) suggests Giant Platelets or microcytic RBC fragmentation (Schistocytes)
  • WBC Histogram (3-Part Differential)
    • Methodology: A lytic agent shrinks the WBC cytoplasm around the nucleus. The analyzer sorts the remaining volumes into three distinct peaks
    • Lymphocytes (35–90 fL): The first, small peak
    • Mononuclear Cells (90–160 fL): The middle valley/plateau (Monocytes, Eosinophils, Basophils)
    • Granulocytes (160–450 fL): The large peak on the right (Neutrophils)
    • R-Flags: Discriminator alerts (R1, R2, R3, R4) indicate that the valleys between peaks are not clean, suggesting abnormal overlaps like Nucleated RBCs (R1 region) or Immature Granulocytes (R3 region)

Scatter Plots (Scattergrams)

Scatter plots provide a multi-dimensional analysis required for the 5-Part Differential. Generated via Flow Cytometry, these graphs plot two or more specific physical or chemical properties against each other. This allows the analyzer to separate cells that are similar in size but different in internal structure (e.g., Eosinophils vs. Neutrophils). Common axes include Forward Scatter (Size), Side Scatter (Granularity/Complexity), and Fluorescence (RNA/DNA content)

  • Cluster Interpretation
    • Lymphocytes: Found in the bottom-left. They are small (Low Forward Scatter) and agranular (Low Side Scatter)
    • Monocytes: Found in the mid-to-upper left. They are large (High Forward Scatter) but have moderate complexity due to vacuolization
    • Neutrophils: The largest cluster, found in the mid-right. They have moderate size but high granularity (High Side Scatter)
    • Eosinophils: Found in the far right. Their dense, crystalline granules refract light intensely, giving them the highest Side Scatter/Depolarization values
    • The “Ghost” Region: The area below the lymphocytes represents background noise. A dense population here usually indicates Lyse-Resistant RBCs or unlysed nRBCs
  • Identifying Pathology
    • Left Shift: An upward extension of the Neutrophil cluster indicates Immature Granulocytes (IGs) like bands and metamyelocytes, which have higher RNA content or slightly different density
    • Blasts: These cells are typically large (High Forward Scatter) with high RNA (High Fluorescence) but have no granules (Low Side Scatter). They typically appear in the upper-left quadrant, bridging the gap between Lymphocytes and Monocytes
    • Variant Lymphocytes: Reactive lymphocytes often appear as a smear or “tail” extending from the normal lymphocyte cluster upward toward the monocyte region, reflecting their increased cytoplasm and RNA activity

Digital Imaging Systems

Digital Imaging (DI) automation, such as CellaVision, modernizes the traditional manual differential. These systems function as an interface between the slide maker and the laboratory scientist, utilizing high-quality optics and Artificial Neural Networks (ANN) to pre-classify cells. This technology changes the laboratory scientist’s role from “counting” to “verifying”

  • Operational Workflow
    • The instrument scans the slide at low power to find the monolayer (Feather Edge)
    • It switches to high power to capture digital images of WBCs, RBCs, and Platelets
    • The ANN segments the images (separating nucleus from cytoplasm) and extracts features like N:C ratio, chromatin texture, and granule color to assign a classification (e.g., Seg, Lymph, Blast)
  • Verification: The laboratory scientist reviews the cells on a monitor in a “Gallery View,” where cells are grouped by type. Misclassified cells can be re-categorized via drag-and-drop. The system also presents pre-graded RBC morphology (e.g., Polychromasia 2+) for approval
  • Advantages
    • Standardization: Every slide is reviewed under identical lighting and magnification, reducing inter-observer variability
    • Ergonomics: Reduces the repetitive strain injuries associated with manual microscopy
    • Telepathology: Allows for remote consultation with pathologists on difficult cases and creates digital archives for education and competency assessment
  • Limitations: The software is dependent on stain quality. Poor staining or smudge cells (which lack defined borders) often result in a high percentage of “Unclassified” cells that require human intervention