1) Automated blood cell counters have evolved from traditional manual counting methods to modern analyzers that can analyze multiple blood parameters from a single sample quickly and precisely. 2) Automated counters minimize errors compared to manual methods by eliminating issues like cell recognition mistakes and distribution errors. They provide results for many parameters not available through manual counting. 3) Modern analyzers can measure parameters like white blood cell, red blood cell, hemoglobin, and platelet counts as well as differentials. This integration of tests saves time compared to running samples separately. Microscopic review is still needed when flags are present.

1. Automated Blood Cell Counter
Prof. (Brig. Gen.) Dr MA Mohsin
MBBS, MCPS, MPhil (Path)
Professor & Head
Dept. of Applied Laboratory Sciences
Advisor, Dept. of Pathology
Bangladesh University of Health Sciences

2. “How can I have possibly come so far,
And still have so far to go ?”
Blood has always fascinated man, being
regarded as the essence of life.

3. Evolution of Automated Cell Counter
 Traditional cytometer – manual
 Kart Principle – Coulter Counter
 A advanced haematology analyzer.
A simple instrument can analyze more parameters of
multiple sample.

4. Haemocytometer

5. Neubaur’s Chamber

6. Automated Blood Cell Counter

7. Automated Blood Cell Counter
Sysmex XT i2000
Cell DYN Ruby

8.  Automation minimizes or does away with the need for
manual intervention.
 Even semi-automation involves steps like the dilution
of blood samples and allows for the measurement of
only fewer variables.
 With a fully automated system, all that is required is
an appropriate blood sample.
 Errors are a major issue with manual counting. There
are problems with cell recognition such as
distinguishing lymphocytes from monocytes and these
may be overestimated or underestimated.

9.  Other sources of error with manual counts pertain to
distribution of cells on the slide and statistical
sampling error. One the other hand, automated cell
counters ensure a high level of precision and accuracy
for cell sizing.
 Automated leukocyte differentials significantly reduce
the time and cost of performing routine examinations.

10. State of the Art Hematology Analyzers
 Hematology analyzers also come with on-
board storage for thousands of patient reports
and even allow for customization of these
reports with patient identification and color
histogram.

11. Advantages of Automated Hematology Analyzers
 Modern automated hematology systems are designed to meet
the needs of high volume laboratories. They can measure
several analytical parameters such as WBC or leukocyte count,
lymphocyte percent and number, mononuclear cell percent and
number, granulocyte percent and number, RBC, hemoglobin
concentration, hematocrit, mean corpuscular volume,
hemoglobin concentration, red cell, platelet count, and more.
Incorporating a wide range of parameters on one instrument
minimizes the need to run one sample on several parameters.
 No slide distribution error
 Many parameters not available from a manual count
 More efficient and cost effective than manual method

12. Principles of Automated Cell Counters
Impedance (conductivity) System
(coulter)
Optical System (Light Scattering)
Flow Cytometry
Selective Lysis
Special Stains

13. Analytic Goals
 CBC Count
Leukocytes
Erythrocytes
Hemoglobin
Mean cell volume
Platelets
 Leukocyte Differential Count
Neutrophils
Lymphocytes
Monocytes
Eosinophils
Basophils
 Reticulocyte Count

14. Whole Blood Reportable Parameters
WBC
RBC
HGB
HCT
MCV
MCH
MCHC
PLT
MPV

15. Leukocyte Differential Count
Extended Differential Count
- Immature Granulocytes
- Nucleated RBCs
Immature Reticulocyte Fraction
Reticulocyte Indices
RBC Distribution Width
Schistocytes (FRBCs)
Platelet Indices
Reticulated Platelets and Immature Platelet
Fraction

16. Clinical Applications of Reticulocyte Parameters
Guidance of iron and EPO therapy in
hemodialysis patients
Diagnosis of iron deficiency in patients with
inflammation or chronic disease
Diagnosis of iron deficiency in early childhood

17.  Cell Identification Error in Manual Counting
 Mostly associated with distinguishing lymphocytes
from monocytes, bandsfrom segmented forms and
abnormal cells (variant lymphocytes from blast )
 Lymphocytes overestimated, monocytes underestimated
 Slide Cell Distribution Error
 Increased cell concentration along edges and in the
feather edge, also bigger cells found there i.e.
monocytes, eosinophils and neutrophils
 Statistical Sampling Error

18. WBC Differential Ordered
 Automated differential performed
 No flags - automated differential is reported
 Flags - Slide made, labeled, stained &
reviewed
 Review with Microscope

19. Review Rate
 Whenever the automated cell counter flags a
specimen, the technologist has to-
 Retrieve the tube
 Make a slide
 Stain the slide
 Review the slide
 Either release the results from the cell counter or
perform a manual differential
 These steps consume time, labor and money !!!

20. Blood Films

21. Blood Cells

22. Peripheral Blood Film (Typical)

23. Peripheral Blood Film (Atypical)

24. Peripheral Blood Film (Atypical)

25.  The technological evolution as applied to hematology
analyzers has provided new opportunities.
 The possibility of determining the fraction of immature
platelets by using a simplified method opens the door to new
applications.
 It should be remembered that despite the essential role of
automation in the modern hematology laboratory, microscopic
control of pathologic samples remains indispensible, so much
so that in certain cases, it alone is diagnostic.
 Moreover, knowledge of the limits of the specific analyzer in
use is of paramount importance for the correct interpretation of
results.

26. Thanks To All
For Patient Hearing