Automation in Hematology part 2

1. AUTOMATION IN HEMATOLOGY
By
Dr.Varughese George

2. PART 2

3. I N D E X
PART 1
I. Necessity for Automation.
II. Advantages & Disadvantages of Automation.
III. Types of Automated Hematology Analyzers.
IV. Principles involved in Automation.
V. Pentra ES 60 Haematology Analyzer.
VI. Pentra DF Nexus Haematology Analyzer.
PART 2
I. Histograms.
II. Flags
III. Quality Control

4. Histograms
 Graphical representation
of numerical data of
different cell populations
in a cell counter.
 x-axis => cell size
 y-axis => no: of cells
 Gives info on
 Average size
 Distribution of size

5. Discrimination thresholds
 Moving or fixed discriminator separates the
distribution curve for the volume
 WBC Discriminator
 The automated counter sets a LD flunctuating between 30-60 fl & an UD fixed at
300 fl.
 WBC is calculated from particle counts > than this LD
 RBC Discriminator
Has two flexible discriminators LD (25-75 fl) & UD (200-250 fl).
RBC is calculated from particle counts between this LD & UD.
 Platelet Discriminator
Three discriminators – LD (2-6 fl), UD (12-30 fl) & a fixed discriminator (8-12 fl)

6. Estimation of RBC Count & MCV – RBC Histogram
Normal RBC distribution curve is Gaussian bell shaped curve.
Analyzer counts RBCs as those which ranges from 36-360 fl.
MCV is perpendicular line from peak of the curve to the base.
Peak of curve should fall within the normal MCV range of 80-100 fl.
There are 2 flexible discriminators – LD (25-75 fl) & UD (200-250 fl)

7. Abnormalities of RBC Histogram
Left shift of the curve in microcytosis.
Right shift of the curve in macrocytosis.
Bimodal peak of the curve in dimorphic population of cells.

8. Estimation of Hematocrit, MCH &
MCHC

9. Estimation of RDW
RDW is expressed as a coefficient of variation of RBC size distribution.
RDW- CV is a better indicator of anisocytosis than RDW-SD.
RBC distribution curve ll get wider as RBC vary more in size.
Normal Range – RDW-CV – 11.0-15.0% RDW-SD – 40.0 - 55.0 fL

10. RDW

11. Estimation of WBC Count
 Hematology analyzers can generate a
 3-part differential count – lymphocytes, monocytes & granulocytes
based on the principle of electrical impedence
Or
 5-part differential count - lymphocytes, monocytes, neutrophils,
eosinophils & basophils
based on different principles –
 light scatter
 electrical impedence
 electrical conductivity
 peroxidase staining

12. Estimation of WBC Count – WBC Histogram
 Cells > 35 fl are counted as WBCs in the WBC/Hb chamber.
Cells with volume 35-90 fl  Lymphocytes.
Cells with volume 90-160 fl  Mononuclear cells.
Cells with volume 160-450 fl  Neutrophils.

13. Abnormalities of WBC Histogram
 Peak to the left of lymphocyte peak – nucleated cells.
 Peak between lymphocytes & monocytes – blast cells, eosinophilia, basophilia,
plasma cells & atypical lymphocytes.
 Peak between monocytes & neutrophils – left shift

14. 2-6 fl 12-30 fl
fixed at
12 fl
Platelet Histogram
PL PU
PLT RBC
100%
20%
 PLT size: 8-12 fL
 PLT detection: between 2 and 30 fL
 Fixed discriminator at 12 fL

15. Estimation of Platelet Count
Platelets are counted by the electrical impedence method in the RBC aperture.
Particles between 2 fl and less than 20 fl are classified as platelets by the analyzer.
MPV is a measurement of the average size of platelets found in blood Normal MPV is 7-10 fl.
↑ MPV ( > 10 fl) d/t destruction of platelets in circulation.
↓ MPV ( < 7 fl) d/t impaired production of platelets in circulation.
 Plateletocrit (PCT) is volume of circulating platelets in a unit volume of blood. Normal PCT is 0.19-0.36%.
 PCT ↑ in thrombocytosis and ↓ in thrombocytopenia.
PDW is a measure of variation in the size of platelets. Standard PDW ranges from 9 to 14 fL
↑ PDW is observed in megaloblastic anemia, CML & after chemotherapy.

16. I N D E X
PART 1
I. Necessity for Automation.
II. Advantages & Disadvantages of Automation.
III. Types of Automated Hematology Analyzers.
IV. Principles involved in Automation.
V. Pentra ES 60 Haematology Analyzer.
VI. Pentra DF Nexus Haematology Analyzer.
PART 2
I. Histograms.
II. Flags.
III. Quality Control.

17. Flagging
 Flags are signals that occur when
an abnormal result is detected
by the automated blood
analyzer.
 Flags are signaled by certain
‘asteriks’ on the report.
 They reduce the False +ve &
False –ve results by mandating
the results of blood smear
examination.

18. RBC Flags
 Seen when LD > preset
height by 10 %
 Shown by
 RBC Count
 HCT, MCV,MCH,MCHC
 Occurs when there is
 platelet aggregation
 RBC fragments
RL Flag

19. RBC Flags
 Seen when UD > preset
height by 10%.
 Shown by
 RBC Count
 HCT, MCV,MCH,MCHC
 Occurs when there are
 Cold agglutinins
RU Flag

20. RBC Flags
 Shown by RDW-SD
 Seen in
 Post Blood tranfusion
 Treated Fe deficiency anemia.
MP- Flag

21. WBC Flags
 Generated when curve deviates
from the baseline on the LD.
 Various causes for this are –
 Platelet aggregates (clotted
sample, EDTA incompactibility)
 Lyse-resistant RBCs.
 Erythroblasts.
 Cryoagglutinates.
 Giant platelets.
WL Flag

22. WBC Flags
 Generated when there is
deviation of the curve on the UD
or if it does not end at the
baseline.
 Various causes for this are :-
 Hyperleucocytosis.
WU Flag

23. WBC Flags - T1 & T2 Flags
Peak between T1-T2 : The middle cell count - Eosinophils, Monocytes, Blasts, promyelocytes,
myelocytes and metamyelocytes.
Peak between LD-T1 : Lymphocytes
Peak between T2-UD : Neutrophils.
T1 & T2 flags appears when discrimination between lymphocytes, middle cells & neutrophils is
not possible which happens in presence of abnormal/higher leucocyte counts as in Chronic
Myeloid Leukemia.

24. WBC Flags - F1, F2, F3 Flags
 Sometimes, the cell Fractions
may be mixed.
 F1 & F2 or F2 or F3 merge into
each other over large areas.
 F1 (small cell inaccurate) flag :
Acute Lymphocytic Leukemia
 F2 (middle cell inaccurate) flag :
eosinophil, Acute Myeloid
Leukemia, monocytosis, etc
 F3 (large cell inaccurate) flag:

25. Platelet Flags
 This occurs when the LD
> the preset height by
10%
 Shown by
 Platelet count
 MPV
 P-LCR
 Occurs due to noise.
PL Flag

26. Platelet Flags
 This occurs when the
UD> the preset height by
> 40%.
 Occurs in
 Hemolytic anemias with
fragmented cells.
 Large platelets.
PU Flag

27. Platelet Flags

29. I N D E X
PART 1
I. Necessity for Automation.
II. Advantages & Disadvantages of Automation.
III. Types of Automated Hematology Analyzers.
IV. Principles involved in Automation.
V. Pentra ES 60 Haematology Analyzer.
VI. Pentra DF Nexus Haematology Analyzer.
PART 2
I. Histograms.
II. Flags
III. Quality Control

30. Quality Control / Quality Assurance/Quality Assessment
 Quality Control => measures that must be included
during each assay run that the test is working properly.
 Quality Assurance => overall program that ensures
that the final results reported by the lab are correct
 Quality Assessment => means to determine the
quality of results generated by the lab

31. QUALITY CONTROL
 Measure of precision – how well the measurement system reproduces the
same results over time and under varying operating conditions.
 Designed to detect, reduce & correct deficiencies in a laboratory’s internal
analytical processes prior to release of patient’s reports.
 Should approximate the same matrix as patient’s specimens, taking into
account properties such as viscosity, turbidity, composition and color.
 Should be simple to use, with minimal vial to vial comparability.
 Should be stable for long periods of time and available in large enough
quantities for a single batch to last at least 1 year.

32. Types of Quality Control
Internal
 Continuous evaluation of reliability
of the daily works of the laboratory
with validation of tests.
 Primary tool required is called a
control – a specimen with a
predetermined range of result values,
processed in the same manner as
patient sample.
 If the result of a test on a control
sample is different from its known
value, this indicates a problem in the
equipment or the methods being
used.
External
 Evaluation by an outside agency of
the comparability a laboratory's
testing to a source outside the
laboratory.
 This comparison can be made to
the performance of a peer group of
laboratories or to the performance
of a reference laboratory.
 The analysis of performance is
retrospective.

33. Accuracy and Precision
 Accuracy is a measure of rightness.
 It refers to closeness to the true value.
 Precision is a measure of exactness.
 It refers to reproducibility of the test.

34. Control
 A solution that contains the same constituents as those being
analyzed in the patient sample.
 Commercially produced pooled RBCs/sera or stabilized
anticoagulated whole blood.
 Should have same test properties as that of a blood sample.
 At least 1 control specimen should be used for every batch.
 If large specimens, use 1 control for every 20 specimens.
 For most tests, a “normal” control and an “abnormal” control are
analyzed with each patient test or batch of tests.
 The results are compared with the manufacturer’s range of values
and plotted on a Levey-Jennings Chart.

35. Levey Jennings Graphs
 A graphical method for displaying control
results and evaluating whether a procedure is
in-control or out-of-control
 Control values are plotted versus time
 Lines are drawn from point to point to accent
any trends, shifts, or random excursions
 Consecutive values of control are recorded and
the standard deviation is calculated.
 The mean and ± 2 SD are plotted on a Levey-
Jennings chart.
 As long as the control value are between the ± 2
SD lines on the L-J chart, the control values are
“in control”
 If they are outside the ± 2 SD lines, they are 'out
of control'

36. Westgard Control Rules
 Proposed by Dr. James Westgard
on lab quality control.
 Set the basis for evaluating
analytical run for medical
laboratories.
 There are 6 basic rules.

37. 12s Rule . Warning rule to trigger careful inspection of the control data
A single control measurement exceeding 2 standard deviations of control limits either
above or below the mean.
No cause for rejecting a run

38. 13s rule
A single control measurement exceeds the mean plus 3s or the mean minus 3s
control limit.
The run must be rejected.

39. 22s rule
2 consecutive control measurements exceed exceeds the +2SD or -2SD
control limit .
The run must be rejected.

40. R4s rule
1 control measurement exceed the +2SD and the other exceeds the -2SD
control limit .
The run must be rejected.

41. 41s rule
4 consecutive control measurements exceed exceeds the +1SD or -1SD
control limit .
The run must be rejected.

42. 10x rule
10 consecutive quality control results for one level of control are on one
side of the mean
The run must be rejected.

43. ‘Out of Control’
 Stop testing
 Identify and correct the issue.
 Repeat testing on patient samples and controls.
 Don’t report patient results until the issue is sorted out
and the controls indicate proper performance

44. Errors
 Systematic error is evidenced by a change in the mean of
control values.
 The change in mean maybe
• Gradual - demonstrated as a trend in control values.
• Abrupt – demonstrated as a shift in control values.
 Random error is any deviation away from the expected
result.

45. Errors
Trend Shift
 Gradual loss of reliability in test
system.
Causes
 Deterioration of instrument light
source.
 Gradual accumulation of debris in
sample/reagent tubing and
electrode surfaces.
 Aging of reagents.
 Gradual deterioration of –
 Control materials.
 Incubation chamber
temperature.
 Light filter integrity.
 Calibration.
 Sudden/dramatic +ve or –ve change in
test system
Causes
 Sudden failure or change in the light
source.
 Change in reagent formulation.
 Major instrument maintenance.
 Sudden change in incubation
temperature.
 Change in room temperature or
humidity.
 Failure in sampling system.
 Failure in reagent dispense system.
 Inaccurate calibration/recalibration.

46. Calibrators
 Determines the accuracy and precision of the
analyzer using a specifically formulated product
in order to recover each parameter within close
tolerances of known target values and limits.
 Finetunes the hematology analyzer to provide the
most accurate results possible.
 Coefficients of variation and percent difference
recovery must be within their specified limits.

47. Why to Calibrate?
Calibration is necessary
To ensure readings from an instrument
are consistent with other measurements.
To determine the accuracy of the
instrument readings.
To establish the reliability of the
instrument i.e. that it can be trusted.

48. When to Calibrate?
At installation
After the replacement of any component that
involves dilution characteristics or the primary
measurements (such as the apertures)
When advised to do so by your service
representative