automated blood cell count - bhs.be · no slide distribution error ... a review. part ii: white...

© 2008 Universitair Ziekenhuis Gent 1

Automated blood cell count

Veronique Stove

Clinical biologist Core lab

20 oktober 2013


Quantitative

laboratory

hematology

Automation in Hematology

J. LEHNER, B. GREVE, U. CASSENS

Transfus Med Hemother 2007; 34:328-339

The CBC at the Turn of the Millenium: An Overview

P. WARD

Clin Chem 2000; 46:1215-1220

3 3 © 2008 Universitair Ziekenhuis Gent

First half of the 20th century

Blood cell counts (red cells, white cells, platelets): appropriately diluted blood samples and a ruled counting chamber (hemocytometer).

Hemoglobin concentration: colorimetrically by the cyanomethemoglobin method.

The hematocrit (packed cell volume): high speed centrifugation of a column of blood, either in a specially designed tube (the Wintrobe tube), or in sealed microcapillary tubes (ie, the "spun" hematocrit, often obtained by fingerstick blood collection).

Microscopic reticulocyte counting: based on supravital staining of cytoplasmic ribosomal RNA

The white blood cell differential: by examining and enumerating by class (eg, granulocytes, lymphocytes, monocytes) 100 to 200 individual white blood cells on a suitably stained blood smear.

Exclusively manual techniques


First half of the 20th century

Calculated indices

MCV (fL) = ____________________ HCT (%) x 10

RBC (millions/µL)

MCH (pg/RBC) = ____________________ HGB (g/dL) x 10

RBC (millions/µL)

MCHC (g/dL) = ____________________ HGB (g/dL) x 100

HCT (%)

Maxwell Wintrobe

(1932)


Disadvantages of manual cell counting

Laborious

Imprecise (hemocytometer)

Errors in leukocyte differential count:

Distributional error

Error due to inter-observer variability

Statistical error

Total number of cells counted

Differential 100 200 500 1000 10 000

3 0-9 1-7 1-5 2-5 2.7-3.3

6 2-13 3-11 4-9 4-8 5.5-6.5

15 8-24 10-21 12-19 12-18 14.6-15.4

40 30-51 33-48 35-45 36-44 39.5-40.5


Wallace COULTER


1956: Coulter impedance measurement


1960s: Multichannel instruments

Anticoagulated whole blood samples were

aspirated into the apparatus

automatically aliquoted and diluted into RBC and WBC counting chambers (baths) for cell counting and sizing with impedance apertures

into a spectrophotometric cuvette for hemoglobin determination using the cyanmethemoglobin method.

calculations of red cell indices were automatically performed.

Towards high throughput, low cost and fast TAT with the

ability to produce immediate (STAT) results.


1970s: Automated platelet counting

improvement of the cell counting apertures

More accurate cell sizing

Reliable and accurate platelet counts.

Coincidence -> Hydrodynamic focussing


1970s: Cell counting by light scattering

Hydrodynamic

focussing

(Sysmex)

Diluted blood sample

Pulse amplitude ~ Cell volume

Flow cell


1980s: Three-part differential


Early 1990s: Five-part differentials

PREPARATION

Selective lysis of red cells and counting of white cells

Special stains

DETECTION

Impedance technology

Direct current (DC): pulse height ~ cell volume

Radiofrequency current (RF): pulse height ~ nuclear size and density

Optical system

Scattered laser light

Fluorescence light


Lysis of RBC and PLT

Perforation of WBC

RNA/DNA staining

Lysis of RBC, PLT and WBC

EXCEPT Basophils

WBC

WBC


Perforation of RBC and WBC

RNA/DNA staining

Optical PLT

Impedance PLT Immuno PLT


Advantages of automated cell counters

Excellent analytical performance

Closed-tube analysis

No inter-observer variability

No slide distribution error

Eliminate statistical variations

Potential of reflex testing

Availability of extra parameters e.g. MCV, RDW, Ret-He, …

More efficient (> 100 analyses/hour) and cost effective than

manual method


Analysers

Cell Dyn® (Abbott)

Coulter® LH 780 and other (Beckman Coulter)

ADVIA® 2120 and other(Siemens Diagnostics)

X-Class Hematology Systems (Sysmex)


Cell counters Smear-stainer Tube sorter ESR analyser

Trend:

Integrated ‘lavender top’ automation system


Trends:

All in one systems

Microscope Smear-stainer Analysers


Trends:

All in one systems


Key to successful use of automation


Detection of spurious cell counts

Every hematology analyser is affected !

Operators must be aware of the characteristics of their analyser + be able to recognize and circumvent anomalous results

Specific condition of patient

Sampling

conditions

Technical problems

Total

testing

process All suspected spurious cell

counts / morphologies

should be validated with

microscopic examination of

slides


Spurious counts and spurious results on haematology analysers: a review. Part I: platelets

M. ZANDECKI, F. GENEVIEVE, J. GERARD, A. GODON

Volume 29, Issue 1, pages 4–20, February 2007

Spurious counts and spurious results on haematology analysers: a review. Part II: white blood cells, red

blood cells, haemoglobin, red cell indices and reticulocytes

M. ZANDECKI, F. GENEVIEVE, J. GERARD, A. GODON

Volume 29, Issue 1, pages 21–41, February 2007


Expert flagging system

Flags to signal poor reliability of quantitative results

(e.g. turbidity/Hb interference, WBC abnormal

scattergram, PLT clumps, RBC agglutination, …)

Morfology flags (blasts, IG, atypical lymph, RBC

fragments, …)

Limit check

Delta check


http://www.islh.org/web/consensus_rules.php


Flowchart

DM96 (CellaVision)


Examples of spurious results


Parameter Run 1 Run 2

30 min

37°C

Run 3

Plasma

exchange

WBC 5.02 5.25 6.70 10 3/uL

RBC 0.71 0.90 3.44 10 6/uL

HGB 11.9 11.9 11.6 g/dL

HCT 8.6 10.9 36.9 %

MCV 121.1 121.1 107.3 fL

MCH 167.6 132.2 33.7 pg

MCHC 138.4 109.2 31.4 g/dL

PLT 195 196 205 10 3/uL

Spurious increase in MCHC (>36g/dL)

MCHC = HGB x 100 / HCT (%) normal range: 31.9 - 34.9 g/dL

Cold agglutinins RBC aggr

MCV =

HCT / RBC x 10

MCH =

HGB / RBC x 10


Spurious increase in MCHC (>36g/dL)

Parameter Run 1 Run 2

Plasma

exchange

WBC 12.07 13.28 10 3/uL

RBC 2.47 2.62 10 6/uL

HGB 15.9 8.8 g/dL

HCT 23.4 24.9 %

MCV 94,7 95.0 fL

MCH 64.4 33.6 pg

MCHC 67.9 35.3 g/dL

PLT 519 192 10 3/uL

Hypertriglyceridemia (>2000 mg/dL)

MCHC = HGB x 100 / HCT (%)


Spurious PLT counts

HEMATOLOGY

Screening

Red blood cells 4.78 10E6/µL 3.79 - 5.23

Hemoglobin 14.7 g/dL 11.7 - 15.7

Hematocrit 43.7 % 34.9 - 46.9

MCV 91.4 fL 80.5 - 99.7

MCH 30.8 pg/cel 26.6 - 33.8

MCHC 33.6 g/dL RBC 33 - 36

Red cell distribution width 12.6 % 11.1 - 14.2

Platelets - 54 10E3/µL 170 - 394

Thrombocytes - citrate 198 10E3/µL

Screening thrombocytes Thrombocyte aggregates

EDTA-dependent pseudothrombocytopenia


Spurious leukocyte counts

Lipids

(Parental nutrition)

Lysis resistant RBC

(HbC, HbS) Nucleated red

blood cells

(Neonates, Path.

circumstances)

Normal


Opportunities

of automated hematology


MCV Delta check

| Current – Previous result |

Average

Change in MCV indicates

Transfusion

Sample mishandling

Sample mix-up

Parameter TAT

(p50 percentile)

Chemistry 44 min

Coagulation 39 min

Hematology 15 min

> 5%

Example

(93 – 87) / 93 = 7%


Extended parameters

Extended differential count

Immature granulocytes (infections, neonatal sepsis, cancer, …)

Nucleated red blood cells (neonates / numerous conditions in adults)

Hematopoietic progenitor cells (time to harvest)

RBC and Reticulocyte parameters

Immature reticulocyte fraction (IRF) - early index of erythropoeisis

Reticulocyte Hemoglobin content (Ret-He) – iron status

Hypochromic RBC

Microcytic RBC

Platelet parameters

Immature platelet fraction (IPF) – early index of thrombopoiesis


Screening formulas

Thalassemia

Hereditary spherocytosis

Iron status – Iron therapy

Index Formula TT

England and Fraser index (1973) MCV – RBC – 5 x Hb – K (3,4) < 0

Mentzer index (1973) MCV / RBC < 13

Srivastava index (1973) MCH / RBC < 3,8

Shine and Lal index (1977) MCV ² x MCH x 0.01 < 1530

RDW index (1987) MCV x RDW / RBC < 220

Ricerca index (1987) RDW / RBC < 3,3

Green and King index (1988) MCV ² x RDW / (100 x Hb) <72

Ehsani index (2005) MCV – 10 x RBC < 15

Sirdah et al.’s index (2007) MCV – RBC – 3 x Hb < 27


Screening formulas

Thalassemia

Hereditary spherocytosis

Mullier et al., Annals of hematology (2011); 90:759-768.

Persijn et al., Annals of hematology (2011)


Conclusion

Essential role of automation in the modern hematology laboratory

Microscopic control of pathologic samples remains indispensable

Of major importance for correct interpretation of results: Knowledge of the limits of your specific analyser

automated blood cell count - bhs.be · no slide distribution error ... a review. part ii: white...

Documents