histogram

1. Automated determinations of platelet counts have replaced chamber counts in labora-
tories for years already and have greatly simplified and clearly improved cell count de-
termination. Counting chambers have either long been collecting dust in some drawers
or are only used to check seemingly doubtful values. One of the most important rea-
sons for automated counting is – aside from time savings – the clearly lower statistical
error due to the greater number of cells examined. However, despite the automated
cell count, releasing the platelet value will require a more precise review.
On most haematology analysers, the
platelet count is done by impedance
measurement. To determine cell concen-
tration, cells are passed one after
the other through a capillary opening
(Fig. 1). When a cell passes the meas-
uring orifice, the electrical voltage above
the transducer is changed and results in
an electrical signal which is proportion-
ate to the cell’s volume. These impulses
result in a volume distribution curve for
the corresponding cell population. The
sum of impulses within a certain size
distribution will result in the correspond-
ing cell number. This measuring principle
is further improved through hydrodynamic
focusing. This centred stream principle
will ‘jacket’ the stream of particles by
a sheath flow so that the particles are
passed centrally and one after the other
through the measuring capillary (Fig. 2).
This almost completely excludes any
interference factors such as double
passages (coincidences), recirculation,
Platelet distribution curves:
interpretation, potentials and limitations
Sysmex Xtra Online | June 2011
impedance
vacuumdirect voltage source
(appr. 100 Volt)
constant direct current
external electrode
capillary orifice
blood cells
internal electrode
blood suspension
sample cup
Fig. 1 The capacitance measurement principle
Fig. 2 Sheath flow principle with hydrodynamic focussing

2. 2Sysmex Xtra Online | June 2011 | 6 pages
Platelet distribution curves: interpretation, potentials and limitations
etc. and cells will thus be counted with utmost precision. This also applies for counts
with extremely low and extremely high PLT concentrations.
Despite all the technologies ensuring a
safe result, the assessment must take
into account that a cell count is primarily
a particle determination which takes only
the cell volume into account. Red blood
cells (RBC) and platelets will be separated
from each other due to their cell volume.
Aside from numerical platelet values, the
analyser also mostly supplies a volume
distribution curve which is very impor-
tant for determining the platelet morphology and thus provides still further informa-
tion on the platelet value. The volume distribution curve (histogram) presents the sum
of all impulses of the respective cell population of a specific size (Fig. 3).
Platelet and red blood cells populations are separated by means of flexible discrimina-
tors. Due to the flexible discriminators PL (lower discriminator) and PU (upper discrimi-
nator) (Fig. 3), the populations will be optimally separated from each other. Platelets of a
physiological size of 8–12 fL are measured in a range between 2–30 fL with the flexible
discriminator PU setting the optimum separation from the red blood cells. They have
a size of 80–100 fL and are recorded from 25 fL to 250 fL. Due to this procedure of the
automated haematology instrument, technical measuring errors may occur in the analy-
sis of certain samples. Platelets having a greater volume than 30 fL, or red blood cells
smaller than 25 fL can falsify the measuring result. Also, other very small particles such
as cytoplasm fragments may be erroneously counted as platelets. The most frequent
interference factors are giant platelets and fragmentocytes. But microerythrocytes and
platelet aggregates are also responsible for wrong counting results.
In such cases, mere volume separation is not sufficient for unambiguous cell count
analysis, and it is necessary to verify the cell count. Because of a cell volume >30 fL,
giant platelets are taken for red blood cells. Under the microscope, this is evident by
a massive anisocytosis of platelets, with platelets which partly reach the size of a
red blood cell. Even larger platelet aggregates can be erroneously counted among
the red blood cells, while smaller, looser aggregates are torn apart due to the sheath
flow method. Fragmentocytes and microerythrocytes, in turn, are counted among
platelets.
In all these cases, however, an abnormal volume distribution curve and thus possibly a
false measurement can be detected. The volume distribution curve should always begin
at the baseline and end at the baseline. If deviations from the baseline are detected,
the flexible discriminator will search for the optimum position to separate the two
populations from each other. In these cases, the analyser generates an alarm to make
Fig. 3 Display of a platelet histogram
10 fL 20 fL 30 fL 40 fL
20%
12 fL PUPL
100%

3. 3Sysmex Xtra Online | June 2011 | 6 pages
Platelet distribution curves: interpretation, potentials and limitations
the user aware that the value should be checked – either by a more precise evaluation
of the histogram or by the actual verification of the platelet value by means of another
method.
If a false analysis of platelets is suspected, the counting value can be reviewed by the
method of the conventional counting chamber. However, it must be taken into account
that the counting chamber analysis is subject to many manual errors and requires a
certain experience and routine.
A second possibility is the semiquantitative estimation of platelets by means of the
Fonio method. This method allows an orientation evaluation of the cell count and an
accuracy check of the automatic count. With a 1,000-fold magnification (eyepiece 10,
lens 100), one platelet per display is equivalent to twenty-thousand platelets/μL in
circulating blood. In case of a discrepancy between the automated analysis and the
estimated value, the chamber count should be used.
Immunological marking of platelets with specific, monoclonal antibodies is a good
possibility to check the value but unfortunately, it is also very expensive and not
always suitable for routines.
Another alternative to check the platelet value is a staining of platelets by means of
an RNA fluorescence dye. The platelet RNA will be stained and – based on the fluo-
rescence activity and the volume of cells – the exact platelet value, including giant
platelets, will be determined by automation. Most Sysmex instruments integrate RNA
staining of platelets as a method and, in case of interferences, switches over to the fluo-
rescence platelet value – by means of an automatic algorithm.
Parameters facilitating platelet histogram interpretation:
Aside from an evaluation of the histogram, there are also different additional parameters
such as P-LCR, MPV, PDW and PCT, providing a multitude of information on platelet
morphology.

4. 4Sysmex Xtra Online | June 2011 | 6 pages
Platelet distribution curves: interpretation, potentials and limitations
P-LCR (platelet large cell ratio)
The P-LCR indicates the percentage
of large platelets with a volume > 12 fL.
Aside from the two flexible discrimina-
tors which delimit the volume distribu-
tion curve, there is additionally a fixed
discriminator at 12 fL (Fig. 4). The share
of platelets >12 fL in the total platelet
number is presented in %. The standard
range is 15–35%. An increase of the pa-
rameter may be an indication for platelet
aggregates, microerythrocytes and giant
platelets.
PDW (platelet distribution width)
The PDW indicates the platelet distri-
bution width measured at 20% relative
height of the total height of the curve
(Fig. 5). An increased PDW is an indica-
tion for the anisocytosis of platelets.
Standard PDW ranges from 9 to 14 fL.
MPV (mean platelet volume)
This parameter provides a statement
on the MPV between the lower discrimi-
nator PL and the upper discriminator PU.
The standard range is between 8–12 fL.
Pct (platelet crit)
The platelet crit is equivalent to the sum of platelet impulses which are individually
detected by means of the impedance measurement principle and thus it is the
equivalent to the haematocrit of the red blood cells. If there is an abnormal height of
the volume distribution curve at the lower or upper discriminator so that one or several
of the indicated parameters can no longer be determined, the parameters will be
marked by ‘- - -’; the platelet value will be marked and the analyser generates an alarm.
In this case, the histogram curve must be checked for correctness of the result. For
a more precise evaluation of a platelet histogram, the curves can be divided into three
different categories. We call these curves A, B and C curves.
Fig. 4 Display of the P-LCR
Fig. 5 Display of the PDW
10 fL 20 fL 30 fL 40 fL
20%
12 fL PUPL
100%
10 fL 20 fL 30 fL 40 fL
20%
12 fL PUPL
100%
P-LCR
Referenzbereich 9–14 fL
PDW
Calculation
MPV (fL) =
Pct (%)
PLT (x 103
/μL)

5. 5Sysmex Xtra Online | June 2011 | 6 pages
Platelet distribution curves: interpretation, potentials and limitations
‘A curve’:
The platelet histogram starts at the base-
line but does not end there since there
is an interference with microerythro-
cytes. Due to the extremely small eryth-
rocytes, there will be no clear volume
separation between the two cell popula-
tions. Since, however, the overlapping
of both cell populations is approximately
the same on both sides of the discrimina-
tor, this platelet value can be used if the
MCV shows a standard value. In this case,
a chamber count would be statistically
much more imprecise.
‘B curve’:
Here again, the platelet histogram
does not end on the baseline. Deviation
from the baseline is major and there is
no separation between the two popula-
tions. There is a total overlapping of both
populations. A possible cause might here
be fragmentocytes. Fragmentocytes ‘slip’
into the platelet population and do not
allow any clear separation between red
blood cells and platelets. In any event,
this platelet value is questionable and
requires verification.
‘C curve’:
This case also requires verification of
the platelet value. The flexible upper dis-
criminator always looks for the optimum
place to separate the populations. How-
ever, due to giant platelets or micro-clots,
no clear separation can be found; instead,
there is major overlapping. The platelet
value should be verified, for example, by
means of the Fonio method.
Fig. 6 Display of the ‘A curve’
10 fL 20 fL 30 fL 40 fL
20%
PUPL
100%
Fig. 7 Display of the ‘B curve’
10 fL 20 fL 30 fL 40 fL
20%
PUPL
100%
Fig. 8 Display of the ‘C curve’
10 fL 20 fL 30 fL 40 fL
20%
PUPL
100%

6. 6Sysmex Xtra Online | June 2011 | 6 pages
Platelet distribution curves: interpretation, potentials and limitations
Sysmex Europe GmbH
Bornbarch 1, 22848 Norderstedt, Germany, Phone +49 40 52726-0 · Fax +49 40 52726-100 · info@sysmex-europe.com · www.sysmex-europe.com
Please find your local Sysmex representative address under www.sysmex-europe.com
Abnormal platelet distribution on the lower discriminator PL is rather rare. This will
be triggered by particles with a volume < 2 fL. Cause for it could be an increased blank
value, bacteria, fungi or cell debris. In this case, the instrument’s blank value should
be checked and, if necessary, the reagent should be replaced.
Potential platelet interference factors in impedance measurements
Giant platelets PLT ▼ n Evaluate histogram
n If necessary, check by Fonio method or chamber count
n Optical (Fluorescence platelets), if available
(e.g. XT-4000i, XE-5000)
Fragmentocytes PLT ▲ n Fragmentocytes and platelets have
no clear volume separation
n Evaluate histograms
n If necessary, check by Fonio method or chamber count
n Optical (Fluorescence platelets), if available
(e.g. XT-4000i, XE-5000)
Microerythrocytes PLT ▲ n Microerythrocytes and platelets have
no clear volume separation
n Evaluate histograms
n If necessary, check by Fonio method or chamber count
n Optical (Fluorescence platelets), if available
(e.g. XT-4000i, XE-5000)
Platelet aggregates PLT ▼ n Evaluate histograms
n With implausible thrombocytopenia,
clarify an EDTA-induced
n Pseudothrombocytopenia through
a second sample in citrate
Table 1