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Simple optical method of qualitative assessment of
sperm motility: preliminary results
Agnieszka Sozańska a, Krystyna Kolwas a, Jacek Galas b, Narcyz Błocki b, Adam Czyżewski b
a Institute of Physics Polish Academy of Science, Al. Lotników 32/46 PL-02-668 Warsaw, Poland
bInstitute of Applied Optics, Kamionkowska 18, PL-03-805 Warsaw, Poland
P h a s e p la te
INTRODUCTION
In humans, as in animal species, the relationship between semen characteristics and in vivo
or in vitro fertility outcome is not very clear yet. Motility is commonly believed to be one of the
most important characteristics associated with the fertilizing sperm ability. In many laboratories
the sperm mobility assessment is made with use of a conventional microscope observation by
trained personnel according to rather subjective criteria due to the individual skill of a person
performing the analysis. During such estimation of concentration and of mobility of sperm cells
the important errors can be introduced. In particular the subjectivity of the analysis makes any
comparison of results difficult or impossible.
The purpose of this study was to find some simple, cheap, objective and repeatable method
for the semen motility assessment which can be used in a common storage centres as well as for
our further experimental trials. We have proposed the method of the processing of the optical
contrast of the sperm images illustrating dynamics of the sperm cells movement and the
appropriate analysis of a grey scale level of the superimposed images. The elaborated numerical
algorithm gives us information about the amount of relative sperm motility.
The presented method of sperm motility assessment is a process that involves three
successive steps. The first one concerns the sample preparation (washing, dilution,
centrifugation, etc.); the second one concern the image acquisition with use of the negative
phase-contrast microscope connected to the CCD camera; and the last one is about the image
acquisition and the processing method.
Specimen staining, microscope magnification and system optics have been chosen
to maximise the properties of the data stored by a PC computer coupled via the fire-wire
connection to the camera. Those parameters are essential and are known to be able to change
significantly the results of measurements.
O b je c tiv e
Condenser
Im a g in e p la n e
S p e c im e n
C o n d e n s e r a n n u lu s
Fig.1. Phase Contrast Microscope Scheme
For sperm visualization dynamics we used the negative phase contrast microscope integrated with a
CCD camera connected to a PC computer via fire wire connection.
The phase contrast microscope is equipped with two additional components in comparison with the
traditional amplitude microscope:
• a phase plate in the form of the ring (Fig.1) that retards light by exactly 1/4 wavelength
in the centered, ring-shaped area located at the back foal plane of objective lens
• a matching phase annulus (Fig.1) consisting of a clear ring on a black field located in
the condenser
N u m b e r o f firs t fra m e
RESULTS
Sperm motility was registered for each sample for diluted and non diluted spermatozoa at
the beginning of the experiment (zero starting time), and repeated after the same periods of time:
30 min, 1 h, 1.5 h. During this process the samples were incubated in temperature of 37°C in the
water bath.
After numerical processing of all the frames movie we can see spermatozoa as some white
spots (see Fig. 2) with high contrast on a black background. The whiteout area corresponding to
sperm cells are displayed with much better contrast than at the original images from the phase
contrast microscope (compare Fig.2).
White o ut a re a
p e rc e nta g e
Num ber of
fra m e s
F re q u e n c y o f
im a g e a q u is itio n
Fig.2. Comparison of pictures frames before (the left one) and after setting the threshold
value (the right one).
Evaluation of the gray scale level for the total area of the superimposed frames in
comparison with the first one gives as the information about motility of the sperm cells in
percents. For immobile cells the measured change in the total gray scale level would be 0%.
Fig..4. The calculation of sperm motility for ten samples with
proposed procedure for several times of incubation
100
Fig.3. A working window of the analysing program in use.
The output percentages the total gray scale level gives us the relative motility of the
sperm cells allowing for studying the changes of the sperm vitality due to some external
factors with precision corresponding to the accuracy of the measurement (less than 1%).
Fig. 3 presents a program window illustrating some sample data after numerical processing.
A
B
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Motility 0min.
Motility 30 min
Motility 1h
Motility 1,5 h
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Since our statistics is not very rich, we use the Empirical Rule for data sets: that is a normal,
bell-shaped distribution with approximately 95% of all the data falling in the range of errors
bellow the two standard deviation (2) of the mean (<x>). We assume for the value of c:
c 
95 %
W max
where Wmax is the maximum value of whiteout percentage found in our experiment.
Such a choice of c value allows as to introduce a common scaling for our motility
measurements. We find our hypothesis valid because the deviation from the mean
value is small for every experimental trial.
C
D
Fig. 5. Comparison of kinematics profiles of spermatozoa (A, B – circling tracks corresponding
to hyperactivated and damage sperm cells, C – long tracks, D- ideal tracks corresponding to
non-hyperactivated sperm cells).
The method presented in this study can be applied to:
• sperm motility assessment
• sperm tracks detection and analysis, which could gives us interesting information about the state
of spermatozoa and its morphological condition.
Conclusions:
The method presented here provides a new simple solution in analyzing sperm quality with results
comparable in accuracy to some more expensive methods. We plan still to improve the method using
still more reach statistics of the results. We also plan to continue studies of sperm motility under
different conditions.