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Can the Sperm Class Analyser (SCA) CASA-Mot System for Human
Sperm Motility Analysis Reduce Imprecision and Operator
Subjectivity and Improve Semen Analysis?
Chey G Dearinga, Channa N. Jayasenab, Kevin Lindsayc
aEastern Institute of Technology, Taradale Campus, Hawkes Bay, New Zealand, 4112,
bAndrology Laboratory, Hammersmith Hospital, Imperial College NHS Trust, London,
United Kingdom, W120HS.
uUnaffiliated, Cornwall, UK.
Semen analysis is considered mandatory for suspected infertility in men though
its clinical value has recently become questionable. Sperm motility is an
essential parameter for semen analysis, though is limited by high measurement
uncertainty, which includes operator subjectivity. Computer-Assisted Sperm
Analysis (CASA) is recognised as able to reduce measurement uncertainty
compared with manual semen analysis. The objective of this study was to gather
the evidence to determine whether the Sperm Class Analyser (SCA) CASA-Mot
system could reduce specific components of sperm motility measurement
uncertainty compared with the WHO manual method in a routine diagnostic
single-laboratory setting. The criteria examined included operator subjectivity,
precision, accuracy against internal and external quality standards, and a pilot
sub-study examining the potential to predict an IVF fertilisation rate. Compared
with the manual WHO method on 4000 semen samples, SCA reduces but does
not completely eliminate operator subjectivity. This work suggests that SCA and
CASA-Mot are useful tools for well-trained staff that allow rapid, high-number
sperm motility categorisation with less analytical variance than the manual
equivalent. Our initial data on a pilot sub-study suggest that SCA motility may
have superior predictive potential compared with the WHO manual method for
predicating IVF fertilisation.
Keywords: SA, CASA, CASA-Mot, sperm, motility
Introduction
Semen Analysis (SA) is mandatory in the investigation of suspected infertility or
subfertility in men [1]. In addition to infertility, SA may provide stratification of the
probability of natural conception [2, 3], and be used as an aid for the selection of
appropriate Assisted Reproductive Technology (ART) [4, 5]. SA parameters vary
depending on clinical requirements, available technology, expertise and afforded
timeframes. The fundamental parameters are semen volume, sperm count, sperm
motility (SM) and morphology. The clinical usefulness of SA is limited due to large
within‐ and between‐subject biological variation [6] and the influences of a growing
number of environmental, lifestyle and socioeconomic factors [7-9]. SA is also hindered
by substantial analytical variance [10, 11]. The World Health Organisation (WHO),
with regular updated editions of its SA manual, has attempted to address analytical
variance concerns through promoting standardisation. However, evidence suggests that
this has not been universally successful [12-16]. SA is thus associated with a high level
of measurement uncertainty [17] which limits it’s clinical value.
SM may be considered to be a particularly limited analysis as it suffers from
both operator subjectivity and a lack of any traceable standard [18]. Also, SM is limited
in that many sperm are simply a ‘redundant fraction’ because very few post-coital
sperm reach the site of fertilisation [19, 20]. However, the few sperm that do reach the
site of fertilisation are aided by means of a motile flagella [20]. Because of this, it is
generally accepted that a high proportion of sperm that are immotile or exhibiting poor
motility will adversely affect male fertility [21]. SM is thus, considered an essential
parameter of SA in spite of its limitations. Historically, SM has been categorised into
four grades of motility based on velocity [22]. However, in 2010 the WHO
amalgamated two grades, creating a simpler three grade system [23] in response to
operator difficulties in accurate classification of sperm velocity [24]. This
reclassification removed velocity as a measure, and was not adopted universally [25]. It
has proved highly controversial [26] and may have even decreased the clinical value of
SA [17]. Certainly evidence supports that sperm velocity is a useful variable [27-30]. A
solution to high analytical variance and operator difficulties in accurate classification of
sperm velocity is to replace manual elements of analysis with automation. Development
of computer assisted sperm analysis (CASA) has resulted in systems that are capable of
analysing vast numbers of sperm in short time frames [31, 32]. However, in spite of the
enormous potential of such systems, they remain largely underutilised in clinical
diagnostic laboratories [32].
The objective of this study was to compare the SCA CASA-mot system with the
WHO method for SM in a single laboratory setting. While a full validation of SCA
CASA-Mot was beyond the scope of this study, we wanted to examine operator
subjectivity, precision, and performance against external and internal standards. In
addition, we sort to perform a pilot sub-study to compare SCA CASA-Mot with WHO
SM for predicting IVF fertilisation.
Methods
Study Population and Samples
A total of 4422 men attending the Andrology Laboratory (Andrology
Laboratory, Hammersmith Hospital, Imperial College NHS Trust, London, UK) for SA
were included in this study. Azoospermia cases were excluded for all experiments.
Asthenozoospermia cases were excluded for all experiments with the exception of
experiment two.
Samples were produced by masturbation into non-toxic plastic containers at
room temperature (23 0C ± 3 0C) in private collection rooms adjacent to the laboratory
after 2–8 days abstinence. Samples were analysed after liquefaction (30–60 min) at
room temperature. After mixing, a 5 µm aliquot was transferred with a glass capillary to
a Leja 20µm chamber (20µm Leja slides, Leja; Gynotec Malden, Nieuw Vennep, The
Netherlands. After allowing flow within the specimen to cease, samples were analysed
on a heated (37 ± 0.10C) microscope stage.
For the IVF fertilisation pilot sub study 55 cases were included after exclusion
of men with female partners receiving IUI (9 cases), ICSI (73 cases), use of
frozen/thawed sperm (9 cases) and significant SCA sperm tracking error (one case).
Stimulation method was not examined as a factor but included GnRH antagonist (25
cases) and GnRH analogue (30 cases).
SCA Spermatozoa Motility
The SCA (SCA version 4.1, Microptic, S.L. Viladomat, Barcelona, Spain) system used
has been validated for count [33] against the WHO recommended [34] Improved
Neubauer Haemocytometer. The microscope used with SCA is an Olympus BH-2
(Olympus, Southend-on-Sea, UK), used with an x10 phase objective with no
magnification in the trinocular head. SCA accommodates frame rates between 25-100
frames/second. Acquisition parameters for all current experiments are 25 images
acquired at an acquisition rate of 25 images per second.
WHO Spermatozoa Motility
In order to include Grade a motility in this study, WHO SM was performed using the
1999 WHO method [22] under phase contrast at 200x magnification. Operators were
four experienced (3-25 years) technicians who participated in quality control (QC) and
external quality assurance (EQA) processes in a laboratory which performs SA on 90-
225 samples per week. In the UK, SA EQA is provided by the UK National External
Quality Assessment Service (NEQAS). The Andrology Laboratory and has never been a
poor performer in the EQA scheme.
Experiment 1: Motility Comparisons
Separate aliquots from 225 patient’s samples were analysed for SM by four
trained operators using the WHO method and by one operator using SCA. WHO and
SCA operators had no view of each other’s workstation and analysed samples
contemporaneously using different chambers. Results were recorded independently and
collated at the end of the experiment.
Experiment 2: Operator Subjectivity Comparison
SM operator subjectivity was estimated by collating and analysing 10 months of
sequential patient SA results (n=4000) from our laboratory. Each operator (n=4)
provided 1000 patient SA results, 500 for SCA and WHO methods respectively.
Operator subjectivity was estimated for SM grades a, b, c, d and a+b by calculating the
probability that individual operator SA results originated from the same distribution.
Experiment 3 Precision and Internal Standard Comparisons
Digital videos (n=10) were created from single ejaculates from men (n=10)
using the SCA system. Each video comprised of 10 microscope fields of view, each of
which were 15 seconds long in duration, giving a total duration of 150 seconds per
video. In an effort to estimate realistic variance in a diagnostic laboratory, operators
(n=4) analysed videos during the same sessions as they performed routine SA on
patients samples. Videos were analysed prior to beginning SA for the session and after
each sixth patient’s sample. Videos were randomly selected for each analysis and
operators did not have access to their own or other operator’s results. Each operator
recorded a minimum of 10 repeats for each of the 10 videos.
WHO and SCA motility within-operator precision profiles were calculated from video
results and compared. Precision was calculated using coefficient of variation (CV%).
Each CV% calculation consisted of 400 sperm (200 analysed twice). CV% was
calculated for each operator and SCA for each motility grade for each the 10 videos,
giving a total of 160 within-operator comparisons per method..
Each video was also given an internal standard result. This was achieved during group
sessions were every individual spermatozoa on each video was examined. During
examination SCA motility tracks were viewed and measured on the video screen with a
string ruler calibrated against a stage micrometre. Each sperm and track was repeatedly
viewed and measured until all four operators reached consensus upon the correct WHO
grade classification.
Experiment 4: External Standard Comparison
NEQAS samples for SM are videos of neat semen prepared by the NEQAS
Reproductive Science Scheme (Reproductive Medicine, Andrology Laboratories, Saint
Mary’s Hospital, Manchester, UK). A total of 32 NEQAS videos representing 2 years
of EQA (distributions 213 to 252) were analysed for SM by one operator using the
WHO method and by SCA. NEQAS videos do not run on SCA. SCA analysis was
performed by focussing a camera lens (Penatx, TV Zoom Lens 12.5-77mm 1:1.8) on a
computer screen playing the videos at a distance of approximately two meters from the
camera.
Experiment 5: Predicting IVF Pregnancy
The WHO SM method was compared with SCA for predicting IVF fertilisation
in a blinded design by using two separate clinics. SA was performed at one clinic (The
Andrology Laboratory), while IVF treatment was performed at a separate clinic (IVF
Hammersmith, Hammersmith Hospital, London, UK). The SA was a pre-treatment
fertility workup sample used to aid ART selection. The same chamber was used for both
analyses. The WHO method was performed first followed by the SCA method with no
time delay. After exclusion (see study population above) 55 SA results from patients
who attended the Andrology Laboratory and produced a single ejaculate for fertility
workup prior to their female partners IVF treatment were collated. All collated SA
results were matched with female partners IVF outcomes provided by the IVF treatment
centre. Data provided by the IVF treatment centre precluded any other analysis.
Experiment 6: Error Assessment
Spurious motility (SCA motility signals recorded from stationary objects) was
examined by performing SCA analysis on heat treated immotile sperm. 16 samples were
prepared in chambers and heat immobilised by placing chambers on a hot plate at 60 0C.
SCA analysis was performed 160 times (10 replicates on each of 16 chambers, one per
patient).
Statistics
Distributions were tested for normality with descriptive statistics and the
D'Agostino and Pearson omnibus normality test to examine suitability for parametric
testing. Correlations were performed by Spearman’s rank correlation and regression
calculated using Deming regression. Bland-Altman plots were constructed to test for
bias. Coefficient of Variation (CV%) was calculated from a minimum of 10 replicates
for each category examined. The Wilcoxon matched pairs test was used to compare
SCA and WHO categories. Receiver Operator Characteristics curves were used to
compare WHO and SCA for IVF fertilisation prediction. Operator subjectivity was
estimated by the Kruskal–Wallis test by ranks with Dunn's Multiple Comparison Test as
a post hoc test. All data were analysed using Prism version 4.0 (GraphPad Version
4.01,San Diego, CA, USA, www.graphpad.com).
Results
Experiment 1: Motility Comparisons
On patients samples (n=220), SCA compared with the WHO method recorded lower a
grade motility (SCA median = 12, WHO median = 43, p<0.001), higher b grade (SCA
median = 11.5, WHO median = 9, p<0.001), higher c grade (SCA median = 13, WHO
median = 5, p<0.001) and higher d grade motility (SCA median = 62, WHO median =
41, p<0.001). Only a class (r=0.58 p<0.001) and d class (r=0.63, p<0.001) correlated
between methods. Bland Altman plots demonstrated proportional bias with each WHO
grade.
Experiment 2: Operator Subjectivity Comparison
The assessment of between operator variance demonstrated that SCA does not
fully eliminate between operator variance. However, variance between operators is
much reduced in comparison with the WHO method (Figure 1).
Figure 1. Operator Subjectivity for Sperm Motility WHO vs SCA
0 20 40 60 80 1000
1020304050607080 Operator WHO
Operator SCA
SCA p=0.18 (4.92)
WHO p<0.0001 (61.76 Kruskal-Wallis statistic)
Number* of significant post hoc tests
0*
4*
Percentile
Gra
de a
(%)
0 20 40 60 80 1000
10
20
30
40
50
SCA p=0.0319 (8.82)
WHO p<0.0001 (88.46) 5*
1*
Percentile
Gra
de b
(%)
0 20 40 60 80 1000
10
20
30
40
SCA p=0.0005 (17.72)
WHO p<0.0001 (57.46)
2*
3*
Percentile
Gra
de c
(%)
0 20 40 60 80 1000
20
40
60
80
100
WHO p<0.0001 (37.37)
3*
SCA p=0.0048 (12.91)1*
Percentile
Gra
de d
(%)
Figure 1. Individual operator (n=4) SM grade percentiles from SA results (n=4000) are
presented. WHO (n=2000) and SCA (n=2000) methods are compared with p values
(Kruskal-Wallis statistic) and the number* of significant post hoc tests.
Experiment 3 Precision and Internal Standard Comparisons
For within-operator variance, SCA was more precise than the WHO method
(Figure 2).
0 10 20 30 40 50 60 70 80 9005
10152025303540455055
WHOSCA
Mean Motility %
CV
%
Figure 2. WHO vs SCA precision profiles (mean and 95%CI are shown)
For all 10 videos, the WHO method overestimated motility and SCA was generally
closer to consensus results. This was most apparent for grade a motility (figure 3).
WH
OC
onse
nsus
SCA
WH
OC
onse
nsus
SCA
WH
OC
onse
nsus
SCA
WH
OC
onse
nsus
SCA
WH
OC
onse
nsus
SCA
WH
OC
onse
nsus
SCA
WH
OC
onse
nsus
SCA
WH
OC
onse
nsus
SCA
WH
OC
onse
nsus
SCA
WH
OC
onse
nsus
SCA
0
10
20
30
Video Video Video Video Video Video Video Video Video Video 1 2 3 4 5 6 7 8 9 10
WHOConsensusSCA
Gra
de a
%
Figure 3. a class motility, SCA exhibited lower variance and values closer to internal consensus.
Experiment 4: External Standard Comparison
SCA and WHO methods were similarly close to NEQAS designated values for c
and d grade motility, neither method produced results father than two standard
deviations from the NEQAS designated values. For NEQAS samples with greater than
20% grade a sperm, SCA recorded a proportionally lower number of grade a sperm
compared with the WHO method and NEQAS designated values. SCA categorised a
higher proportion of grade b sperm at these values (Figure 4).
Figure 4. Two years of SCA and WHO with NEQAS
0 10 20 30 40 50 60 70 80
0
25
50
75
100
NEQAS 2SDWHOSCA
NEQAS
NEQAS Designated value
Rap
id (
Gra
de a
)
10 20 30 40 500
25
50
75
NEQAS Designated value
Slu
ggis
h (G
rade
b)
5 10 15 20 25 30-10
0
10
20
30
40
50
NEQAS Designated value
Non
Pro
gres
sive
(G
rade
c)
10 20 30 40 500
25
50
75
NEQAS Designated value
Imm
otile
(G
rade
d)
Experiment 5: Predicting IVF Fertilisation
Female partner median and interquartile range data on this cohort were as
follows: age 36 years (31-38), number of oocytes per retrieval 9 (6-14), oocyte
fertilisation rate 67 % (50-85), cycle number 1 (1-1). Male partner median and
interquartile range data on this cohort were as follows: semen volume 3.1 mL (2.2-3.8),
count 59 x106/mL (38-79), progressive motility 50% (41-62), total motility 60% (52-
70), days of abstinence 3 (2-3).
ROC analysis using the median fertilisation rate of 67% as a binary diagnostic
threshold (28 cases positive and 27 cases negative) demonstrated that semen analysis
motility from a single pre-treatment sample is predicative of fertilisation rate at
treatment. Both progressive (p=0.027) and total motility (p=0.018) from SCA produced
significant areas under the curve. Motility the WHO method was not significant (Table
1).
Variable ROC Area 95% Confidence Interval
Lower Bound Upper Bound p
WHO Progressive Motility .594 .441 .747 .232
WHO Total Motility .558 .403 .712 .464
SCA Progressive Motility .673 .527 .820 .027
SCA Total Motility .685 .541 .829 .018
Figure 3. SCA motility was a greater discriminator of IVF success than the WHO
manual method
Experiment 6: Error Assessment
SCA erroneously recorded motility on 4.7 % (95% CI 3.8 – 5.7) of heat
immobilised sperm which correlated (p=0.02, r=-0.35) with sperm count. By WHO
classification motility was; a class motility = 0.03 % (0.0-0.7), b class motility = 1.3 %
(1.1-1.5), and c class motility = 3.1 % (2.7-3.5).
Discussion
The primary aim of this study was to compare SCA CASA-Mot with the WHO method
for SM in a single laboratory setting. We also sort to examine operator subjectivity,
precision, performance against external and internal standards. Also, as a pilot sub-
study, we compared SCA with WHO for predicting IVF fertilisation. Our evidence
suggests that SCA CASA-Mot in comparison with the WHO method; (1) decreases
operator subjectivity, (2) offers greater precision, (3) produces results that are closer in
agreement to an internal standard, and (4) produces results that are similar in agreement
to an external standard. In addition on limited preliminary evidence, SCA CASA-Mot
compared with the WHO method may offer greater diagnostic potential for appropriate
ART selection. However, SCA is not a “black box” technology and cannot be used
without specific training, both in SA and in the use of CASA-Mot.
Our results on a large dataset (n=4000) suggest substantial operator subjectivity for SM
with the WHO method. In comparison, SCA reduces but does not fully eliminate
operator subjectivity. Central tendency calculations are recognised [35] SA quality
tools, and are established methods for examining bias [36, 37]. The advantages are that
operators are blind to this quality assessment and a complete data set of actual SA
results can be examined. Additionally, uncertainties related to differences between
patient samples and quality material (Alvarez et al., 2003) and concentration levels [38]
are avoided. However, observation numbers, timeframes, changes in patient
populations, equipment, consumables or testing environments are all possible
confounding factors [35]. While seasonal effects on semen parameters have been
reported [39, 40], the combined central tendency measures for our laboratory did not
deviate with season. Other than the use of SCA, nor were there changes in equipment or
consumables. The operators involved in the current study were trained, experienced
staff who participated in robust quality assurance practices and the laboratory has never
been a poor performer in the EQA scheme. CASA-Mot appears more consistent than the
manual equivalent though operator variation remains a significant source of error, which
is similar to previous findings [41]. Moreover, we believe that this may not be apparent
in quality systems without similar large dataset analysis. We suggest that CASA-Mot is
preferential to the WHO method for controlling SM operator subjectivity.
This current study used operator consensus values as a quasi internal standards
as SM lacks any true traceable standard [18]. These internal standards, where a group of
trained experienced operators achieved WHO classification consensus for each
spermatozoa, were closer to SCA than WHO results. These findings are in accordance
with previous studies highlighted that sperm motility is subjective [24, 42] and easily
overestimated [24, 43]. Most notably from our results, only SCA was able to distinguish
a grade motility with reliability, which is similar to findings with other CASA-Mot
systems [24]. This is important as evidence clearly supports that sperm velocity is a
useful variable [27-29]. Considering recent reports that the loss of velocity as a SA
variable has increased clinical uncertainty [17], we believe that CASA-Mot increases
the usefulness of SA.
We used an EQA scheme as an external standard and observed SCA achieved
similar agreement as with the WHO method, though also noted SCA records
proportionally lower grade a and higher grade b motility. These differences between the
WHO and SCA methods with NEQAS designated values has striking similarity to the
differences observed when both methods are compared with our internal standard
results. Our internal standard results clearly demonstrates that the WHO method
overestimates grade a motility. We believe the NEQAS designated values are similarly
overestimated. Moreover, as we demonstrated operator subjectivity is reduced with
SCA, EQA results may improve for laboratories with multiple operators who adopt
CASA-Mot analysis. The introduction of CASA has been favoured by several authors
[43-46] and we support this view from these results.
Precision with the WHO method was comparable [47] or higher [42, 48] than
previously reported between-operator variances for sperm motility. However, unlike in
previous studies, operators were required to perform this analysis under significant time
demands in a busy working laboratory. Additionally, the assessment was not part of a
training scheme [42, 48], not part of our internal quality control practices. It is
interesting to note that the same operators when performing our internal quality control
for SM (quite separate from this study), use a CV upper limit of 10% and are routinely
well below this threshold. This is similar to results produced by well-trained operators
during training schemes [42, 48]. We believe operators using WHO methods are
capable of achieving very reproducible results, however the results of our study are an
accurate reflection of WHO method imprecision on patient samples in a busy
laboratory. In contrast, SCA proved to offer greater precision than the WHO method.
Thus, CASA-Mot is preferential in terms of precision compared with the WHO method.
It was beyond the scope of this work to attempt to provide any SCA values that
can be applied to any populations of interest. However, the results of a pilot-sub study
on IVF fertilisation prediction from motility on 55 couples comparing SCA and the
WHO method are interesting: Only the SCA produced significant ROC areas. While
this data is preliminary and indeed limited, we believe that SCA motility with decreased
operator variance and increased precision may offer greater diagnostic potential than the
WHO method. Further work on this is warranted. There are limitations from this current
study. We have not fully validated SCA, which may require plotting sperm tracks on
acetate sheets to verify velocities and examining errors where sperm collide or
encounter other particles. We used a frame rate of 25 frames s-1 and 60 frames s-1 or
faster are often preferred [49]. However, this appears to be less of a concern with the
aim of reducing operator variance [50]. Additionally, we observed when increasing the
frame rate (SCA allows users to select between 25-100 frames s -1) increasing velocity
parameters and thus decided to employ the more commonly reported 25 frames s-1
In conclusion, SCA CASA-Mot offers less operator subjectivity, greater
precision, and is closer in agreement to an internal laboratory standard than the WHO
method. SCA CASA-Mot can be used with a video based EQA scheme with
comparable results to the WHO method. We believe from limited evidence that SCA
CASA-Mot may offer greater diagnostic potential for appropriate ART selection
compared with the WHO method. Considering the continuing questions concerning the
usefulness of SA, we believe that CASA-Mot should be trialled by more laboratories
and that operator subjectivity should be a parameter specifically examined during the
trial.
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