Improving Characterization of Porous Scaffolds:
SEM vs. Two Photon Confocal Microscopy to
Estimate Average Pore Diameter
Ekanki Saxena

Abstract—Tissue engineering has achieved much when it comes
to scaffold fabrication techniques. However, there has been a lack
of attention on improving characterization techniques to assess
the success of scaffold fabrication techniques. The use of SEM to
estimate the average pore diameter of a three-dimensional scaffold
is still the primary technique. This paper examines the use of two
photon confocal microscopy to determine the average pore
diameter of a porous polycarbonate polyurethane scaffold. Thus,
this paper will compare characterization accuracy of the two
techniques: SEM and two photon confocal microscopy. Also
developed here is a statistical model to extract the characteristic
pore diameter of a particular scaffold, and to assess its closeness
to expected pore diameter values. The statistical model can serve
as a tool to evaluate the success of different fabrication
procedures.
Index Terms—biomaterials, dansyl, pore diameter, scaffold
characterization.
I. INTRODUCTION
micro-structural properties of the three dimensional construct
that are key are porosity, pore diameter, pore shape, pore
interconnectivity, and surface area-to-volume ratio[2].
Required pore diameter is primarily predetermined by the
application of the scaffold. Each cell type has a characteristic
diameter in suspension, which is used as a guideline to set a
pore diameter requirement[1]. Fibroblasts, which are required
for many applications like dental mucosa, generally require 515μm[1] for proper in-growth.
This paper briefly summarizes general techniques used to
obtain a porous scaffold. The main focus is on solvent casting
and particulate leaching, and a development of a statistical
model to characterize the average pore size of a threedimensional scaffold. It is critical to assess the success of a
particular fabrication technique to achieve a desired average
pore size. The two techniques used to measure average pore
diameter were scanning electron microscopy and two photon
confocal microscopy. The resulting measurements were
compared for accuracy in predicting average pore diameter; in
this way the best method of measurement was deciphered.
T issue Engineering is the all-encompassing header for the
guided regeneration of tissue with the aid of a threedimensional scaffold. The general principles behind tissue
engineering are: a polymer resin is synthesized and moulded
into an appropriate shape, cells from the patient are cultured in
vitro and seeded onto the construct, and then the structure is
implanted into the patient to replace damaged tissue. The
eventual goal of this construct is to regenerate damaged or
non-functional tissue by the growth of seeded cells, and the
eventual resorption of the biomaterial. There are obviously
many requisite constraints on the ideal scaffold, in order for it
to optimally perform its intended function. Some of these
constraints include biocompatibility, biostability, mechanical
strength, surface chemistry, cell adhesion, cell proliferation,
resorption of the biomaterial in vivo, and permeability.
Inarguably, many of these constraints are dependent on pore
diameter[1].
The main purpose of pores in the scaffold is for the ingrowth of seeded cells. In addition, control of pore size is
needed for cell migration, mass transport of nutrients and
wastes, and vascularization[1]. In this effect, some important
II. MATERIALS PREPARATION
A. Scaffold Fabrication Techniques
Some previously used scaffold processing techniques include:
gas foaming[1], phase separation[1], emulsification and freezedrying[4], rapid prototyping, IPC Production[1], and solvent
casting and particulate leaching[1]. Amongst these various
techniques, solvent casting and particulate leaching is the most
prominent for fabricating a porous three-dimensional scaffold
[1], [2], [3], [4].
A modified method, derived from particulate leaching was
used to fabricate a polycarbonate polyurethane with spherical
pores. Paraffin sphere foam was prepared using previously
described techniques[10]. The paraffin spheres had a particle
diameter distribution of 150 – 180 μm. A polymer made of
dansylated lysine diisocyanate and polycarbonate diol was
made in DMAC solvent, and added to the paraffin sphere
mould. The solvent was later evaporated. The paraffin was
removed according to methods previously detailed[10].
2
B. Scanning Electron Microscopy
The sample examined by SEM was sliced to reveal the centre
surface. The sample was dried in ethanol, and coated with
platinum in preparation for viewing with SEM.
C. Two Photon Confocal Microscopy
A dansyl label was attached as a pendent group to lysine. This
fluorescent molecule is attached for viewing the porous
scaffold with the confocal microscope. Dansyl molecule
attachment is easily incorporated into previously described
scaffold fabrication techniques. The molecules disperse evenly
throughout the polymer along with the lysine.
Two photon confocal microscopy allows the viewing of
several levels of the sample. The image of each slice can be
examined to get a integral three-dimensional characterization
of the material. In this case, the diameter of several selected
pores will be measured at several levels, and then this data will
be used to determine the average pore diameter in the polymer
scaffold.
D. Measurement of Pore Diameter – Raw Data Collection
Software was used to measure the diameter of each pore, at
each slice of the image. 30 pores were selected at random for
both techniques (SEM & Confocal Microscopy). These pores
were followed through various slices for the samples analyzed
via confocal microscopy, and the changing diameters were
recorded. The diameter raw data was put through the
developed statistical model, in order to get an estimate of
average pore diameter (see Figure 1). The sample analyzed via
SEM was cut into half, so the inner surface was exposed. Raw
data was collected from the image of this surface.
was measured was recorded. These maximum diameters
served as the raw data for the confocal microscopy technique.
For SEM, only one surface was examined, and 30 pore
diameters were measured on this surface, and served as raw
data.
A histogram was constructed using this raw data, with 10
classes. A test was performed to assess the goodness-of-fit of
the data to a Gaussian PDF. Once this Gaussian nature of the
data is confirmed, then significance tests and statistical
analysis can be carried out using the raw data. (Refer to Figure
1 for data handling procedure.). Goodness-of-fit was assessed
via a Χ2 test. Figure 2 and Figure 3 show the histograms
constructed for each of the two characterization techniques.
Statistical analysis was performed using the two-sided z –
test for both mean, and standard deviation. The average pore
diameter and standard deviation was calculated, along with the
95% confidence interval around both values. The hypothesis
test on the mean was performed using the two-sided t-test.
Chose N pores
Get the maximum
diameter after
examining all slices,
for each pore.
Diameter – raw data
III. STATISTICAL MODEL DEVELOPMENT
A. Assumptions
It was assumed, based on evidence provided by Shum et. al.,
that the pores were spherical. Also, in accordance with the
paraffin sphere fabrication techniques, it was assumed that the
spheres were within the diameter range at which they were
sieved. The diameter measurements that were recorded (raw
data) were taken as “error-free” or independent variables. It
was further assumed that the particle diameter was a Gaussian
random variable. Based on these assumptions the mean pore
diameter could be calculated, and significance tests could be
performed on the final estimate of average pore diameter to
determine the confidence interval. The mean and standard
deviation values were used to compare the two characterization
techniques.
B. Model
In this paper, the two photon confocal microscope provides 5
slices of the material, or 5 diameters for each pore selected for
examination. After choosing 30 pores on the images, the
diameter of each of the chosen pores was measured as it
changed from slice to slice. Once all the slices have been
examined, for each of the 30 pores the maximum diameter that
Construct a histogram
for maximum pore
diameter (i.e. on the
basis of the raw data).
Calculate mean pore
diameter based on this
raw data, and perform
significance tests.
Fig. 1. Schematic of Statistical Model and Data Handling
IV. RESULTS
A. Goodness-of-fit to a Gaussian PDF
The goodness-of-fit test answers the question whether the
Gaussian PDF closely approximates the raw data distribution.
The chi-square test gave a p-value value of 0.879 (see Table
2) for the confocal microscopy data. This p-value is greater
than the threshold value of 0.05, and therefore the null
hypothesis can be accepted, that there is no significant
difference between the raw data distribution and the theoretical
Gaussian PDF. The chi-square test gave a p-value of 0.00045
for the SEM data. This p-value is less than the threshold value,
3
and therefore, the null hypothesis must be rejected. The SEM
data does not closely approximate the Gaussian distribution.
Even though the SEM data does not conform to the
Gaussian PDF, it is known that the particle distribution of the
paraffin spheres was Gaussian. Therefore, it was on the basis
of the assumption that the underlying PDF is Gaussian, that
further statistical analysis was performed on the SEM raw data.
Number of Pores
Histogram - SEM Raw Data
8
7
6
5
4
3
2
1
0
V. CONCLUSION
152 155 158 161 164 167 170 173 176 179
Midpoint - Pore Diamter (μm)
F
ig. 2. Histogram – Pore Diameter for SEM data.
Histogram - Confocal Microscopy Raw
Data
Number of
Pores
made here was that the population (i.e. paraffin sphere particle
size distribution) was a Gaussian random variable, with a
population mean equal to the median, which is 165 μm.
Ho: μ = 165 μm
z = 0.1444
The p-value was determined to be 0.557, which is a lot
greater than 0.05, and therefore, the null hypothesis can be
accepted. Thus the sample average pore diameter is very close
to the population average diameter, when assessed using
confocal microscopy.
Similarly, the average pore diameter determined using the
SEM raw data was also tested.
Ho: μ = 165 μm
z = -37.83
The p-value in this case was approximately 0, which is less
than the threshold value of 0.05. Therefore, in this case the
null hypothesis was rejected. Thus, it can be safely said that
the determined average pore diameter is not characteristic of
the population average pore diameter of the scaffold.
6
4
2
0
152 155 158 161 164 167 170 173 176 179
Midpoint - Pore Diameter (μm)
Fig. 3. Histogram – Pore Diameter for Confocal Microscopy data.
B. Statistical Analysis
Using the confocal microscopy data, the average pore diameter
was calculated to be 165.2 μm. The 95% confidence interval
about the mean was calculated to be 6.54 μm. The standard
deviation was calculated to be 7.6 μm. The 95% confidence
interval about the standard deviation was found to be 4.16 μm
(see Table 1).
Using the SEM data, the average pore diameter was
calculated to be 112.6 μm. The 95% confidence interval about
the mean was calculated to be 21.63 μm. The standard
deviation was calculated to be 39.48. The 95% confidence
interval about the standard deviation was found to be 34.08 μm
(see Table 1).
C. Hypothesis Test of the Mean of a Normal Distribution
A hypothesis test was also performed to assess the departure of
the sample mean from that of the population. The assumption
Currently, one of the best methods to estimate average pore
diameter is the use SEM, followed by equations to determine
porosity. The limitations of SEM are that only one surface of
the scaffold can be examined, thus an accurate measure of pore
diameter, and in turn porosity, cannot be made using this
method.
The use of two photon confocal microscopy allows several
layers of the scaffold to be examined simultaneously, to
determine more precisely the average pore diameter of the
scaffold. The use of the statistical models described above
aids in determining whether this value is close to what was
expected during the fabrication procedure. Statistical analysis
on the confocal microscopy data found that the average pore
diameter (165.2 μm) in the scaffold very closely approximated
our expected pore diameter (165 μm). SEM data did not yield
an average pore diameter that was characteristic of the porous
scaffold, and thus it underestimated the pore diameter.
Accurately determining pore diameter is crucial to calculating
overall porosity[2], in addition to being a key method of
characterizing a three-dimensional scaffold.
It should be further noted, that all the maximum diameters
for the confocal microscopy data were within the particle size
distribution of the paraffin spheres. However, the pore
diameters as assessed by SEM varied over a wider range. This
is evident when the standard deviation of the raw data is
examined (see Table 1).
Therefore, this dansyl labeling technique and the use of twophoton confocal microscopy instead of scanning electron
microscopy is a definite improvement on the current scaffold
characterization methods. It provides a better estimate of
average pore diameter, with a smaller standard deviation, and a
narrower distribution as is demonstrated by the 95%
confidence intervals (see Table 1).
Other fabrication techniques besides solvent leaching can
utilize this model to determine whether the technique is
producing desired results. This model can serve as a tool to
4
optimize scaffold fabrication techniques, and move forward the
search for accurately predicting average pore diameters in
porous scaffold with consistency.
This model can be improved in two ways. Firstly, if more
layers of the material can be seen, then the maximum diameter
of each pore can be measured with increased accuracy. More
accurate measurements of pore diameter (raw data) will set the
stage for a more correct picture of average pore diameter in the
porous scaffold. Secondly, increasing the number of pores that
are examined (i.e. increasing the sample size of the raw data)
will also make the data more Gaussian, with a smaller standard
deviation or spread, so that estimated average value will
approach the population average value for pore diameter.
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Table 1: Values calculated for assessment of Raw Data: Mean, Standard
Deviation, 95% Confidence Intervals, goodness-of-fit statistics.
Scanning
Confocal
Electron
Microscopy
Microscopy
Average Pore Diameter (μm)
112.6 ± 10.82 165.2 ±3.27
Standard Deviation (μm)
39.48 ± 10.82 7.6 ± 2.08
95% Confidence Interval for Mean
21.64
6.54
95% Confidence Interval for SD
34.08
4.08
2
Goodness-of-fit (Χ0 )
26.28
3.066
Goodness-of-fit (p-value)
0.00045
0.879
[10]

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