Medical & Biological Engineering & Computing (2021) 59:1709–1721
https://doi.org/10.1007/s11517-021-02382-2
ORIGINAL ARTICLE
Gradient‑based impedance synthesis for breast and lung cancer cell
screening deploying planar and nano‑structured electrodes
Muhammad Awais Aslam1 · Kashif Riaz1
· Muhammad Mubasher Saleem2
Received: 3 December 2019 / Accepted: 8 May 2021 / Published online: 8 July 2021
© International Federation for Medical and Biological Engineering 2021
Abstract
World Health Organization articulated 9.8 million casualties globally in 2018 due to cancer. Cancer, as the world’s second
most fatal disease, can be recuperated well if diagnosed at an early stage. In this work, a gradient-based impedance synthesis
of normal and cancerous cells of breast and lungs, is demonstrated numerically for early-stage cancer detection. Low-voltage
single-cell level examination is employed for indomitable diagnosis. MCF-7 and MCF-10A are utilized as breast cancer
and breast normal cells, respectively; likewise, SK-MES and NL-20 are utilized as lung cancer and lung normal cell. Preexamination numerical setup validity ensured with multiple test regimes. Micro-scaled planar and nano-structured electrodes
are employed individually to witness the effect of the electrode’s structure during electrical impedance examination of cancer
and non-cancer cell. Frequency range, at which differential impedance effect is found detectable, for breast and lung cancer
cell pairs is determined to be 1­ 07 Hz and 1­ 08 Hz, respectively. By surpassing the conventional impedance spectroscopy with
tedious data fitting formalities, the gradient synthesis technique for cancer detection is introduced. The gradient synthesis
for cancer detection is found independent of electrode shape effect. Gradient for breast cancer cell is found to be 2 times
greater than the normal breast cell while for lung cancer cell it is found to be 1.5 times greater than the normal lung cell. Our
results suggest that as the frequency of applied electrical stimulus increases, impedance of cancerous cell falls at the rate
almost double than its counterpart normal cell. This work provides a theoretical basis for further experimental exploration
of gradient-based impedance synthesis in cancer therapy and serves as a design tool for performance optimization.
Keywords Breast cancer · Gradient impedance synthesis · Lung cancer · Nanospike electrodes · Single-cell analysis (SCA)
1 Introduction
Improvement in diagnostics results an increase in life expectancy, as more accessible and accurate way of blight detection leads towards rescuing millions of people all around the
world. Carcinogenesis is one of the exponentially growing
disorder as one out of 5 men and one out of 6 women is
diagnosed with cancer globally in 2018, reported by World
Health Organization (WHO). Early-stage cancer prognosis
can be a way forward to its successful annihilation.
* Kashif Riaz
kashif.riaz@itu.edu.pk
1
Electrical Engineering Department, Information Technology
University, Lahore 54000, Pakistan
2
Department of Mechatronics Engineering, National
University of Science and Technology, Islamabad 44000,
Pakistan
Most of the current cancer detection techniques are invasive, vacillating, non-reproducible, expensive, with labelled
detection, and have a very high false detection rate with
values up to 20–50% [1]. So non-invasive, explicit, less
expensive, reproducible, and label-free cancer detection
techniques are present day requirements [2–4].
Single-cell analysis (SCA) has proved to be a very efficient way to detect cancer. Instead of cellular assays, which
are accompanied with a large number of cells under examination and take the average values of results at the end,
single-cell-based examinations are more realistic and accurate against cellular malfunctioning which can efficiently
be interpreted afterwards [5]. This is because when a cell is
being disseminated through blight, i.e., viruses, bacteria, or
infection, its morphology changes and its electrical, chemical, biological, and adhesive properties also change [6]. If
one could manage to interpret electrical changes in a cell
like its impedance, capacitance, or conductance which are
directly related to the cell health, clear biomarkers could be
13
Vol.:(0123456789)
1710
obtained for diagnosis in comparison to other delayed and
inexplicit biological detection techniques [7].
Electrical impedance spectroscopy (EIS) of single cell
gives a detail insight into the cell, i.e., one can interpret cellular morphological, physiological, and pathological changes
inside the cell since the change in the cell health results in
corresponding change in impedance [8]. On the other side,
the effect of these electrophysiological variations takes time
to become prominent symptoms or detectable at tissue or
organ levels [9]. Moreover, the permittivity and conductivity variation with respect to frequency are not identical at
tissue level and cell level which ultimately results in contrast
behavior in their impedance results [10]. Moreover, multiple
cellular assays are more prone towards wrong or less accurate detection [11]. Thus, by single-cell impedance analysis,
cancer can be diagnosed at its incubation period.
Electrode shape is an important constraint in the impedance measurement of a single cell as impedance results are
different using different electrode shapes [12, 13]. In singlecell applications, effect of micro planar, circular, and rectangular electrodes along with electrodes with nano-protrusion
on cell has been discussed in detail in [12, 14, 15]. The
potential distribution across the cell is found best and almost
equal in the case of planar and circular electrodes than the
other shapes mentioned. This uniform potential distribution
across the cell leads to a better penetration of current into
the cell and hence accurate impedance measurements. The
nano-structured electrodes have multiple other advantages
over conventional micro/macro electrodes as they do not
require surface functionalization to effectively capture the
cell in between, which results in economy of time and less
parasitic noises [16–18]. The major advantage of nanospike
type electrodes, presented in this paper, is their high current
densities so that one can operate them at really low voltage
to get desired results with maximum cell viabilities. This
makes nanospike electrodes economical and power efficient
as well [14, 18]. For SCA, the application of high voltages
may lead to several chemical reactions in cell solution which
lead to sample contamination, bubble production, and morphological and chemical changes in cell and sometimes cell
lysis [16, 19–22]. Moreover, most of such high-voltage setups are not portable. In comparison to high-voltage-based
cell analysis, low-voltage methods of anomaly detection in
cells are more flexible and highly reproducible since the
impact of voltage on cell is low and cell can release itself to
the original formation after the removal of voltages which
allows to perform multiple experiments on the same cell.
Kesse et al. [23] demonstrated impedance spectroscopy
by culturing cells on electrodes and observed the impedance
change as the cell grows. The sensing arrangement was used
for the detection of cancer but it had high response time
due to the attachment process. Cho et al. [17] performed an
impedance analysis on normal and abnormal red blood cells
13
Medical & Biological Engineering & Computing (2021) 59:1709–1721
and reported differences on the basis of impedance magnitude and phase variations. In these two studies, no equivalent circuit model for impedance data fitting is reported
which was a passive approach. Jang et al. [24] introduced
a microfluidic setup for HeLa cell capture and impedance
spectroscopy. In [24], a simple equivalent circuit model,
close to experimental setup of impedance spectroscopy, for
the impedance data fitting is presented and variation in cell
impedance ­Zcell is used as an indication parameter for cancer characterization. Wang et al. [25] performed an impedance analysis on the human cervical cancer cell lines for
frequency range up to 100 kHz, and introduced empirical
relation with result validation up to 0.6 V only, as discrepancies in impedance results were observed at 1 V. A simplistic equivalent circuit is also used to fit data and for the
calculation of overall impedance magnitude and phase. Ren
et al. [11] performed an impedance spectroscopy to track
single-cell properties. A mesh of resistor–capacitor-based
equivalent circuit is introduced to make a database of cell
properties after fitting. Membrane capacitance is utilized as
one of the identification marks along with three other nonelectrical parameters, i.e., cell adhesion, cell diameter, and
cell-electrode distance.
Electrochemical impedance spectroscopy is reported by
Siddiqui et al. [13] for biosensing applications. Detailed
investigation is done for the electrode shape effect on impedance spectrum. The impedance data is fitted in Randle’s
model for parameter extraction and electron transfer resistance is used as a parameter of identification. Tabasi et al.
[26] demonstrated impedance spectroscopy for the detection of human epidermal growth factor receptor 2 protein
(HER2). Modified randle’s model is used for the data fitting and parameter extraction and charge transfer resistance
parameter is reported as an identification mark.
One of the major drawbacks of conventional impedance
spectroscopies is to fit the impedance data after impedance
spectroscopy in the electrical circuit configuration to get
the identification mark [11, 12, 14, 25]. Data fitting is itself
a tedious and vague formality to indicate biomarker. It is
mostly non-redundant because it is not sure that impedance
data will be fitted to already develop circuit model. Most
of the times, one has to design the circuit independently
according to impedance data trend. Though there can be
many circuits to which same data can be fitted, but it requires
physical equivalence to experimental setup to get the marker
of identification. Moreover, impedance data may fit exactly
to an electrical circuit but the circuit itself cannot be justified as an equivalent of experimental setup. This results in
a trade-off between some parameter values, e.g., membrane
capacitance and electrode surface to cell capacitance values, to get a better fitting circuit configuration. Thus, there
are many variations including multiple circuit models, multiple possible parameters of identification, and parameter
Medical & Biological Engineering & Computing (2021) 59:1709–1721
trade-off in conventional impedance spectroscopy that uses
data fitting.
In this paper, a gradient synthesis method is introduced
which allows to clearly identify the differential behavior of
cancer and non-cancer cell without data fitting. One must
observe gradient behavior as impedance trends from midrange frequency to high-frequency range. It is because of
change in dielectric properties of biological cell due to alpha
and beta dispersion and at higher frequencies impedance
decrease more rapidly due increase in ionic opening [14,
24, 25]. The proposed method is applicable on the impedance data of conventional impedance spectroscopies, implemented either using Nyquist or bode plots of impedance.
In the present work, impedance analysis is performed on
cancerous and non-cancerous cell pairs of two particular
organs, i.e., the breast and lungs, for early cancer detection.
The whole impedance analysis is done using two different
types of electrodes, i.e., planar and nanospike, to investigate
the electrode shape effect on impedance values of cancer and
non-cancer cells. Moreover, a gradient synthesis technique is
introduced for clear cancer characterization which does not
require any extensive and inexplicit data fitting formalities.
2 Methodology
Figure 1 shows the layout of impedance spectroscopy for
cancer detection using gradient synthesis. Initially, a rectangular setup with a spherical cell enclosed in electrodes is
created in a finite element modelling tool followed by testing of simulation setup for simulation validations. After the
simulation validations, impedance examination is performed
for breast normal and cancerous cell detection. Then, the
1711
electrode shape is changed from planar to nanospike and
impedance examination for breast cancer cell pair is performed. After this, the same numerical analysis is performed
on more blood-perfused organs, i.e., lung cancer and lung
normal cell with planar and nanospike electrodes. After getting all impedance results, the next part is to deploy data
synthesis. The proposed gradient detection technique results
for normal and cancerous breast and lung cell pair with both
types of electrodes are obtained. In gradient synthesis, the
percentage impedance drop of all types of cell under examination is determined and gradients are calculated. This data
synthesis is performed for range of frequency up to detectable frequency range. Details for detectable frequency range
can be found in Section 4.1. After the completion of all these
numerical examinations and synthesis, the impedance results
are compared for detection (Fig. 1).
3 Simulation setup for impedance analysis
Two simulation setups are considered for analysis; one is
macro setup of 0.7 × 1 m rectangular setup with two planar
electrodes of 0.7 m length having 0.3 m distance between
them. This setup suggested here is for macro level examination. This setup is used for initial simulation validity test and
for recording the electrode shape variation effects on electric
potential distribution between the electrodes. After the initial
simulation validity, the whole setup is shifted to microlevel
for real-sized cell examination, circumscribed by electrodes,
and remaining testing and cancer impedance spectroscopy
examinations are carried out on this setup. Microlevel simulation setup is selected as we are intended to conduct single-cell
level examination. This micro simulation setup consists of a
Fig. 1 The layout of impedance spectroscopy for cancer detection using gradient synthesis
13
1712
27 × 31 µm rectangular setup with two planar electrodes (le) of
23 µm length. The average cell diameter (dav,c) used is 16 µm
[18] and distance between electrodes (de) is 10 µm distance
between the electrodes. The reason behind the selection of this
microlevel dimension is that the cell should be truly encapsulated between electrodes and the effect of cell and electrode
surface interaction can be analyzed. There are multiple physics modules for examination in commercially available FEM
(finite element method) solvers, like electromagnetic, electric
current, and streamline flow. The numerical simulation trials
are performed in electric current physics. This physics interface solves a current conservation equation based on Ohm’s
law using the scalar electric potential as the dependent variable. Stationary, frequency-domain, small-signal analysis, and
time-domain modelling could be supported domains/solvers in
Fig. 2 The results of simulation validation tests with and without
cell encapsulated between the electrodes are shown. a Surface electric potential variation at 1 V for simulation validation, where σe and
εr,e are conductivity and permittivity of PbS electrolyte. b 1-D electric potential distribution at 1 V according to electric potential theory
E = -∇V (i.e., potential variation only in y coordinate position according to Poisson equation) which validates the simulation. c Surface
plot of electric field distribution having normal breast cell enclosed in
13
Medical & Biological Engineering & Computing (2021) 59:1709–1721
all space dimensions. We used frequency domain for impedance examination (stationary domain was also employed in
one of simulation validation test, Fig. 2b). The current conservation equation for electric potential employed during numerical examination is given as:
∇ ∙ J = Qj
(1)
J = 𝜎E + j𝜔D + Je
(1a)
E = −∇V
(1b)
where J is the current density, Qj is the charge, E is the
electric field, D is the displacement field, Je is the electron
current density, 𝜎 is the electrical conductivity, and V is
planar electrodes, where σnb and εr,nb are conductivity and permittivity of normal breast cell, respectively. σe and εr,e are conductivity and
permittivity of PbS electrolyte respectively and their values can be
found in Table 1. d Electric field distribution between two electrodes,
a normal cell enclosed, shows permittivity and conductivity difference of inner cell and outer electrolyte and shows the higher strength
of electric field at the boundary of cell and electrodes
Medical & Biological Engineering & Computing (2021) 59:1709–1721
the applied voltage. Gold is used as an electrode material
and PBS (phosphorous buffer saline) as an electrolyte. Low
voltages are employed to get desired results with maximum
cell viabilities. Additionally, increasing the operation voltage reduces the magnitude of the cell impedance because
a strong electric field may promote the exchange of ions
between the cytoplasm and the isotonic solution. So, 0.1 V
dc is chosen to minimize the effect of this signal during
impedance measurements [24]. Voltages are applied for
frequency sweep ­(105–109 Hz). Upper electrode is applied
with potential and lower electrode is at ground potential.
All simulations are performed in commercially available
finite element method software. Cell dielectric parameters
for lungs are taken from [27]. In [27], Egot et al. performed
seven experiments to analyze permittivity and conductivity
for the range of 200 MHz to 2 GHz. After fitting the data
mean values of conductivity and permittivity for lung cell,
the pair was retrieved. Similarly, for breast cell, parameters
are taken from [28]. In [28], An et al. scanned the frequency
range from 0.1 MHz to 0.1 GHz and calculated conductivity
values. Permittivity assumed to be near water’s permittivity
and assumed constant throughout the frequency range. The
frequency range used in the current work is ­105 to ­109 Hz
which is within the scanned range of the above discussed
literature. In this frequency range, biological cell parameters (conductivity and permittivity) show less variations
[29] which also authenticate the use of average approximation on cell parameters in this targeted range. That is why
dielectric cell parameters used are assumed to be effective
for our case study. Details about parameter selection can be
found in [27, 28]. All the values of constants and average
value of cell parameters used in the calculations and simulations are given in (Table 1).
Table 1 Values of constants and
average value of cell parameters
used in normal and cancer
cell models for impedance
spectroscopy
References
[28]
[28]
[12, 25]
[28]
[30]
[12, 25]
[27]
[27]
[27]
[27]
[12, 18]
[12]
1713
3.1 Simulation validity tests
3.1.1 Without cell inclusion
Several tests are conducted to confirm the validity of simulation and physics applied according to the electrostatics and
electric potential theory. First, the simulation is checked for
the basic electric field equation, i.e., E = V/d. The distance
between the electrodes varied to measure the normalized
electric field and then the results are compared with the calculated ones. At an applied voltage of 1 V, the electric field
values are obtained, through FEM (finite element method)
simulations, with distances between electrodes of 5.5 µm,
13 µm, and 23 µm are 1.82 × ­105 V/m, 7.69 × ­104 V/m,
and 4.34 × ­104 V/m respectively (supporting Fig. 1) which
showed a close agreement with the analytically calculated
values. Initially, the effect of corner-shaped planar electrodes
on electric field shape is analyzed through FEM simulations. The results showed that the electric field shape at the
corner is too distorted and very non-uniform (supporting
Fig. 2a, b) which is undesired for biological experiments
where a uniform or concentrated electric field is required.
Moreover, corner-shaped planar electrodes may undergo
degradation with frequency of utilization. Thus, the corner
edges of electrodes are then replaced with round ends. The
results show that with round edges, a uniform and streamlined electric field is obtained (Supporting Fig. 2c, d) along
with limiting the degradation effect. The electric potential
variation is checked as predicted by the electrical theory,
i.e., in 2D the electric potential in the center between two
electrodes changes only in the y coordinate position. The
results obtained through FEM simulations are found to be
in good agreement with the predicted theories in literature
[25] (Fig. 2a, b).
Parameters
Description
Values
𝜎 nb
𝜎 cb
𝜎e
𝜀0
𝜀r,nb
𝜀r,cb
𝜀r,e
𝜎 nL
𝜎 cL
𝜀r,nL
𝜀r,cL
dav,c
de
le
Conductivity of interior cell for MCF-10A
Conductivity of interior cell for MCF-7
Conductivity of exterior cell medium
Dielectric permittivity of free space
Permittivity of interior cell for MCF-10A
Permittivity of interior cell for MCF-7
Permittivity of exterior cell medium
Conductivity of interior cell for NL-20
Conductivity of interior cell for SK-MES
Permittivity of interior cell for NL-20
Permittivity of interior cell for SK-MES
Average diameter of cell
Distance between electrodes
Length of electrodes
0.3 S/m
0.23 S/m
2 × ­10−5 S/m
8.85 × ­10−12 As/Vm
80
78.69
136
0.89
0.77
48.1
45.6
16 µm
10 µm
23 µm
13
1714
To select the electrolyte/extracellular material/cell culture, medium pure water, saline 0.9%, and PBS are tested
numerically for their impedances at higher frequency. Saline
0.9% showed low impedance and nonlinear behavior at high
frequency and water showed high impedance and nonlinear
behavior with high frequency. PBS showed intermediate
impedance values which are slightly influenced by higher
frequencies and showed almost linear behavior (Fig. 3a).
Thus, PBS is chosen as an electrolyte for further testing and
impedance spectroscopy. On the other hand, as we have to
deal with higher frequencies in biological manipulations and
at higher frequencies, the morphology of biological setup
gets affected (bubble production, evaporation, degradation)
[18]. 0.9% saline solution is pure salt solution (having salt
PH) which might hamper cell or denature the cell in biological manipulations [31]. On the other hand, PBS is a buffer
saline in which disodium hydrogen phosphate is also added
with sodium chloride and this buffer helps to maintain constant PH [25, 32]. Due to that, most of the cell do not undergo
denaturing. As we know at high frequencies the current density will be higher (supporting Fig. 3). So, we prefer such
electrolyte whose response to higher frequencies should be
minimum so that if we note any abruption or change it will
be assumed that it is not due to electrolyte and solemnly due
biological matter under observation (in our case it is cell).
This is the reason linear behavior of PBS (Fig. 3b) was taken
into account as superior at higher frequencies.
Medical & Biological Engineering & Computing (2021) 59:1709–1721
setup discussed in the last section, are performed before
our actual cancer and non-cancer impedance examination.
At first, electric field intensity variation is investigated in
between the electrodes. Highest electric field is observed at
the boundary of cell and electrodes (Fig. 2c) (greater rate
of increase of intracellular electric field relative to extracellular) which advocate the conductivity and permittivity of
both intracellular and extracellular space are not identical
(Fig. 2d). To analyze the effect of increasing the frequency
on current density, a frequency vs. current analysis is carried out in the frequency range of 10 to 300 MHz. The
results showed that with an increase in frequency, the current density increases (Fig. 3b), which is in agreement with
the previous studies [15]. Detailed electric potential and
current variations at very high-frequency range are shown
in (supplementary Fig. 3). This test helped us to select suitable frequency sweep under examination considering two
points, suitable current passage and avoiding cell lysis [18].
As cell lysis is also a constraint while biological manipulation which should be taken under account. Secondly, to
observe the passage of current through the cell w.r.t to frequency employed as we are dealing with impedance of cell
so higher will be the current passage through the cell lesser
will be the impedance of cell [24, 25].
4 Results and discussion
An elliptical-round cell is sandwiched in between the electrodes and again simulation validity tests, with simulation
MCF-10A is used as the normal breast cell and MCF-7 is
used as breast cancer cell. NL-20 is used as lung normal cell
and SK-MES is used as lung cancer cell in the following
impedance analysis.
Fig. 3 a Cell enclosed, current, and frequency analysis for the range
of 10 to 300 MHz (only five instances and shown here) which clearly
shows as the frequency increases current density increases (for detail
visualization, see supporting Fig. 4). b Impedance analysis of three
extracellular material or electrolytes, i.e., water, saline 0.9%, and
PBS, for higher frequencies.
3.1.2 With cell inclusion
13
Medical & Biological Engineering & Computing (2021) 59:1709–1721
4.1 Impedance spectroscopy
The impedance of normal breast cell MCF-10A was found
higher in detectable frequency range than that of cancerous counterpart MCF-7, as previous studies [23, 25, 33–35]
showed that cancer cell has higher dielectric properties than
normal cell. For lung cancer cell’s SK-MES and lung normal
cell’s NL-20 impedances, the same behavior was observed
but in the lung’s case the difference in the impedance of
normal and its cancerous counterpart is less. The impedance
of lung normal cell is slightly higher than the lung cancerous
counterpart. These results were in good agreement with the
results presented previously in the literature [11, 14, 25].
Impedance spectroscopy was performed for three ranges
of frequencies, i.e., low-frequency range ­105 to ­107 Hz,
intermediate frequency range 1­ 0 7 to 1­ 0 9 Hz, and highfrequency range ­109 + Hz (up to 100 GHz). This is because
biological cells behave differently in different range of
frequencies which is a result of variation in the dielectric properties of biological cell from alpha dispersion to
beta dispersion [36]. So, the range of frequency in which
differential behavior of biological cells is very clear usually annotated as detectable frequency range. We found
detectable results of impedances for both organ cell pairs
in intermediate frequency range. According to Wang et al.
[25], in low-frequency range, the conductivity and permittivity of cell increase which results in low impedance
values with rapid change in this frequency range. This concludes in favor of our results that in low-frequency range
the difference between normal and cancerous cell impedance is not detectable. Due to rapid change in impedance, the constant comparable impedance values are not
obtained. In mid-range or intermediate frequency range,
the conductivity increases and permittivity is reduced
slowly according to Wang et al. [25]. Thus, one will get
much smoother and less variable or almost constant values for impedance as a result. In this range, the difference
between the impedance of the both cell pairs (breast normal and breast cancerous and lung normal and cancerous)
is observable and detectable. For higher frequency range,
the conductivity increases and permittivity reduces sharply
to zero which may cause the cell break down. This results
in equal impedances of both normal and cancerous cells
Table 2 Comparative analysis
of the reasons behind the
determination of detectable
frequency range
1715
which is almost equal to zero (Table 2). The particular
detectable frequency range of impedance spectroscopy
for breast cancer detection was observed around 1­ 07 Hz.
And for lung cancer detection, it was found to be around
­108 Hz (Fig. 4).
The starting impedance (impedance at low frequency)
of normal cells in frequency spectra was observed lower
than that of cancerous counterpart. This is because of
two reasons, the first one is that the normal cell contains
much higher ions and charged particles in them [37–39]
in contrast to the cancerous cell whose major constituent is water [37], since cancer cell loses almost all of its
mineral which are the source of ion production under the
influence of electric field. The second reason is that at
the turn from lower frequencies to intermediate frequencies, there is high permittivity and conductivity of cell
start increasing rapidly which ultimately cause reduction
in impedance [25].
For lung cancer and normal cells, the impedance results
were found in good agreement with the findings presented by
Egot-Lemaire et al. [27]. In [27], it was shown that either of
both due to high blood profusion and extracellular matrix or
normal and malignant lung cell shows almost same behavior
for permittivity and conductivity. In the current work, we are
particularly targeting the impedance of normal and cancer
lung cells instead, which on the other hand is function of
their permittivities and conductivities. This is also confirmed
by the slight impedance difference in our results for both
normal and malignant lung cell. In [27], for intermediate
frequency range, the dielectric properties of normal lung
cells were reported to be a bit higher than that of its counterpart malignant cell, which is consistent with our results. So,
our results of impedance for lungs (which is the function of
conductivity and permittivity) are in good agreement with
the previous work presented in the literature.
4.2 Electrode shape effect
The whole numerical analysis of impedance spectroscopy
for cancer detection was again done with different shapes
of electrode to analyze the electrode shape effect on impedance. This time, some nano protrusions (nanospikes) were
included on the planar electrode surface. Impedance results
Frequency
Low ­105 to ­107 Hz
Intermediate ­107 to ­109 Hz
High ­109 + Hz
Conductivity [25]
Permittivity [25]
Impedance [25]
Increases
Increases
Reduces
Increases
Slow reduce
Slow reduce (almost constant)
Increases
Reduces sharply
Almost zero
(cell breakdown)
Equal
Our detectable results Low (detectable @boundary
(of impedance)
of intermediate f range)
High detectable
13
1716
Medical & Biological Engineering & Computing (2021) 59:1709–1721
Fig. 4 a Results of impedance spectroscopy for breast cancer cell
MCF-7 and breast normal cell MCF-10A in its detectable frequency
range, i.e., 1­ 07 Hz using planar and nanospike electrodes. b Results of
impedance spectroscopy for lung cancer cell SK-MES and lung nor-
mal cell NL-20 in its detectable frequency range, i.e., ­108 Hz using
planar and nanospike electrodes (zoomed section shows clear differentiation between impedance results for lung cell pair)
for normal and cancerous breast cell pair and for normal
and cancerous lung cell pair were analyzed in the detectable
frequency range. As nanospike electrode was proved to be
an efficient shape with multiple advantages, i.e., can capture
cell better, economical, to fabricate, etc., as discussed in the
above section. Design details of nanospike electrodes can be
found in [18]. The results obtained were in good agreement
with our previous results of impedance spectroscopy using
planar electrodes. But the overall impedances for all four cell
models were 1 to 2 unit lesser using nanospike electrodes
than the impedances obtained using the planar electrodes.
This was because of high aspect ratio of nanospikes [18]
or sharp edges which results in concentrated electric field
(Fig. 5a). This concentrated electric field increased the overall current density (Fig. 5b) resulting in less impedances.
Surface plots of electric field and current density at 100 kHz
are shown (Fig. 5b) to analyze differential effect of electrode
shape.
The nanospike electrodes are found better over planar
electrode. They have multiple other advantages over conventional micro/macro electrodes and found best during examination, as they do not require surface functionalization to
effectively capture the cell in between, which results in economy of time and less parasitic noises [14, 17, 18]. The major
advantage of nanospike type electrodes is their high current
densities (due to spike shape) so that one can operate them at
really low voltage to get desired results with maximum cell
viabilities. This makes nanospike electrodes economical and
power efficient as well. Nanospike electrodes are economical
to fabricate as they can be fabricated on aluminum foil with
scalable and controllable electrochemical anodization and
etching processes [14, 18].
13
4.3 Gradient synthesis for detection
In this section, an effective method of cancer detection is
proposed, which includes some statistical analysis after
achieving impedance data and provides a much better differentiation between the impedances of normal and cancerous
cells. In this method of cancer cell detection, the gradient
calculation of impedance drop for all frequency range up to
the detectable frequency range is proposed (Fig. 6).
For further synthesis, the initial and final values of impedance gradient up to detectable frequency range were utilized.
This impedance data for all types of cells under examination and for both the electrode types (planar and nanospike
electrodes) used in the numerical analysis was plotted for
clear understanding (Supporting Fig. 5). Impedance plot
with sweep of complete frequency range depicts a linear
gradient up to detectable frequency range for each cell type
as shown in Fig. 6. First of all, percentage drop in impedance was analyzed which itself an indication to differentiate
between cancer and non-cancer cells.
As shown in Fig. 7, the percentage drop in impedance for
breast cancer cell MCF-7, for complete range of frequencies
up to detectable one, was around 16%, while the percentage
impedance drop of normal breast cell MCF-10A was just
9% using planar electrode. All the results obtained using
nanospike electrodes were also in good agreement with the
results obtained for planar electrodes.
Medical & Biological Engineering & Computing (2021) 59:1709–1721
1717
Fig. 5 Surface and contour plots of electric field and current density respectively, for a planar and b nanospike electrodes at 100 kHz
which shows that due to high aspect ratio and sharp edges, nanospike
electrodes have higher current density than planar electrodes, where
σnb and εr,nb are conductivity and permittivity of normal breast cell,
respectively. σe and εr,e are conductivity and permittivity of PbS electrolyte respectively and their values can be found in Table 1
Percentage impedance drop is a clear indication for breast
cancer but it has also shown very good results for the lung
cancer. For lung cancer cell, the percentage impedance drop
was around 28% and for normal lung cell, it was observed
to be 22% using planar electrode. As discussed in the previous section, using conventional impedance spectroscopy,
the difference in impedance of lung normal and cancer cells
was very less. Those results were perfectly in accordance
to the previous work done on lung cancer detection using
dielectric properties [27] with the valid reason of higher
blood profusion. But the fact is that conventional impedance spectroscopy results for lungs cannot be use for cancer
detection effectively.
On the other hand, percentage drop and gradients method
showed a clear differentiation for breast cancer but performed exceptionally well for the lung cancer also. Percentage impedance drop was calculated using formula Eq. 2:
Fig. 6 a Impedance variation plot of breast normal cell MCF-10A
and breast cancerous cell MCF-7, throughout the range of frequencies (starting from lower to higher frequency) using planar and nanospike electrodes. Zi and Zf are initial and final impedance points used
in Eq. (2) and Table 3. b Impedance variation plot of lung normal cell
NL-20 and lung cancerous cell SK-MES, throughout the range of frequencies (starting from lower to higher frequency) using planar and
nanospike electrodes
Zdrop = (1 − (Zf ∕Zi )) × 100
(2)
13
1718
Medical & Biological Engineering & Computing (2021) 59:1709–1721
Fig. 7 With reference to Fig. 6, the percentage drop in impedance
is plotted here. The bar plot is plotted for both types of electrodes.
And the results from both electrodes are in good agreement with each
other, i.e., the percentage drop in impedance for cancer cells of both
organs is prominently higher than their normal counterpart
where Zf is the final value of impedance and Zi is the initial value of impedance, their values can be found in Table 3.
The next part of quantitative analysis of impedance data is
gradient calculation (Fig. 8)
Although the percentage change in impedance is higher
for planar electrodes as compared to nanospike electrodes,
yet these nano-structured electrodes are preferred over planar ones in biological cell impedance spectroscopy. The planar electrodes have relatively longer response time as cells
take time to attach themselves on planar electrode surfaces.
Surface chemistry techniques are used to modify electrode
surfaces to enhance cell-electrode adhesion process. This
will minimize the parasitic signals from gaps between cell
membrane and planar electrode surfaces. Modifications
through the surface chemistry involve complex chemical and
electrochemical preparation steps. This results in undesirable electrochemical reactions at the surface of electrodes
which have impact on sensing and electrode stability. Nanostructured electrodes can directly penetrate into cell membrane and enhance the cell-electrode adhesion very quickly
without surface modification [18]. The electrical information
can be extracted directly from cell membrane and can be
used for different applications like cancer cell detection and
discrimination.
Using the abovementioned gradient method of cancer
detection, the impedance gradient obtained would always
be negative which proved the fact that as the frequency
increases, the impedance decreases [14] (Table 3). The gradient of cancerous cell for both organs cell pairs was found
1.5 to 2 times greater than the gradient of its counterpart
normal cell. It depicts that up to detectable frequency range,
the impedance of cancer cell decreases more faster than the
normal cell which, in fact, is the validation of the reported
result in the literature that the dielectric properties of cancer
cells are higher than the normal cell [27] and cancerous cells
are much diluted than normal cells [37, 40]. Gradient for
breast cancer cell MCF-7 was found to be 2 times greater
than the gradient of normal breast cell MCF-10A and gradient of lung cancer cell SK-MES was almost 1.5 times greater
than the gradient of normal lung cell NL-20 (Table 3).
This method of cancer detection was found independent
of electrode shape. The behavior of gradient for both the cancer cell pairs was same irrespective of electrode shape, i.e.,
the gradient of breast cancer cell was double than the normal breast cell for both electrode shapes and for lungs it was
1.4 times. The differentiation is clear and justified and using
this gradient synthesis, the complex and less efficient data fitting technique can be avoided to get marker of identification.
The only limitation of this gradient-based detection is when
there is not gradient formation or very minor non detectable
gradient is found in impedance spectroscopy results which
Table 3 Quantitative analysis and data synthesis of logarithmic impedance plot in Fig. 6 for cancer detection
Type of cells
Planar electrodes
MCF-7
MCF-10A
SK-MES
NL-20
Nanospike electrode
MCF-7
MCF-10A
SK-MES
NL-20
13
Initial value of impedance, Zi (ohms)
Final value of impedance up to
detectable range, Zf (ohms)
%drop (Zdrop)
Gradient
Multiple
increase (for
cancer cell)
3.3450
2.5528
0.9979
0.8629
2.8239
2.3028
0.7237
0.6653
15.578
9.793
27.478
22.899
− 0.1834
− 0.0879
− 0.0760
− 0.0550
2 times
3.1056
2.3802
0.9283
0.8032
2.6760
2.1619
0.6974
0.6369
13.833
9.1714
24.873
20.7046
− 0.1508
− 0.0773
− 0.0641
− 0.0461
2 times
1.4 times
1.4 times
Medical & Biological Engineering & Computing (2021) 59:1709–1721
Fig. 8 The histogram shows that for breast cancer cell, the gradient is
two times higher than its normal breast cell. And for lungs, the gradient of lung cancer cell is 1.4 times higher than its normal lung cell.
And most importantly this quantity we found is independent of electrode shape, i.e., trend of gradient with both electrodes for both cell
types is exactly in agreement with each other. Details can be seen in
Table 3
is very uncertain to happen. Usually all EIS spectra contain
gradient which can be synthesized using the abovementioned
technique. The whole experimentation presented in this paper
leads towards an effective and non-invasive early detection of
cancer at a very low-voltage level. In the light of the above
discussion, it is shown that the proposed gradient-based cancer
detection technique is easy to perform, economical, and effective as well because it uses a single-cell level characterization.
Moreover, the proposed gradient-based impedance detection
technique finds utility in all EIS applications to avoid tedious data fitting process. Specifically, it is applicable in DNA
biosensors, bacterial contamination analysis, detection of
microorganisms by the means of EIS, detection of interfacial
behavior of molecules, EIS-based body composition analysis,
and assessment of food quality which includes dairy products,
fruits, and oils [41, 42]. The proposed detection techniques can
certainly find their application in micro total analysis system
(µ-TAS) and portable biomedical detector, i.e., lab on chip and
smart health care devices.
5 Conclusion
A gradient-based impedance synthesis has been presented
for early-stage cancer detection. For the first time, cancerous
cell and normal cell of same particular organ are taken under
numerical examination for cancer detection.
Breast and lung cancer cells and their normal counterparts
are analyzed for impedance detection using micro-scaled
planar and nanospike electrodes independently. Differential
1719
effects of impedance for cancer and its normal counterpart
have been found in detectable frequency range which vary
organ to organ. Effect of electrode sculpt on normal and
cancer cell impedance has been rigorously considered. The
results of impedance for both electrode shapes have been
found in good agreement with each other. Overall impedance
for sharp edge nanospike electrodes is found 1.5 to 2 unit
lesser due to the high current density. A technique using gradient synthesis has been proposed and extensively analyzed
for cancer detection which is found independent of electrode
shape effect since it utilizes gradient calculation. The results
depicted that impedance of cancer cell declines with the rate
double to its normal counterpart as frequency of applied
pulse increases. This assured that under electrical manipulation, cancer cell behaves as divergent unlike healthy cell.
Using a very low voltage of 0.1 V, we here successfully
analyzed a set of techniques leading to gradient synthesis
which is universal in its application in spectroscopy. Indeed,
it is a cheaper and much accurate way to analyze behavioral dissimilarities under the influence of electrical stimulus
because it deals with cell level dissimilarities to characterize
fatal disease like cancer here. Furthermore, it finds application in today’s app-based online health monitoring setups,
µ-TAS system, lab on chip, and in smart portable devices.
For future research, this method can be explored experimentally as we did numerically in this research, for explicit and
very early-stage cancer prognosis.
Supplementary Information The online version contains supplementary material available at https://d​ oi.o​ rg/1​ 0.1​ 007/s​ 11517-0​ 21-0​ 2382-2.
References
1. Elmore JG, Barton MB, Moceri VM et al (1998) Ten-year risk of
false positive screening mammograms and clinical breast examinations. N Engl J Med 338:1089–1096
2. Hong J, Kandasamy K, Marimuthu M et al (2011) Electrical cellsubstrate impedance sensing as a non-invasive tool for cancer cell
study. Analyst 136:237–245
3. Vargas AJ, Harris CC (2016) Biomarker development in the precision medicine era: lung cancer as a case study. Nat Rev Cancer
16:525537
4. Mangé A, Dimitrakopoulos L, Soosaipillai A et al (2016) An
integrated cell line-based discovery strategy identified follistatin
and kallikrein 6 as serum biomarker candidates of breast carcinoma. J Proteomics 142:114–121. https://​doi.​org/​10.​1016/j.​
jprot.​2016.​04.​050
5. Mao Y, Shin K-S, Wang X et al (2016) Semiconductor electronic label-free assay for predictive toxicology. Sci Rep 6:1–8
6. Abercrombie M, Ambrose E (1962) The surface properties of
cancer cells: a review. Cancer Res 22:525–548
7. Schermelleh L, Carlton PM, Haase S et al (2008) Subdiffraction
multicolor imaging of the nuclear periphery with 3D structured
illumination microscopy. Science 80(320):1332–1336
8. Hong J, Lan K, Jang L (2012) Electrical characteristics analysis
of various cancer cells using a microfluidic device based on
13
1720
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
Medical & Biological Engineering & Computing (2021) 59:1709–1721
single-cell impedance measurement. Sensors Actuators B Chem
173:927–934. https://​doi.​org/​10.​1016/j.​snb.​2012.​06.​046
Mansor MA, Ahmad MR (2015) Single cell electrical characterization techniques. 12686–12712. https://​doi.​org/​10.​3390/​
ijms1​60612​686
Scharfetter H (1999) Structural modeling for impedance-based
non-invasive diagnostic methods. Thesis for the habilitation
at the faculty of Electrical Engineering, Technical University
Graz.Graz
Ren D, Chui CO (2018) Feasibility of tracking multiple single-cell properties with impedance spectroscopy. ACS sensors
3:1005–1015
Wang M-H, Chang W-H (2015) Effect of electrode shape on
impedance of single HeLa cell: a COMSOL simulation. Biomed
Res Int, pp 1–9
Nanofiber C, Arrays E, Electrochemical U et al (2010) Characterization of carbon nanofiber electrode arrays using electrochemical
impedance spectroscopy: effect of scaling down electrode size.
ACS Nano 4:955–961
Riaz K, Zhao C, Lau TS, et al. (2015) Low-cost Nano-spike BioImpedance Sensor (NBIS) without surface functionalization for
detection and phenotyping of cancer cells. In: 2015 Transducers-2015 18th International Conference on Solid-State Sensors,
Actuators and Microsystems (TRANSDUCERS). IEEE, pp
367–370
Forbes RG, Edgcombe CJ, Valdre U (2003) Some comments on
models for field enhancement. Ultramicroscopy 95:57–65
He H, Chang DC, Lee Y-K (2007) Using a micro electroporation
chip to determine the optimal physical parameters in the uptake
of biomolecules in HeLa cells. Bioelectrochemistry 70:363–368
Cho YH, Yamamoto T, Sakai Y et al (2006) Development of
microfluidic device for electrical/physical characterization of
single cell. J Microelectromechanical Syst 15:287–295
Riaz K, Leung S-F, Fan Z, Lee Y-K (2017) Electric field enhanced
3D scalable low-voltage nano-spike electroporation system. Sensors Actuators A Phys 255:10–20. https://​doi.​org/​10.​1016/j.​sna.​
2016.​12.​022
Movahed S, Li D (2011) Microfluidics cell electroporation. Microfluid Nanofluid 10:703–734
Lee WG, Demirci U, Khademhosseini A (2009) Microscale electroporation: challenges and perspectives for clinical applications.
Integr Biol 1:242–251
Geng T, Lu C (2013) Microfluidic electroporation for cellular
analysis and delivery. Lab Chip 13:3803–3821
Potter H, Heller R (2018) Transfection by electroporation. Curr
Protoc Mol Biol 121:3–9
Giaever I, Keese CR (1993) A morphological biosensor for mammalian cells. Nature 366:591–592
Jang L-S, Wang M-H (2007) Microfluidic device for cell capture
and impedance measurement. Biomed Microdevices 9:737–743
Wang M-H, Jang L-S (2009) A systematic investigation into
the electrical properties of single HeLa cells via impedance
measurements and COMSOL simulations. Biosens Bioelectron
24:2830–2835
13
26. Tabasi A, Noorbakhsh A, Sharifi E (2017) Reduced graphene
oxide-chitosan-aptamer interface as new platform for ultrasensitive detection of human epidermal growth factor receptor 2.
Biosens Bioelectron. https://​doi.​org/​10.​1016/j.​bios.​2017.​04.​020
27. Egot-Lemaire S, Pijanka J, Sulé-Suso J, Semenov S (2009)
Dielectric spectroscopy of normal and malignant human lung
cells at ultra-high frequencies. Phys Med Biol 54:2341
28. An J, Lee J, Lee SH et al (2009) Separation of malignant human
breast cancer epithelial cells from healthy epithelial cells using
an advanced dielectrophoresis-activated cell sorter (DACS).
Anal Bioanal Chem 394:801–809. https://​d oi.​o rg/​1 0.​1 007/​
s00216-​009-​2743-7
29. Nasir N, Al Ahmad M (2020) Cells electrical characterization:
dielectric properties, mixture, and modeling theories. J Eng,
https://​doi.​org/​10.​1155/​2020/​94754​90
30. Guido I, Jaeger MS, Duschl C (2011) Dielectrophoretic stretching of cells allows for characterization of their mechanical
properties. Eur Biophys J 40:281–288. https://​doi.​org/​10.​1007/​
s00249-​010-​0646-3
31. Hamaguchi K, Geiduschek EP (1962) The effect of electrolytes
on the stability of the deoxyribonucleate helix. J Am Chem Soc
84:1329–1338. https://​doi.​org/​10.​1021/​ja008​67a001
32. RSC (2020) Phosphate-buffered saline solution. In: R. Soc. Chem.
https://​www.​rsc.​org/​publi​shing/​journ​als/​prosp​ect/​ontol​ogy.​asp?​
id=​CMO:​00017​51&​MSID=​B1039​33B. Accessed 22 Jan 2021
33. Niemtzow RC (1985) Transmembrane potentials & characters
immune & tumor cell. CRC-Press Inc., ed.1. ch.1:7–20, Boca
Raton, Florida
34. Blad B, Baldetorp B (1996) Impedance spectra of tumour tissue in
comparison with normal tissue; a possible clinical application for
electrical impedance tomography. Physiol Meas 17:A105–A115
35. Stern RG, Milestone BN, Gatenby RA (1999) Carcinogenesis and
the plasma membrane. Med Hypotheses 52:367–372
36. Martinsen OG, Grimnes S (2014) Bioimpedance and bioelectricity
basics, ed. 3. ch.3 Dielectrics. Academic press, Cambridge
37. Haltiwanger S (2003) The electrical properties of cancer cells. In:
The Rife 2003 International Conference in Seattle, Washington
38. Brown GC (1999) The energy of life: the science of what makes
our minds and bodies work. ch.3–4, ppp 15–28. Free Press, New
York
39. Ho M-W (1996) Bioenergetics and biocommunication. Comput
Cell Mol Biol Syst 251–264
40. Aslam MA, Riaz K, Mahmood MQ, Zubair M (2019) Hybrid
analytical-numerical approach for investigation of differential
effects in normal and cancer cells under electroporation. RSC
Adv 9:41518–41530
41. Grossi M, Riccò B (2017) Electrical impedance spectroscopy
(EIS) for biological analysis and food characterization : a review
6:303–325
42. Randviir EP, Banks CE (2013) Electrochemical impedance spectroscopy: an overview of bioanalytical applications. Anal Methods
5:1098–1115. https://​doi.​org/​10.​1039/​C3AY2​6476A
Publisher’s note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
Medical & Biological Engineering & Computing (2021) 59:1709–1721
team/​muham​mad-​awais-​aslam/
Muhammad Awais Aslam : is a
research associate in Nanotech
Lab of Electrical Engineering
Department of Information
Technology University (ITU),
Lahore, Pakistan. He did his
graduation in Electrical Engineering from University of Engineering and Technology (UET),
Lahore, Pakistan. His current
research interests are MEMS,
NEMS, numerical and analytical
modelling of biophysical processes, AI-based deep medicine,
and early detection of cancer. W:
http:// ​ n anot ​ e chlab. ​ i tu. ​ e du. ​ p k/​
Kashif Riaz : is an assistant professor in Electrical Engineering
Department of Information
Technology University (ITU),
Lahore, Pakistan. He is one of
the supervisors of Nanotech Lab.
He did his PhD from Hong Kong
University of Science and Technology (HKUST). His current
research interests are on design,
modelling, simulation, and characterization of nano-structures
for biological manipulations and
application using electrical
methods like electroporation for
biomolecules delivery, irreversible electroporation for cancer cell lysis, extraction of proteins from
cell using electroporation, and cancer cell detection using electrical
method at low voltages. W: http://​n anot​e chlab.​i tu.​e du.​p k/​t eam/​
dr-​kashif-​riaz/
1721
Muhammad Mubasher Saleem :
received his B.Sc. Electrical
Engg. from University of Engineering and Technology (UET)
Lahore (2008), MS in Electronic
Engineering from Ghulam Ishaq
Khan Institute of Engineering
Sciences and Technology
(GIKI), Topi (2010) and Ph.D.
degree in Mechanical Engineering from Politecnico di Torino,
Italy (2015). His PhD research
work was related to RF-MEMS
design optimization, fabrication,
testing, and failure analysis for
the space applications, in collaboration with Fondazione Bruno Kessler (FBK), Trento, Italy. He has
also worked and published in the field of MEMS inertial sensors
(Microgroscopes and Microaccelerometers). W: http://​www.​nust.​edu.​
pk/​INSTI​TUTIO​NS/​Colle​ges/​CEME/​Depar ​tments/​Mecha​troni​cs%​
20Eng​ineer​ing/​Facul​ty/​Pages/​Dr-​Muham​mad-​Mubas​her-​Saleem.​aspx
13