Indium Tin Oxide Coated Surface Plasmon
Resonance Based Biosensor for Cancer Cell
Detection
Abstract—This A novel conventional single-core SPR-based
cancerous or malignant cell detector sensor is demonstrated for
the rapid identification monitoring cancer-affected distinct cell
types. Each cancer-infected cell's refractive index (RI) is
contrasted to such RI of its own healthy individual, and significant
variations in optical properties are discovered. Moreover, the
concentration of cancerous cells in liquid is estimated at 80%, as
well as the finite element method (FEM) is used for detection
(FEM). A thin Indium Tin oxide (ITO) film coating (50 nm)
separates the silica and cancer cell parts, allowing for a plasmonic
band gap to vary the spectral shift. The suggested sensor has a
significant level of birefringence of 0.035 and a length of the
coupling of up to 70 µm. On the other hand, the proposed model
gives an ideal wavelength sensitivity level between around
10357.14 nm/RIU and 17750 nm/RIU, with a sensor resolution of
1.41×10-3 RIU and 7.37×10-3 RIU. In addition, the transmittance
variance of cancerous cells varies from nearly 4100 dB/RIU to
6800 dB/RIU, in primary polarization mode, the amplitude
sensitivities for various cancer cells ranges from about -405 RIU-1
to -430 RIU-1, with such a detection limit of 0.025.
Keywords—Cancer cells, Cancer Sensing and Detection, Monocore Bowl shaped SPR, Birefringence, and Sensitivity.
I. INTRODUCTION
The Surface plasmon resonance (SPR) already have shown
great promise in the field of sensing. A silicon dioxide core fiber
with microscopic round air pockets runs the length of SPR [1].
In order to have more design freedom, We must do an
investigation into the FEM using a complete vector software
program, COMSOL Multiphysics version 5.1. In biomedical
research, though, using SPR-based photonic fiber (PCF), illness
monitoring, diagnostics, and detection may be performed to
assure better treatment. The very first sensor for sensing glucose
from the blood was created by Clark et al. [2]. On a daily basis,
new techniques including microfluidic [3], electrolytic [4],
phagocytic [5], and cellular cancer detection [6] is being
provided. After the growth of separate sites, Yaroslavsky et al.
carried out a case study of malignant cancer detection [7],
optoelectronic influence on microstructure [8], and body fluids
containing malignancy [8], [9]. Sun et al. found a breast cancer
biomarker (HER-2) [10]. All following cancer cell detection
models, on the other hand, were either based solely on stratum
basale with sensitivity levels or less 7000 nmRIU-1 or included
sensitivity values for other malignant cell traits. In comparison
to normal cells (80% concentration), however, our proposed
framework achieves exceptional results in terms of increased
sensing in the quick diagnosis of cancer (30–70%
concentration). via cell secretions, as shown by our research.
Many cancer viruses' internal protein structures vary depending
on their optical features, as we all know. The measured values
of tumor tissue will also differ. This refractive indices reaction
contributes in the differentiation of healthy cells from malignant
cells. As a result, the proposed system will be superior to any
previously developed model. This article describes an SPRbased optical sensor that can quickly detect cells that have been
impacted by malignancy, including leukemia (Jurkat),
lymphoma (HeLa), adrenal gland cancer cell (PC12), two types
of breast cancer cell (MDA-MB231 and MCF-7) and skin
cancer cell (Basal). Furthermore, the percentage of malignant
cells in the liquid state is predicted to be around 80%, as well as
the detection method is the Finite Element Method (FEM). The
suggested D-shaped PCF-SPR malignancy tests were performed
at wavelengths spanning from 0.5 to 2.0 µm in order to
determine its performance. The purpose is to describe a sensor
with increasing wavelength and amplitude sensibility, minimal
loss, and good birefringence that is simple to make. The
proposed approach will take cancer cell detection to an entirely
new level. TABLE I
II. EASE OF USE
The mono-core transmission modes in a bowl-shaped
structure dominate the suggested model's bi-sectional
perspective. As a background, a silica arc has been employed
and PML as a component.
(a)
(b)
(c)
Fig. 1 (a) Bowl shaped proposed fiber design; (b) core mode for x- polarization;
(c) core mode for y-polarization
A sequence of air holes with widths of r1=500 nm, r2=200 nm,
r3=300 nm, and pitch P=2µm restricts the internal lattice
structure in the core area, which includes the ring structure
shown in Fig. 1, to alter the mode confinement At the bottom
of the structure, a single layer of biosample is formed and
separated from the silica by a thin Indium Tin oxide (ITO)
coating with a thickness of 50 µm. Depending on the size of the
air holes; the bio-samples are more or less sensitive. Table I
displays the biosamples refractive indices and dielectric
constants. Use individually unaffected cells to compare the
sensitivity variations of cancerous cells of different types.
Additionally, the suggested model is an enhanced PCF in the
D-shape with an enlarged form, providing greater optical
parameter flexibility and improving sensing performance. The
layer of the analyte is connected to the flat section of the "D" in
the D-shape SPR PCF. However, in our model, it is connected
to the below of "D," which adds steadiness and resilience to the
sensing process. This is due to the gap between both the fiber
core's center and the metallic layer's interface., the entire core
radius can develop properly, resulting in an increase in
plasmon. The conventional D-shape, on the other hand, results
in a poorly formed core on the analyte side, reducing plasmon.
As a consequence, the sensitivity of the reaction will be
reduced. Because of its simple design, the suggested sensor
may be manufactured using existing technologies such as
solgel, extrusion, and drilling techniques. Due to the reliance on
surface plasmon incident at the metal-analyte interface,
imperfections in the production of air holes have almost no
impact on PCF biosensor performance. Air holes, on the other
hand, are utilized as a gate for the core mode, which is unrelated
to plasmonic incidence. Thus, it should be relevant only to PCF
and not to SPR-based PCF.
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III. THEORITICAL ANALYSIS
The suggested cancer sensor's primary purpose is to discover
cancer using the FEM approach and develop plasmonic
resonance in order to define the overall change of light
absorption by the relevant bio-sample. The wavelength
sensitivity(nm/RIU),transmission spectrum, and transmittance
variance (dB/RIU) of D-shaped SPR are analyzed from the
outcome in different modes of X-polarization and Ypolarization. After calculating the inference of the mono-core
structure of the coupling length, the following equations must be
used. To divide these modes into two groups, we used the
following criteria: The suggested SPR PCF requires deep mode
confinement for X-polarization modes (nx) and Y-polarization
modes (ny) represented in Fig. 1. (b). According to the
Sellmeier's RI equation for fused silica material [20], The
suggested model's effective RI may be computed as follows:
n ( RIU ) = 1 +
B3 2
B1 2
B2  2
+
+
 2 − C1  2 − C2  2 − C3
(1)
Where n is the effective refractive index (RI) of fused-silica
and
B1=0.696163,
B2=0.4079426,
B3=0.8974794,
C1=0.0046914826 µm2 , C2=0.0135120631 µm2, and
C3=97.9340025 µm2 are the Sellmeier’s constants for fused
silica, respectively.
The D-Shaped SPR-PCF birefringence (B) or refractive
index difference between various super modes of X polarization
and Y polarization [11], [12] given below:
B = nxi − niy
(2)
Here, i denotes the proposed model's X or Y polarization.
For X and Y polarization, Eq. 2 considers the whole range of
refractive index differences between various modes with respect
to the wavelength.
Any plasmonic structure encounters the issue of mode
confinement loss (αc), which cannot be eliminated.
Concealment-loss is a term that is often used to describe a
structure's sensitivity. The suggested model's confinement-loss
be estimated as,
 c ( dB / cm ) = 8.686 
2

 10 4
(3)
Here, lambda (λ) denotes the wavelength that is taken into
account for the suggested structure. In general, coupling length
refers to the shortest distance at which the most significant
quantity of light may easily travel through the tiny silica core.
For the D-shaped SPR PCF [11], [12], the coupling length
Lc of the mono core in X polarization and Y polarization can be
determined by following equation:
Lc (  m) =

2 B
(4)
Where B is the birefringence. We must determine the length
of the D-shaped SPR PCF's coupling length cancer sensor for
various wavelengths using Eq. (4). The length of the D-shaped
SPR PCF coupler is clearly inversely related to the wavelength.
The suggested structure allows for an optical field to flow
through the mono core, which allows for improved cancer
sensing. The optical power output that goes through the silica
core is specified to compute the sensing,
Pout ( watt ) =
sin 2 nx − ny

IV. RESULT ANALYSIS AND DISCUSSION
(5)
The fiber's whole length is denoted by the letter L. As a
result, we can use Eq. 5 to calculate the optical power that goes
through the mono-core along the proposed PCF with a variable
fiber length L. The transmittance spectrum [11], [12] may be
examined when light travels through the proposed fiber,
P 
Tr (dB ) = 10  log10  out 
 Pin 
(6)
The maximum power input and output are designated as Pin
and Pout, respectively. Nevertheless, it is possible to measure the
wavelength sensitivity of the presented sensor by subtracting the
total variation in RI from the displacement of the acute zenith of
the transmittance curl at destined wavelength. The wavelength
sensitivity for density level may be characterized as [13], [11],
and [12].
S w ( nm / RIU ) =
 p
n
(7)
The fluctuation of peak wavelength is denoted by Δλp, while
the variation of cancer cell RI is denoted by Δn. Thus, Eq. 7 is
used to determine a cancer cell's sensitivity, and the
transmittance curve may be adjusted using the transmittance
variance or Tr sensitivity.
The Refractive Index variation between healthy and
cancerous cells is nb, and txb1:txb2 is the maximum amplitude Tr
curves for b1 and b2 bio-samples, respectively. However, any
difference in the resolution of the suggested structure may
readily detect any change in the Refractive Index of the biosamples. As a result, the suggested model's resolution may be
assessed by,
(
Sv dB
(t
) =  max
max ( n

RIU
− t xb 2 ) 

b1 − nb 2 ) 
xb1
Every figure in this study illustrates the optical features of
healthy and cancer-affected cell bio-samples as a function of
wavelength. Both the X-axis and Y-axis curves are depicted by
the circular and triangular markers, respectively. Figure 2
depicts the RI's reaction to a shift in wavelength. The biosamples refractive index is steadily decreasing, making it clear
RI's prepositional curvature features a straight line as well as a
linear structure. To begin, the bio-sample has its maximum RI,
then falls to its lowest. The total system will be affected linearly
if we swap the refractive index for different bio-samples. The
highest possible range of RI is 1.46 to 1.47 for biological
samples. Figures 3 and 4 show the X-and Y-polarization loss
spectra as a function of the wavelength, the spp mode, and the
core mode. The junction position between the core guiding
mode and the spp directing mode provide the biggest high point
result of the maximum confinement loss for every specific
cancer or malignant cell bio-sample. This suggested model
predicts that cancer cell bio-samples will have a few crossing
spots in the X and Y polarizations at wavelengths of 1.2 µm,
1.3 µm, 1.4 µm, 1.5 µm, 1.6 µm, 1.7 µm, and 1.22 µm, 1.34
µm, 1.45 µm, 1.51 µm, 1.67 µm, 1.73 µm, respectively. This is
consistent with the results of previous studies. There is also a
note stating that this sensor has the best sensitivity in that area.
A cancer model based on these confinement loss curves shows
X-polarization losses of 467 dBcm-1, 557 dBcm-1, 657 dBcm-1,
840 dBcm-1, 1030 dBcm-1, and 1144 dBcm-1, Y-polarization
losses of and 450 dBcm-1, 510 dBcm-1 , 650 dBcm-1, 830 dBcm1
,1031 dBcm-1, 1176 dBcm-1 respectively. The loss curve, as
well as the intersection point of both the core mode and spp
mode, define the amplitude sensitivity and mode resolution of
the presented cancer sensor
(8)
Here, ∆n denotes the RI difference, while ∆λmin and ∆λpeak
denotes the lowest and maximum wavelength differences,
respectively, for that particular Refractive Index of the healthy
cells and cancerous or malignant cells for cancer diagnosis. For
the matching cancer cells, the values of ∆n are 0.014, 0.024,
0.014, 0.014, 0.014, 0.014 and 0.02, 0.1 nm is the ∆λmin and
∆λpeak are 0.26,0.2,0.18,0.17,0.16,0.14 and 0.19. The phasedetection technique used to manage the amplitude interrogation
method is directly affected by the sensor's resolution. The
amplitude sensitivity equation may be used to reduce the
complexity of the amplitude interrogation approach.
The suggested cancer sensor's amplitude sensitivity can be
assessed using
RI ( RIU ) = n 
min
 peak
(9)
Here, the confinement loss of the individual bio-samples is
denoted by αc, while the variation in loss and RI between
healthy and malignant cells is denoted by αc and ∆n,
respectively.
Fig. 5 The loss in mode confinement of Y-polarization vs. wavelength for
different types of cancer cells, as well as the SPP mode as well as Core
mode at 80% concentration for the proposed structure.
Fig. 6 The amplitude sensitivity vs. wavelength for the proposed structure.
Bio-samples of malignant cells are shown in Figure 5 in
relation to their amplitude sensitivity in terms of wavelength.
The suggested model generates a severe negative spike in
amplitude sensitivity for every individual malignant cell biosample. As indicated in Table II, the maximum amplitude
sensitivity for each associated cancer cell bio-sample is around
-405 RIU-1, -407 RIU-1, -412 RIU-1, -420 RIU-1, -425 RIU-1,
and -430 RIU-1. The proposed model appears to be more reactive
to the amplitude variation of the corresponding malignant cells
in biomedical samples, which increases the resolution of the
presented cancer sensor. The cancer sensor proposed here has a
maximum interrogative resolution of around 7.37×103 RIU,
1.41×102 RIU, 6.67×103 RIU, 9.35×103 RIU, 8.75×103 RIU, and
1.54×102 RIU.
Fig. 8 Computed RIU as function of wavelength for x & y polarization of the
proposed structure
Fig. 9 Calculated coupling length as function of wavelength for the proposed
structure
Fig. 10 The birefringence response vs. wavelength for the proposed structure
Fig. 7 The calculated transmittance vs. wavelength for the proposed
structure
In this case, the suggested cancer detector sensor may
surpass all existing models. As seen in Figure 6, the plasmon's
birefringence is critical for bio-sample detection on SPR-based
PCF. The maximum practicable birefringence limits between
nearly 0.02 and 0.04, showing an upward rising slope, as the
birefringence of the proposed structure has a direct effect on its
coupling length as well as wavelength sensitivity. In terms of the
postulated wavelength fluctuation, it is straightforward to assert
that the birefringence of the matched cancer cells behaves
linearly along a straight line. The birefringence of the suggested
sensor starts at 0.02 and increases linearly with wavelength
variation of a high birefringence ending of 0.04.
V. DATA TABLE ANALYSIS
TABLE I
THE REFRACTIVE INDICES FOR JURKAT, HELA, PC12, MBA-MD 231,MCF-7
AND CANCEROUS CELL AS WELL AS THEIR CORRESPONDING NORMAL CELLS
Cell Name
Jurkat
HeLa
PC12
MDA-MB-231
MCF-7
Basal
Cell type and
Concentration Level
Blood Cancer (80%)
Normal cell (30-70%)
Cervical Cancer (80%)
Normal cell (30-70%)
Adrenal Glands Cancer
(80%)
Normal cell (30-70%)
Breast Cancer (80%)
Normal cell (30-70%)
Breast Cancer (80%)
Normal cell (30-70%)
Skin Cancer (80%)
Normal cell (30-70%)
Refractiv
e Index
1.39
1.376
1.392
1.368
1.395'
Reference
1.381
1.399
1.385
1.401
1.387
1.38
1.36
[10] - [13]
[10] - [13]
[10] - [13]
[10] - [13]
[10] - [13]
[12],[13]
[12], [13]
[10] - [12]
[10] - [12]
[10] - [13]
[10] - [13]
[10] - [13]
TABLE II
THE RELATIVE SENSITIVITY PROFILE FOR JURKAT, HELA, PC12, MBAMD- 231, MCF-7 AND CANCEROUS CELL AS WELL AS THEIR
CORRESPONDING NORMAL CELLS
Cell
Nam
e
Jurka
t
HeLa
PC12
MDA
MB231
MCF
-7
Basal
Cell
&
Dens
ity
Level
Blood
Cancer
(8 0%)
Blood
Cancer
(8 0%)
Cervical
Cancer
(8 0%)
Cervical
Cancer
(8 0%)
Adrenal
Glan
ds
Canc
er
(80%)
Adre
nal
Glan
ds
Canc
er
(80%
)
(80%)
Breast
Canc
er
(80
%)
Brea
st
Canc
er
(80%)
Brea
st
Canc
er
(80%)
Brea
st
Canc
er
(80%)
Skin
Canc
er
(80
%)
Skin
Canc
er
(80%)
Sw(nm
/RIU)
Sa(R
IU-1)
RI(RIU)
Sv(dB/R
IU
)
DL
1.11×104 -405
7.37×10-3
5857.14
.014
1.07×104 -330
7×10-3
5357.14
1.04×104 -407
1.41×10-2
3571.42
1.02×104 -304
1.4×10-2
3333.33
1.03×104 -412
6.67×10-3
5500
1.0×104
-375
1×10-2
5357.14
1.8×104
-420
9.35×10-3
6785.71
1.78×104
-380
9.33×10-3
6071.42
1.84×104
-425
8.75×10-3
5714.28
1.81×104
-410
8.75×10-3
5642.85
1.78×104
-435
1.54×10-2
4166.67
1.75×104
-430
15×10-2
3900
.024
.014
.014
.014
.02
The coupling length varies gradually as the wavelength
increases in Figure 7. The coupling length varies smoothly
(80%) with wavelength variation for normal cells (30–70%)
and malignant cells (90–100%). The maximum length of a
possible connection ranges between about 35 and 70 µm,
showing an upward-curving tendency, as seen in the
illustration. Additionally, the proposed model's coupling
length has a direct effect on the transmittance. The
transmittance of the recommended model reveals the cancer
sensor's sensing capabilities. The variation in transmittance as
the wavelength of the malignant cell varies is seen in Figure
8. The maximum transmittance is in the middle of -100 and 200 dB, and the pick point for every cell bio sample
demonstrates the optimum sensing capability at that place, as
seen in the figure. Using equations. (6), (7), and (8) in Table
II, the optimal wavelength respondents for blood cancer
(Jurkat) is 11071.43 nmRIU-1, cervical cancer (HeLa) is
10416.67 nmRIU-1, adrenal glands cancer(PC12) is 10357.14
nmRIU-1, breast cancer (MDA-MB-231) cell is 18214.28
nmRIU-1, and breast cancer(MCF-7) cell is 18428.57 nmRIU1
and skin cancer (Basal) has a sensitivity of about 17750
nmRIU-1. The fundamental shortcoming of prior models has
been that they depended on the activity of adjacent cancer
cells to identify a single cancer cell. They compared just one
malignant cell's performance to that of another cancerous cell.
Therefore, the proposed structure's primary objective is to
distinguish various kinds of cancer cell bio-samples from their
normal body counterparts. This is the most effective means of
detecting cancer. Normal cells (30–70%) and malignant cells
(80%) exhibit birefringence in terms of wavelength
fluctuation.
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VI. CONCLUSION
A more optimized and enlarged variant of the D-shape PCF
is suggested, which has more optical parameter flexibility and
enhanced sensitivity over the original model. In terms of
wavelength sensing performance, the proposed model
outperforms any other current or prior models, with wavelength
sensing performance of approximately 11071.43 nmRIU-1,
10416.67 nmRIU-1, 10357.14 nmRIU-1, 18214.28 nmRIU-1,
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breast [type-1,2] and skin cancer respectively with a maximum
detection limit which is almost 0.02.
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