RETRACTED: Ultra-Sensitive Biosensor with Simultaneous Detection (of Cancer and Diabetes) and Analysis of Deformation Effects on Dielectric Rods in Optical Microstructure

Abstract

This study proposes a refractive index sensor for the simultaneous detection of cancer and diabetes based on photonic crystals (PhC). The proposed PhC composed of silicon rods in the air bed arranged in a hexagonal lattice forms the fundamental structure. Two tubes are used to place the cancerous or diabetic samples for measurement. The sensor’s transmission characteristics are simulated and analyzed by solving Maxwell’s electromagnetic equations using the finite-difference time-domain approach for samples being studied. Therefore, diabetes and cancer are detected according to the changes in the refractive index of the samples using the laser source centered at 1550 nm. Considering the findings, the sensor’s geometry changes to adjust the suggested sensitivity and quality factor of structure. According to the results, transmission power ranges between 91 and 100% based on the sample. Moreover, sensitivity ranges from 1294 to 3080 nm/RIU and the maximum Figure of Mertie is nearly FOM = 1550.11 ± 150.11 RIU⁻¹ with the detection in range 31 × 10⁻⁶ RIU. In addition, the small area (61.56 μm²) of biosensor results in its appropriateness for different uses in compact photonic integrated circuits. Next, we changed the shape of the dielectric rods and investigated their effects on the sensitivity parameter. The sensitivity and figure of merit after changes in the shape of dielectric rods and nanocavities are at best S = 20,393 nm/RIU and FOM = 9104.017 ± 606.93 RIU⁻¹, receptively. In addition, the resolution detection range is 203.93 × 10⁻⁶ RIU.

1. Introduction

Studies have shown the major benefits of the integrated optical circuits (IOCs) over electronic integrated circuits (EICs) [1,2,3,4,5,6,7,8,9,10,11,12]. In fact, IOCs enjoy lower loss rate, a much greater propagation speed, lower error rate of data transmission, as well as very high security in comparison with the electrons in EICs [12,13,14,15,16,17,18,19,20,21,22,23,24]. On the one hand, they have contributed importantly to the design of all-optical circuits because of their specific features, one of which is that their photonic bandgap (PBG) that prevents lights of certain wavelengths from propagating in one, two, or any number of polarization directions within the PhC structure. PhCs are designed in one, two, and three-dimensional (3D) structures, whose two-dimensional (2D) structure has been considered by researchers due to its greater applications and fabrication simplicity. Research groups designed a variety of structures using two-dimensional PhCs such as optical filters [25,26,27,28,29,30,31,32], Full adders [33,34,35], encoders [36], comparators [37,38], Flip-Flop [39], analog-to-digital converters [40,41], registers [42,43], memories [44,45,46], sensors [47,48], Biosensors [49,50]. Photon crystals are designed in one-dimensional (1D), 2D and 3D, which is a proposed structure in the present research according to the 2D PhCs.

Interestingly, biosensors are devices employed for detection of the samples with diverse features. Researchers have adopted two general approaches to detection: (1) the use of conventional labels to represent analyzes, and (2) the use of non-invasive unlabeled methods, in which any markers should not be used for identifying the analytes. Since no label is attached to the molecules, therefore, the actual nature and data of the biodegradable material remain constant. Furthermore, it is possible to use the biosensors in cancer research for analyzing the changes in proteins or target cell lines [51]. Therefore, all-optical biosensors have been recognized to be proper for disposable rapid detection. It should be noted that the key performance of the structure of the PhC-based biosensors is determined with regard to the used samples’ refractive index. Moreover, the structure we presented in our research has the ability to simultaneously detect two samples of human blood and tear fluid, which makes the function of the proposed structure different from the similarly designed structure, and on the other hand, samples of two different people can be identified simultaneously. Given inadequate and crowded hospital conditions, this can be a good option to speed up the diagnosis and the number of people diagnosed with the disease [52].

Among recent work on biosensors there has been the integration of colloidal metal nanoparticles (NPs) with high metamorphic adsorbents as a promising mechanism for overcoming the poor bonding properties and poor detection of these devices. This will provide promising solutions in the future [53]. In addition, an alternative class of unlabeled, in situ, selective and highly sensitive plasmonic biosensors based on cyclic multipolar electrodynamics has been developed and introduced. In the field of theoretical physics, optical dynamic rings are also suitable solutions [54].

One kind of cancer usually starts in the bone marrow and is followed by the formation of multiple abnormal WBCs. These white blood cells (WBCs) are not fully formed and are known to be either blast cells or leukemia cells. Their symptoms are bruising and bleeding, extreme tiredness, higher risk of infections and fever, which are caused by the absence of healthy blood cells [55,56]. The disease can be diagnosed by bone marrow biopsies and blood tests. In fact, acute myeloid leukemia (AML), acute lymphoid leukemia (ALL), less common chronic myeloid leukemia (CML), and chronic lymphocytic leukemia (CLL) have been proposed as the four important leukemia. Leukemia is a part of a wider group known as neoplasms that include bone marrow, blood, as well as the lymphatic system called lymphoid and hematopoietic tumors [57]. It is well known that diabetes is one of the metabolic disorders in the human body so that the body loses the production function of the first hormones in the disease, or resists insulin. Therefore, normal function of the insulin production is lost. Actually, the major contribution of insulin has been recognized to be the decrease in blood sugar using a variety of mechanisms. Practitioners have introduced two major kinds of diabetes. Destruction of beta cells in the pancreas in type 1 diabetes will be followed by the impaired insulin production. On the other hand, insulin resistance is developed in the body and in type 2 diabetes, which can be subsequently followed by the degeneration of beta pancreas Cells and full failure to produce insulin. It was found that obesity, dementia, and genetic factors contribute significantly to type 2 diabetes. Hence, blood glucose tests should be done for screening and diagnosing diabetes. Therefore, testing for the absence or presence of diabetes would be often accompanied by bleeding and pain. In the present research, using human tear fluid, we differentiate a diabetic from a normal person [58].

The structure of the biosensor is determined according to the 2D finite difference time domain approach (2D-FDTD). Thus, the grid size (ΔX, ΔZ) is chosen in various values in the FDTD solution. For achieving a steady-state in the simulations, it is based on Equation (1), illustrating the light propagation in a PhC and is obtained by solving Maxwell’s electro-magnetic equations [59].

$$\nabla \times (\frac{1}{\epsilon }\nabla \times H)={(\frac{\omega }{C})}^{2}H$$

(1)

where ε is the permittivity and ω represents the frequency. According to Equation (1), frequency “ω” has shown to be proportionate to the dielectric function (ε = n² or n = √ ε), where n is the refractive index of dielectric rods). As can be seen, by changing the dielectric function, so frequency changes. Finally, dielectric function of ε with frequency n is inversely proportional [60,61].

The perturbation theory covers the change in frequency of the ω band relative to its original value because of the changes made in the small refractive index RI (Equation (2)) [62]:

$$\frac{\Delta \omega }{\omega }\approx -\frac{\Delta RI}{RI}{f}_a$$

(2)

where f_a is part of the optical energy in the analyte and is defined as follows [62]:

$$f_a=\frac{{\displaystyle {\int }_{V_a}\epsilon (r){\left|E(r)\right|}^{2}dV}}{{\displaystyle {\int }_V\epsilon (r){\left|E(r)\right|}^{2}dV}}$$

(3)

Here, V_a is the volume that the analyte fills. The sensitivity of the sensor is [50]:

$$S=\frac{\Delta \omega }{\Delta RI}\approx \frac{\omega }{RI}{f}_a$$

(4)

Now if we rewrite Equation (4) in the form of wavelength, then the sensitivity value is equal to Equation (5) [50]:

$$S=\frac{\Delta {\lambda }_0}{\Delta RI}\approx (\frac{nm}{RIU})$$

(5)

The FWHM represents the full width at half magnitude of the optical signal. Moreover, Q.f implies the quality factor derived from Equation (6) [50]:

$$Q.f=\frac{{\lambda }_0}{FWHM}$$

(6)

Another important parameter employed for describing the ability of the sensor, considering the full width at half the maximum (FWHM) resonance, is the figure of merit (FOM), computed through Equation (7) [50]:

$$FOM=\frac{S}{FWHM}(RI{U}^{-1})$$

(7)

The λ₀ parameter indicates the resonant frequency of the output signal. In addition, Δλ shows the differences between the resonant frequencies of both output signals detected in the biosensor. ΔRI refers to the differences between the samples’ refractive index that are used in the diagnosis. A laser source with continuous-wave tuning provides optical signal input to the structure and its outputs, and thus it analyzes the optical output in the structure of a digital time monitor.

2. Materials and Methods

2.1. Band Structure

Now, we design and simulate the proposed basic structure. There is an optical gap created in the TM polarization mode. For obtaining the most suitable radius of the dielectric rods, for which the band = width of the photon band is maximum, we utilize a photon band-width diagram in terms of saturation r/a for the polarization mode TM by flat wave clamp (PWE). Then, the constant value of the network a = 600 nm is chosen so that the refractive index is n = 3.46 and the radius of the dielectric rods in the structure is r = 120 nm. Figure 1a shows the basics of PhC structure and Brillouin. Figure 1b depicts the working mode of the optical signal as well as the proposed structure. As can be seen, TE mode scatters the optical signal in the structure, but with the TM mode is reflected.

Figure 2a shows the Gap map for the TE and TM polarization modes. As shown by the figure, the blue areas correspond to the TM polarization mode and the pink areas correspond to the TE polarization mode. As can be seen in this figure, the number of blue areas is greater for different radii. Hence, this new structure can work in different radii of dielectric rods with TM polarization mode. Figure 2b demonstrates the photonic band-gap range with a free spectral range of FSR = 833 nm in ranges a/λ = 0.275~0.445. Finally, the structure wave-length ranges from λ = 1.348 µm~2.181 µm.

2.2. Optical Biosensor

For a better understanding, we depict this new structure in three-dimensions in Figure 3a. As shown in this figure, the dielectric rods are placed on a silicon substrate. Figure 3b addresses the two dimensions of the structure and has two linear nanocavities that can simultaneously detect two cancer cells and diabetes cells in one or two different humans. Hexagonal photonic crystal with silicon rods is placed in the air substrate (n_air = 1) with a refractive index of n₀ = 2.46. In addition, the lattice index equals a = 500 nm. Tunable laser source with a central wavelength of λ = 1550 nm is employed for the structure input wave-guide. Furthermore, the radius of red nanocavity is R_C1 = 0.9 a, and the radius of light cyan nanocavity is R_C2 = 1.1 a. This structure works in such a way that we place a sample of human blood in a red nanocavity and a sample of human tear fluid is poured into a light cyan nanocavity. Based on the samples’ refractive index, the resonance wavelength shifts and two resonant wavelengths are received simultaneously at the output of the structure. The structure works in such a way that a sample of human blood is placed inside a red nanocavity and a sample of human tear fluid is poured into a light cyan nanocavity. Based on the refractive index of the samples, the resonance wavelengths have shifted and at the output of the structure as two resonance wavelengths are received simultaneously.

Table 1. A brief list of the parameters used in the new biosensor.

Parameters	Symbols	Quantity	Unit
Central wave-length	λ0	1550	nm
Normalized band gap (TM)	a/λ	0.276–0.446	-
The corresponding photonic bandgap	λ	1345–2173	nm
Lattice constant	a	600	nm
Rod radius	r	120	nm
Background refractive index (air)	ngb	1	-
Linear refractive index	n0	3.46	-
Radius of the red tube	RC1	540	nm
The cyan tube radius	RC2	660	nm
X length	∆x	5400	nm
Y length	∆y	11,400	nm

presents each parameter applied in the design of the suggested structure.

3. Result and Discussion

The 2D-FDTD approach has been used to simulate the sensitive biosensor. In the FDTD solution method, the network size (∆_X, ∆z) a/16, which is equal to 37.5 nm, is selected. In this way and in the simulations that we want to reach a steady-state, we must act according to Equation (8). Therefore, the time step is equal to Δt = 0.02421875 us in this simulation, and the value of the PML. Width is selected to be 500 nm. The starting point of the solution in the FDTD method is to follow the Maxwell equations (1). Parameter C represents the light speed in air [20].

$$Dt\le \frac{1}{c\sqrt{\frac{1}{D{x}^2}+\frac{1}{D{y}^2}}}$$

(8)

In Figure 4, first, we place the tear fluid and blood samples of healthy individuals with refractive indexes of 1.35 and 1.36 into the red and light cyan nanocavities, respectively. With regard to this figure, 2 resonance wave-lengths are taken at the output, the values of the resonance wave-lengths refer to the healthy cases. Moreover, we utilize a resonant wavelength with a central frequency of 0.387 to the structure. Therefore, the shifted resonant wave-length for the blood sample of the healthy human equals λ_S2 = 1.59315 µm but the shifted wave-length for the tear sample of a normal human equals λ_S1 = 1.56235 µm. So, when these two resonance wave-lengths are taken at the output of this new structure, it is found that the cases are healthy and thus any diabetes or cancer cells do not exist in the samples. Major factors in the optical biosensor include the amount of sensitivity (S), quality factor (Q.f), the figure of merit (FOM), full width at half maximum (FWHM), as well as the detection limits (DL). For the resonance wave-length of the refractive index of 1.35 tears fluid normal samples, FWHM equals 1.8 nm, but it is 2.2 nm for the refractive index of 1.36 blood normal. In the detection of a healthy case who does not have any diabetes and cancer cells, the figure of merit is FOM = 1550.11 ± 150.11 RIU⁻¹ and S equals 3080 nm/RIU. Finally, the transfer power percentage is 95% for sample1 and 100% for sample2. Figure 4 represents the resonance wavelength of the normal blood samples and tears fluids, which is shown in section (a) normalized transmission power and in section (b) transmission power in dB scale.

Up to this section, only human normal cell sample1 and tear fluid sample2 were examined. In the following, we introduce the refractive index values of different cancer cells and diabetes cells and examine all the values and determine the intensification wavelengths of each refractive index.

Table 2. Refractive index of blood sample1 and tears fluid sample2 of human.

Analytic Used	Refractive Index
Sample1	RI
Basal cells (Normal)	1.360
Basal cells (Cancerous)	1.380
Hela cells (normal)	1.368
Hela Cells (Cancerous)	1.392
MDA-MB-231 Cells (normal)	1.385
MDA-MB-231 Cells (Cancerous)	1.399
Sample2	RI
Normal Cells of diabetes	1.350
Effected Cells of diabetes	1.410

shows the Refractive index of normal cells of different cancer and diabetes cells.

Figure 5 shows basal cells normal and basal cancer cells with refractive indexes of 1.360 and 1.380, respectively. The basal cell normal is placed in sample1 and the basal cancer cell is placed in sample2. In addition, basal cancer cells form in the external layer of the skin (epidermis) because of the intensified sun exposure. Their spread to other parts of the body has not been observed [52]. Moreover, the refractive index of cancer cells is 1.38 but the healthy stem normal cells have 1.36 refractive index. Figure 5a plots the sensor output for both kinds of basal cancer and normal cells, without cancer cells, which in each case shows a specific amplitude wave-length. Furthermore, FWHM equals 2.2 nm for normal cells and 2 nm for the basal cancer cells. The figure of merit parameter level is FOM = 940.475 ± 025 RIU⁻¹ at best, so that sensitivity for this state is S = 1893 nm/RIU. Then, Figure 5b depicts the sensor output for detecting the absence or presence of Hela cancer cells, which have been introduced as humans’ cancer cells that cannot be very controlled compared to normal cells. These cells are cancerous because of infections with the human papillomavirus 18 (HPV18) [53]. Hela cells have a refractive index of 1.392 but the normal HeLa cell-lines have a refractive index of 1.368. FWHM equals 1.9 nm for Hela cell carcinomas and 2.2 nm for normal cells. Consequently, the figure of merit parameter level has been shown to be FOM = 940.475 ± 025 RIU⁻¹ at best, but sensitivity for this state of S =1642 nm/RIU. Finally, transmission power for the normal and Hela cell is TE_N = 99% and TE_H = 95%. It should be noted that we extracted MDA-MB-231 from the human chest and then isolated it from pleural disease that has been extracted from a case with breast cancer [54]. The level of the FOM suitability shape value is FOM = 6097 RIU⁻¹ cancer cells. In this regard, Figure 5c demonstrates the resonance wavelength for the MDAMB-231 normal and cancer Cells. According to the analysis, the refractive index of such a cancer equals 1.399 but the normal cells of breast have a deflection coefficient of 1.385. Diabetes detections are made on the humans’ tear fluid and refractive index for normal people equals 1.35 but it equals 1.41 in diabetic people. Figure 5d shows the resonance wave-length for the normal cells as well as the presence of the diabetic cells from the sensor outputs. Moreover, transmission power for the normal and diabetes cell and sensitivity for this state of S = 1294 nm/RIU is TE_H = 100% and TE_N = 95%. Additionally, FWHM equals 1.8 and 1.9 nm for the normal and diabetes cells, respectively.

Here, we have studied and analyzed the radius effect of sample1 and sample2 nanocavities as important structure parameters. Figure 6a shows the effects of the nanocavity radius of sample1 on the transmission power percentage, resonant wavelength and FWHM. These calculations are computed for the state of a normal person with a basal cell normal refractive index of 1.36. Considering the figure, the percentage of power transfer in a radius of R_C1 = 540 nm would reach 100% so that the most acceptable radius for reducing the power losses to zero and passing 100% of the transmitted power is this radius. Put differently, full width at half the maximum in various radii has other values, but in the radius of R_C1 = 540 nm, it has less value, which represents the optical signal received with the lowest bandwidth. Figure 6b examines the effects of sample2 radius with a refractive index of 1.38 on the basal cell (Cancer) on the major structural factors. Hence, when the radius of the sample nanocavity sample2 increases to R_C2 < 660 nm, we see the same amount of transfer power, but if the radius enhances, we observe reduction in the amount of transfer power. Thus, R_C1 = 660 nm with 94% transfer power would be the best value of radius. Moreover, the amount of band-width reaches the minimum in this radius. Therefore, by studying and considering the findings, we were able to select the best radii for samples 1 (R_C1 = 540 nm) and samples 2 (R_C2 = 660 nm).

In the final section,

Table 3. Calculation of the major factors in the biosensor with the tear fluid and blood samples.

Analytic	RI	λ0 (µm)	FWHM (nm)	Q.f	T.E (%)	FOM (RIU−1)	S (nm/RIU)
Sample1
Basal cell (Normal)	1.360	1.59315	2.2	840.45	100	-	Ref
Basal cell (Cancerous)	1.380	1.63101	2.0	946.50	94	940.475	1893
Hela cell (normal)	1.368	1.60010	2.2	746.36	99	-	Ref
Hela Cell (Cancerous)	1.392	1.63951	1.9	864.25	95	805.283	1642
MDA-MB-231 Cell (normal)	1.385	1.60511	2.1	464.33	93	-	Ref
MDA-MB-231 Cell (Cancerous)	1.399	1.63611	1.9	861.11	91	1109.51	2214
Sample2
Normal diabetic cells	1.350	1.56235	1.8	867.97	95	-	Ref
Effected diabetic cells	1.410	1.64001	1.9	863.31	100	699.96	1294

presents final results calculated and analyzed. The table calculates the values of sensitivity parameters, transmission power, average band-width, figure of merit, and quality factor for various refractive indexes in nanocavity of sample1 and sample2. The best detection and the highest sensitivity obtained for the detection of normal blood MD-MB-231 Cell (normal) in nanocavity sample1 is equal to 2214 nm/RIU. The highest form of competence is to detect a normal blood MD-MB-231 Cell (Cancerous) in nanocavity sample2, which is equal to FOM = 1109.51 ± 55.235 RIU¹.

Deformations Effects on Results

In this section, we design the base of our structure as a cubic lattice index with square dielectric rods. In fact, the PhC is made up of dielectric rods in the air Substrate and the PhC lattice constant equals a = 500 nm. Figure 7a depicts the difference of the refractive index between the substrate air and the dielectric rod. Moreover, square dielectric rods are chosen in X_(Scale) = Z_(Scale) = 212.5 nm sizes. Figure 7b demonstrates the Brillouin zone and Kath for a square dielectric rod. Considering the figure, refractive index enhances from (n_(air) = 1~n_(silicon) = 3.46) or (Ɛ_(air) = 1~ε_(silicon) = 11.9716). An important thing is that the refractive index is computed as epsilon (ε = n²).

We want to examine the effects of the dielectric rod shape on the results. So, we redesign the proposed structure with square dielectric rods and compare the results (Figure 8). In the new design, we change the dielectric rods to a square shape, and the grid structure is the same as a hexagon. The dimensions and specifications of the structure with square rods are in accordance with the structure with circular rods. Figure 5 redesigns the proposed biosensor structure with square rods. The two-dimensions of silicon dielectric rods are X_(Scale) = Z_(Scale) = 687.5 nm.

We found that as the dielectric bars deformed into squares, the sensitivity of the structure increased significantly. First, we placed samples of healthy human blood and tears fluid in square cavities and calculated the results. With regard to Figure 9a, the resonant wavelengths generated for the samples are very long and have increased about 9-fold. As the distance between the resonant wavelengths increases and resolution detection range is ∆λ = 203.963 nm, so does the sensitivity. The sensitivity value in this measurement is equal to S = 20,393 nm/RIU. Then the figure of merit value equals FOM = 9104.017 ± 606.93 RIU⁻¹. The transfer power in sample1 is equal to TE = 88% and in sample2 is equal to TE = 86%. In Figure 9b, to calculate the quality factor and FWHM, we calculate the values of the resonant wavelengths in dB scale. The quality factor for blood and tear fluid samples is 613.02 and 603.49, respectively.

In this section we want to calculate the results of different blood and tears fluid samples in the new structure with square rods. Figure 8 shows the detection of a normal person from a diseased person using blood and tear fluid samples simultaneously. In Figure 10a, we placed the blood sample of a normal person in a red square nanocavity (sample1) and the blood sample of a cancer person in a blue square nanocavity (sample2). Therefore, we received an output signal with two resonant wavelengths at the same time, that a resonant wavelength for a normal person and for cancer person equal to λ_S1 = 1.26733 µm and λ_S2 = 1.48922 µm, respectively. In this detection, the distance between the resonant wave-lengths increases compared to the previous structure (circle rods), which equals ∆λ = 221.89 nm. Moreover, an important sensitivity parameter for basal cell detection was obtained from normal cell S = 11,094.5 nm/RIU. Then the Figure of Merit parameter was calculated FOM = 4860.447 ± 64 RIU⁻¹. In Figure 10b, a blood sample of a normal person is placed in a red square nanocavity and a blood sample of a cancer cell is placed in a blue square nanocavity. This section has been examined to detect Hela cells. Detection of Hela cancer cells from normal cells was calculated with sensitivity S = 10,370 nm/RIU and FOM = 4611.165 ± 422.64 RIU⁻¹. Considering this figure, the distance between the resonant wavelengths enhances and the amount of transmission power decreases. The minimum distance between the resonant wavelengths and maximum sensitivity are calculated in Figure 10c with a resolution detection range value of ∆λ = 202.35 nm and S = 14,453.57 nm/RIU. In addition, in the detection of normal cells from diabetes cells in Figure 10d, the maximum distance between the resonant wavelengths and the lowest sensitivity were calculated, which are equal to ∆λ = 524.11 nm and S = 8735.16 nm/RIU, respectively.

To better understand the effects of dielectric rod shape (square and circle) on the most important parameter of the structure, the results of the sensitivities at different refractive index is calculated in Figure 11. As you can see, when square rods are used, the sensitivity of the new structure increases significantly and the average sensitivity increases by almost 8000 nm/RIU. The lowest value in increasing the sensitivity is related to the diabetic cell with a value of 7441.16 nm/RIU. It was found that the highest value in increasing sensitivity is related to basal cells with a value of 12,239.57 nm/RIU.

Table 4. Comparison of the detection sample1 and sample2, transmission power, quality factor, sensitivity parameters of new sensor with the previous sensors.

Ref	Detect Samples	Q.f	FOM (RIU−1)	TE (%)	S (nm/RIU)
Ref [63]	Blood, Tear’s fluid	6141	48,543 ± 118	100	10,000
Ref [64]	Blood	650 ± 50	1400 ± 200	80	2500
Ref [65]	Blood and Tears fluid	1082	-	-	6.5764
Ref [66]	Glucose	-	-	86	422
Ref [67]	Glucose	1.11 × 105	1117	92	462
Ref [68]	Blood	262	-	100	-
Ref [69]	-	-	88	98	263
Ref [69]	-	1264	84	90	840
This work	Tears fluid	946.50	9104.017 ± 606.93	100	20,393

is a comparison of the important factors of the structure devised in the present research with other studies. According to the table, this new structure outperforms other structures with regard to the transmission power, detection sensitivity, figure of merit, simultaneous application of detection of both samples with two intensified nanocavities, and quality factor.

4. Conclusions

As mentioned earlier, our new sensor, using the tears fluid and human blood samples, can differentiate persons with diabetes and cancer from healthy ones. Moreover, simultaneous detection of two samples with two resonance nanocavity is considered an important property that distinguishes this structure. By diagnosing these cells, cancer cells, diabetic cells in blood samples and human tear fluid, diseases can be detected. The main task is detection by two resonance nanocavities at the center of the biosensor structure. Due to the significance of sensitivity and accuracy in designing the sensors, FWHM = 1.8 nm and sensitivity and figure of merit after changes in the shape of dielectric rods and nanocavities are at best S = 20,393 nm/RIU and FOM = 9104.017 ± 606.93 RIU⁻¹, receptively. In addition, the resolution detection range is 203.93 × 10⁻⁶ RIU.