# Wave-Shaped Microstructure Cancer Detection Sensor in Terahertz Band: Design and Analysis
## 7 Conclusions  
This article introduces a high-sensitivity biosensor for cancer cell detection. The suggested sensor model is sufficiently versatile for detecting and categorizing different cancer cells. Table 3 displays the optical specifications for the HC-PCF sensor that is suggested for the detection of cancer cells at 3 THz. Our theoretical research suggests that excellent sensitivity for a variety of cancer cells can be achieved with minimal CL. Additionally, as shown in Table 2, modeling results demonstrate that our proposed PCF structure performs better overall than the previous PCF structure for cancer cell detection. The key PCF design parameters have been significantly improved as a result of this study to maximize production efficiency. Our study has several limitations to consider. Our goal was to achieve high sensitivity with low losses, which required us to think beyond common shapes and develop a slightly complex model. As a result, the design we proposed may be challenging to fabricate using methods other than 3D printing technology. Hence, we recommend using 3D printing technology for the fabrication process. It is also important to note that environmental factors such as temperature, humidity, and pH may affect the performance of the biosensor we proposed. Figure 14: Schematic Diagram of this work for Cancer Cell Detection. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Analyte** & **RS (\%)** & **CL (dB/cm)** & **EML (cm\({}^{-1}\))** & **EA (m\({}^{2}\))** & **B** & \(\beta\) & **NA** \\ \hline \hline Adrenal Gland Cancer & 99.9277 & \(6.1\times 10^{-10}\) & \(8.55\times 10^{-5}\) & \(4.22\times 10^{-7}\) & \(1\times 10^{-9}\) & 0.0152 & 0.0865 \\ Blood Cancer & 99.9243 & \(6.1\times 10^{-10}\) & \(8.96\times 10^{-5}\) & \(4.23\times 10^{-7}\) & \(>1\times 10^{-9}\) & 0.0152 & 0.0864 \\ Breast Cancer Type-1 & 99.9302 & \(6.1\times 10^{-10}\) & \(8.24\times 10^{-5}\) & \(4.21\times 10^{-7}\) & \(>1\times 10^{-9}\) & 0.0152 & 0.0866 \\ Breast Cancer Type-2 & 99.9314 & \(6.1\times 10^{-10}\) & \(8.09\times 10^{-5}\) & \(4.21\times 10^{-7}\) & \(>1\times 10^{-9}\) & 0.0152 & 0.0866 \\ Cervical Cancer & 99.9257 & \(6.1\times 10^{-10}\) & \(8.79\times 10^{-5}\) & \(4.23\times 10^{-7}\) & \(>1\times 10^{-9}\) & 0.0152 & 0.0864 \\ Skin Cancer & 99.9169 & \(6.0\times 10^{-10}\) & \(9.88\times 10^{-5}\) & \(4.25\times 10^{-7}\) & \(>1\times 10^{-9}\) & 0.0153 & 0.0862 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The proposed HC-PCF sensor’s optical parameters for cancer cell detection at 3.0 THz. The proposed biosensor has a lot of potential in implementing other bio applications such as the Microfluidic Invasion Chemotaxis Platform for 3D Neurovascular Co-Culture [52], 3D-Printed Microneedles (MNs) [53], etc., to increase the overall performance and improve the user experience. Microfluidic Invasion Chemotaxis Platform for 3D Neurovascular Co-Culture can be used to study tissue and organ models and model human diseases to check the performance of our biosensor for detection in systems that include more than one cell. Additionally, we can implement 3D-printed MNs for collecting analytes from the human body for our proposed sensor as they are user-friendly and minimally invasive, offering less pain and lower tissue damage than conventional needles. So, by incorporating these technologies with our proposed biosensor, the overall performance and user experience can enhance greatly. The proposed biosensor has a great deal of potential for quickly identifying different cancer cells because it has improved sensitivity and sophisticated packaging to protect the detecting head. The authors firmly believe that the suggested PCF structures can be made, thanks to recent developments in 3D nano-fabrication methods. Software, M.H.M. ; Validation, A.A.C. ; Investigation, M.M.N. ; Resources, M.R.I. ; Data curation, M.S.H. ; Supervision, M.R.H.K. All authors have read and agreed to the published version of the manuscript.