PCF-Based SPR Sensors' Air-Hole Attributed Performance Evaluation for Detection of Breast and Adrenal Gland Cancer

Both normal and malignant cells in the human body are classified as intrinsic fluidic cells, and they all have different refractive indices (RIs). Refractometric surface plasmon resonance (SPR) sensors using photonic crystal fiber (PCF) can be used to examine fluidic samples to help diagnose diseases. By comparing variations in resonance wavelength to the typical cell loss peak, these sensors may identify malignant cells. In order to identify breast and adrenal gland cancers, this study examines the numerical evaluation of four PCF-based SPR sensors. These four models, which were built with different air-hole dimensions, were examined for their sensitivity to RI. To strengthen the connection between the PCF and the gold layer, they have a Ti02 coating. Using the full-vector finite element approach, computational calculations were performed using the COMSOL Multiphysics program. Results show that within a limited range of 1.395 to 1.401, the sensors are effective in differentiating between MDA-MB-231, MCF-7, and PC-12, which are cell types that are associated with breast cancer and adrenal gland cancer. Four models (called ‘a’, ‘b’ ‘c’, and ‘d’) for the detection of breast cancer and adrenal gland cancer cells have computed wavelength sensitivities of 10,000 nm/RIU, 7142.857 nm/RIU, and 9285.714 nm/RIU, respectively. By comparison, the amplitude sensitivity that was estimated was -2658.02 RIU-<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</sup>, −1599.52 RIU-<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</sup>, and −843.181 RIU-<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</sup>• Moreover, the model ‘c’ showed the most wavelength shift (140 nm) when compared to the models ‘a’, ‘b’, and ‘d’. The enhanced efficiency presents opportunities for enhanced non-invasive malignant cell identification skills in terms of early detection.