Non-invasive leukemia detection via CSRR sensor

• The present investigation is done to detect cancer by non-invasive approach without the need of drawing blood sample invasively and hence the person will not undergo any pain. • There have been demands for non-invasive pain-free blood chemistry monitoring that would guarantee more affordable, careful and early detection of cancer. • Radio frequency (RF)/Microwave sensing technologies have shown to be more promising for non-invasive glucose monitoring due to the non-destructive nature of the electromagnetic (EM) waves when penetrating inside the biological tissues compared to other ionizing types of radiation such as X-rays that bring hazardous effects. • As non-invasive glucose monitoring is possible, the same could be applied for non-invasive blood cancer detection using microwave sensor. • The primary objective of this work is designing a metamaterial based biosensor to non-invasively detect the blood cancer in humans. This paper introduces a novel non-invasive approach for detecting leukemia cancer using a complementary split-ring resonator (CSRR) biosensor at the 2.45 GHz Industrial, Scientific and Medical (ISM) band. A CSRR biosensor is designed and optimized using the Ansys HFSS simulation software, which utilizes a copper split-ring resonator on a dielectric FR-4 epoxy substrate. The sensor geometry was fine-tuned iteratively to achieve a maximum sensitivity of 46.96 %, which is crucial for biomedical applications. Standard photolithography techniques were adopted to create the sensor, whose performance is validated by making scattering parameter measurements with the help of a vector network analyzer (VNA) yielding excellent agreement with the results of simulations. This biomarker-sensitive CSRR-based sensor uses a fingertip placed non-invasively on an active sensor area. The non-invasive Real-time testing was done on healthy individuals aged 18 to 46 across various blood groups (A1+, B +, O +), with comparative tests involving simulated data for HL-60 leukemia cancer cells. The results showed a downward frequency shift in the presence of cancer cells compared to healthy samples. Sensitivity and permittivity analysis, with permittivity specifically analyzed using MATLAB, confirmed the sensor's ability to differentiate between healthy and cancerous conditions effectively. Furthermore, real-time testing demonstrated consistent S 21 parameter behavior, highlighting the sensor's reliability. The main results obtained were a considerable shift downward in the resonant frequency in the case of HL-60 cancer cells in simulation and real-time measurements. This behavior demonstrates the potential of the sensor to identify biomarkers of early-stage cancers by interacting with cells and tissues under the skin. The integration of VNA with the CSRR biosensor allowed for monitoring and analysis with high accuracy, establishing a reliable framework for non-invasive cancer screening.