# Exploring the Potential of Sensing for Breast Cancer Detection
## 6 Challenges for Existing Techniques and Prospects  
NMRI pictures can express a minimal change inside a medium. Sometimes doctors suggest the consideration of the breast under an MRI experimental setup and observe a small change associated with breast cancer to determine cancerous cells further. NMRI can successfully select a shift inside the breast even though the mammogram cannot do that [57; 58; 59]. NMRI is suitable for early breast cancer detection, but the availability of NMRI is challenging in different parts of world. Sometimes, patients feel uncomfortable with NMRI due to its relation to nuclear technology. Most of these methods are cost-effective, time-consuming, and unavailable worldwide. Again, this method is hard to manage for early detection of breast cancer or regular checkups for cancerous cells. Microwave imaging is considered an effective method for early breast cancer detection. However, these methods have some limitations. The dielectric properties of the breast phantom are not precisely measured. The contrast between the tumor and other tissues' dielectric properties is minimal for detecting the existence of a tumor inside the breast specifically. Antennas are the most critical components in microwave imaging systems. The mutual coupling between these antennas also increases with the increasing antenna numbers of a microwave imaging system [45]. This mutual interaction of the antenna's radiation further leads to a low-resolution tumor position and size image. On the other hand, a lot of data are associated with different functions and orientations of the antennas. So, it is essential to utilize a specific method to determine the physical properties of individual data related to simulation. So, in that case, we again face a significant challenge in encapsulating extensive data and defining a specific binary decision corresponding to this large dataset. Several researchers applied the concept of artificial intelligence or neural networks to certify individual datasets and predict the future of breast cancer [166; 167; 168; 169; 170; 171; 172; 173; 174]. So, artificial intelligence is one of the most promising tools for generalizing the problem for individuals' datasets and determining the corresponding possibilities. In MITI, the scattering between the incident electromagnetic wave and living tissue reduces the intensity of the incident light, and the absorption of electromagnetic waves by the living tissue sometimes causes deformation of the cells. On the other hand, the temperature variation and the sound wave associated with electromagnetic phenomena ultimately provide an indication of a tumor in a regime instead of a specific point. SPR has many advantages; viz., it is a level-free method, and potential leveling artifacts are not required. It is a direct method because it measures the binding of the actual analyte. This method can provide information about the evolution of the experiment in real time. However, SPR has some disadvantages. SPR is designed for mass change, decreasing with the distance from the surface. The LOD is around 200 nanometers, and this method is also dependent on the material, especially gold and silver. Highly viscous materials cannot be considered for an experiment, and the sample must be homogeneous to be used in the investigation. Sample preparation and probe attachment to the metal surface are challenging. A colorimetric biosensor is a fast, inexpensive, and portable detection device that can be used for the early detection of cancer biomarkers. However, this process has trouble determining the individual components of a mixture. Chemometric methods have been considered for encapsulating large datasets of red, green, and blue values [175]. Moreover, challenges are also associated with the reproducibility of imaging and printing. SERS can be applied to find the information of a submicron system. SERS can determine the bonding information associated with different phases of materials.