Microwave Imaging For Stroke Detection In Brain Literature Review Homework Answer

Answer :

Introduction 

Microwave imaging helps to provide brain stroke monitoring and detection. This concept is widely known as microwave tomography. This is widely used in medical science to create images of various internal organs of a human body. Generally, a stroke is considered a disturbance of blood supply to the brain (Pastorino, 2010). These strokes are categorized under two types, namely ischemic and hemorrhagic. In this regard, this paper aims towards providing a literature review on areas such as brain image challenges, dielectric properties of biological tissues, forward and inverse problems, and Huygens principle. While stroke is considered as the number three cause of death, the detection of the same becomes essential in biophysics. 

Stroke Detection in Brain 

Every three minutes, someone dies due to a stroke. That is why its detection becomes essential to consider in the first place. According to Varoquax and other authors' research, early detection can decrease the chances of death due to stroke by 80% (Varoquaux et al., 2010). In this regard, the current diagnosis methods include C.T. scan and MRI as well. Both these methods of diagnosis are considered to be time-consuming and harmful as well. That is why microwave imaging is given higher priorities to detect a stroke in the brain. This helps to provide non-ionizing radiations, which also have zero side effects on the human body. Additionally, this method is considered fast, portable, and cheap, enabling medical science to conduct stroke detection via microwave tomography (Salucci et al., 2017). One such research by Rahman and other authors has conducted vast development that also exploits dielectric variation in the human brain (Rahman et al., 2020). For this purpose, the microwave helmet comes into consideration. These helmets are places on the head and consist of an antenna that detects blood circulations. This concept of biophysics is processed through amplifying signals in which the data is pre-processed. At last, the algorithm helps to create an image that was the main requirement. For this purpose, the head phantom's roles and responsibilities become essential to differentiate between the seven types of tissues present inside a human brain. These include skin, fat, skull, dura, blood, cerebral spinal fluid, white matter, and grey matter. Below is the image that reflects the head phantom. The left figure is about the dielectric profile of the head phantom, and the right reflects the conductivity profile of the phantom. 

Dielectric Profile of Human Brain; (Varoquaux et al., 2010)

To conduct the pre-processing steps successfully, some dignified steps echoed by old research conducted by Ireland and mates (Ireland, Bialkowski and Abbosh, 2013). The first step is generating different antenna signals referred to as An(t), and the n is equal to any natural number starting from one. The next step includes the process of obtaining the difference between signals via a designated formula. The formula is Dn(t)=An(t)-An+1(t). Similarly, the pre-processing step's final step helps provide the signal loss compensation referred to as Fn(t). The signal loss compensation can be derived via Fn(t)= Dn(t)y(t), and the y(t) can be derived through the formula y(t)=1/e-at, where a is echoed as the compensation factor. It has also been echoed by Merunka and other authors' relevant research that the role of imaging system also counted as essential in the process of stroke detection in the brain through microwave detection (Merunka et al., 2019). The imaging system consists of four major components: the body to be an image, the boundary point, light source position, and point to be imaged. For this purpose, the algorithm is derived from Fermat's principle (E=37 for Z). This helps to echo the final intensity calculation that reflects the information about the compensated signals. Lastly, the frequency commonly used in the entire process lies between 0.5 MHz and 2 GHz, and the value of healthy head phantom is referred to as 'a'. Based on this value proposition, different heat maps and intensities are obtained, which detect a stroke in the human brain. 

Brain Image Challenges 

There are several imaging techniques employed regularly so that brain stroke diagnosis can be made simpler. This regard challenges the MRI (Magnetic Resonance Imaging) and C.T. scan (Computed Tomography). As per a research study, it has been found that the microwave imaging process is based on the scattering of electromagnetic waves. It is employed because it is perhaps capable of fulfilling various essential requirements. These include requirements and challenges such as being time-consuming, portable, and non-ionizing to achieve the images (Jugno, Balsiger and Reyes, 2020). These processes offer to process the images of stroke detection and provide a piece of in-depth knowledge about the areas where blood clots are observed. The major challenges in this regard include the processes of repetition that require to be fulfilled in the first place. For this purpose, the microwave imaging process relies on and depends upon various properties that help to provide the opportunity to examine the anatomical region of stroke (Sohani et al., 2020). In this regard, a recent study conducted by Milligan and folks has concluded that a hemorrhagic stroke inside the brain reflects various challenges such as the measurement of detection, location of a brain haemorrhage, the respective dielectric properties (Milligan, Balwani and Dyer, 2019). That is why in the modern biophysics area, human tissues' properties are widely given preferences and also discussed and measured. Amongst all the researchers, it has been observed that the issues with brain imaging processes are most prominent in terms of MWI prototypes. For this purpose, two prototypes are echoed loud, namely the stroke finder and BRIM G2. Both these processes the best but offer various challenges associated with image processing processes for stroke detection. 

While the early clinical trials ensure high probability and productivity of processing the images for stroke detection, BRIM G2 helps developing an exhibit to explain stroke tomography. This is perhaps considered to be comprised of 177 radiating elements that include rectangular shaped ceramic-loaded antennas. These antennas are found to be working with radiation of 1 GHz. In this regard, the major challenges that are found to be associated with the imaging processes include EMTensor and prototyping. That is why an old survey has conducted research based on empirical evidence that helped to conclude that the brain haemorrhage issues contribute to around a 20% increase in the challenges associated with the dielectric properties (He et al., 2011). Thus, to overcome these challenges and reconstruct the imaging processes, the measured data are required to be stabilized with relevant nonlinear solutions and inverse scattering processes. This way, the loopholes associated with achieving clear image processing of stroke in the human brain can be resolved. As a result, the dielectric properties can be aligned parallel with the images. For this purpose, the roles and responsibilities of the mentioned limitations for MWT systems can be counted as essential for processing a clear imaging structure of the human brain and also setting-up a clear image of the anechoic chambers. 

Dielectric Properties of Biological Tissues 

The dielectric properties of biological tissues are played an essential role in the development processes of non-invasive diagnostic processes of microwave and therapeutic systems. As per the research conducted by Gabreil, Camelia, and Peyman, it has been found that there is not much information available about healthy tissues, but in contrast, the gaps in D.P.s of the tissues that are unhealthy are found to be associated with different ages (Gabreil, Camelia and Peyman, 2018). Each tissue in this regard is supposed to be designated by proper dielectric property as per the dependency on solid fractions and the respective water content values. Further, the obtained dielectric properties of the solid fractions have to be aligned right with the water content that is either increasing or decreasing. In comparison, another research showed that the conditions of the dielectric properties are associated with the solid fraction counting and the water content that is commonly found to be in-line with 19 different tissues and around 61 pigments of the human brain (Sohani et al., 2020). These conditions can be evaluated via simple mathematical analysis, and it will also help determine the water content of the respective tissues. For this purpose, the study conducted by researchers has echoed that the dry-weighing method suits the best to determine the water content of the respective tissues (Rossmann and Haemmerich, 2014). The dielectric properties of the respective tissues are then generated using the calculation of D.P.s of tissues at any pathology. In this regard, the roles and responsibilities of the respective evaluation of dielectric properties, water content, drying-weighing compatibility, biological tissues, and solid fractions become essential to be counted. 

Further, the D.P.s (Dielectric Properties) of the respective biological tissues have been compiled and researched using appropriate methods to find the relationship between their accuracies. In this regards, the research conducted by Yilmaz and folks has shown that there is a need for such information so that the development of non-inverse and low-cost microwave imaging systems becomes easier to achieve and process (Yilmaz, Foster and Hao, 2014). The structure and evaluation of the tissues help achieve higher dielectric rates compared with the tumour tissues that usually have higher D.P. values. Some of the previous investigations have shown that the water content of the tissue decrease with a decrease in human age (Abdilla, Sammut and Mangion, 2013). This is why the process of image processing becomes complex if diagnosed after a certain age group. In comparison, there is no such information available that provides a piece of in-depth knowledge about the infrastructure of dielectric tissue counting. The number of research done in this regard is limited and hence, finding information about different conditions on a single tissue is difficult. Furthermore, researchers also explored the impact of temperature on different tissues with microwave ablation thermal sensing. Tissues are the biological element that is considered a heterogeneous material containing dissolved organic molecule, ions, insoluble matter, water, and macromolecules. These dielectric elements are the primary features of organ tissue. Furthermore, it is also described that any change in the composition of tissue material leads to a change in their properties. Thus the dielectric properties get compromised up to a certain level. 

Forward and Inverse Problem

The concept of brain stroke is limited to age-related illness that also becomes an issue when the individuals start ageing. That is why early diagnosis and treatment are considered to be playing an essential role. In this regard, the role of microwave imaging for stroke detection in the brain becomes crucial to be counted as a diagnosis process (Sohani et al., 2020). In this process, the concept of obtaining brain images is counted as common to be aligned with the diagnosis (Shea et al., 2010). One of the main areas where the complications and issues can show up is the areas associated with forwarding and inverse imaging problems. Both the C.T. (Computed Tomography) and NMR (Nuclear Magnetic Resonance) processes are acknowledging the aspects associated with imaging processes, which is why the regulations and processes of both inverse and forward processes become essential to be considered in the first place. As per the research conducted by Oosterom, the processes associated with MWI (Microwave Imaging) are perhaps counted as essential and potential for achieving the fast and accurate diagnostic insights of the human brain (Oosterom, 2012). In this regard, focusing both on forwarding modelling and inverse modelling becomes essential to align right with the DMWI processes that are commonly known as differential microwave imaging processes. To eliminate the issues and problems associated with forwarding and inverse processes, gain knowledge in various areas becomes essential. These include areas such as biology, physics, chemistry, and engineering as well. That is why having efficient solvers to the model of E.M. fields that is commonly referred to as electromagnetic fields, become essential to be aligned with both UHF and SHF bands. 

Forward and Inverse Problems; (Falchetto, Marasteanu and Banedetto, 2011)

The forward problems are found to be arising from a scatter that is also described by using its constructive parameters. The study by Egger and mates in this regard has echoed loud that the importance of various techniques becomes essential to minimize the impact of forwarding problems (Egger, Greberger and Schlotbom, 2010). These include techniques such as FDTD (Finite Difference Time Domain), FEM (Finite Elements Method), and E.I. (Integral Equation) method. For the majority of times, VIE is also found to be given and offered more priority. This technique stands for Volume Integral Equation and stands apart to formulate the diagnosis for the forward problem. Similarly, the inverse problem includes issues associated with the concept of scatterer’s composition. This could be easily understood via the research conducted by former associates who concluded that the inverse problems usually arise due to the constructive parameters aligned with the set of field measurements (Coli et al., 2019). In biomedical and health applications, the measurements and diagnosis are conducted outside the scatterer, which is why the MWI probes surround the complications due to inverse problems. These include the reasons such as non-linearity in the total field empowerment of incident on the head model of the human brain and the second-order interactions. For this purpose, the researchers have echoed that the role and importance of small and large conditioning numbers come into action to resolve the issues and problems associated with forwarding and inverse problems. These two condition numbers are represented below – 

Condition Numbers; (Gramfort, Kowalski and Hamalainen, 2012)

Huygens Principle 

The Huygens principle is considered a geometric tool that gives an in-depth analysis of the position of the wave-front that is perhaps based on prior knowledge and experimental analysis. This principle considered light as a wave and not as a particle. As per the research conducted by Lvanshyn, Kress, and Serrano, it has been found that the Huygens principle involves the participation of wave-fronts to seek wavelets and thus, propagates at a speed that is dependent upon the medium used (Lvanshyn, Kress and Serranho, 2010). Through this way, the new wave-front is observed various wavelets bound that on the surface tangent. Below is the wave representation of the Huygens principle that is applied to two different wave-fronts – 

Huygens Wavefronts; (Paul, 2014)

In the above diagram, the black dots represent the integrity of many points on the real and first wave-front that is taken as the point source. Similarly, the red arcs are found to be representing the spherical wavelets that propagate from the original spot. And lastly, the blue lines are the surface of tangents on which the incidents will be acknowledged (Sohani et al., 2020). In this regard, the Huygens principle states that every point observed and obtained on the wave-front can be considered as a secondary source that will spread out in the forward direction concerning the medium of light. However, the researchers have concluded that Huygens principle is not correct in terms of optical study, and the wave equation in this regard needs to be considered as per the time frame and not as per the source (Rajabalipanah et al., 2019). Thus, it could be possibly intervened that the Huygens principle is correct in terms of waves study but not in the area of optics or biophysics. 

Conclusion

To conclude, this paper aimed towards providing a literature review on areas such as brain image challenges, dielectric properties of biological tissues, forward and inverse problems, and Huygens principle. For this purpose, it has been found that all the concepts discussed above are required to be made in-line with the primary subject of microwave imaging for stroke detection in the brain to obtain better empirical studies and shreds of evidence.