|Rizky Maharani||Neuroscience Center – University of Muhammadiyah Prof Dr. HAMKA, Gandaria IV no. 24, South Jakarta 12120, Indonesia|
|Rizki Edmi Edison||Neuroscience Center – University of Muhammadiyah Prof Dr. HAMKA, Gandaria IV no. 24, South Jakarta 12120, Indonesia|
|Muhammad Fathul Ihsan||CTECH Labs Edwar Technology, Jalur Sutera Kav. Spektra Blok 23 BC No. 10-12, Alam Sutera, Tangerang, Banten 15320, Indonesia|
|Warsito Purwo Taruno||CTECH Labs Edwar Technology, Jalur Sutera Kav. Spektra Blok 23 BC No. 10-12, Alam Sutera, Tangerang, Banten 15320, Indonesia|
Brain Electrical Capacitance Volume Tomography (Brain ECVT) is a new technique that realizes real-time volumetric imaging of dynamic changes in electrical activity of the brain and allows total interrogation of the whole volume inside a helmet-shaped sensor. The technique has been used for investigating numerous brain functional abnormalities, including brain tumors, based on permittivity different from the tumor case, as compared to the normal brain. However, interpretation of the conventional Brain ECVT image is not practical for clinical purposes, as the image resolutions are high in the cortical area and lower in the middle region. The technique provides relatively good sensitivity when the tumor is located near the cortex. In this study, we developed a novel method, namely the average subtraction technique, to process the reconstructed image of the brain obtained by Brain ECVT. The technique generates a three-dimensional intracranial distribution of permittivity that correlates with the electrical activity map of the brain with improved resolution in the center region of the brain. The technique provides better insight into brain intracranial electrical activity, which is quite distinctive when there is tumor development inside the brain. The technique may lead to better detection of brain tumors inside the brain based on the electrical activity scan.
Brain ECVT; Brain tumor; Image reconstruction
In neurosciences, non-invasive imaging methods could provide useful information in two broad areas: imaging of variations or abnormalities in structure and imaging of normal or abnormal functional activity of the brain. While the coding of information in brain pathways has long been of interest in this field, the lack of methods capable of measuring the brain structure in a simple and non-invasive fashion has hampered research. The ease of diagnosing structural abnormalities in neurology has been transformed since the development of X-ray CT in the 1970s and, more recently, MRI.
However, brain tumors are already known to have dielectric properties and different permittivity from the normal brain (Yoo, 2004). Generally, an abnormal mass in the brain may cause propagation signals that reach the cortex of the brain. Furthermore, the phenomenon named “brain signal death” will decrease the signals detected by the ECVT sensor (Taruno et al., 2013b) producing specific image construction. However, interpreting such images is not yet practical. In this research, we propose an alternative algorithm for image reconstruction that will make it easier to interpret brain tumor detection by using Brain ECVT.
In this study, we developed an image reconstruction method, called average subtraction, and applied it to a brain image obtained by Brain ECVT. The technique provides a three-dimensional distribution of permittivity that correlates with the electrical activity of the whole brain with an improved resolution, particularly in the center region of the brain. The technique showed a distinctive difference in the electrical activity of the intracranial brain with tumor cases, as compared to the normal brain. The technique may lead to better detection of brain tumors based on an electrical activity scan using ECVT. Further quantification of electrical activity differences is still needed for tumor detection, as the electrical activity may also vary in the presence of brain stimulations or other abnormalities that could affect brain electricity.
Berawi, M.A., 2015. Technology Breakthrough: A Need for Continuous Improvement. International Journal of Technology, Volume 6(3), pp. 302–305
Bunyaratavej, K., Siwanuwatn, R., Chantra, K., Khaoroptham, S., 2010. Duration of Symptoms in Brain Tumors: Influencing Factors and Its Value in Predicting Malignant Tumors. Journal of the Medical Association of Thailand, Volume 93(8), pp. 903–910
Butowski, N.A., 2015. Epidemiology and Diagnosis of Brain Tumors. Continuum, Volume 21(2 Neuro-oncology), pp. 301–313
Elfani, M., Putra, N.K., 2013. Biomedical Engineering and Its Potential for Employment in Indonesia. International Journal of Technology, Volume 4(1), pp. 34–44
Hamilton, W., Kernick, D., 2007. Clinical Features of Primary Brain Tumors: A Case-Control Study using Electronic Primary Care Records. The British Journal of General Practice, Volume 57(542), pp. 695–699
Hanid, M., Mohamed, O., Othman, M., Danuri, M.S.M., Mei Ye, K., Berawi, M.A., 2019. Critical Success Factors (CSFS) in University-Industry Collaboration (UIC) Projects in Research Universities. International Journal of Technology. Volume 10(4), pp. 667–676
Holle, D., Obermann, M., 2013. The Role of Neuroimaging in the Diagnosis of Headache Disorders. Therapeutic Advances in Neurological Disorders, Volume 6(6), pp. 369–374
Taruno, W.P., Baidillah, M.R., Sulaiman, R.I., Ihsan, M.F., Fatmi, S.E., Muhtadi, A.H., Haryanto, F., 2013a. 4D Brain Activity Scanner using Electrical Capacitance Volume Tomography (ECVT). In: Biomedical Imaging (ISBI), IEEE 10th International Symposium on, San Francisco, pp. 1006–1009
Taruno, W.P., Baidiliah, M.R., Sulaiman, R.I., Ishan, M.F., Yusaf, A., Widada, W., Aljohani, M., 2013b. Brain Tumor Detection using Electrical Capacitance Volume Tomography (ECVT). In: Neural Engineering, 6th International IEEE EMBS Conference, pp. 743–746
Taruno, W.P., Ihsan, M.F., Baidiliah, M.R., Tandian, T.A., Mahandra, M., Aljohani, M., 2014. Electrical Capacitance Volume Tomography for Human Brain Motion Activity Observation. In: Middle East Conference on Biomedical Engineering (MECBME), pp. 147–150
Walker, D., Hamilton, W., Waller, F.M., Watts, C., 2013. Strategies to Accelerate Diagnosis of Primary Brain Tumors at the Primary-Secondary Care Interface in Children and Adults. CNS Oncology, Volume 2(5), pp. 447–462
Wang, F., Marashdeh, Q., Fan, L.S., Warsito, W., 2010. Electrical Capacitance Volume Tomography: Design and Applications. Sensors, Volume 10(3), pp. 1890–1917
Warsito, W., Marashdeh, Q., Fan, L.S., 2007. Electrical Capacitance Volume Tomography. Sensor Journal, Volume 27(4), pp. 525–535
Wrench, M., Minn, Y., Chew, T., Bondy, M., Berger, M., 2002. Epidemiology of Primary Brain Tumors: Current Concepts and Review of the Literature. Neuro-Oncology, Volume 4(4), pp. 278–299
Yoo, D.S., 2004. The Dielectric Properties of Cancerous Tissues in a Nude Mouse Xenograft Model. Bioelectromagnetics, Volume 25 (7), pp. 492–497