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Development of biomedical optical technologies for early cancer detection

Development of biomedical optical technologies for early cancer detection

 

 

 

 

 

Optical Scattering Properties of Stochastically Inhomogeneous Cell Models: Impact on High-Resolution Cancer Imaging

Cancer is a significant health problem throughout the entire world. For most types of cancer, however, early detection increases the chances for successful treatment and is a key factor in reducing mortality. Hence, there is an increasing demand for highly sensitive and cost-effective screening and diagnostic tools. In current clinical practice, cancer is diagnosed through histopathologic analysis following invasive biopsy. This process is time-consuming, expensive, and painful for patients since it requires excision of tissue sections. Technological advances that have the potential to enable early noninvasive diagnosis of precancerous changes are likely to positively impact management of the cancer problem and to improve public health.

Optical diagnostics is a rapidly developing and promising technology that can enable early cancer detection. Here, we illuminate the tissue sample under investigation with an optical source. Light interacts with tissue and emerges back on the surface. We can collect this remitted light using an optical sensor and we can analyze the detected optical signal to determine whether the tissue is cancerous or not. The process is completely noninvasive, real-time, inexpensive, and robust. We can achieve high resolution and molecular specificity; further, we have the ability to scan large tissue areas since tissue excision is not required.

Modeling studies play an integral role in technology development and assessment, and the field of optical diagnostics is definitely no exception. My project supported by the Campus Research Fund was titled "Optical Scattering Properties of Stochastically Inhomogeneous Cell Models: Impact on High-Resolution Cancer Imaging". This was a two-year project that started in September 2014; it was successfully completed in August 2016. The main goal of the project was to construct normal and precancerous cell models and to numerically analyze their optical properties. Construction of realistic cell models necessitates a detailed documentation of changes associated with cancer progression. In collaboration with researchers at The British Columbia Cancer Research Center in Vancouver, Canada, we analyzed images obtained from normal and precancerous tissue samples and we quantified morphological, structural, and biophysical properties of normal and cancer cells. We then constructed three-dimensional models based on these properties and we employed electromagnetic simulation methods to study differences in how normal and cancer cells respond to and scatter light. Our work can be used to establish a quantitative understanding of diagnostic features observed in optical signals acquired from normal and precancerous tissues. Overall, the results obtained in this project are expected to provide guidelines for design and optimization of optical diagnostic techniques.

Research Group
I received my B.S. degree in Physics, and my M.S. and Ph.D. degrees in Biomedical Engineering from The University of Texas at Austin, USA, in 2000, 2002, and 2005, respectively. I joined the Physics Group at METU Northern Cyprus Campus as a faculty member in 2014. My research in the fields of biophotonics and nanophotonics focuses on development and assessment of novel optical technologies for early cancer diagnosis.

My education and academic experience over the past twenty years have equipped me with the necessary knowhow and skill set to work at the intersection of medical physics and biomedical engineering. It is highly exciting and truly rewarding to carry out interdisciplinary research that is targeted at improvement of healthcare. I intend to follow up on this project and continue to collaborate with my colleagues at The British Columbia Cancer Research Center to contribute to development of biomedical technologies for early cancer detection.

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