Table of Contents

Other Research Projects

Micro and Nano-Biosensing/Imaging Devices

Conventional optical spectroscopy and imaging systems are large, complex and costly optoelectronic instruments comprised of lasers, spectrophotometers, and detectors. Often, their size is the limiting factor for their use in certain applications such as in-situ monitoring of physiological processes and distributed environmental sensing. In practice, there are strong demands for miniaturized, integrated devices for biomedical applications.

Recent advances in micro-photonics and electronic devices have led to small but efficient components/modules. These technologies are mostly built upon well-established microelectronic technologies for integrated circuitry. When conventional devices are replaced with micro-components, new applications and capabilities can be facilitated. Moreover, it usually leads to significant cost reductions and increases in yield associated with mass production.

The overall objectives of this project area include (i) develop novel micro-optical sensing and imaging device technology with spectrally- and temporally-resolved optical signal acquisition; (ii) investigate the integration and packaging of complete sensing/imaging devices; and (iii) study the applications of such devices in biomedical and environmental applications. The proposed program will be based on the Micro/Nano Systems Lab and focus on integrated device technology development. Its success will allow translation of such technology to applications in biomedical diagnosis, drug discovery, and environmental monitoring.


Publications:


Hyperspectral Imaging of Skin Erythema for Individualized Radiotherapy


Publications:


Optical Biopsy based on time-resolved fluorescence and diffuse reflectance spectroscopy

Time resolved fluorescence (TRF) spectroscopy and diffuse reflectance (DR) spectroscopy have been used as minimally-invasive optical biopsy modalities. They offer real-time alternatives to invasive tissue biopsies. Fluorescence lifetime is independent of intensity variations and adds an additional source of contrast compared to steady state fluorescence. Diffuse reflectance allows for quantitative measurement of optical properties of tissue. Combining both DR and TRF modalities in one optical biopsy instrument allows for the integration of diffuse reflectance, time-resolved, and steady-state spectra for tissue diagnosis as well as real-time correction of the fluorescence lifetime and spectrum based on optical property measurements in-situ.
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Applications of Fluorescence Lifetime Imaging

Barrett’s esophagus (BE) is a precancerous disease with the potential to become esophageal adenocarcinoma, a malignant cancer with a five year survival rate of 12%. Early detection and treatment of BE is crucial to the survival of the patient; however, current detection techniques can be erroneous and slow. A more favourable method of treatment is a real time seek-and-treat strategy at the cellular level through the use of photodynamic therapy. 5-Aminolevulenic acid (5-ALA) has previously been tested as a contrast agent to highlight features at a single cell level. In addition to this, machine learning can be used to extract these highlighted morphological and textural features of the cells to more accurately target specific cells. This procedure has the potential to alleviate cost and discomfort to the patient in comparison to the current biopsy and histology treatment as there is no need to remove samples from the patient. We are working to enhance the detection of BE and implement confocal microendoscopy as a medium for treatment. In order to do this, we use fluorescence imaging of an in vitro model of BE as well as image processing and tools for classification to properly detect and classify the cells. We iteratively test the classification software to ensure sensitive and specific identification for treatment. Our results determined that the algorithm is quick and both highly sensitive and specific at classifying multiple datasets. This is a promising outcome as it is a step toward the implementation of microendoscopy. The speed and accuracy of the algorithm indicates a feasible system. Photodynamic therapy with the help of machine learning is a promising route for cancer prevention.

Publications:

Photoacoustic Tomography for Breast Cancer Detection

The goal of the project is to develop a breast imager that can generate functional tomograms of neoplasms like MRI, but with the speed and convenience of mammography and without the painful breast compression , risky X-ray radiations or radioactive infusions. This can be achieved by using photoacoustics.