5 research outputs found

    Online learning combining virtual lectures, at-home experiments and computer simulations: a multidisciplinary teaching and learning approach

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    We developed a fully-remote biophotonics workshop integrating webinars, computer simulations and at-home experiments to meet the needs of undergraduate students with diverse backgrounds and learning styles. Similar strategies/resources could be used in multidisciplinary programs

    Insights into Biochemical Sources and Diffuse Reflectance Spectral Features for Colorectal Cancer Detection and Localization

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    Colorectal cancer (CRC) is the third most common and second most deadly type of cancer worldwide. Early detection not only reduces mortality but also improves patient prognosis by allowing the use of minimally invasive techniques to remove cancer while avoiding major surgery. Expanding the use of microsurgical techniques requires accurate diagnosis and delineation of the tumor margins in order to allow complete excision of cancer. We have used diffuse reflectance spectroscopy (DRS) to identify the main optical CRC biomarkers and to optimize parameters for the integration of such technologies into medical devices. A total number of 2889 diffuse reflectance spectra were collected in ex vivo specimens from 47 patients. Short source-detector distance (SDD) and long-SDD fiber-optic probes were employed to measure tissue layers from 0.5 to 1 mm and from 0.5 to 1.9 mm deep, respectively. The most important biomolecules contributing to differentiating DRS between tissue types were oxy- and deoxy-hemoglobin (Hb and HbO2), followed by water and lipid. Accurate tissue classification and potential DRS device miniaturization using Hb, HbO2, lipid and water data were achieved particularly well within the wavelength ranges 350–590 nm and 600–1230 nm for the short-SDD probe, and 380–400 nm, 420–610 nm, and 650–950 nm for the long-SDD probe

    Evaluation of wavelength ranges and tissue depth probed by diffuse reflectance spectroscopy for colorectal cancer detection

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    Abstract Colorectal cancer (CRC) is the third most common type of cancer worldwide and the second most deadly. Recent research efforts have focused on developing non-invasive techniques for CRC detection. In this study, we evaluated the diagnostic capabilities of diffuse reflectance spectroscopy (DRS) for CRC detection by building 6 classification models based on support vector machines (SVMs). Our dataset consists of 2889 diffuse reflectance spectra collected from freshly excised ex vivo tissues of 47 patients over wavelengths ranging from 350 and 1919 nm with source-detector distances of 630-µm and 2500-µm to probe different depths. Quadratic SVMs were used and performance was evaluated using twofold cross-validation on 10 iterations of randomized training and test sets. We achieved (93.5 ± 2.4)% sensitivity, (94.0 ± 1.7)% specificity AUC by probing the superficial colorectal tissue and (96.1 ± 1.8)% sensitivity, (95.7 ± 0.6)% specificity AUC by sampling deeper tissue layers. To the best of our knowledge, this is the first DRS study to investigate the potential of probing deeper tissue layers using larger SDD probes for CRC detection in the luminal wall. The data analysis showed that using a broader spectrum and longer near-infrared wavelengths can improve the diagnostic accuracy of CRC as well as probing deeper tissue layers

    Label-Free Optical Spectroscopy for Early Detection of Oral Cancer

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    Oral cancer is the 16th most common cancer worldwide. It commonly arises from painless white or red plaques within the oral cavity. Clinical outcome is highly related to the stage when diagnosed. However, early diagnosis is complex owing to the impracticality of biopsying every potentially premalignant intraoral lesion. Therefore, there is a need to develop a non-invasive cost-effective diagnostic technique to differentiate non-malignant and early-stage malignant lesions. Optical spectroscopy may provide an appropriate solution to facilitate early detection of these lesions. It has many advantages over traditional approaches including cost, speed, objectivity, sensitivity, painlessness, and ease-of use in clinical setting for real-time diagnosis. This review consists of a comprehensive overview of optical spectroscopy for oral cancer diagnosis, epidemiology, and recent improvements in this field for diagnostic purposes. It summarizes major developments in label-free optical spectroscopy, including Raman, fluorescence, and diffuse reflectance spectroscopy during recent years. Among the wide range of optical techniques available, we chose these three for this review because they have the ability to provide biochemical information and show great potential for real-time deep-tissue point-based in vivo analysis. This review also highlights the importance of saliva-based potential biomarkers for non-invasive early-stage diagnosis. It concludes with the discussion on the scope of development and future demands from a clinical point of view

    Mobile multi-configuration clinical translational Raman system for oral cancer application

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    Early diagnosis of oral cancer is critical to improve the survival rate of patients. Raman spectroscopy, a non-invasive spectroscopic technique, has shown potential in identifying early-stage oral cancer biomarkers in the oral cavity environment. However, inherently weak signals necessitate highly sensitive detectors, which restricts widespread usage due to high setup costs. In this research, the fabrication and assembly of a customised Raman system that can adapt three different configurations for the in vivo and ex vivo analysis is reported. This novel design will help in reducing the cost required to have multiple Raman instruments specific for a given application. First, we demonstrated the capability of a customized microscope for acquiring Raman signals from a single cell with high signal-to-noise ratio. Generally, when working with liquid samples with low concentration of analytes (such as saliva) under a microscope, excitation light interacts with a small sample volume, which may not be representative of whole sample. To address this issue, we have designed a novel long-path transmission set-up, which was found to be sensitive towards low concentration of analytes in aqueous solution. We further demonstrated that the same Raman system can be incorporated with the multimodal fibre optical probe to collect in vivo data from oral tissues. In summary, this flexible, portable, multi-configuration Raman system has the potential to provide a cost-effective solution for complete screening of precancer oral lesions
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