This PDF file contains the front matter associated with SPIE Proceedings Volume 11213, including the Title Page, Copyright information, Table of Contents, Author and Conference Committee lists.

This study presents a novel technology for in vivo cochlear imaging in sensorineural hearing loss (SNHL). SNHL is the most common type of permanent hearing loss and is associated with damaged hair cells of the cochlea. State of the art clinical imaging does not have sufficient resolution to show inner ear microstructure. We are developing and testing a dual-modal endoscopic instrument that combines optical coherence tomography (OCT) and autofluorescence imaging (AFI) for dynamic cochlear imaging. If successful, this approach will improve our understanding of the cellular basis of SNHL and enable the development of targeted therapies for inner ear disorders.

The inner ear is a small and sophisticated organ, mainly comprising of the vestibular system and cochlea, responsible for hearing function and plays a crucial role in the life wellness.There have been several studies of investigating the cochlear structures with OCT, and most of these studies used OCT systems with a central wavelength of 1.3 µm. However, the utility of 1 µm OCT system for cochlear imaging application has yet been explored albeit the capability of providing OCT images with a higher axial resolution. Therefore, in this study, we have developed a 1.3 µm and a 1 µm OCT system allowing quantitative and spectroscopic comparison of the cochlear microstructures.

Oral cancer is one of the major cancers worldwide with >50% 5-year survival-rates owing to lack of early diagnosis. In view of this, in-vivo, exfoliative cells, and serum Raman spectroscopy have been actively pursued as theranostic solution. These studies successfully demonstrated stratification of healthy, malignant and premalignant oral conditions. In the present study, Serum Raman spectroscopy (SRS) which enables minimal invasiveness and distant diagnosis is rigorously evaluated in the experimental oral carcinogenesis, hamster buccal-pouch model. Sequential spectral variations have been observed across 14 weeks in controls and carcinogen (DMBA) treated hamster sera. Processed Raman spectra of sera (Weeks 1, 4, 8, 10, 12 and 14) were subjected to PCA and PC-LDA, both week-wise and group-wise. Serum spectra of untreated and physical injury controls showed misclassification as tumor/DMBA treated group at later weeks. Also misclassifications between injury and tumor spectra (12 and 14 weeks) have been observed suggesting chronic mechanical irritations/injuries as an important etiological factor in oral carcinogenesis. On the other hand, spectra of DMBA treated and physical injury group do not classify as untreated or vehicle control spectra, suggesting the significance of SRS as a rapid and objective diagnostic adjunct tool.

Oral cancers are major killers among the South Asian Nations primarily due to late detection. The biochemical variations during cancer progression especially in the early stages needs to be explored to further detection and treatment regimen. Diagnosis and treatment protocols are dependent on histopathology, which is time-consuming and requires high-degree of expertise. Optical techniques such as Raman spectroscopy present immense potential towards label-free objective optical biopsy methods and has been shown to identify healthy, premalignant, cancerous changes along with inflammatory conditions and cancer field-effects in vivo. Raman mapping of tissue-sections can provide molecular level changes in oral mucosa layers during malignant transformation. In the present study, we have undertaken mapping of healthy and carcinogen-treated tissues from Hamster buccal-pouch, the widely used experimental carcinogenesis model. Two parallel cryosections of 5 and 20 micron were obtained. The 5-micron sections were stained to obtain histopathological correlation while selected areas from the 20-micron sections were mapped (WITec-Alpha-300R, 50X objective, 532nm). Maps were constructed using WITec-Project-5.1 software. Spectra from the regions of interest were processed and subjected PCA-based linear discriminant analysis using Unscrambler software. Initial findings suggest several informative clusters in tissue sections and segregation of healthy and tumor spectra with high accuracy. Further studies with more samples will involve analysis of the clusters and detailed correlation with histopathology to understand biochemical and morphological variations to achieve optical biopsy.

In this study, we proposed and designed a transmission mode polarized hyperspectral imaging microscope (PHSIM). The hyperspectral imaging (HSI) component is based on the snapscan with a hyperspectral camera. The HSI wavelength range is from 467-700 nm. Polarized light imaging is realized by the integration of two polarizers and two liquid crystal variable retarders (LCVR), which is capable of full Stokes polarimetric imaging. The new imaging device was tested for the detection of squamous cell carcinoma (SCC) in H&E stained oral tissue slides of 8 patients. One normal area and one cancerous area on each slide are selected to make the comparison. The preliminary results indicated that the spectral curves of the Stokes vector parameters (S0, S1, S2, S3) of the normal area on the H&E stained oral tissue slides are different from those of SCC in certain wavelength range. Further work is required to apply the new polarized hyperspectral imaging microscope to a large number of patient samples and to test the PHSIM system in different cancer types.

As we know, fluorescence lifetime imaging has demonstrated the ability to accurately detect materials and tissue constituents^1–3. Current fluorescence lifetime systems rely on accurate temporal sampling to capture the tails of the decaying emission. These data are often fit to an exponential decay model^3,4. Although these methodologies are powerful tools but they are often implemented as point measurement systems and require significant postprocessing to compute decay times or coefficients^5–8. In some applications these factors can hinder clinical translation. Based on these observations, our group has developed algorithms and built simple, fast, and wide field imaging system^9,10. This method uses a gated charge-coupled device (CCD) and a liquid light cable guided LED to compare the decay-time image intensity vs excited state image intensity, thus generating a spatially resolved maps of relative differences in autofluorescence decay of tissue constituents. This approach ensures very fast updating speed (< 2 sec per frame), big field of view (20 mm x 20 mm), excellent depth of field (up to 6 mm) for surface curvature of interested target at reasonable working distance (~50 mm). This innovative imaging system has a temporal resolution of 0.16 nanosecond, spatial resolution of 70 μm and has proved the capability to differentiate visibly similar tissue types, which has been validated with both fluorescent dyes and ex vivo human tissue samples in comparison to commercially available FLIM microscope. This work establishes a foundation to confirm the utility of our upgraded DOCI system for intraoperative tissue differentiating/imaging. Validation with a larger number of samples is currently ongoing.

There us a significant need for point of care pathology technologies that provide microscopic resolution without the processing that is typically required. 20,000,000 biopsies per year in the USA each present a week delay in cancer care while they are processed and analyzed. Bedside confocal microscopy offers an alternative but has typically been difficult to perform due to the irregularity of surgical specimens and reflectance artifact. The sample irregularity makes it hard to put the correct plane of tissue in the conjugate focal plane and the reflectance artifact that arises from the glass/water interface at the window surface onto which the sample is pressed, gives the appearance of tissue outside the specimen (where there is no tissue, false positive for tissue). We present newly developed computational and electromechanical solutions to these problems and analysis of specimens under our clinical research study.

The CO₂ laser has proved its worth in daily clinical use for soft tissue surgery because of the good cutting quality. Now DPSS Er:YAG laser systems are available, which promise a better cutting efficiency and minor thermal damages. Goal of this study was the comparison of both laser systems for soft tissue cutting.

Firstly, an experimental set-up was realized with a clinical CO₂ laser system with micromanipulator and focusing unit. The Er:YAG laser system was an experimental set-up (DPM40, Pantec Biosolutions AG) with focusing unit in order to achieve the same spot diameter (500 μm). For both, a computer-controlled translation stage with sample holder was used to move the sample (mucosa of fresh porcine tongues) with a defined velocity while irradiation by various laser parameters. Additionally, for the Er:YAG laser system, the influence of the laser power, cutting velocity, and pulse repetition rate on to the cut depth and thermal damage was examined. While irradiation the tissue effects were recorded by a video camera, adapted on a surgical microscope. After irradiation, the samples were analyzed by light microscopy. Also, histological sections were prepared and microscopically analyzed.

The Er:YAG laser shows higher cutting depth (about 1 mm (Er:YAG) compared to 500 μm (CO₂) at 7.7 W and 5 mm/s) and less coagulation damage (about 70 μm compared to 120 μm). Both the cutting depth and thermal damage zone can be adjusted in a wide range by varying the irradiation parameters.

In conclusion, these experiments demonstrate significant advantages of the diode pumped Er:YAG laser system for soft tissue cutting compared to the CO₂ laser, in particular it is more efficient and causes minor thermal damage.

In recent years, the use of convolutional neural networks has been rapidly increasing in computer vision related tasks, thanks to its versatility and flexibility in its ability to be trained with large swaths of data. In the biomedical field, neural networks have great potential to streamline and perform tasks on the level of human ability without the drawbacks of human error potentially tainting the results. This study evaluates the efficiency and accuracy of a trained neural network in segmenting the trachea of rats before and after exposure to methyl isocyanate (MIC) and a drug candidate, nitro-oleic acid (NO₂OA) . The images of the trachea were gathered using optical coherence tomography. The neural network was modeled after the U-net convolutional network model for biomedical image segmentation. Accuracy was evaluated by taking cross-sectional areas of the trachea and using the Sørensen-Dice similarity coefficient comparing the neural network’s prediction of segmentation to manual segmentation of the trachea. The trained neural network showed an accuracy similar, but not perfect, to human analysis of the trachea.

Phonation is a unique ability tightly connected to the vocal folds’ biomechanical properties. Unfortunately, radiological imaging modalities have insufficient resolution and contrast to assess the 3D vocal fold morphology, therefore limiting our understanding of the pathogenesis of laryngeal lesions. Herein, we investigate the three-dimensional human vocal fold fiber distribution and orientation with Optical coherence tomography (OCT), Two-photon excitation fluorescence (TPEF) and Second harmonic generation (SHG). The findings are summarized in a 3D model of the human vocal folds and suggest why vocal pathology occurs predominantly in discrete areas of the vocal fold.

Current laser surgery on vocal chords requires the patient to be under general anaesthesia due to relatively low cutting speed and precision. Even minor surgeries can change vocal properties, requiring lengthy post-operative therapy. To solve this problem and reduce recovery time we propose a laryngoscope capable of performing the surgery while the patient is awake. To realize this, it is necessary for each cut to be made on the shortest time scale with the highest precision possible. It is also important to have high speed feedback to initiate or terminate the cutting process as well as to maintain the proper cutting position. In this laryngoscope we employ a coaxial MHz OCT and laser cutting system with a MEMS galvo scanner combined with a high speed stereo camera set. The MHz OCT is responsible for axial feedback and measuring the depth of cut while the stereo camera set is used to adjust the MEMS scanner for lateral offsets. We have determined the optimal optical layout for the laryngoscope using Zemax and have developed 3D CAD models of the prototype demonstrator prior to fabrication and assembly. This new laryngoscope could make laser cuts up to 50% smaller in width than traditional multimode fiber based cuts, in addition to reducing overall surgery time and increasing the precision of each cut.

Tumors of the upper respiratory tract are the sixth most common tumor entity in humans. Currently a dedicated screening method enabling a direct onsite diagnosis is missing. This can lead to delayed diagnoses and worse outcomes of the patients. An optical method enabling a direct distinction between healthy tissue, dysplastic tissue and cancerous tissue would be an ideal tool for the detection of tumors of the upper respiratory tract. In this study we used fluorescence lifetime imaging (FLIM) of NADH and FAD to image the metabolic state in different tissue samples of the upper aerodigestive tract (UADT). Due to the different metabolic pathways that are active in healthy and tumor cells their metabolic states differ significantly. FLIM datasets of tissue samples from 25 patients were recorded directly after surgery ex vivo in a special tissue culture medium at 37°C on a dedicated microscope using multiphoton excitation. By calculating the fluorescence-lifetime redox ratio (FLIRR) based on the FLIM measurements, we were able to visualize the metabolic state of the cells. We found that healthy tissue, dysplastic tissue and cancerous tissue showed significant differences in the FLIRR. This study suggests that the FLIRR might be a sensitive and robust parameter for the differentiation of cancerous and pre-cancerous UADT tissue and that optical metabolic imaging could be a valuable tool for an early tumor diagnosis within this area.

Here we present a study where we used in vivo hyperspectral imaging (HSI) for the detection of upper aerodigestive tract (UADT) cancer. Hyperspectral datasets were recorded in 100 patients before surgery in vivo. We established an automated data interpretation pathway that can classify the tissue into healthy and tumorous using, different deep learning techniques. Our method is based on convolutional neural networks (CNNs) with 2D spatial or 3D spatio-spectral convolutions combined with a state-of-the-art Densenet architecture. Using both the spatial and spectral domain improves classification accuracy notably. Our 3D spatio-spectral Densenet classification method achieves an average accuracy of over 80%.