699 research outputs found

    Multimodal snapshot spectral imaging for oral cancer diagnostics: a pilot study

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    Optical imaging and spectroscopy have emerged as effective tools for detecting malignant changes associated with oral cancer. While clinical studies have demonstrated high sensitivity and specificity for detection, current devices either interrogate a small region or can have reduced performance for some benign lesions. We describe a snapshot imaging spectrometer that combines the large field-of-view of widefield imaging with the diagnostic strength of spectroscopy. The portable device can stream RGB images at 7.2 frames per second and record both autofluorescence and reflectance spectral datacubes in < 1 second. We report initial data from normal volunteers and oral cancer patients

    Cylindrical illumination with angular coupling for whole-prostate photoacoustic tomography

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    Current diagnosis of prostate cancer relies on histological analysis of tissue samples acquired by biopsy, which could benefit from real-time identification of suspicious lesions. Photoacoustic tomography has the potential to provide real-time targets for prostate biopsy guidance with chemical selectivity, but light delivered from the rectal cavity has been unable to penetrate to the anterior prostate. To overcome this barrier, a urethral device with cylindrical illumination is developed for whole-prostate imaging, and its performance as a function of angular light coupling is evaluated with a prostate-mimicking phantom

    Optical Imaging With a High-Resolution Microendoscope to Identify Cholesteatoma of the Middle Ear

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    Objectives/Hypothesis: High-resolution optical imaging is an imaging modality that allows visualization of structural changes in epithelial tissue in real time. Our prior studies using contrast-enhanced microendoscopy to image squamous cell carcinoma in the head and neck demonstrated that the contrast agent, proflavine, has high affinity for keratinized tissue. Thus, high-resolution microendoscopy with proflavine provides a potential mechanism to identify ectopic keratin production, such as that associated with cholesteatoma formation, and distinguish between uninvolved mucosa and residual keratin at the time of surgery. Study Design: Ex vivo imaging of histopathologically confirmed samples of cholesteatoma and uninvolved middle ear epithelium. Methods: Seven separate specimens collected from patients who underwent surgical treatment for cholesteatoma were imaged ex vivo with the fiberoptic endoscope after surface staining with proflavine. Following imaging, the specimens were submitted for hematoxylin and eosin staining to allow histopathological correlation. Results: Cholesteatoma and surrounding middle ear epithelium have distinct imaging characteristics. Keratin-bearing areas of cholesteatoma lack nuclei and appear as confluent hyperfluorescence, whereas nuclei are easily visualized in specimens containing normal middle ear epithelium. Hyperfluorescence and loss of cellular detail is the imaging hallmark of keratin, allowing for discrimination of cholesteatoma from normal middle ear epithelium. Conclusions: This study demonstrates the feasibility of high-resolution optical imaging to discriminate cholesteatoma from uninvolved middle ear mucosa based on the unique staining properties of keratin. Use of real-time imaging may facilitate more complete extirpation of cholesteatoma by identifying areas of residual disease

    A Toposcopic Investigation of Brain Electrical Activity Induced by Motion Sickness

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    A toposcope was constructed as a new tool to study signal frequency and phase relationships in electroencephalogram (EEG) records collected while subjects were experiencing motion sickness. This new tool, named TOPOS, is a software-based, multi-featured version of Grey Walter and Harold Shipton\u27s device which they first produced in the late 1940s. The TOPOS graphical display permits the study of instantaneous frequency relationships between the input channels and a reference signal of fixed or varying frequency. TOPOS adds a correlation grid to aid observers in detecting channel-to-reference correlation levels. Users can also vary several display parameters via menus to optimize the analysis environment. Sinusoidal test inputs of known frequency produced recognizable and predictable patterns on the TOPOS display, depending on the existing channel-to-reference frequency relationships. Motion-sickness-affected EEG was input to TOPOS in order to study the correlation between the displays of each channel and four separate references: a 1.5-Hz sinusoid, and three channels of the EEG itself. Rapidly varying correlations were observed in each case

    Frequency domain diffuse optical tomography with a single source and detector via high- speed hypocycloid scanning

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    Diffuse Optical Imaging (DOI) relies on the fact that near infrared light (600-1000 nm) is strongly scattered in biological tissue, and weakly absorbed by tissue chromophores such as blood, fat, water, and melanin. In frequency domain DOI, intensity modulated light is introduced into the tissue and the observed absorption and phase changes enable absolute concentrations of these chromophores to be calculated. These concentrations provide valuable insight into tissue metabolic activity that have proven useful for a variety of clinical outcomes from exercise physiology to predicting tumor response to treatment. Diffuse Optical Tomography (DOT) is an extension of DOI that allows three dimensional reconstruction of tissue chromophore concentrations. Typically, DOT requires a large number (~10-100) of light sources and detectors to collect the data necessary for 3D reconstruction. In these systems, each source and detector pair probes a specific volume of tissue and an algorithm is used to reconstruct tissue chromophore concentration within each voxel. However, the use of large numbers of fibers results in imaging systems that are large, expensive, unwieldy, and often anatomically specific (i.e. systems are constructed for breast measurements and cannot be easily used on other anatomical locations). In this poster I will present a new method for DOT that uses a single source and detector fiber in a potentially hand-held format that is able to probe a large volume of tissue using rapid scanning of each fiber in a hypocycloid pattern. Please click Additional Files below to see the full abstract

    Exploiting diffuse reflectance measurement uncertainty estimates in spatial frequency domain imaging

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    Spatial frequency domain imaging (SFDI) is a wide-field, noncontact diffuse optical imaging technique that has garnered significant interest for a variety of applications, including the monitoring of skin and breast lesions in clinical settings, and the progression of Alzheimer’s disease and drug delivery to the brain in mouse models. In most applications, diffuse reflectance measurements are used to quantify the optical absorption and reduced scattering coefficients of the turbid medium, and with these, chromophore concentrations of interest are extracted (e.g., hemoglobin in tissue). However, uncertainties in estimated absorption and reduced scattering values are rarely reported, and we know of no method capable of providing such uncertainties when look-up table-based inversion algorithms are used to recover the optical properties. Quantifying these uncertainties would have several important benefits. For example, they could be propagated forward to yield uncertainties in estimated chromophore concentrations, which could have profound implications for the interpretation of experimental results. They could also be employed to help guide the selection of spatial frequencies used for SFDI measurements, given the requirements of the specific application. In this work, we make two novel contributions. First, we show how knowledge of the accuracy of diffuse reflectance measurements from an SFDI instrument (i.e., diffuse reflectance uncertainty estimates) can be transformed to yield quantitative predictions of uncertainties for recovered absorption and reduced scattering values. Second, we use diffuse reflectance uncertainty estimates directly in a new algorithm for the recovery of optical properties. This algorithm performs equivalently to a standard look-up table-based approach but is up to ~200X faster (per pixel). To transform diffuse reflectance uncertainty estimates into uncertainty estimates for the absorption and reduced scattering coefficients, we employ the Cramer-Rao bound (CRB). The CRB is a lower bound that defines the best achievable precision (i.e., lowest variance) of any unbiased estimator for a given data model. It is often used in the statistical signal processing community, especially in the sonar and radar signal processing communities, to perform feasibility studies and system design. We calculate the CRBs for the absorption and reduced scattering coefficients and use them as our estimates of uncertainties for these parameters. We show that these estimates agree with results from Monte Carlo simulations to better than 0.1% for the common scenario where optical properties are computed with a look-up table using two spatial frequencies. We validate our simulations with tissue-mimicking phantom experiments and in vivo measurements on a human volunteer. This method of generating uncertainty estimates opens the door to several exciting possibilities. For example, the analytical form of the CRB calculation can be exploited to quickly generate “maps” of uncertainty estimates as a function of optical properties and spatial frequencies, thereby providing a tool that can be used to efficiently explore this trade space. The CRB-derived uncertainty estimates can also be propagated into chromophore uncertainty estimates. With knowledge of the spatial frequencies and wavelengths used for a given application, it is possible to pre-compute look-up tables of optical property and/or chromophore uncertainty estimates, which would be a significant advantage for applications requiring real-time performance. Diffuse reflectance uncertainty estimates can also be used to speed up optical property recovery with no performance penalty. We have developed a new algorithm to do this that in simulation performs equivalently to a standard look-up table-based approach employing linear interpolation but is up to ~200X faster (per pixel)
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