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

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

Multispectral optical imaging for the detection and delineation of oral neoplasia

Despite the accessibility of the oral cavity to inspection, patients with oral cancer most often present at a late stage, leading to high morbidity and mortality. Multispectral widefield optical imaging has emerged as a promising technology to aid clinicians in screening and resection of oral neoplasia, but current approaches rely on subjective interpretation. This work focuses on the design, construction, and clinical testing of a novel multispectral widefield optical imaging device for objective screening and delineation of oral neoplasia. The Multispectral Digital Microscope (MDM) acquires in vivo images of oral tissue in autofluorescence, narrow band reflectance, and orthogonal polarized reflectance modes that the diagnostic value of each modality may be qualitatively and quantitatively evaluated alone and in combination. Using in vivo imaging data collected from 56 patients and 11 normal volunteers, combined with computer aided diagnostics, a sensitivity of 100% and a specificity of 91.4% was achieved for discriminating oral dysplasia and cancer from normal tissue in an independent validation set. A single feature calculated from the autofluorescence images at 405 nm excitation was used to achieve this performance. Disease probability maps were constructed using this feature to help identify areas with a high probability of abnormality. Autofluorescence imaging at 405 nm excitation also provided the greatest image contrast which was significantly higher than that using standard white-light illumination. Features extracted from other imaging types did not appear to aid in diagnosis. Ex vivo image data from the MDM was combined with image data from a high-resolution microendoscope (HRME) in order to determine if a synergistic relationship existed between these devices. The ability to objectively diagnose oral lesions substantially increased when using both devices in combination compared to using either alone. This combination of devices provides a practical means of screening the entire mucosal surface for suspicious regions, using the MDM, and then using the HRME for confirmation of diagnosis. This work has demonstrated that widefield autofluorescence imaging at 405 nm excitation can be highly effective for the objective discrimination of oral lesions

Exploiting diffuse reflectance measurement uncertainty estimates in spatial frequency domain imaging

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)

A combined frequency domain near infrared spectroscopy and diffuse correlation spectroscopy system for monitoring the sternocleidomastoid muscle

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Optical sampling depth in the spatial frequency domain.

We present a Monte Carlo (MC) method to determine depth-dependent probability distributions of photon visitation and detection for optical reflectance measurements performed in the spatial frequency domain (SFD). These distributions are formed using an MC simulation for radiative transport that utilizes a photon packet weighting procedure consistent with the two-dimensional spatial Fourier transform of the radiative transport equation. This method enables the development of quantitative metrics for SFD optical sampling depth in layered tissue and its dependence on both tissue optical properties and spatial frequency. We validate the computed depth-dependent probability distributions using SFD measurements in a layered phantom system with a highly scattering top layer of variable thickness supported by a highly absorbing base layer. We utilize our method to establish the spatial frequency-dependent optical sampling depth for a number of tissue types and also provide a general tool to determine such depths for tissues of arbitrary optical properties

Shortwave infrared imaging and spectroscopy in the time and spatial frequency domains

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Spatial frequency domain imaging for monitoring immune-mediated chemotherapy treatment response and resistance in a murine breast cancer model

Spatial Frequency Domain Imaging (SFDI) can provide longitudinal, label-free, and widefield hemodynamic and scattering measurements of murine tumors in vivo. Our previous work has shown that the reduced scattering coefficient (μ's) at 800 nm, as well as the wavelength dependence of scattering, both have prognostic value in tracking apoptosis and proliferation during treatment with anti-cancer therapies. However, there is limited work in validating these optical biomarkers in clinically relevant tumor models that manifest specific treatment resistance mechanisms that mimic the clinical setting. It was recently demonstrated that metronomic dosing of cyclophosphamide induces a strong anti-tumor immune response and tumor volume reduction in the E0771 murine breast cancer model. This immune activation mechanism can be blocked with an IFNAR-1 antibody, leading to treatment resistance. Here we present a longitudinal study utilizing SFDI to monitor this paired responsive-resistant model for up to 30 days of drug treatment. Mice receiving the immune modulatory metronomic cyclophosphamide schedule had a significant increase in tumor optical scattering compared to mice receiving cyclophosphamide in combination with the IFNAR-1 antibody (9% increase vs 10% decrease on day 5 of treatment, p < 0.001). The magnitude of these differences increased throughout the duration of treatment. Additionally, scattering changes on day 4 of treatment could discriminate responsive versus resistant tumors with an accuracy of 78%, while tumor volume had an accuracy of only 52%. These results validate optical scattering as a promising prognostic biomarker that can discriminate between treatment responsive and resistant tumor models.1830878 - U.S. National Science Foundation; W81XWH-15-1-0070 - U.S. Department of DefensePublished versio

Cylindrical illumination with angular coupling for whole-prostate photoacoustic tomography

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

Preliminary investigation of non-invasive blood pressure estimation using speckle contrast optical spectroscopy

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