KEYWORDS: In vivo imaging, Optoacoustics, Spectroscopy, Signal to noise ratio, Short wave infrared radiation, Tissue optics, Light scattering, Pulsed laser operation, Laser sources, Biomedical optics
In this work we developed a novel near-infrared two-path optoacoustic spectrometer (NiR-TAOS) that could sense OA intensity changes due to metabolite concentration changes in-vivo. The main aim of dividing the optical path in two is 1) perform real time correction of the laser emission profile of the laser source at different wavelengths and, 2) perform pulse to pulse correction to remove laser beam fluctuation and instability to increase signal to noise ratio. Signal to noise ratio improvement was significant not only at spectral peaks, but also at all other wavelengths. The system can be used for broad applications in biomedical measurements such as various metabolites in the SWIR.
An advantage of fluorescence methods over other imaging modalities is the ability to concurrently resolve multiple moieties using fluorochromes emitting at different spectral regions. Simultaneous imaging of spectrally separated agents is helpful in interrogating multiple functions or establishing internal controls for accurate measurements. Herein, we investigated multimoiety imaging in the context of a limited-projection-angle hybrid fluorescence molecular tomography (FMT), and x-ray computed tomography implementation and the further registration with positron emission tomography (PET) data. Multichannel FMT systems may image fluorescent probes of varying distribution patterns. Therefore, it is possible that different channels may require different use of priors and regularization parameters. We examined the performance of automatically estimating regularization factors implementing priors, using data-driven regularization specific for limited-projection-angle schemes. We were particularly interested in identifying the implementation variations between hybrid-FMT channels due to probe distribution variation. For this reason, initial validation of the data-driven algorithm on a phantom was followed by imaging different agent distributions in animals, assuming superficial and deep seated activity. We further demonstrate the benefits of combining hybrid FMT with PET to gain multiple readings on the molecular composition of disease.
Rheumatoid arthritis (RA) is the most common chronic inflammatory joint disease, with a prevalence of 0.5 to 1% in the general population. Imaging can possibly aid in early diagnosis, crucial to effective personalized therapeutic strategies and treatment follow-up. The intravenous administration of indocyanine green (ICG) has been considered for identifying synovial hyperperfusion as an RA physiological biomarker. However, while the distribution of ICG in the human hand is a time-dependent process, the particular biodistribution dynamic patterns established following intravenous administration have not yet been studied. For this reason, the dynamic relationships of ICG distribution in the human hand in RA patients using a method based on principal component analysis are analyzed. In vivo analyses were corroborated by simulations of clinical scenarios using a finite element method. Observations of spatiotemporal characteristics are contrasted to fluorescence intensity images and magnetic resonance images of the hand joints, employed as the anatomical and diagnostic reference. Processing results for 450 joints from 5 healthy volunteers and 10 patients show that image features obtained from the spatiotemporal analysis offer good congruence with synovitis and reveal better detection performance compared to observations of raw fluorescence intensity images.
We present a method for reduction of image artifacts induced by the optical heterogeneities of tissue in fluorescence molecular tomography (FMT) through identification and compensation of image regions that evidence propagation of emission light through thin or low-absorption tunnels in tissue. The light tunneled as such contributes to the emission image as spurious components that might substantially overwhelm the desirable fluorescence emanating from the targeted lesions. The proposed method makes use of the strong spatial correlation between the emission and excitation images to estimate the tunneled components and yield a residual image that mainly consists of the signal due to the desirable fluorescence. This residual image is further refined using a coincidence mask constructed for each excitation-emission image pair. The coincidence mask is essentially a map of the "hot spots" that occur in both excitation and emission images, as such areas are often associated with tunneled emission. In vivo studies are performed on a human colon adenocarcinoma xenograft tumor model with subcutaneous tumors and a murine breast adenocarcinoma model with aggressive tumor cell metastasis and growth in the lungs. Results demonstrate significant improvements in the reconstructions achieved by the proposed method.
Depth-resolved imaging of fluorescent molecules in tissue using a non-invasive optical modality called fluorescent
molecular tomography (FMT) has found applications in pre-clinical and clinical studies. While FMT offers unique and
affordable functional imaging capabilities, its resolution is limited due to the diffusive nature of light propagation in
tissue. In this paper we offer a framework for investigating the resolution of FMT using information-theoretic concepts.
Specifically, we analyze the amount of useful information that exists in a set of emission measurements. The information
content of the measurements directly affects the actual resolution that can be achieved in the reconstructed threedimensional
fluorescence images. The relationship between this information content and the measurement geometry is
further discussed where it is shown that expanding the measurement size does not necessarily increase the information
content. The concept of capacity as defined for multi-input
multi-output channels is applied to the linear model of FMT.
Assuming a uniform non-zero a priori probability distribution for the fluorophore concentrations in the volume voxels,
we derive an expression for the information capacity of the FMT system matrix. This capacity essentially indicates an
upper limit on the amount of data that can be extracted from emission measurements. The capabilities of various detector
configurations in resolving fluorescent tubes inserted in a
gel-based tissue phantom are analyzed in a continuous-wave
FMT system using the proposed framework. It is observed that the information capacity of source-detector
configurations of different scales directly affects the performance in terms of resolution in the reconstructed fluorescent
images.
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