Preparation of a high-concentration Au nanoring (NR) water solution and its applications to the enhancement of image contrast in optical coherence tomography (OCT) and the generation of the photothermal effect in a bio-sample through localized surface plasmon (LSP) resonance are demonstrated. Au NRs are first fabricated on a sapphire substrate with colloidal lithography and secondary sputtering of Au, and then transferred into a water solution through a liftoff process. By controlling the NR geometry, the LSP dipole resonance wavelength in tissue can cover a spectral range of 1300 nm for OCT scanning of deep tissue penetration. The extinction cross sections of the fabricated Au NRs in water are estimated to give levels of 10(-10)-10(-9) cm(2) near their LSP resonance wavelengths. The fabricated Au NRs are then delivered into pig adipose samples for OCT scanning. It is observed that, when resonant Au NRs are delivered into such a sample, LSP resonance-induced Au NR absorption results in a photothermal effect, making the opaque pig adipose cells transparent. Also, the delivered Au NRs in the intercellular substance enhance the image contrast of OCT scanning through LSP resonance-enhanced scattering. By continuously OCT scanning a sample, both photothermal and image contrast enhancement effects are observed. However, by continually scanning a sample with a low scan frequency, only the image contrast enhancement effect is observed.
We have simulated photon migration with various sourcedetector separations based on a three-dimensional Monte Carlo code. Whole brain MRI structure images are introduced in the simulation, and the brain model is more accurate than in previous studies. The brain model consists of the scalp, skull, CSF layer, gray matter, and white matter. We demonstrate dynamic propagating movies under different source-detector separations. The multiple backscattered intensity from every layer of the brain model is obtained by marking the deepest layer that every photon can reach. Also, the influences of an absorption target on the brain cortex are revealed.
Brain age is an imaging-based biomarker with excellent feasibility for characterizing individual brain health and may serve as a single quantitative index for clinical and domain-specific usage. Brain age has been successfully estimated using extensive neuroimaging data from healthy participants with various feature extraction and conventional machine learning (ML) approaches. Recently, several end-to-end deep learning (DL) analytical frameworks have been proposed as alternative approaches to predict individual brain age with higher accuracy. However, the optimal approach to select and assemble appropriate input feature sets for DL analytical frameworks remains to be determined. In the Predictive Analytics Competition 2019, we proposed a hierarchical analytical framework which first used ML algorithms to investigate the potential contribution of different input features for predicting individual brain age. The obtained information then served as a priori knowledge for determining the input feature sets of the final ensemble DL prediction model. Systematic evaluation revealed that ML approaches with multiple concurrent input features, including tissue volume and density, achieved higher prediction accuracy when compared with approaches with a single input feature set [Ridge regression: mean absolute error (MAE) = 4.51 years, R2 = 0.88; support vector regression, MAE = 4.42 years, R2 = 0.88]. Based on this evaluation, a final ensemble DL brain age prediction model integrating multiple feature sets was constructed with reasonable computation capacity and achieved higher prediction accuracy when compared with ML approaches in the training dataset (MAE = 3.77 years; R2 = 0.90). Furthermore, the proposed ensemble DL brain age prediction model also demonstrated sufficient generalizability in the testing dataset (MAE = 3.33 years). In summary, this study provides initial evidence of how-to efficiency for integrating ML and advanced DL approaches into a unified analytical framework for predicting individual brain age with higher accuracy. With the increase in large open multiple-modality neuroimaging datasets, ensemble DL strategies with appropriate input feature sets serve as a candidate approach for predicting individual brain age in the future.
This study demonstrates a new approach for evaluating the properties of indium tin oxide (ITO) conducting glass and identifying defects using optical coherence tomography (OCT). A swept-source OCT system was implemented to scan the ITO conducting glass to enable two-dimensional or three-dimensional imaging. With OCT scanning, the defects can be clearly identified at various depths. Several parameters in addition to morphological information can be estimated simultaneously, including the thickness of the glass substrate, the refractive index, reflection coefficient, and transmission coefficient, all of which can be used to evaluate the quality of ITO conducting glass. This study developed a modified method for evaluating the refractive index of glass substrates without having to perform multiple scans as well as a segmentation algorithm to separate the interfaces. The results show the potential of OCT as an imaging tool for the inspection of defects in ITO conducting glass.
Blood coagulation is the clotting and subsequent dissolution of the clot following repair to the damaged tissue. However, inducing blood coagulation is difficult for some patients with homeostasis dysfunction or during surgery. In this study, we proposed a method to develop an integrated system that combines optical coherence tomography (OCT) and laser microsurgery for blood coagulation. Also, an algorithm for positioning of the treatment location from OCT images was developed. With OCT scanning, 2D/3D OCT images and angiography of tissue can be obtained simultaneously, enabling to noninvasively reconstruct the morphological and microvascular structures for real-time monitoring of changes in biological tissues during laser microsurgery. Instead of high-cost pulsed lasers, continuous-wave laser diodes (CW-LDs) with the central wavelengths of 450 nm and 532 nm are used for blood coagulation, corresponding to higher absorption coefficients of oxyhemoglobin and deoxyhemoglobin. Experimental results showed that the location of laser exposure can be accurately controlled with the proposed approach of imaging-based feedback positioning. Moreover, blood coagulation can be efficiently induced by CW-LDs and the coagulation process can be monitored in real-time with OCT. This technology enables to potentially provide accurate positioning for laser microsurgery and control the laser exposure to avoid extra damage by real-time OCT imaging.
We demonstrate a swept-source optical coherence tomography system, including a broadband frequency sweeping light source with the central wavelength around 1250 nm, to achieve an axial resolution of 2.4 microns in tissue. IntroductionThe spectral-domain optical coherence tomography (SDOCT) scheme using a fast frequency-sweeping light source (called a swept source) has the advantage of simple signal detection. However, the available swept source still sets constraint in SDOCT operation. So far, only the swept-source SDOCT operations of -1300 nm in central wavelength were reported. Although the fabrication of swept sources with the central wavelength shorter than one micron was reported, its further development for SDOCT operation is still unclear. Regarding the SDOCT operation in the 1300 nm wavelength range, so far the spectral full-widths at half-maximum (FWHMs) of the available swept (laser) sources are smaller than 120 nm, leading to the axial resolution limit of 6.2 microns in free space. Although the increase of the spectral width can be implemented, it may face certain technical difficulties, such as the slow-down of the frequency sweeping speed and the reduction of laser output power in increasing the laser tunable spectral width. Therefore, increasing the spectral width of a swept source for higher axial resolution in the 1300-nm spectral range without relying on the development of frequency-sweeping cw laser is important for SDOCT development. In this paper, we report the implementation of a swept-source SDOCT system based on a sweeping-frequency scheme of a spectrumexpanded Cr:forsterite laser. The output spectrum of a mode-locked Cr:forsterite laser is expanded from 35 nm to a FWHM of 150-220 nm through a high numerical-aperture (NA) fiber. The laser beam of expanded spectrum was swung through a setup of a resonance-scanning mirror. Then, the small aperture of a fiber collimator, connected to a fiber for delivering light to a free-space interferometer, receives the frequency-sweeping light for SDOCT operation. In the built SDOCT system, the largest sweeping spectral FWHM of 220 nm leads to the axial resolution of 3.3 microns in free space and hence 2.4 microns in tissue.
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