KEYWORDS: Near infrared spectroscopy, Optical coherence tomography, Light sources, Arteries, 3D image processing, In vivo imaging, Imaging technologies, Reliability, Data acquisition, Spectral calibration
Intravascular optical coherence tomography (OCT) is a high-resolution catheter-based imaging method that provides three-dimensional microscopic images of coronary artery in vivo, facilitating coronary artery disease treatment decisions based on detailed morphology. Near-infrared spectroscopy (NIRS) has proven to be a powerful tool for identification of lipid-rich plaques inside the coronary walls. We have recently demonstrated a dual-modality intravascular imaging technology that integrates OCT and NIRS into one imaging catheter using a two-fiber arrangement and a custom-made dual-channel fiber rotary junction. It therefore enables simultaneous acquisition of microstructural and composition information at 100 frames/second for improved diagnosis of coronary lesions.
The dual-modality OCT-NIRS system employs a single wavelength-swept light source for both OCT and NIRS modalities. It subsequently uses a high-speed photoreceiver to detect the NIRS spectrum in the time domain. Although use of one light source greatly simplifies the system configuration, such light source exhibits pulse-to-pulse wavelength and intensity variation due to mechanical scanning of the wavelength. This can be in particular problematic for NIRS modality and sacrifices the reliability of the acquired spectra. In order to address this challenge, here we developed a robust data acquisition and processing method that compensates for the spectral variations of the wavelength-swept light source. The proposed method extracts the properties of the light source, i.e., variation period and amplitude from a reference spectrum and subsequently calibrates the NIRS datasets. We have applied this method on datasets obtained from cadaver human coronary arteries using a polygon-scanning (1230-1350nm) OCT system, operating at 100,000 sweeps per second. The results suggest that our algorithm accurately and robustly compensates the spectral variations and visualizes the dual-modality OCT-NIRS images. These findings are therefore crucial for the practical application and clinical translation of dual-modality intravascular OCT-NIRS imaging when the same swept sources are used for both OCT and spectroscopy.
Laser scanners are essential for scientific research, manufacturing, defense, and medical practice. Unfortunately, often times the speed of conventional laser scanners (e.g., galvanometric mirrors and acousto-optic deflectors) falls short for many applications, resulting in motion blur and failure to capture fast transient information. Here, we present a novel type of laser scanner that offers roughly three orders of magnitude higher scan rates than conventional methods. Our laser scanner, which we refer to as the hybrid dispersion laser scanner, performs inertia-free laser scanning by dispersing a train of broadband pulses both temporally and spatially. More specifically, each broadband pulse is temporally processed by time stretch dispersive Fourier transform and further dispersed into space by one or more diffractive elements such as prisms and gratings. As a proof-of-principle demonstration, we perform 1D line scans at a record high scan rate of 91 MHz and 2D raster scans and 3D volumetric scans at an unprecedented scan rate of 105 kHz. The method holds promise for a broad range of scientific, industrial, and biomedical applications. To show the utility of our method, we demonstrate imaging, nanometer-resolved surface vibrometry, and high-precision flow cytometry with real-time throughput that conventional laser scanners cannot offer due to their low scan rates.
We describe a real-time image processor that has enabled a new automated flow through microscope to screen cells in
flow at 100,000 cells/s and a record false positive rate of one in a million. This unit is integrated with an ultrafast optical
imaging modality known as serial time-encoded amplified microscopy (STEAM) for blur-free imaging of particles in
high-speed flow. We show real-time image-based identification and screening of budding yeast cells and rare breast
cancer cells in blood. The system generates E-slides (an electronic version of glass slides) on which particles of interest
are digitally analyzed.
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