Wavefront image sensor chip

We report the implementation of an image sensor chip, termed wavefront image sensor chip (WIS), that can measure both intensity/amplitude and phase front variations of a light wave separately and quantitatively. By monitoring the tightly confined transmitted light spots through a circular aperture grid in a high Fresnel number regime, we can measure both intensity and phase front variations with a high sampling density (11 µm) and high sensitivity (the sensitivity of normalized phase gradient measurement is 0.1 mrad under the typical working condition). By using WIS in a standard microscope, we can collect both bright-field (transmitted light intensity) and normalized phase gradient images. Our experiments further demonstrate that the normalized phase gradient images of polystyrene microspheres, unstained and stained starfish embryos, and strongly birefringent potato starch granules are improved versions of their corresponding differential interference contrast (DIC) microscope images in that they are artifact-free and quantitative. Besides phase microscopy, WIS can benefit machine recognition, object ranging, and texture assessment for a variety of applications

Advances in Optics for Biotechnology, Medicine and Surgery

The guest editors introduce a Biomedical Optics Express feature issue that includes contributions from participants at the 2013 conference on Advances in Optics for Biotechnology, Medicine and Surgery XIII

Depth resolved detection of lipid using spectroscopic optical coherence tomography

Optical frequency domain imaging (OFDI) can identify key components related to plaque vulnerability but can suffer from artifacts that could prevent accurate identification of lipid rich regions. In this paper, we present a model of depth resolved spectral analysis of OFDI data for improved detection of lipid. A quadratic Discriminant analysis model was developed based on phantom compositions known chemical mixtures and applied to a tissue phantom of a lipid-rich plaque. We demonstrate that a combined spectral and attenuation model can be used to predict the presence of lipid in OFDI images

Feasibility of the Assessment of Cholesterol Crystals in Human Macrophages Using Micro Optical Coherence Tomography

The presence of cholesterol crystals is a hallmark of atherosclerosis, but until recently, such crystals have been considered to be passive components of necrotic plaque cores. Recent studies have demonstrated that phagocytosis of cholesterol crystals by macrophages may actively precipitate plaque progression via an inflammatory pathway, emphasizing the need for methods to study the interaction between macrophages and crystalline cholesterol. In this study, we demonstrate the feasibility of detecting cholesterol in macrophages in situ using Micro-Optical Coherence Tomography (µOCT), an imaging modality we have recently developed with 1-µm resolution. Macrophages containing cholesterol crystals frequently demonstrated highly scattering constituents in their cytoplasm on µOCT imaging, and µOCT was able to evaluate cholesterol crystals in cultured macrophage cells. Our results suggest that µOCT may be useful for the detection and characterization of inflammatory activity associated with cholesterol crystals in the coronary artery

Dual modality intravascular optical coherence tomography (OCT) and near-infrared fluorescence (NIRF) imaging: a fully automated algorithm for the distance-calibration of NIRF signal intensity for quantitative molecular imaging

Intravascular optical coherence tomography (IVOCT) is a well-established method for the high-resolution investigation of atherosclerosis in vivo. Intravascular near-infrared fluorescence (NIRF) imaging is a novel technique for the assessment of molecular processes associated with coronary artery disease. Integration of NIRF and IVOCT technology in a single catheter provides the capability to simultaneously obtain co-localized anatomical and molecular information from the artery wall. Since NIRF signal intensity attenuates as a function of imaging catheter distance to the vessel wall, the generation of quantitative NIRF data requires an accurate measurement of the vessel wall in IVOCT images. Given that dual modality, intravascular OCT–NIRF systems acquire data at a very high frame-rate (>100 frames/s), a high number of images per pullback need to be analyzed, making manual processing of OCT–NIRF data extremely time consuming. To overcome this limitation, we developed an algorithm for the automatic distance-correction of dual-modality OCT–NIRF images. We validated this method by comparing automatic to manual segmentation results in 180 in vivo images from six New Zealand White rabbit atherosclerotic after indocyanine-green injection. A high Dice similarity coefficient was found (0.97 ± 0.03) together with an average individual A-line error of 22 µm (i.e., approximately twice the axial resolution of IVOCT) and a processing time of 44 ms per image. In a similar manner, the algorithm was validated using 120 IVOCT clinical images from eight different in vivo pullbacks in human coronary arteries. The results suggest that the proposed algorithm enables fully automatic visualization of dual modality OCT–NIRF pullbacks, and provides an accurate and efficient calibration of NIRF data for quantification of the molecular agent in the atherosclerotic vessel wall.National Institutes of Health (U.S.) (NIH R01HL093717)Merck & Co., Inc