Low-cost, chromatic confocal endomicroscope for cellular imaging in vivo

Kulkarni, Nachiket; Masciola, Andrew; Nishant, Abhinav; Kim, Kyung‐Jo; Choi, Heejoo; Gmitro, Arthur F.; Freeman, Esther E.; Semeere, Aggrey; Nakalembe, Miriam; Kang, Dongkyun

doi:10.1364/boe.434892

Cited by 14 publications

(4 citation statements)

References 38 publications

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“…As a result, this study utilized pCLE to visually display the microstructure of the liver in vivo . The conventional method of morphological examination typically entails taking samples and creating sections for observation ( 29 ). pCLE is a blend of confocal laser microscopy and traditional electronic endoscopy.…”

Section: Discussionmentioning

confidence: 99%

In vivo evaluation of liver function by multimodal imaging in an alcohol-induced liver injury model

Song,

Wang,

Jia

et al. 2023

Quant Imaging Med Surg

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Background Visually evaluating liver function is a hot topic in hepatology research. There are few reliable and practical visualization methods for evaluating the liver function in vivo in experimental studies. In this study, we established a multimodal imaging approach for in vivo liver function evaluation and compared healthy mice with chronic alcoholic liver injury (cALI) model mice to explore its potential applicability in experimental research. Methods In vivo fluorescence imaging (IVFI) technology was utilized to visually represent the clearance of indocyanine green from the liver of both healthy mice and mice with cALI. The reserve liver function was evaluated via IVFI using the Cy5.5-galactosylated polylysine probe, which targets the asialoglycoprotein receptor of hepatocytes. Hepatic microcirculation was assessed through laser speckle perfusion imaging of hepatic blood perfusion. The liver microstructure was then investigated by in vivo confocal laser endomicroscopy imaging. Finally, hepatic asialoglycoprotein receptor expression, histology, and the levels of serum alanine aminotransferase and aspartate aminotransferase were measured. Results In vivo multimodal imaging results intuitively and dynamically showed that indocyanine green clearance [mean ± standard deviation (SD): 30.83±14.71, 95% confidence interval (CI): 20.3 to 41.35], the fluorescence signal intensity (mean ± SD: 1,217.92±117.63; 95% CI: 1,148.38 to 1,290.84) and fluorescence aggregation area (mean ± SD: 5,855.80±1,271.81; 95% CI: 5,051.57 to 6,653.88) of Cy5.5-galactosylated polylysine targeting the asialoglycoprotein receptor, and hepatic blood perfusion (mean ± SD: 1,494.86±299.33; 95% CI: 1,316.98 to 1,690.16) in model mice were significantly lower than those in healthy mice (all P<0.001). Compared to healthy mice, the model mice exhibited a significant decline in liver asialoglycoprotein receptor expression (mean ± SD: 219.03±16.34; 95% CI: 208.97 to 230.69; P<0.001), increased serum alanine aminotransferase (mean ± SD: 149.70±47.89 U/L; 95% CI: 81.75 to 128.89; P=0.01) and aspartate aminotransferase levels (mean ± SD: 106.30±36.13 U/L; 95% CI: 122.01 to 180.17; P=0.021), hepatocyte swelling and deformation, disappearance of the hepatic cord structure, partial necrosis, and disintegration of hepatocytes. The imaging features of fluorescence signals in liver regions, hepatic blood perfusion and microstructure were biologically related to hepatic asialoglycoprotein receptor expression, serum indices of liver function, and histopathology in model mice. Conclusions Utilizing in vivo multimodal imaging technology to assess liver function is a viable approach for experimental research, providing dynamic and intuitive visual evaluations in a rapid manner.

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Section: Discussionmentioning

confidence: 99%

In vivo evaluation of liver function by multimodal imaging in an alcohol-induced liver injury model

Song,

Wang,

Jia

et al. 2023

Quant Imaging Med Surg

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“…From this comparison, commercial traditional reflectance confocal microscopy has high resolution, allowing clear visualization of cells and gastric gland ducts. TSCCM's resolution is not [12] 2 μm 4 μm 125 μm 4 volumes/s Sharma et al 2022 [13] 0.87 μm 8 . 6 μm 1550 μm 0.2 volumes/s as high as commercial reflectance confocal microscopy, but it can also resolve cells.…”

Section: Biomedical Tissue Imagingmentioning

confidence: 99%

Time‐stretch Chromatic Confocal Microscopy for Multi‐Depth Imaging

Yang,

Zhang,

Liu

et al. 2023

Laser & Photonics Reviews

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Chromatic confocal technology has enabled multispectral information detection without any axial mechanical scanning. Especially, the chromatic confocal sensor is well applied in industry, such as device defect detection and ranging. However, for 3D imaging, chromatic confocal microscopy (CCM) still suffers from insufficient speed due to the slow refresh rate of a traditional spectrometer. To address this problem, a time‐stretch chromatic confocal microscopy (TSCCM) is presented for multi‐depth imaging. A supercontinuum laser is stretched and then focused on the sample using a home‐built chromatic lens, which disperses the laser to a different depth. The time‐of‐flight signal is collected by a high‐speed photodiode and is recorded and analyzed by a 3 GHz digitizer. A novel approach is achieved to significantly improve the speed of multi‐depth imaging with an up to 1 MHz A‐scan rate and 5 Hz volumetric imaging speed, which is an order faster compared with previous work of spectrometer‐based chromatic confocal microscopy. Multi‐depth volumetric imaging of nude‐mouse skin is performed to show the potential for biomedical applications. In this method, with its high A‐scan rate and multi‐depth imaging capability, a virtual tissue “light detection and ranging (LIDAR)” may be achieved.

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“…Most IVM devices generate images in the en face orientation, or parallel to the surface of the tissue. While these en face images are orthogonal to standard histology sections (typically vertical cross sections), the use of axial scanning, 42 – 45 oblique orientation of the imaging plane, 46 spectral encoding of depth, 47 multiplane scanning, 48 or other methods to adjust imaging depth can enable effective evaluation of cytomorphology and cellular arrangement through the desired layers and volume of tissue. A number of examples are shown in Fig.…”

Section: Translational Challengesmentioning

confidence: 99%