Volumetric Refractive Index Measurement and Quantitative Density Analysis of Mouse Brain Tissue with Sub‐Micrometer Spatial Resolution

Lee, Ariel J.; Hugonnet, Hervé; Kim, Young Seo; Kim, Joon-Goon; Ku, Taeyun; Park, Yong Keun

doi:10.1002/adpr.202300112

Cited by 4 publications

(3 citation statements)

References 58 publications

(33 reference statements)

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“…QPI has been applied across a wide range of fields, including cell biology 13-15 , microbiology 16-18 , immunology 19-21 , and biophysics 22,23 . Among these, holotomography (HT), a 3D QPI technique, has proven effective for analyzing thick samples, such as 3D cell-culture models 24-26 , thick tissues 27-29 , and embryos 30-34 from various species including C . elegans 33 , Bovine 31 , pig 32,35 , and mouse embryos 34,36 .…”

Section: Introductionmentioning

confidence: 99%

“…QPI has been applied across a wide range of fields, including cell biology [13][14][15] , microbiology [16][17][18] , immunology [19][20][21] , and biophysics 22,23 . Among these, holotomography (HT), a 3D QPI technique, has proven effective for analyzing thick samples, such as 3D cell-culture models [24][25][26] , thick tissues [27][28][29] , and embryos [30][31][32][33][34] from various species including C.elegans 33 , Bovine 31 , pig 32,35 , and mouse embryos 34,36 . Despite HT's evident potential in developmental biology, previous studies have yet to delve into the 3D subcellular intricacies of early embryo development.…”

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confidence: 99%

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Noninvasive time-lapse 3D subcellular analysis of embryo development for machine learning-enabled prediction of blastocyst formation

Lee,

Kim,

Shin

et al. 2024

Preprint

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In developmental biology and in vitro fertilization (IVF), image-based assessment of embryos is pivotal. Traditional methods in clinical IVF have been constrained to 2D morphokinetic profiling and manual selection, hindered by the absence of noninvasive techniques for quantitative 3D imaging over extended durations. Here, we overcome these limitations by employing low-coherence holotomography to monitor mouse preimplantation embryo development from the 2-cell stage to the expanded blastocyst. This approach enables the generation of 3D refractive index tomograms of unlabeled embryos, facilitating the observation of subcellular developmental dynamics. We investigated the 3D spatiotemporal profiles of embryo development, identifying key morphokinetic parameters that distinguish between embryos with differing developmental outcomes specifically, Grade A embryos that successfully progressed to expanded blastocysts within 72 hours, and Grade C embryos that did not. Using machine learning, we demonstrate the 3D morphokinetic parameters can offer a noninvasive, quantitative framework for predicting embryos with high developmental potential.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

Noninvasive time-lapse 3D subcellular analysis of embryo development for machine learning-enabled prediction of blastocyst formation

Lee,

Kim,

Shin

et al. 2024

Preprint

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“…With the advantages of label-free imaging capabilities and quantitative measurements, QPI has become an invaluable tool for investigating histopathological specimens, including structures of diverse cancers 7-16 , Alzheimer's disease 17 , and Crohn's disease 18 . While the studies predominantly focused on 2D specimens, recent advancements in 3D QPI techniques are now being applied to various histopathological specimens [19][20][21][22] . While using label-free imaging techniques, QPI images may lack subcellular specificity.…”

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confidence: 99%

Revealing 3D cancer tissue structures using holotomography and virtual hematoxylin and eosin staining via deep learning

park,

Shin,

Kim

et al. 2023

Preprint

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In standard histopathology, hematoxylin and eosin (H&E) staining stands as a pivotal tool for cancer tissue analysis. However, this method is limited to two-dimensional (2D) analysis or requires labor-intensive preparation for three-dimensional (3D) inspection of cancer tissues. In this study, we present a method for 3D virtual H&E staining of label-free colon cancer tissues, employing holotomography and deep learning. Holotomography is used to measure the 3D refractive index (RI) distribution of the label-free colon cancer slides. A deep learning-based image-to-image translation framework is integrated into the resulting 3D RI distribution, enabling virtual H&E staining in 3D. Our method has been applied to colon cancer tissue slides with thicknesses up to 20 µm, with conventional chemical H&E staining providing a direct validation for the method. This framework not only bypasses the conventional staining process but also provides 3D structures of glands, lumens, and individual nuclei. The results demonstrate enhancement in histopathological efficiency and the extension of the standard histopathology into the 3D realm.

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Label‐free three‐dimensional imaging and quantitative analysis of living fibroblasts and myofibroblasts by holotomographic microscopy

Sbrana,

Chellini,

Tani

et al. 2024

Microscopy Res & Technique

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Holotomography (HT) is a cutting‐edge fast live‐cell quantitative label‐free imaging technique. Based on the principle of quantitative phase imaging, it combines holography and tomography to record a three‐dimensional map of the refractive index, used as intrinsic optical and quantitative imaging contrast parameter of biological samples, at a sub‐micrometer spatial resolution. In this study HT has been employed for the first time to analyze the changes of fibroblasts differentiating towards myofibroblasts – recognized as the main cell player of fibrosis – when cultured in vitro with the pro‐fibrotic factor, namely transforming growth factor‐β1. In parallel, F‐actin, vinculin, α‐smooth muscle actin, phospho‐myosin light chain 2, type‐1 collagen, peroxisome proliferator‐activated receptor‐gamma coactivator‐1α expression and mitochondria were evaluated by confocal laser scanning microscopy. Plasmamembrane passive properties and transient receptor potential canonical channels' currents were also recorded by whole‐cell patch‐clamp. The fluorescence images and electrophysiological results have been compared to the data obtained by HT and their congruence has been discussed. HT turned out to be a valid approach to morphologically distinguish fibroblasts from well differentiated myofibroblasts while obtaining objective measures concerning volume, surface area, projection area, surface index and dry mass (i.e., the mass of the non‐aqueous content inside the cell including proteins and subcellular organelles) of the entire cell, nuclei and nucleoli with the major advantage to monitor outer and inner features in living cells in a non‐invasive, rapid and label‐free approach. HT might open up new research opportunities in the field of fibrotic diseases.Research Highlights Holotomography (HT) is a label‐free laser interferometric imaging technology exploiting the intrinsic optical property of cells namely refractive index (RI) to enable a direct imaging and analysis of whole cells or intracellular organelles. HT turned out a valid approach to distinguish morphological features of living unlabeled fibroblasts from differentiated myofibroblasts. HT provided quantitative information concerning volume, surface area, projection area, surface index and dry mass of the entire fibroblasts/myofibroblasts, nuclei and nucleoli.

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Volumetric Refractive Index Measurement and Quantitative Density Analysis of Mouse Brain Tissue with Sub‐Micrometer Spatial Resolution

Cited by 4 publications

References 58 publications

Noninvasive time-lapse 3D subcellular analysis of embryo development for machine learning-enabled prediction of blastocyst formation

Noninvasive time-lapse 3D subcellular analysis of embryo development for machine learning-enabled prediction of blastocyst formation

Revealing 3D cancer tissue structures using holotomography and virtual hematoxylin and eosin staining via deep learning

Label‐free three‐dimensional imaging and quantitative analysis of living fibroblasts and myofibroblasts by holotomographic microscopy

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