Multiscale label-free volumetric holographic histopathology of thick-tissue slides with subcellular resolution

Hugonnet, Hervé; Kim, Yeon Wook; Shin, Seungwoo; Hruban, Ralph H.; Hong, Seung‐Mo; Park, Yong Keun

doi:10.1101/2020.07.15.205633

Cited by 10 publications

(12 citation statements)

References 30 publications

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“…This tool provides novel insights based on the endogenous composition of tissues, while also providing the same critical information contained within today's gold standard (H&E) without the need for staining. The method is fast, low-cost, simple, and provides subcellular resolution, which overcomes critical limitations of other label-free optical methods applied to histopathology (15,(72)(73)(74)(75). Finally, this same quantitative approach can be applied broadly across histopathological analysis of many tissue types and diseases.…”

Section: Discussionmentioning

confidence: 95%

Prostate cancer histopathology with label-free multispectral deep UV microscopy quantifies phenotypes of tumor grade and aggressiveness

Soltani

Ojaghi

Qiao

et al. 2021

Preprint

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Identifying prostate cancer patients that are harboring aggressive forms of prostate cancer remains a significant clinical challenge. To help address this problem, we develop an approach based on multispectral deep-ultraviolet (UV) microscopy that provides novel quantitative insight into the aggressiveness and grade of this disease. First, we find that UV spectral signatures from endogenous molecules give rise to a phenotypical continuum that differentiates critical structures of thin tissue sections with subcellular spatial resolution, including nuclei, cytoplasm, stroma, basal cells, nerves, and inflammation. Further, we show that this phenotypical continuum can be applied as a surrogate biomarker of prostate cancer malignancy, where patients with the most aggressive tumors show a ubiquitous glandular phenotypical shift. Lastly, we adapt a two-part Cycle-consistent Generative Adversarial Network to translate the label-free deep-UV images into virtual hematoxylin and eosin (H&E) stained images. Agreement between the virtual H&E images and the gold standard H&E-stained tissue sections is evaluated by a panel of pathologists who find that the two modalities are in excellent agreement. This work has significant implications towards improving our ability to objectively quantify prostate cancer grade and aggressiveness, thus improving the management and clinical outcomes of prostate cancer patients. This same approach can also be applied broadly in other tumor types to achieve low-cost, stain-free, quantitative histopathological analysis.

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Section: Discussionmentioning

confidence: 95%

Prostate cancer histopathology with label-free multispectral deep UV microscopy quantifies phenotypes of tumor grade and aggressiveness

Soltani

Ojaghi

Qiao

et al. 2021

Preprint

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“…This allowed automated tomogram measurements in adjacent tiles for an extended lateral field of view. A detailed description of the algorithm utilized for stitching the tiles can be found elsewhere [48]. The transmitted laser light after scattering through the sample was collected by an objective lens (UPlanSAPO20X, numerical aperture (NA) = 0.75; Olympus Inc.), and interference patterns were created with the reference beam.…”

Section: Optical Diffraction Tomographymentioning

confidence: 99%

Label-free monitoring of 3D cortical neuronal growth in vitro using optical diffraction tomography

Lee¹,

Yoon

Han

et al. 2021

Preprint

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The highly complex central nervous systems of mammals are often studied using three-dimensional (3D) in vitro primary neuronal cultures. A coupled confocal microscopy and immunofluorescence labeling are widely utilized for visualizing the 3D structures of neurons. However, this requires fixation of the neurons and is not suitable for monitoring an identical sample at multiple time points. Thus, we propose a label-free monitoring method for 3D neuronal growth based on refractive index tomograms obtained by optical diffraction tomography. The 3D morphology of the neurons was clearly visualized, and the developmental processes of neurite outgrowth in 3D spaces were analyzed for individual neurons.

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“…To perform large FoV measurements, multiple 3D RI tomograms were measured at various lateral positions and stitched into one large FoV tomogram. To accomplish this, a motorized sample stage was synchronized with the image acquisition, and the stitching algorithm was used to seamlessly connect multiple 3D RI tomograms (23).…”

Section: Large Field-of-view (Fov) Imagingmentioning

confidence: 99%

Three-Dimensional Label-Free Imaging and Quantification of Migrating Cells during Wound Healing

Lee

Hugonnet

Park

et al. 2020

Preprint

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The wound healing assay provides essential information about collective cell migration and cell-to-cell interactions. It is a simple, effective, and widely used tool for observing the effect of numerous chemical treatments on wound healing speed. To perform and analyze a wound healing assay, various imaging techniques have been utilized. However, image acquisition and analysis are often limited in two-dimensional space or require the use of exogenous labeling agents. Here, we present a method for imaging large-scale wound healing assays in a label-free and volumetric manner using optical diffraction tomography (ODT). We performed quantitative high-resolution three-dimensional (3D) analysis of cell migration over a long period without difficulties such as photobleaching or phototoxicity. ODT enables the reconstruction of the refractive index (RI) tomogram of unlabeled cells, which provides both structural and biochemical information about the individual cell at subcellular resolution. Stitching multiple RI tomograms enables long-term (24 h) and large field-of-view imaging (> 800 × 400 μm2) with a lateral resolution of 110 nm. We demonstrated the thickness changes of leading cells and studied the effects of cytochalasin D. The 3D RI tomogram also revealed increased RI values in leading cells compared to lagging cells, suggesting the formation of a highly concentrated subcellular structure.STATEMENT OF SIGNIFICANCEThe wound healing assay is a simple but effective tool for studying collective cell migration (CCM) that is widely used in biophysical studies and high-throughput screening. However, conventional imaging and analysis methods only address two-dimensional properties in a wound healing assay, such as gap closure rate. This is unfortunate because biological cells are complex 3D structures, and their dynamics provide significant information about cell physiology. Here, we presented three-dimensional (3D) label-free imaging for wound healing assays and investigated the 3D dynamics of CCM. High-resolution subcellular structures as well as their collective dynamics were imaged and analyzed quantitatively. Our label-free quantitative 3D analysis method provides a unique opportunity to study the behavior of migrating cells during the wound healing process.

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Multiscale label-free volumetric holographic histopathology of thick-tissue slides with subcellular resolution

Cited by 10 publications

References 30 publications

Prostate cancer histopathology with label-free multispectral deep UV microscopy quantifies phenotypes of tumor grade and aggressiveness

Prostate cancer histopathology with label-free multispectral deep UV microscopy quantifies phenotypes of tumor grade and aggressiveness

Label-free monitoring of 3D cortical neuronal growth in vitro using optical diffraction tomography

Three-Dimensional Label-Free Imaging and Quantification of Migrating Cells during Wound Healing

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