Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM)

Majeed, Hassaan; Keikhosravi, Adib; Kandel, Mikhail E.; Nguyen, Tuan Hung; Liu, Yuming; Kajdacsy-Balla, André; Tangella, Krishnarao; Eliceiri, Kevin W.; Popescu, Gabriel

doi:10.1038/s41598-019-50143-x

Cited by 34 publications

(36 citation statements)

References 64 publications

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“…While a low-cost version of a SHG microscope has been created, it still ranges around USD 40,000 [12]. Alternatives exist, for instance, spatial light interference microscopy (SLIM) has demonstrated better TACS3 detection along with better discernment of the tumor border, due to SLIM ability to measure linear and also non-linear collagen [3,13]. The value of SHG may be in the binary confirmation of the presence/ absence of linear collagen, as seen in past research which visualized the TACS3 collagen pattern in intact, unfixed human mammary gland samples [10].…”

Section: Tacs Detectionmentioning

confidence: 99%

Tumor-associated collagen signatures: pushing tumor boundaries

et al. 2020

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In 2006, a new model of invasive breast tumor emerged and, since 2011, is gaining recognition and research momentum. "Tumor-associated collagen signatures" describe 3 distinct layers of collagen which radiate outward in shells from the main body of the tumor. The outermost layer (TACS3) features branches of collagen radiating away from the tumor, 90°perpendicular to the tumor surface. TACS3 increases tumor span and correlates directly with metastasis, though presently difficult to detect in breast tissue. TACS is an emerging model but has been validated by multiple labs in vitro and in vivo, specifically for breast cancer prognostics. Newly recognized and accepted tumor borders will impact both R0 resections and downstream surgical reconstruction. This review aims to comprehensively introduce and connect the ranging literature on linearized collagen of invasive tumor borders. Using PubMed keyword searches containing "aligned," "linear," "oriented," and "organized," we have gathered the studies on TACS, integrated the concept into the clinic, and projected future platforms.

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Section: Tacs Detectionmentioning

confidence: 99%

Tumor-associated collagen signatures: pushing tumor boundaries

et al. 2020

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“…Here, we use our recently devised color spatial light interference microscopy (cSLIM) 23 as a quantitative phase imaging (QPI) technique [24][25][26][27][28][29][30][31][32][33][34] to quantify myelin in brain tissue. QPI is a technique that can evaluate nanometer scale pathlength changes in biological specimens.…”

mentioning

confidence: 99%

Quantifying myelin content in brain tissue using color spatial light interference microscopy (cSLIM)

Popescu

Caputo

Lee

et al. 2020

Preprint

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Deficient myelination of the brain is associated with neurodevelopmental delays, particularly in high-risk infants, such as those born small in relation to their gestational age (SGA). New methods are needed to further study this condition. Here, we employ Color Spatial Light Interference Microscopy (cSLIM), which uses a brightfield objective and RGB camera to generate pathlength-maps with nanoscale sensitivity in conjunction with a regular brightfield image. Using tissue sections stained with Luxol Fast Blue, the myelin structures were segmented from a brightfield image. Using a binary mask, those portions were quantitatively analyzed in the corresponding phase maps. We first used the CLARITY method to remove tissue lipids and validate the sensitivity of cSLIM to lipid content. We then applied cSLIM to brain histology slices. These specimens are from a previous MRI study, which demonstrated that appropriate for gestational age (AGA) piglets have increased internal capsule myelination (ICM) compared to small for gestational age (SGA) piglets and that a hydrolyzed fat diet improved ICM in both. The identity of samples was blinded until after statistical analyses.

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“…The interference is created by waves propagating on a nearly identical path, which confers SLIM subangstrom path-length temporal sensitivity ( 37 ). Owing to these features and complete automation of data acquisition, SLIM can be used to study cell behavior of long periods of time and large fields of view across microscope slides and multiwell plates ( 18 , 34 ). To demonstrate the potential for SLIM to be used in a high-throughput setting, we imaged a whole microscope slide prepared according to Materials and Methods .…”

Section: Resultsmentioning

confidence: 99%

“…This way, the QPI and fluorescence (or staining) channels integrate seamlessly, providing both specific and quantitative information (for a recent implementation for pathology applications, see ref. 34). Of course, this solution does not avoid the fact that labels are needed to gain specificity, which brings in limitations due to fixation, photobleaching, and phototoxicity (35,36).…”

Section: Significancementioning

confidence: 99%

Reproductive outcomes predicted by phase imaging with computational specificity of spermatozoon ultrastructure

Kandel

Rubessa

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

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The ability to evaluate sperm at the microscopic level, at high-throughput, would be useful for assisted reproductive technologies (ARTs), as it can allow specific selection of sperm cells for in vitro fertilization (IVF). The tradeoff between intrinsic imaging and external contrast agents is particularly acute in reproductive medicine. The use of fluorescence labels has enabled new cell-sorting strategies and given new insights into developmental biology. Nevertheless, using extrinsic contrast agents is often too invasive for routine clinical operation. Raising questions about cell viability, especially for single-cell selection, clinicians prefer intrinsic contrast in the form of phase-contrast, differential-interference contrast, or Hoffman modulation contrast. While such instruments are nondestructive, the resulting image suffers from a lack of specificity. In this work, we provide a template to circumvent the tradeoff between cell viability and specificity by combining high-sensitivity phase imaging with deep learning. In order to introduce specificity to label-free images, we trained a deep-convolutional neural network to perform semantic segmentation on quantitative phase maps. This approach, a form of phase imaging with computational specificity (PICS), allowed us to efficiently analyze thousands of sperm cells and identify correlations between dry-mass content and artificial-reproduction outcomes. Specifically, we found that the dry-mass content ratios between the head, midpiece, and tail of the cells can predict the percentages of success for zygote cleavage and embryo blastocyst formation.

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Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM)

Cited by 34 publications

References 64 publications

Tumor-associated collagen signatures: pushing tumor boundaries

Tumor-associated collagen signatures: pushing tumor boundaries

Quantifying myelin content in brain tissue using color spatial light interference microscopy (cSLIM)

Reproductive outcomes predicted by phase imaging with computational specificity of spermatozoon ultrastructure

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