Intranuclear birefringent inclusions in paraffin sections by polychromatic polarization microscopy

Vitkunaite, Aiste; Laurinavičienė, Aida; Plancoulaine, Benoît; Rasmusson, Allan G.; Levenson, Richard M.; Shribak, Michael; Laurinavičius, Arvydas

doi:10.1038/s41598-021-85667-8

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…Apart from the structural changes we observe several spots with relatively high linear retardance, dichroism and circular depolarization values that are not visible in the intensity images. This phenomenon most likely is related to the presence of intra-nuclear birefringent inclusions (IBI) due to the insufficient dewaxing [8]. Since these spots are located along the gastric gland walls, we expected them to represent the inflammatory cells [9].…”

Section: Resultsmentioning

confidence: 99%

Digital histology of gastric tissue biopsies with liquid crystal-based Mueller microscope and machine learning approach

Kim,

Lee,

Ossikovski

et al. 2024

Liquid Crystals Optics and Photonic Devices

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We investigated gastric tissue biopsies using a liquid crystal-based Mueller microscope and a machine-learning approach to examine the degree of inflammation. Machine learning and statistical analysis were performed with the multidimensional dataset including the polarimetric properties (linear retardance and dichroism, and circular depolarization) and total transmitted intensity images of the unstained thin sections of gastric tissue to identify and quantify the microstructural differences between healthy control, chronic gastritis, and gastric cancer.

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Section: Resultsmentioning

confidence: 99%

Digital histology of gastric tissue biopsies with liquid crystal-based Mueller microscope and machine learning approach

Kim,

Lee,

Ossikovski

et al. 2024

Liquid Crystals Optics and Photonic Devices

View full text Add to dashboard Cite

show abstract

“…This artifact 10 is related to the presence of residual paraffin left in some cell nuclei because of insufficient deparaffinization and clearing during tissue processing. Based on the results of [42], we attribute the presence of the pixels which demonstrate high polarimetric values to a paraffin intake by the nuclei of the specific cells. Furthermore, we expect these cells to be the inflammatory ones as they are aligned along the walls of gastric glands [43].…”

Section: Resultsmentioning

confidence: 99%

Optical diagnosis of gastric tissue biopsies with Mueller microscopy and statistical analysis

Novikova¹,

Kim²,

Lee³

et al. 2022

J. Eur. Opt. Society-Rapid Publ.

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We investigate a possibility of producing the quantitative optical metrics to characterize the evolution of gastric tissue from healthy conditions via inflammation to cancer by using Mueller microscopy of gastric biopsies, regression model and statistical analysis of the predicted images. For this purpose the unstained sections of human gastric tissue biopsies at different pathological conditions were measured with the custom-built Mueller microscope. Polynomial regression model was built using the maps of transmitted intensity, retardance, dichroism and depolarization to generate the predicted images. The statistical analysis of predicted images of gastric tissue sections with multi-curve fit suggests that Mueller microscopy combined with data regression and statistical analysis is an effective approach for quantitative assessment of the degree of inflammation in gastric tissue biopsies with a high potential in clinical applications.

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High-fidelity and rapid cellular-level Mueller matrix imaging for tissue identification with unstained sections

Wang

Cao

et al. 2021

Biomed. Opt. Express

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Mueller matrix polarimetry is regarded as a promising technique in the field of biomedicine, especially for pathological diagnosis. However, the current studies on Mueller imaging of pathological sections are all at the tissue-level, and the cellular-level polarization information is difficult to obtain. To overcome this challenge, we first propose a cellular-level Mueller matrix imaging method for accurate quantitative identification of tissues in this study. Benefiting from the significant birefringent behavior of paraffin in unstained sections, the proposed method can locate the paraffin distribution areas of retardance images by involving Otsu’s algorithm. Then, the real cellular-level polarization information (e.g., depolarization) is acquired. The efficiency of the proposed method was demonstrated on unstained rat tissue samples. The results showed that the obtained depolarization images are highly consistent with the stained microscopic images in terms of the morphology and arrangement of the tissues at cellular level. Finally, this method was preliminarily applied to the detection of human lung cancer tissue section, effectively realizing the quantitative differentiation of normal, inflamed, and malignant areas in unstained section. This study provides a possible approach for the rapid and accurate diagnosis of cancer.

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Intranuclear birefringent inclusions in paraffin sections by polychromatic polarization microscopy

Cited by 4 publications

References 13 publications

Digital histology of gastric tissue biopsies with liquid crystal-based Mueller microscope and machine learning approach

Digital histology of gastric tissue biopsies with liquid crystal-based Mueller microscope and machine learning approach

Optical diagnosis of gastric tissue biopsies with Mueller microscopy and statistical analysis

High-fidelity and rapid cellular-level Mueller matrix imaging for tissue identification with unstained sections

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