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Compressive hyperspectral microscopy for cancer detection
SIGNIFICANCE: Hyperspectral microscopy grants the ability to characterize unique properties of tissues based on their spectral fingerprint. The ability to label and measure multiple molecular probes simultaneously provides pathologists and oncologists with a powerful tool to enhance accurate diagnos...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society of Photo-Optical Instrumentation Engineers
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10491981/ https://www.ncbi.nlm.nih.gov/pubmed/37692564 http://dx.doi.org/10.1117/1.JBO.28.9.096502 |
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author | Oiknine, Yaniv Abuleil, Marwan Brozgol, Eugene August, Isaac Y. Barshack, Iris Abdulhalim, Ibrahim Garini, Yuval Stern, Adrian |
author_facet | Oiknine, Yaniv Abuleil, Marwan Brozgol, Eugene August, Isaac Y. Barshack, Iris Abdulhalim, Ibrahim Garini, Yuval Stern, Adrian |
author_sort | Oiknine, Yaniv |
collection | PubMed |
description | SIGNIFICANCE: Hyperspectral microscopy grants the ability to characterize unique properties of tissues based on their spectral fingerprint. The ability to label and measure multiple molecular probes simultaneously provides pathologists and oncologists with a powerful tool to enhance accurate diagnostic and prognostic decisions. As the pathological workload grows, having an objective tool that provides companion diagnostics is of immense importance. Therefore, fast whole-slide spectral imaging systems are of immense importance for automated cancer prognostics that meet current and future needs. AIM: We aim to develop a fast and accurate hyperspectral microscopy system that can be easily integrated with existing microscopes and provide flexibility for optimizing measurement time versus spectral resolution. APPROACH: The method employs compressive sensing (CS) and a spectrally encoded illumination device integrated into the illumination path of a standard microscope. The spectral encoding is obtained using a compact liquid crystal cell that is operated in a fast mode. It provides time-efficient measurements of the spectral information, is modular and versatile, and can also be used for other applications that require rapid acquisition of hyperspectral images. RESULTS: We demonstrated the acquisition of breast cancer biopsies hyperspectral data of the whole camera area within [Formula: see text]. This means that a typical [Formula: see text] biopsy can be measured in [Formula: see text]. The hyperspectral images with 250 spectral bands are reconstructed from 47 spectrally encoded images in the spectral range of 450 to 700 nm. CONCLUSIONS: CS hyperspectral microscopy was successfully demonstrated on a common lab microscope for measuring biopsies stained with the most common stains, such as hematoxylin and eosin. The high spectral resolution demonstrated here in a rather short time indicates the ability to use it further for coping with the highly demanding needs of pathological diagnostics, both for cancer diagnostics and prognostics. |
format | Online Article Text |
id | pubmed-10491981 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Society of Photo-Optical Instrumentation Engineers |
record_format | MEDLINE/PubMed |
spelling | pubmed-104919812023-09-10 Compressive hyperspectral microscopy for cancer detection Oiknine, Yaniv Abuleil, Marwan Brozgol, Eugene August, Isaac Y. Barshack, Iris Abdulhalim, Ibrahim Garini, Yuval Stern, Adrian J Biomed Opt Microscopy SIGNIFICANCE: Hyperspectral microscopy grants the ability to characterize unique properties of tissues based on their spectral fingerprint. The ability to label and measure multiple molecular probes simultaneously provides pathologists and oncologists with a powerful tool to enhance accurate diagnostic and prognostic decisions. As the pathological workload grows, having an objective tool that provides companion diagnostics is of immense importance. Therefore, fast whole-slide spectral imaging systems are of immense importance for automated cancer prognostics that meet current and future needs. AIM: We aim to develop a fast and accurate hyperspectral microscopy system that can be easily integrated with existing microscopes and provide flexibility for optimizing measurement time versus spectral resolution. APPROACH: The method employs compressive sensing (CS) and a spectrally encoded illumination device integrated into the illumination path of a standard microscope. The spectral encoding is obtained using a compact liquid crystal cell that is operated in a fast mode. It provides time-efficient measurements of the spectral information, is modular and versatile, and can also be used for other applications that require rapid acquisition of hyperspectral images. RESULTS: We demonstrated the acquisition of breast cancer biopsies hyperspectral data of the whole camera area within [Formula: see text]. This means that a typical [Formula: see text] biopsy can be measured in [Formula: see text]. The hyperspectral images with 250 spectral bands are reconstructed from 47 spectrally encoded images in the spectral range of 450 to 700 nm. CONCLUSIONS: CS hyperspectral microscopy was successfully demonstrated on a common lab microscope for measuring biopsies stained with the most common stains, such as hematoxylin and eosin. The high spectral resolution demonstrated here in a rather short time indicates the ability to use it further for coping with the highly demanding needs of pathological diagnostics, both for cancer diagnostics and prognostics. Society of Photo-Optical Instrumentation Engineers 2023-09-09 2023-09 /pmc/articles/PMC10491981/ /pubmed/37692564 http://dx.doi.org/10.1117/1.JBO.28.9.096502 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. |
spellingShingle | Microscopy Oiknine, Yaniv Abuleil, Marwan Brozgol, Eugene August, Isaac Y. Barshack, Iris Abdulhalim, Ibrahim Garini, Yuval Stern, Adrian Compressive hyperspectral microscopy for cancer detection |
title | Compressive hyperspectral microscopy for cancer detection |
title_full | Compressive hyperspectral microscopy for cancer detection |
title_fullStr | Compressive hyperspectral microscopy for cancer detection |
title_full_unstemmed | Compressive hyperspectral microscopy for cancer detection |
title_short | Compressive hyperspectral microscopy for cancer detection |
title_sort | compressive hyperspectral microscopy for cancer detection |
topic | Microscopy |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10491981/ https://www.ncbi.nlm.nih.gov/pubmed/37692564 http://dx.doi.org/10.1117/1.JBO.28.9.096502 |
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