Literature DB >> 30447049

Development and evaluation of realistic optical cell models for rapid and label-free cell assay by diffraction imaging.

Shuting Wang1,2, Jing Liu1,2, Jun Q Lu1,3, Wenjin Wang1,4, Safaa A Al-Qaysi3,5, Yaohui Xu1,2, Wenhuan Jiang3, Xin-Hua Hu1,3.   

Abstract

Methods for rapid and label-free cell assay are highly desired in life science. Single-shot diffraction imaging presents strong potentials to achieve this goal as evidenced by past experimental results using methods such as polarization diffraction imaging flow cytometry. We present here a platform of methods toward solving these problems and results of optical cell model (OCM) evaluations by calculations and analysis of cross-polarized diffraction image (p-DI) pairs. Four types of realistic OCMs have been developed with two prostate cell structures and adjustable refractive index (RI) parameters to investigate the effects of cell morphology and index distribution on calculated p-DI pairs. Image patterns have been characterized by a gray-level co-occurrence matrix (GLCM) algorithm and four GLCM parameters and linear depolarization ratio δL have been selected to compare calculated against measured data of prostate cells. Our results show that the irregular shapes of and heterogeneity in RI distributions for organelles play significant roles in the spatial distribution of scattered light by cells in comparison to the average RI values and their differences among the organelles. Discrepancies in GLCM and δL parameters between calculated and measured p-DI data provide useful insight for understanding light scattering by single cells and improving OCM.
© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  cell analysis; cell models; diffraction imaging; light scattering

Mesh:

Year:  2018        PMID: 30447049     DOI: 10.1002/jbio.201800287

Source DB:  PubMed          Journal:  J Biophotonics        ISSN: 1864-063X            Impact factor:   3.207


  1 in total

1.  Analysis of polarized diffraction images of human red blood cells: a numerical study.

Authors:  Wenjin Wang; Li Min; Peng Tian; Chao Wu; Jing Liu; Xin-Hua Hu
Journal:  Biomed Opt Express       Date:  2022-02-03       Impact factor: 3.732

  1 in total

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