Literature DB >> 27539534

Quantitative phase imaging for medical diagnosis.

Hassaan Majeed1, Shamira Sridharan2, Mustafa Mir3, Lihong Ma4, Eunjung Min5, Woonggyu Jung5,6, Gabriel Popescu1.   

Abstract

Optical microscopy is an indispensable diagnostic tool in modern healthcare. As a prime example, pathologists rely exclusively on light microscopy to investigate tissue morphology in order to make a diagnosis. While advances in light microscopy and contrast markers allow pathologists to visualize cells and tissues in unprecedented detail, the interpretation of these images remains largely subjective, leading to inter- and intra-observer discrepancy. Furthermore, conventional microscopy images capture qualitative information which makes it difficult to automate the process, reducing the throughput achievable in the diagnostic workflow. Quantitative Phase Imaging (QPI) techniques have been advanced in recent years to address these two challenges. By quantifying physical parameters of cells and tissues, these systems remove subjectivity from the disease diagnosis process and allow for easier automation to increase throughput. In addition to providing quantitative information, QPI systems are also label-free and can be easily assimilated into the current diagnostic workflow in the clinic. In this paper we review the advances made in disease diagnosis by QPI techniques. We focus on the areas of hematological diagnosis and cancer pathology, which are the areas where most significant advances have been made to date. [Image adapted from Y. Park, M. Diez-Silva, G. Popescu, G. Lykotrafitis, W. Choi, M. S. Feld, and S. Suresh, Proc. Natl. Acad. Sci. 105, 13730-13735 (2008).].
© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  cancer diagnosis; hematological disorders; interferometry; label free imaging; microscopy; pathology; quantitative phase imaging

Mesh:

Year:  2016        PMID: 27539534     DOI: 10.1002/jbio.201600113

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


  25 in total

1.  Harmonically decoupled gradient light interference microscopy (HD-GLIM).

Authors:  Yi Wang; Mikhail E Kandel; Michael J Fanous; Chenfei Hu; HsuanYu Chen; Xiaoxu Lu; Gabriel Popescu
Journal:  Opt Lett       Date:  2020-03-15       Impact factor: 3.776

2.  Large population cell characterization using quantitative phase cytometer.

Authors:  Di Jin; Yongjin Sung; Niyom Lue; Yang-Hyo Kim; Peter T C So; Zahid Yaqoob
Journal:  Cytometry A       Date:  2017-04-26       Impact factor: 4.355

3.  High-throughput, volumetric quantitative phase imaging with multiplexed intensity diffraction tomography.

Authors:  Alex Matlock; Lei Tian
Journal:  Biomed Opt Express       Date:  2019-11-22       Impact factor: 3.732

4.  Synthetic aperture interference light (SAIL) microscopy for high-throughput label-free imaging.

Authors:  Chenfei Hu; Mikhail E Kandel; Young Jae Lee; Gabriel Popescu
Journal:  Appl Phys Lett       Date:  2021-12-08       Impact factor: 3.791

5.  Demystifying speckle field interference microscopy.

Authors:  Azeem Ahmad; Nikhil Jayakumar; Balpreet Singh Ahluwalia
Journal:  Sci Rep       Date:  2022-06-27       Impact factor: 4.996

6.  Tomographic phase microscopy: principles and applications in bioimaging [Invited].

Authors:  Di Jin; Renjie Zhou; Zahid Yaqoob; Peter T C So
Journal:  J Opt Soc Am B       Date:  2017       Impact factor: 2.106

7.  Quantitative phase imaging of stromal prognostic markers in pancreatic ductal adenocarcinoma.

Authors:  Michael Fanous; Adib Keikhosravi; Andre Kajdacsy-Balla; Kevin W Eliceiri; Gabriel Popescu
Journal:  Biomed Opt Express       Date:  2020-02-12       Impact factor: 3.732

8.  Disorder strength measured by quantitative phase imaging as intrinsic cancer marker in fixed tissue biopsies.

Authors:  Masanori Takabayashi; Hassaan Majeed; Andre Kajdacsy-Balla; Gabriel Popescu
Journal:  PLoS One       Date:  2018-03-21       Impact factor: 3.240

9.  Label-free screening of brain tissue myelin content using phase imaging with computational specificity (PICS).

Authors:  Michael Fanous; Chuqiao Shi; Megan P Caputo; Laurie A Rund; Rodney W Johnson; Tapas Das; Matthew J Kuchan; Nahil Sobh; Gabriel Popescu
Journal:  APL Photonics       Date:  2021-07-12

10.  Enhancing optical microscopy illumination to enable quantitative imaging.

Authors:  Emil Agocs; Ravi Kiran Attota
Journal:  Sci Rep       Date:  2018-03-19       Impact factor: 4.379

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