Literature DB >> 18213691

Use of hyperspectral imaging to distinguish normal, precancerous, and cancerous cells.

Anwer M Siddiqi1, Hui Li, Fazlay Faruque, Worth Williams, Kent Lai, Michael Hughson, Steven Bigler, James Beach, William Johnson.   

Abstract

BACKGROUND: The objective of the current study was to test the hypothesis that the cytologic diagnosis of cancer cells can be enhanced by the technique of hyperspectral imaging (HSI).
METHODS: As a proof of principle, HSI was employed to obtain hyperspectrum from a normal human fibroblast, as well as its telomerase-immortalized and SV40-transformed derivatives. Novel algorithms were developed to differentiate among these cell models based on spectral and spatial differences. Using the same technique with modified algorithms, the authors were able to differentiate among normal and precancerous (low-grade [LG] and high-grade [HG]) cervical cells and squamous cell carcinoma (SCC) on liquid-based Papanicolaou (Pap) test slides.
RESULTS: The specificity for identifying normal fibroblast cell type based on spatial and spectral algorithms was 74.2%. The sensitivity for identifying telomerase-immortalized and SV40-transformed cells was 100% and 90.3%, respectively. The system identified normal cervical cells with a specificity of 95.8%. With regard to LG precancerous cells and HG precancerous cells, the sensitivity was 66.7% and 93.5%, respectively. The sensitivity detected for SCC was 98.6%.
CONCLUSIONS: HSI can be utilized in prescreening liquid-based Pap test slides to improve efficiency in Pap test diagnoses with the goal of ultimately reducing the mortality from cervical cancer while reducing health care costs. (c) 2007 American Cancer Society

Entities:  

Mesh:

Year:  2008        PMID: 18213691     DOI: 10.1002/cncr.23286

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  21 in total

1.  Identification of cancerous gastric cells based on common features extracted from hyperspectral microscopic images.

Authors:  Siqi Zhu; Kang Su; Yumeng Liu; Hao Yin; Zhen Li; Furong Huang; Zhenqiang Chen; Weidong Chen; Ge Zhang; Yihong Chen
Journal:  Biomed Opt Express       Date:  2015-03-04       Impact factor: 3.732

2.  Real-time snapshot hyperspectral imaging endoscope.

Authors:  Robert T Kester; Noah Bedard; Liang Gao; Tomasz S Tkaczyk
Journal:  J Biomed Opt       Date:  2011-05       Impact factor: 3.170

3.  Differentiation of peripheral nerve functions and properties with spectral analysis and Karnovsky-Roots staining: a preliminary study.

Authors:  Qintong Xu; Zenggan Chen; Qiong Li; Haifei Liu; Jian Zhang; Wenhua Yao; Ren Zhang; Qingli Li; Hongying Liu; Feng Zhang; William C Lineaweaver
Journal:  Int J Clin Exp Med       Date:  2014-10-15

Review 4.  Medical hyperspectral imaging: a review.

Authors:  Guolan Lu; Baowei Fei
Journal:  J Biomed Opt       Date:  2014-01       Impact factor: 3.170

5.  Automated detection of dual p16/Ki67 nuclear immunoreactivity in liquid-based Pap tests for improved cervical cancer risk stratification.

Authors:  Arkadiusz Gertych; Anika O Joseph; Ann E Walts; Shikha Bose
Journal:  Ann Biomed Eng       Date:  2012-01-04       Impact factor: 3.934

Review 6.  Single-Cell Analysis Using Hyperspectral Imaging Modalities.

Authors:  Nishir Mehta; Shahensha Shaik; Ram Devireddy; Manas Ranjan Gartia
Journal:  J Biomech Eng       Date:  2018-02-01       Impact factor: 2.097

Review 7.  Single cell spectroscopy: noninvasive measures of small-scale structure and function.

Authors:  Charilaos Mousoulis; Xin Xu; David A Reiter; Corey P Neu
Journal:  Methods       Date:  2013-07-22       Impact factor: 3.608

8.  Hyperspectral imaging and quantitative analysis for prostate cancer detection.

Authors:  Hamed Akbari; Luma V Halig; David M Schuster; Adeboye Osunkoya; Viraj Master; Peter T Nieh; Georgia Z Chen; Baowei Fei
Journal:  J Biomed Opt       Date:  2012-07       Impact factor: 3.170

Review 9.  How to evaluate emerging technologies in cervical cancer screening?

Authors:  Marc Arbyn; Guglielmo Ronco; Jack Cuzick; Nicolas Wentzensen; Philip E Castle
Journal:  Int J Cancer       Date:  2009-12-01       Impact factor: 7.396

10.  Detection of Cancer Metastasis Using a Novel Macroscopic Hyperspectral Method.

Authors:  Hamed Akbari; Luma V Halig; Hongzheng Zhang; Dongsheng Wang; Zhuo Georgia Chen; Baowei Fei
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2012-03-23
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