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Differential Diagnosis of Lung Carcinoma With Coherent Anti-Stokes Raman Scattering Imaging.
MedLine Citation:
PMID:  23194042     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Aimed at bridging imaging technology development with cancer diagnosis, this paper first presents the prevailing challenges of lung cancer detection and diagnosis, with an emphasis on imaging techniques. It then elaborates on the working principle of coherent anti-Stokes Raman scattering microscopy, along with a description of pathologic applications to show the effectiveness and potential of this novel technology for lung cancer diagnosis. As a nonlinear optical technique probing intrinsic molecular vibrations, coherent anti-Stokes Raman scattering microscopy offers an unparalleled, label-free strategy for clinical cancer diagnosis and allows differential diagnosis of fresh specimens based on cell morphology information and patterns, without any histology staining. This powerful feature promises a higher biopsy yield for early cancer detection by incorporating a real-time imaging feed with a biopsy needle. In addition, molecularly targeted therapies would also benefit from early access to surgical specimen with high accuracy but minimum tissue consumption, therefore potentially saving specimens for follow-up diagnostic tests. Finally, we also introduce the potential of a coherent anti-Stokes Raman scattering-based endoscopy system to support intraoperative applications at the cellular level.
Authors:
Liang Gao; Zhiyong Wang; Fuhai Li; Ahmad A Hammoudi; Michael J Thrall; Philip T Cagle; Stephen T C Wong
Publication Detail:
Type:  JOURNAL ARTICLE    
Journal Detail:
Title:  Archives of pathology & laboratory medicine     Volume:  136     ISSN:  1543-2165     ISO Abbreviation:  Arch. Pathol. Lab. Med.     Publication Date:  2012 Dec 
Date Detail:
Created Date:  2012-11-30     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7607091     Medline TA:  Arch Pathol Lab Med     Country:  -    
Other Details:
Languages:  ENG     Pagination:  1502-1510     Citation Subset:  -    
Affiliation:
From the Department of Systems Medicine and Bioengineering (Drs Gao, Wang, Li, and Wong and Mr Hammoudi) and the NCI-ICBP Center for Modeling Cancer Development (Drs Li and Wong), The Methodist Hospital Research Institute, and the Department of Pathology and Genomic Medicine, The Methodist Hospital (Drs Thrall, Cagle, and Wong), Weill Cornell Medical College of Cornell University, Houston, Texas; Chroma Technology Corporation, Bellows Falls, Vermont (Dr Gao); and the Department of Electrical and Computer Engineering, Rice University, Houston, Texas (Mr Hammoudi and Dr Wong).
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