Literature DB >> 14992404

Raman spectroscopy for identification of epithelial cancers.

Nicholas Stone1, Catherine Kendall, Jenny Smith, Paul Crow, Hugh Barr.   

Abstract

There is a real need for improvements in cancer detection. Significant problems are encountered when utilising the gold standard of excisional biopsy combined with histopathology. This can include missed lesions, perforation and high levels of inter- and intra-observer discrepancies. The clinical requirements for an objective, non-invasive real time probe for accurate and repeatable measurement of tissue pathological state are overwhelming. This study has evaluated the potential for Raman spectroscopy to achieve this goal. The technique measures the molecular specific inelastic scattering of laser light within tissue, thus enabling the analysis of biochemical changes that precede and accompany disease processes. Initial work has been carried out to optimise a commercially available Raman microspectrometer for tissue measurements; to target potential malignancies with a clinical need for diagnostic improvements (oesophagus. colon, breast, andd prostate) and to build and test spectral libraries and prediction algorithms for tissue types and pathologies. This study has followed rigorous sample collection protocols and histopathological analysis using a board of expert pathologists. Only the data from samples with full agreement of a homogeneous pathology have been used to construct a training data set of Raman spectra. Measurements of tissue specimens from the full spectrum of different pathological groups found in each tissue have been made. Diagnostic predictive models have been constructed and optimised using multivariate analysis techniques. They have been tested using cross-validation or leave-one-out and demonstrated high levels of discrimination between pathology groups (greater than 90% sensitivity and specificity for all tissues). However larger sample numbers are required for further evaluation. The discussions outline the likely work required for successful implementation of in vivo Raman detection of early malignancies.

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Year:  2004        PMID: 14992404     DOI: 10.1039/b304992b

Source DB:  PubMed          Journal:  Faraday Discuss        ISSN: 1359-6640            Impact factor:   4.008


  100 in total

1.  Distinguishing cell types or populations based on the computational analysis of their infrared spectra.

Authors:  Francis L Martin; Jemma G Kelly; Valon Llabjani; Pierre L Martin-Hirsch; Imran I Patel; Júlio Trevisan; Nigel J Fullwood; Michael J Walsh
Journal:  Nat Protoc       Date:  2010-10-07       Impact factor: 13.491

2.  Cervical cancer detection based on serum sample Raman spectroscopy.

Authors:  José Luis González-Solís; Juan Carlos Martínez-Espinosa; Luis Adolfo Torres-González; Adriana Aguilar-Lemarroy; Luis Felipe Jave-Suárez; Pascual Palomares-Anda
Journal:  Lasers Med Sci       Date:  2013-10-03       Impact factor: 3.161

3.  Monitoring of chemotherapy leukemia treatment using Raman spectroscopy and principal component analysis.

Authors:  José Luis González-Solís; Juan Carlos Martínez-Espinosa; Juan Manuel Salgado-Román; Pascual Palomares-Anda
Journal:  Lasers Med Sci       Date:  2014-01-10       Impact factor: 3.161

4.  Sensitivity of coded aperture Raman spectroscopy to analytes beneath turbid biological tissue and tissue-simulating phantoms.

Authors:  Jason R Maher; Thomas E Matthews; Ashley K Reid; David F Katz; Adam Wax
Journal:  J Biomed Opt       Date:  2014       Impact factor: 3.170

5.  Upconversion raster scanning microscope for long-wavelength infrared imaging of breast cancer microcalcifications.

Authors:  Yu-Pei Tseng; Pascaline Bouzy; Christian Pedersen; Nick Stone; Peter Tidemand-Lichtenberg
Journal:  Biomed Opt Express       Date:  2018-09-24       Impact factor: 3.732

6.  Discrimination of prostate carcinoma from benign prostate tissue fragments in vitro by estimating the gross biochemical alterations through Raman spectroscopy.

Authors:  Landulfo Silveira; Kátia Ramos M Leite; Fabricio Luiz Silveira; Miguel Srougi; Marcos Tadeu T Pacheco; Renato Amaro Zângaro; Carlos Augusto Pasqualucci
Journal:  Lasers Med Sci       Date:  2014-03-12       Impact factor: 3.161

7.  Direct detection of malaria infected red blood cells by surface enhanced Raman spectroscopy.

Authors:  Funing Chen; Briana R Flaherty; Charli E Cohen; David S Peterson; Yiping Zhao
Journal:  Nanomedicine       Date:  2016-03-23       Impact factor: 5.307

8.  Using Raman spectroscopy to characterize biological materials.

Authors:  Holly J Butler; Lorna Ashton; Benjamin Bird; Gianfelice Cinque; Kelly Curtis; Jennifer Dorney; Karen Esmonde-White; Nigel J Fullwood; Benjamin Gardner; Pierre L Martin-Hirsch; Michael J Walsh; Martin R McAinsh; Nicholas Stone; Francis L Martin
Journal:  Nat Protoc       Date:  2016-03-10       Impact factor: 13.491

9.  Arcobacter Identification and Species Determination Using Raman Spectroscopy Combined with Neural Networks.

Authors:  Kaidi Wang; Lei Chen; Xiangyun Ma; Lina Ma; Keng C Chou; Yankai Cao; Izhar U H Khan; Greta Gölz; Xiaonan Lu
Journal:  Appl Environ Microbiol       Date:  2020-10-01       Impact factor: 4.792

10.  Real-time in vivo diagnosis of laryngeal carcinoma with rapid fiber-optic Raman spectroscopy.

Authors:  Kan Lin; Wei Zheng; Chwee Ming Lim; Zhiwei Huang
Journal:  Biomed Opt Express       Date:  2016-08-26       Impact factor: 3.732

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