In vivo Near-infrared Raman Spectroscopy: Demonstration of Feasibility During Clinical Gastrointestinal Endoscopy¶

Shim, Martin G.; Song, Louis M. Wong Kee; Marcon, Norman E.; Wilson, Brian C.

doi:10.1562/0031-8655(2000)072<0146:ivnirs>2.0.co;2

Cited by 172 publications

(166 citation statements)

References 15 publications

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“…In comparison, Raman spectroscopy is an inelastic scattering technique based on unique selection rules that produces weak signals and can become overwhelmed by tissue autofluorescence (31). Consequently, Raman requires expensive detectors and sophisticated spectral processing, conditions that can be difficult to translate to the clinic for screening purposes (32,33).…”

Section: Discussionmentioning

confidence: 99%

Detection of endogenous biomolecules in Barrett's esophagus by Fourier transform infrared spectroscopy

Wang

Triadafilopoulos²,

Crawford

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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Fourier transform infrared (FTIR) spectroscopy provides a unique molecular fingerprint of tissue from endogenous sources of light absorption; however, specific molecular components of the overall FTIR signature of precancer have not been characterized. In attenuated total reflectance mode, infrared light penetrates only a few microns of the tissue surface, and the influence of water on the spectra can be minimized, allowing for the analyses of the molecular composition of tissues. Here, spectra were collected from 98 excised specimens of the distal esophagus, including 38 squamous, 38 intestinal metaplasia (Barrett's), and 22 gastric, obtained endoscopically from 32 patients. We show that DNA, protein, glycogen, and glycoprotein comprise the principal sources of infrared absorption in the 950-to 1,800-cm ؊1 regime. The concentrations of these biomolecules can be quantified by using a partial leastsquares fit and used to classify disease states with high sensitivity, specificity, and accuracy. Moreover, use of FTIR to detect premalignant (dysplastic) mucosa results in a sensitivity, specificity, positive predictive value, and total accuracy of 92%, 80%, 92%, and 89%, respectively, and leads to a better interobserver agreement between two gastrointestinal pathologists for dysplasia ( ‫؍‬ 0.72) versus histology alone ( ‫؍‬ 0.52). Here, we demonstrate that the concentration of specific biomolecules can be determined from the FTIR spectra collected in attenuated total reflectance mode and can be used for predicting the underlying histopathology, which will contribute to the early detection and rapid staging of many diseases.dysplasia ͉ pathology ͉ optical biopsy ͉ diagnostics

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Section: Discussionmentioning

confidence: 99%

Detection of endogenous biomolecules in Barrett's esophagus by Fourier transform infrared spectroscopy

Wang

Triadafilopoulos²,

Crawford

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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“…To date only the oesophagus has been examined in any detail with Raman spectroscopy, although only selected pathologies were compared. 17,21 This study followed extremely rigorous sampling procedures to reduce the errors caused by discrepancies in histopathology, sample misorientation and by measuring samples with mixed pathology. In addition, the full spectrum of malignant disease found in each organ was studied, in order to remove any bias likely to be found in studies comparing normal with cancerous tissue, i.e.…”

Section: Introductionmentioning

confidence: 99%

Near‐infrared Raman spectroscopy for the classification of epithelial pre‐cancers and cancers

Stone

Kendall

Shepherd

et al. 2002

J Raman Spectroscopy

414

323

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The use of near-infrared Raman spectroscopy to interrogate epithelial tissue biochemistry and hence distinguish between normal and abnormal tissues was investigated. Six different epithelial tissues from the larynx, tonsil, oesophagus, stomach, bladder and prostate were measured. Spectral diagnostic models were constructed using multivariate statistical analysis of the spectra to classify samples of epithelial cancers and pre-cancers. Tissues were selected for clinical significance and to include those which develop into carcinoma from squamous, transitional or columnar epithelial cells. Rigorous histopathological protocols were followed and mixed pathology tissue samples were discarded from the study. Principal component fed linear discriminant models demonstrated excellent group separation, when tested by crossvalidation. Larynx samples, with squamous epithelial tissue, were separated into three distinct groups with sensitivities ranging from 86 to 90% and specificities from 87 to 95%. Bladder specimens, containing transitional epithelial tissue, were separated into five distinct groups with sensitivities of between 78 and 98% and specificities between 96 and 99%. Oesophagus tissue can contain both squamous and columnar cell carcinomas. A three group model discriminated the columnar cell pathological groups with sensitivities of 84-97% and specificities of 93-99%, and an eight group model combining both columnar and squamous tissues in the oesophagus was able to discriminate pathologies with sensitivities of 73-100% and specificities of 92-100%. It is likely that any overlap between pathology group predictions will have been due to a combination of the difficulty in histologically distinguishing between pre-cancerous states and the fact that there is no biochemical boundary from one pathological group to the next, i.e. there is believed to be a continuum of progression from the normal to the diseased state.

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“…Thus, Raman spectroscopy is likely to be a useful technique. [1][2][3][4][5][6][7][8][9][10][11] The objectives of this study were to evaluate the sensitivity and specificity of Raman spectroscopy in differentiating between cancer and normal breast tissue in a mouse model.…”

Section: Introductionmentioning

confidence: 99%

Raman spectroscopy can differentiate malignant tumors from normal breast tissue and detect early neoplastic changes in a mouse model

et al. 2007

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Raman spectroscopy shows potential in differentiating tumors from normal tissue. We used Raman spectroscopy with near‐infrared light excitation to study normal breast tissue and tumors from 11 mice injected with a cancer cell line. Spectra were collected from 17 tumors, 18 samples of adjacent breast tissue and lymph nodes, and 17 tissue samples from the contralateral breast and its adjacent lymph nodes. Discriminant function analysis was used for classification with principal component analysis scores as input data. Tissues were examined by light microscopy following formalin fixation and hematoxylin and eosin staining. Discriminant function analysis and histology agreed on the diagnosis of all contralateral normal, tumor, and mastitis samples, except one tumor which was found to be more similar to normal tissue. Normal tissue adjacent to each tumor was examined as a separate data group called tumor bed. Scattered morphologically suspicious atypical cells not definite for tumor were present in the tumor bed samples. Classification of tumor bed tissue showed that some tumor bed tissues are diagnostically different from normal, tumor, and mastitis tissue. This may reflect malignant molecular alterations prior to morphologic changes, as expected in preneoplastic processes. Raman spectroscopy not only distinguishes tumor from normal breast tissue, but also detects early neoplastic changes prior to definite morphologic alteration. © 2007 Wiley Periodicals, Inc. Biopolymers 89: 235–241, 2008. This article was originally published online as an accepted preprint. The “Published Online”date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com

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In vivo Near-infrared Raman Spectroscopy: Demonstration of Feasibility During Clinical Gastrointestinal Endoscopy¶

Cited by 172 publications

References 15 publications

Detection of endogenous biomolecules in Barrett's esophagus by Fourier transform infrared spectroscopy

Detection of endogenous biomolecules in Barrett's esophagus by Fourier transform infrared spectroscopy

Near‐infrared Raman spectroscopy for the classification of epithelial pre‐cancers and cancers

Raman spectroscopy can differentiate malignant tumors from normal breast tissue and detect early neoplastic changes in a mouse model

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