Limits...
Diagnostic potential of near-infrared Raman spectroscopy in the stomach: differentiating dysplasia from normal tissue.

Teh SK, Zheng W, Ho KY, Teh M, Yeoh KG, Huang Z - Br. J. Cancer (2008)

Bottom Line: Both the empirical approach and multivariate statistical techniques, including principal components analysis (PCA), and linear discriminant analysis (LDA), together with the leave-one-sample-out cross-validation method, were employed to develop effective diagnostic algorithms for classification of Raman spectra between normal and dysplastic gastric tissues.High-quality Raman spectra in the range of 800-1800 cm(-1) can be acquired from gastric tissue within 5 s.Receiver operating characteristic (ROC) curves further confirmed that the most effective diagnostic algorithm can be derived from the PCA-LDA technique.

View Article: PubMed Central - PubMed

Affiliation: Bioimaging Laboratory, Division of Bioengineering, Faculty of Engineering, National University of Singapore, Singapore 117576, Singapore.

ABSTRACT
Raman spectroscopy is a molecular vibrational spectroscopic technique that is capable of optically probing the biomolecular changes associated with diseased transformation. The purpose of this study was to explore near-infrared (NIR) Raman spectroscopy for identifying dysplasia from normal gastric mucosa tissue. A rapid-acquisition dispersive-type NIR Raman system was utilised for tissue Raman spectroscopic measurements at 785 nm laser excitation. A total of 76 gastric tissue samples obtained from 44 patients who underwent endoscopy investigation or gastrectomy operation were used in this study. The histopathological examinations showed that 55 tissue specimens were normal and 21 were dysplasia. Both the empirical approach and multivariate statistical techniques, including principal components analysis (PCA), and linear discriminant analysis (LDA), together with the leave-one-sample-out cross-validation method, were employed to develop effective diagnostic algorithms for classification of Raman spectra between normal and dysplastic gastric tissues. High-quality Raman spectra in the range of 800-1800 cm(-1) can be acquired from gastric tissue within 5 s. There are specific spectral differences in Raman spectra between normal and dysplasia tissue, particularly in the spectral ranges of 1200-1500 cm(-1) and 1600-1800 cm(-1), which contained signals related to amide III and amide I of proteins, CH(3)CH(2) twisting of proteins/nucleic acids, and the C=C stretching mode of phospholipids, respectively. The empirical diagnostic algorithm based on the ratio of the Raman peak intensity at 875 cm(-1) to the peak intensity at 1450 cm(-1) gave the diagnostic sensitivity of 85.7% and specificity of 80.0%, whereas the diagnostic algorithms based on PCA-LDA yielded the diagnostic sensitivity of 95.2% and specificity 90.9% for separating dysplasia from normal gastric tissue. Receiver operating characteristic (ROC) curves further confirmed that the most effective diagnostic algorithm can be derived from the PCA-LDA technique. Therefore, NIR Raman spectroscopy in conjunction with multivariate statistical technique has potential for rapid diagnosis of dysplasia in the stomach based on the optical evaluation of spectral features of biomolecules.

Show MeSH

Related in: MedlinePlus

Mean normalised gastric Raman spectra (solid line) ±1 s.d. (grey area) obtained from a normal tissue (A) and a dysplasia tissue (B) by multiple measurements (n=5) at various locations for each sample. Each spectrum was normalised to the integrated area under the curve to correct for variations in absolute spectral intensity. All spectra were acquired in 5 s with 785-nm excitation and corrected for spectral response of the system.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2361456&req=5

fig2: Mean normalised gastric Raman spectra (solid line) ±1 s.d. (grey area) obtained from a normal tissue (A) and a dysplasia tissue (B) by multiple measurements (n=5) at various locations for each sample. Each spectrum was normalised to the integrated area under the curve to correct for variations in absolute spectral intensity. All spectra were acquired in 5 s with 785-nm excitation and corrected for spectral response of the system.

Mentions: To assess intrasample variability, multiple Raman measurements (n=5) on each of normal and dysplasia gastric tissues were made at different locations of the same samples. Figure 2 shows an example of the mean normalised Raman spectra ±1 s.d. measured from a normal (A) and a dysplasia (B) gastric tissue, respectively. The overall spectral intensities varied by 30% about the mean for normal tissue, and by 20% for dysplasia tissue. However, the relative Raman peak heights, shapes, and positions showed little intrasample variability for either normal or dysplasia tissue, indicating the relative homogeneity of tissue samples used in this study.


Diagnostic potential of near-infrared Raman spectroscopy in the stomach: differentiating dysplasia from normal tissue.

Teh SK, Zheng W, Ho KY, Teh M, Yeoh KG, Huang Z - Br. J. Cancer (2008)

Mean normalised gastric Raman spectra (solid line) ±1 s.d. (grey area) obtained from a normal tissue (A) and a dysplasia tissue (B) by multiple measurements (n=5) at various locations for each sample. Each spectrum was normalised to the integrated area under the curve to correct for variations in absolute spectral intensity. All spectra were acquired in 5 s with 785-nm excitation and corrected for spectral response of the system.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2361456&req=5

fig2: Mean normalised gastric Raman spectra (solid line) ±1 s.d. (grey area) obtained from a normal tissue (A) and a dysplasia tissue (B) by multiple measurements (n=5) at various locations for each sample. Each spectrum was normalised to the integrated area under the curve to correct for variations in absolute spectral intensity. All spectra were acquired in 5 s with 785-nm excitation and corrected for spectral response of the system.
Mentions: To assess intrasample variability, multiple Raman measurements (n=5) on each of normal and dysplasia gastric tissues were made at different locations of the same samples. Figure 2 shows an example of the mean normalised Raman spectra ±1 s.d. measured from a normal (A) and a dysplasia (B) gastric tissue, respectively. The overall spectral intensities varied by 30% about the mean for normal tissue, and by 20% for dysplasia tissue. However, the relative Raman peak heights, shapes, and positions showed little intrasample variability for either normal or dysplasia tissue, indicating the relative homogeneity of tissue samples used in this study.

Bottom Line: Both the empirical approach and multivariate statistical techniques, including principal components analysis (PCA), and linear discriminant analysis (LDA), together with the leave-one-sample-out cross-validation method, were employed to develop effective diagnostic algorithms for classification of Raman spectra between normal and dysplastic gastric tissues.High-quality Raman spectra in the range of 800-1800 cm(-1) can be acquired from gastric tissue within 5 s.Receiver operating characteristic (ROC) curves further confirmed that the most effective diagnostic algorithm can be derived from the PCA-LDA technique.

View Article: PubMed Central - PubMed

Affiliation: Bioimaging Laboratory, Division of Bioengineering, Faculty of Engineering, National University of Singapore, Singapore 117576, Singapore.

ABSTRACT
Raman spectroscopy is a molecular vibrational spectroscopic technique that is capable of optically probing the biomolecular changes associated with diseased transformation. The purpose of this study was to explore near-infrared (NIR) Raman spectroscopy for identifying dysplasia from normal gastric mucosa tissue. A rapid-acquisition dispersive-type NIR Raman system was utilised for tissue Raman spectroscopic measurements at 785 nm laser excitation. A total of 76 gastric tissue samples obtained from 44 patients who underwent endoscopy investigation or gastrectomy operation were used in this study. The histopathological examinations showed that 55 tissue specimens were normal and 21 were dysplasia. Both the empirical approach and multivariate statistical techniques, including principal components analysis (PCA), and linear discriminant analysis (LDA), together with the leave-one-sample-out cross-validation method, were employed to develop effective diagnostic algorithms for classification of Raman spectra between normal and dysplastic gastric tissues. High-quality Raman spectra in the range of 800-1800 cm(-1) can be acquired from gastric tissue within 5 s. There are specific spectral differences in Raman spectra between normal and dysplasia tissue, particularly in the spectral ranges of 1200-1500 cm(-1) and 1600-1800 cm(-1), which contained signals related to amide III and amide I of proteins, CH(3)CH(2) twisting of proteins/nucleic acids, and the C=C stretching mode of phospholipids, respectively. The empirical diagnostic algorithm based on the ratio of the Raman peak intensity at 875 cm(-1) to the peak intensity at 1450 cm(-1) gave the diagnostic sensitivity of 85.7% and specificity of 80.0%, whereas the diagnostic algorithms based on PCA-LDA yielded the diagnostic sensitivity of 95.2% and specificity 90.9% for separating dysplasia from normal gastric tissue. Receiver operating characteristic (ROC) curves further confirmed that the most effective diagnostic algorithm can be derived from the PCA-LDA technique. Therefore, NIR Raman spectroscopy in conjunction with multivariate statistical technique has potential for rapid diagnosis of dysplasia in the stomach based on the optical evaluation of spectral features of biomolecules.

Show MeSH
Related in: MedlinePlus