Discrimination of normal and malignant stomach mucosal tissues by Raman spectroscopy: A pilot study

Kumar, K. Kalyan; Anand, Ankur; Chowdary, M. V. P.; Keerthi,; Kurien, Jacob; Krishna, C. Murali; Mathew, Stanley

doi:10.1016/j.vibspec.2007.03.007

Cited by 25 publications

(10 citation statements)

References 20 publications

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“…This high chemical specifity constitutes a major advantage of RMS, making it able to detect slight chemical changes in biological samples. 24 RMS achieves diffraction-limited lateral resolution in the micrometer range, which makes it an appropriate tool to imaging cells 25 and tissues. 26 RMS is a suitable technique for cancer diagnosis because of its high sensitivity to molecular and structural changes associated with cancer, such as an increased nucleus-tocytoplasm ratio, disordered chromatin, higher metabolic activity, and changes in lipid and protein levels.…”

Section: Introductionmentioning

confidence: 99%

Development of Raman microspectroscopy for automated detection and imaging of basal cell carcinoma

et al. 2009

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We investigate the potential of Raman microspectroscopy (RMS) for automated evaluation of excised skin tissue during Mohs micrographic surgery (MMS). The main aim is to develop an automated method for imaging and diagnosis of basal cell carcinoma (BCC) regions. Selected Raman bands responsible for the largest spectral differences between BCC and normal skin regions and linear discriminant analysis (LDA) are used to build a multivariate supervised classification model. The model is based on 329 Raman spectra measured on skin tissue obtained from 20 patients. BCC is discriminated from healthy tissue with 90+/-9% sensitivity and 85+/-9% specificity in a 70% to 30% split cross-validation algorithm. This multivariate model is then applied on tissue sections from new patients to image tumor regions. The RMS images show excellent correlation with the gold standard of histopathology sections, BCC being detected in all positive sections. We demonstrate the potential of RMS as an automated objective method for tumor evaluation during MMS. The replacement of current histopathology during MMS by a "generalization" of the proposed technique may improve the feasibility and efficacy of MMS, leading to a wider use according to clinical need.

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Section: Introductionmentioning

confidence: 99%

Development of Raman microspectroscopy for automated detection and imaging of basal cell carcinoma

et al. 2009

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“…As mentioned earlier in Section 4 , analysis was carried out in two different approaches: (1) unsupervised analysis, (2) supervised analysis. We have successfully tested these approaches in our earlier Raman spectroscopic studies of cervix, oral, and breast cancers [ 14 , 15 , 20 , 22 , 24 , 31 , 33 ].…”

Section: Resultsmentioning

confidence: 99%

“…In this table, spectra 1–48 were normal tissue spectra, and spectra 49–108 were of malignant tissues. Efficacy of this approach was demonstrated in our earlier Raman studies of oral, breast, cervix, stomach, and colon cancers [ 14 , 15 , 20 , 22 , 24 , 31 , 33 ].…”

Section: Resultsmentioning

confidence: 99%

“…In the unsupervised approach, scores of factor were used as discriminating parameter whereas, in the supervised mode, Mahalanobis Distance and spectral residuals were used as discriminating parameters [ 35 , 36 ]. We have also explored match/mismatch “limit test” approach which is known to bring out objective and unambiguous discrimination [ 14 , 15 , 20 , 22 , 24 , 31 , 33 ]. The flow chart of the study design is shown in Figure 3 .…”

Section: Discussionmentioning

confidence: 99%

“…Raman spectra were recorded using the setup which was assembled by us [ 14 , 15 , 20 , 22 , 24 , 31 , 33 ]. In brief, this instrumentation employed diode laser (SDL-8530 785 nm, 100 mW) for excitation and HR 320 spectrograph (600 g/mm blazed at 900 nm) and spectrum one liquid N 2 -cooled CCD for dispersion and detection of Raman signals.…”

Section: Laser Raman Spectroscopymentioning

confidence: 99%

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Raman Spectroscopic Methods for Classification of Normal and Malignant Hypopharyngeal Tissues: An Exploratory Study

Pujary

Kodali

et al. 2011

Pathology Research International

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Laryngeal cancer is more common in males. The present study is aimed at exploration of potential of conventional Raman spectroscopy in classifying normal from a malignant laryngopharyngeal tissue. We have recorded Raman spectra of twenty tissues (aryepiglottic fold) using an in-house built Raman setup. The spectral features of mean malignant spectrum suggests abundance proteins whereas spectral features of mean normal spectrum indicate redundancy of lipids. PCA was employed as discriminating algorithm. Both, unsupervised and supervised modes of analysis as well as match/mismatch “limit test” methodology yielded clear classification among tissue types. The findings of this study demonstrate the efficacy of conventional Raman spectroscopy in classification of normal and malignant laryngopharyngeal tissues. A rigorous evaluation of the models with development of suitable fibreoptic probe may enable real-time Raman spectroscopic diagnosis of laryngopharyngeal cancers in future.

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The potential for histological screening using a combination of rapid Raman mapping and principal component analysis

Hutchings

Kendall

Smith

et al. 2009

Journal of Biophotonics

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Rapid Raman mapping was carried out on 20 microm sections of oesophageal biopsy samples. Contiguous 7 microm sections were stained with haematoxylin and eosin (H&E) with histopathology provided by an expert pathologist. The step size and acquisition times were varied and the resulting spectra, principal component (PC) score maps and loads were compared. Overall mapping times were also compared to traditional Raman point mapping. The principal component loads for each of the maps were seen to be similar despite varying the acquisition time and number of spectra. Gross biochemical information was extracted showing good correlation with the H&E sections even for short overall mapping times (30-90 minutes for a 2 mm biopsy, 0.5 s acquisition time per 25.3 microm Raman pixel). This demonstrates that low signal to noise spectral maps are sufficient for the identification of histologically relevant biochemistry using principal component analysis as long as the spectral dataset is large enough.

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Discrimination of normal and malignant stomach mucosal tissues by Raman spectroscopy: A pilot study

Cited by 25 publications

References 20 publications

Development of Raman microspectroscopy for automated detection and imaging of basal cell carcinoma

Development of Raman microspectroscopy for automated detection and imaging of basal cell carcinoma

Raman Spectroscopic Methods for Classification of Normal and Malignant Hypopharyngeal Tissues: An Exploratory Study

The potential for histological screening using a combination of rapid Raman mapping and principal component analysis

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