Simultaneous fingerprint and high-wavenumber fiber-optic Raman spectroscopy enhances real-time in vivo diagnosis of adenomatous polyps during colonoscopy.

Colorectal cancer can be prevented if detected early (e.g., precancerous polyps-adenoma). Endoscopic differential diagnosis of hyperplastic polyps (that have little or no risk of malignant transformation) and adenomas (that have prominent malignant latency) remains an unambiguous clinical challenge. Raman spectroscopy is an optical vibrational technique capable of probing biomolecular changes of tissue associated with neoplastic transformation. This work aims to apply a fiber-optic simultaneous fingerprint (FP) and high wavenumber (HW) Raman spectroscopy technique for real-time in vivo assessment of adenomatous polyps during clinical colonoscopy. We have developed a fiber-optic Raman endoscopic technique capable of simultaneously acquiring both the FP (i.e., 800-1800 cm(-1)) and HW (i.e., 2800-3600 cm(-1)) Raman spectra from colorectal tissue subsurface (<200 µm) for real-time assessment of colorectal carcinogenesis. In vivo FP/HW Raman spectra were acquired from 50 patients with 17 colorectal polyps during clinical colonoscopy. Prominent Raman spectral differences (p < 0.001) were found between hyperplastic (n = 118 spectra), adenoma (n = 184 spectra) that could be attributed to changes in inter- and intra-cellular proteins, lipids, DNA and water structures and conformations. Simultaneous FP/HW Raman endoscopy provides a diagnostic sensitivity of 90.9% and specificity of 83.3% for differentiating adenoma from hyperplastic polyps, which is superior to either the FP or HW Raman technique alone. This study shows that simultaneous FP/HW Raman spectroscopy technique has the potential to be a clinically powerful tool for improving early diagnosis of adenomatous polyps in vivo during colonoscopic examination.

Characterizing variability of in vivo Raman spectroscopic properties of different anatomical sites of normal colorectal tissue towards cancer diagnosis at colonoscopy.

This study aims to characterize the in vivo Raman spectroscopic properties of normal colorectal tissues and to assess distinctive biomolecular variations of different anatomical locations in the colorectum for cancer diagnosis. We have developed a novel 785 nm excitation fiber-optic Raman endoscope that can simultaneously acquire in vivo fingerprint (FP) spectra (800-1800 cm(-1)) and high-wavenumber (HW) Raman spectra (2800-3600 cm(-1)) from the subsurface of colorectal tissue. We applied the FP/HW Raman endoscope for in vivo tissue Raman measurements of various normal colorectal anatomical locations (i.e., ascending colon (n = 182), transverse colon (n = 249), descending colon (n = 124), sigmoid (n = 212), and rectum (n = 362)) in 50 subjects. Partial least-squares (PLS)-discriminant analysis (DA) was employed to evaluate the interanatomical variability. The normal colorectal tissue showed a subtle interanatomical variability in molecular constituents (i.e., proteins, lipids, and water content) and could be divided into three major clusterings: (1) ascending colon and transverse colon, (2) descending colon, and (3) sigmoid and rectum. The PLS-DA multiclass algorithms were able to identify different tissue sites with varying sensitivities (SE) and specificities (SP) (ascending colon: SE: 1.10%, SP: 91.02; transverse colon: SE: 14.06%, SP: 78.78; descending colon: SE: 40.32%, SP: 81.99; sigmoid: SE: 19.34%, SP: 87.90; rectum: SE: 71.55%, SP: 77.84). The interanatomical molecular variability was orders of magnitude less than neoplastic tissue transformation. Further PLS-DA modeling on in vivo FP/HW tissue Raman spectra yielded a diagnostic accuracy of 88.8% (sensitivity: 93.9% (93/99); specificity 88.3% (997/1129) for colorectal cancer detection. This work discloses that interanatomical Raman spectral variability of normal colorectal tissue is subtle compared to cancer tissue, and the simultaneous FP/HW Raman endoscopic technique has promising potential for real-time, in vivo diagnosis of colorectal cancer at the molecular level.

[Rapid identification of potato cultivars using NIR-excited fluorescence and Raman spectroscopy].

Potato is one of the most important food in the world. Rapid and noninvasive identification of potato cultivars plays a important role in the better use of varieties. In this study, The identification ability of optical spectroscopy techniques, including near-infrared (NIR) Raman spectroscopy and NIR fluorescence spectroscopy, for invasive detection of potato cultivars was evaluated. A rapid NIR Raman spectroscopy system was applied to measure the composite Raman and NIR fluorescence spectroscopy of 3 different species of potatoes (98 samples in total) under 785 nm laser light excitation. Then pure Raman and NIR fluorescence spectroscopy were abstracted from the composite spectroscopy, respectively. At last, the partial least squares-discriminant analysis (PLS-DA) was utilized to analyze and classify Raman spectra of 3 different types of potatoes. All the samples were divided into two sets at random: the calibration set (74samples) and prediction set (24 samples), the model was validated using a leave-one-out, cross-validation method. The results showed that both the NIR-excited fluorescence spectra and pure Raman spectra could be used to identify three cultivars of potatoes. The fluorescence spectrum could distinguish the Favorita variety well (sensitivity: 1, specificity: 0.86 and accuracy: 0.92), but the result for Diamant (sensitivity: 0.75, specificity: 0.75 and accuracy: 0. 75) and Granola (sensitivity: 0.16, specificity: 0.89 and accuracy: 0.71) cultivars identification were a bit poorer. We demonstrated that Raman spectroscopy uncovered the main biochemical compositions contained in potato species, and provided a better classification sensitivity, specificity and accuracy (sensitivity: 1, specificity: 1 and accuracy: 1 for all 3 potato cultivars identification) among the three types of potatoes as compared to fluorescence spectroscopy.

Multivariate reference technique for quantitative analysis of fiber-optic tissue Raman spectroscopy.

We report a novel method making use of multivariate reference signals of fused silica and sapphire Raman signals generated from a ball-lens fiber-optic Raman probe for quantitative analysis of in vivo tissue Raman measurements in real time. Partial least-squares (PLS) regression modeling is applied to extract the characteristic internal reference Raman signals (e.g., shoulder of the prominent fused silica boson peak (~130 cm(-1)); distinct sapphire ball-lens peaks (380, 417, 646, and 751 cm(-1))) from the ball-lens fiber-optic Raman probe for quantitative analysis of fiber-optic Raman spectroscopy. To evaluate the analytical value of this novel multivariate reference technique, a rapid Raman spectroscopy system coupled with a ball-lens fiber-optic Raman probe is used for in vivo oral tissue Raman measurements (n = 25 subjects) under 785 nm laser excitation powers ranging from 5 to 65 mW. An accurate linear relationship (R(2) = 0.981) with a root-mean-square error of cross validation (RMSECV) of 2.5 mW can be obtained for predicting the laser excitation power changes based on a leave-one-subject-out cross-validation, which is superior to the normal univariate reference method (RMSE = 6.2 mW). A root-mean-square error of prediction (RMSEP) of 2.4 mW (R(2) = 0.985) can also be achieved for laser power prediction in real time when we applied the multivariate method independently on the five new subjects (n = 166 spectra). We further apply the multivariate reference technique for quantitative analysis of gelatin tissue phantoms that gives rise to an RMSEP of ~2.0% (R(2) = 0.998) independent of laser excitation power variations. This work demonstrates that multivariate reference technique can be advantageously used to monitor and correct the variations of laser excitation power and fiber coupling efficiency in situ for standardizing the tissue Raman intensity to realize quantitative analysis of tissue Raman measurements in vivo, which is particularly appealing in challenging Raman endoscopic applications.

Development of a beveled fiber-optic confocal Raman probe for enhancing in vivo epithelial tissue Raman measurements at endoscopy.

We report on the development of a beveled fiber-optic confocal Raman probe coupled with a ball lens for enhancing in vivo epithelial tissue Raman measurements at endoscopy. Our Monte Carlo simulations show that by selecting a proper fiber-ball lens distance and beveled angle of collection fibers, the confocal Raman probe design can be optimized for maximizing shallower tissue Raman measurements in epithelial tissue; in addition, the ratio of epithelium to stromal Raman photons collected using an optimized confocal Raman probe is approximately 19-fold higher than that using a volume-type Raman probe. Further experiments confirm that the confocal Raman endoscopic probe developed is in favor of probing superficial tissue Raman signals from a two-layer tissue phantom as well as esophagus tissue in vivo during endoscopy. This work suggests the great potential of applying the beveled fiber-optic confocal Raman probe for improving in vivo diagnosis of precancer occurring in epithelial tissue at endoscopy.

Development of a multiplexing fingerprint and high wavenumber Raman spectroscopy technique for real-time in vivo tissue Raman measurements at endoscopy.

We report on the development of a novel multiplexing Raman spectroscopy technique using a single laser light together with a volume phase holographic (VPH) grating that simultaneously acquires both fingerprint (FP) and high wavenumber (HW) tissue Raman spectra at endoscopy. We utilize a customized VPH dual-transmission grating, which disperses the incident Raman scattered light vertically onto two separate segments (i.e., -150 to 1950 cm⁻¹; 1750 to 3600 cm⁻¹) of a charge-coupled device camera. We demonstrate that the multiplexing Raman technique can acquire high quality in vivo tissue Raman spectra ranging from 800 to 3600 cm⁻¹ within 1.0 s with a spectral resolution of 3 to 6 cm⁻¹ during clinical endoscopy. The rapid multiplexing Raman spectroscopy technique covering both FP and HW ranges developed in this work has potential for improving in vivo tissue diagnosis and characterization at endoscopy.

Fiber-optic Raman spectroscopy probes gastric carcinogenesis in vivo at endoscopy.

Intestinal-type gastric carcinogenesis is a complex multi-step disease, and early precursors (e.g. intestinal metaplasia (IM), dysplasia) can be very challenging to identify using conventional white-light endoscopic imaging. This study aims to assess the capability of Raman spectroscopy for multi-class elucidation of intestinal-type gastric carcinogenesis sequence in vivo for improving precancer detection at endoscopy. We employ a novel image-guided Raman endoscopy technique developed for in vivo gastric tissue Raman measurement within 0.5 s during clinical endoscopic examination. We have acquired a total of 1277 in vivo Raman spectra from 83 gastric patients associated with intestinal-type carcinogenesis. In vivo Raman spectroscopy integrated with semi-quantitative spectral modelling (e.g. DNA, lipids, glycoprotein, proteins and blood) reveals the progressive changes of biochemical constituents in gastric tissue associated with preneoplastic and neoplastic transformation (i.e., IM, dysplasia and adenocarcinoma). Multi-class probabilistic partial least squares-discriminant analysis (PLS-DA) diagnostic algorithms based on in vivo Raman spectra are able to identify normal mucosa with sensitivity of 75.88% and specificity of 87.21%; IM with sensitivity of 46.67% and specificity of 87.55%; dysplasia with sensitivity of 83.33%; specificity of 95.80%, and adenocarcinoma with sensitivity of 84.91% and specificity 95.57%, respectively. This work demonstrates that Raman spectroscopy is a sensitive biomolecular probe for monitoring intestinal-type gastric carcinogenesis to realize early diagnosis and detection of precancer and early gastric cancer in vivo during clinical endoscopic examination.

In vivo, real-time, transnasal, image-guided Raman endoscopy: defining spectral properties in the nasopharynx and larynx.

We report for the first time the implementation of transnasal, image-guided Raman endoscopy to directly assess Raman spectral properties of nasopharyngeal and laryngeal tissue in vivo during clinical endoscopic examinations. A rapid 785-nm excitation Raman endoscopy system, coupled with a miniaturized fiber-optic Raman probe, was utilized for real-time, in vivo Raman measurements of different anatomical locations in the head and neck. A total of 874 high-quality in vivo Raman spectra were successfully acquired from different anatomic locations of the nasopharynx and larynx [i.e., posterior nasopharynx (PN) (n=521), the fossa of Rosenmüller (FOR) (n=157), and true laryngeal vocal chords (LVC) (n=196)] in 23 normal subjects at transnasal endoscopy. Difference spectra and principal component analysis (PCA) were employed for tissue characterization, uncovering the tissue variability at the biomolecular level. The PCA-linear discriminant analysis (LDA) provides sensitivity of 77.0% and specificity of 89.2% for differentiation between PN and FOR, and sensitivity of 68.8% and specificity of 76.0% for distinguishing LVC and PN using the leave-one-subject-out, cross-validation method. This work demonstrates that transnasal, image-guided Raman endoscopy can be used to acquire in vivo Raman spectra from the nasopharynx and larynx in real time. Significant Raman spectral differences (p<0.05) identified as reflecting the distinct composition and morphology in the nasopharynx and larynx should be considered to be important parameters in the interpretation and rendering of diagnostic decision algorithms for in vivo tissue diagnosis and characterization in the head and neck.

Diagnosis of early stage nasopharyngeal carcinoma using ultraviolet autofluorescence excitation-emission matrix spectroscopy and parallel factor analysis.

We report the diagnostic ability of ultraviolet (UV)-excited autofluorescence (AF) excitation-emission matrix (EEM) spectroscopy associated with parallel factor (PARAFAC) analysis for differentiating cancer from normal nasopharyngeal tissue. A bifurcated fiber-optic probe coupled with an EEM system was used to acquire tissue AF EEMs using excitation wavelengths between 260 and 400 nm, and emission collection between 280 and 500 nm. A total of 152 AF EEM landscapes were acquired from 13 normal and 16 nasopharyngeal carcinoma (NPC) thawed ex vivo tissue samples from 23 patients. PARAFAC was introduced for curve resolution of individual AF EEM landscapes associated with the endogenous tissue constituents. The significant factors were further fed to a support vector machine (SVM) and cross-validated to construct diagnostic algorithms. Both the EEM intensity landscapes and the PARAFAC model revealed tryptophan, collagen, and elastin to be the three major endogenous fluorophores responsible for the AF signal from normal and NPC tissues. The EEM intensity distribution and PARAFAC factors suggest an increase of tryptophan and a decrease of collagen and elastin in NPC tissues compared to the normal. The classification results obtained from the PARAFAC-SVM modeling yielded a diagnostic accuracy of 94.7% (sensitivity of 95.0% (76/80); specificity of 94.4% (68/72)) for normal and NPC tissue differentiation. This study suggests that UV-excited AF EEM spectroscopy integrated with PARAFAC algorithms has the potential to provide clinical diagnostics of early onset and progression of NPC.

Combining near-infrared-excited autofluorescence and Raman spectroscopy improves in vivo diagnosis of gastric cancer.

This study aims to evaluate the diagnostic utility of the combined near-infrared (NIR) autofluorescence (AF) and Raman spectroscopy for improving in vivo detection of gastric cancer at clinical gastroscopy. A rapid Raman endoscopic technique was employed for in vivo spectroscopic measurements of normal (n=1098) and cancer (n=140) gastric tissues from 81 gastric patients. The composite NIR AF and Raman spectra in the range of 800-1800 cm(-1) were analyzed using principal component analysis (PCA) and linear discriminant (LDA) to extract diagnostic information associated with distinctive spectroscopic processes of gastric malignancies. High quality in vivo composite NIR AF and Raman spectra can routinely be acquired from the gastric within 0.5s. The integrated intensity over the range of 800-1800 cm(-1) established the diagnostic implications (p=1.6E-14) of the change of NIR AF intensity associated with neoplastic transformation. PCA-LDA diagnostic modeling on the in vivo tissue NIR AF and Raman spectra acquired yielded a diagnostic accuracy of 92.2% (sensitivity of 97.9% and specificity of 91.5%) for identifying gastric cancer from normal tissue. The integration area under the receiver operating characteristic (ROC) curve using the combined NIR AF and Raman spectroscopy was 0.985, which is superior to either the Raman spectroscopy or NIR AF spectroscopy alone. This work demonstrates that the complementary Raman and NIR AF spectroscopy techniques can be integrated together for improving the in vivo diagnosis and detection of gastric cancer at endoscopy.

Characterizing variability in in vivo Raman spectra of different anatomical locations in the upper gastrointestinal tract toward cancer detection.

Raman spectroscopy is an optical vibrational technology capable of probing biomolecular changes of tissue associated with cancer transformation. This study aimed to characterize in vivo Raman spectroscopic properties of tissues belonging to different anatomical regions in the upper gastrointestinal (GI) tract and explore the implications for early detection of neoplastic lesions during clinical gastroscopy. A novel fiber-optic Raman endoscopy technique was utilized for real-time in vivo tissue Raman measurements of normal esophageal (distal, middle, and proximal), gastric (antrum, body, and cardia) as well as cancerous esophagous and gastric tissues from 107 patients who underwent endoscopic examinations. The non-negativity-constrained least squares minimization coupled with a reference database of Raman active biochemicals (i.e., actin, histones, collagen, DNA, and triolein) was employed for semiquantitative biomolecular modeling of tissue constituents in the upper GI. A total of 1189 in vivo Raman spectra were acquired from different locations in the upper GI. The Raman spectra among the distal, middle, and proximal sites of the esophagus showed no significant interanatomical variability. The interanatomical variability of Raman spectra among normal gastric tissue (antrum, body, and cardia) was subtle compared to cancerous tissue transformation, whereas biomolecular modeling revealed significant differences between the two organs, particularly in the gastroesophageal junction associated with proteins, DNA, and lipids. Cancerous tissues can be identified across interanatomical regions with accuracies of 89.3% [sensitivity of 92.6% (162∕175); specificity of 88.6% (665∕751)], and of 94.7% [sensitivity of 90.9% (30∕33); specificity of 93.9% (216∕230)] in the gastric and esophagus, respectively, using partial least squares-discriminant analysis together with the leave-one tissue site-out, cross validation. This work demonstrates that Raman endoscopy technique has promising clinical potential for real-time, in vivo diagnosis and detection of malignancies in the upper GI at the molecular level.

In vivo diagnosis of gastric cancer using Raman endoscopy and ant colony optimization techniques.

This study aims to evaluate the clinical utility of image-guided Raman endoscopy for in vivo diagnosis of neoplastic lesions in the stomach at gastroscopy. A rapid-acquisition image-guided Raman endoscopy system with 785-nm excitation has been developed to acquire in vivo gastric tissue Raman spectra within 0.5 sec during clinical gastroscopic examinations. A total of 1,063 in vivo Raman spectra were acquired from 238 tissue sites of 67 gastric patients, in which 934 Raman spectra were from normal tissue whereas 129 Raman spectra were from neoplastic gastric tissue. The swarm intelligence-based algorithm (i.e., ant colony optimization (ACO) integrated with linear discriminant analysis (LDA)) was developed for spectral variables selection to identify the biochemical important Raman bands for differentiation between normal and neoplastic gastric tissue. The ACO-LDA algorithms together with the leave-one tissue site-out, cross validation method identified seven diagnostically important Raman bands in the regions of 850-875, 1,090-1,110, 1,120-1,130, 1,170-1,190, 1,320-1,340, 1,655-1,665 and 1,730-1,745 cm(-1) related to proteins, nucleic acids and lipids of tissue and provided a diagnostic sensitivity of 94.6% and specificity of 94.6% for distinction of gastric neoplasia. The predictive sensitivity of 89.3% and specificity of 97.8% were also achieved for an independent test validation dataset (20% of total dataset). This work demonstrates for the first time that the real-time image-guided Raman endoscopy associated with ACO-LDA diagnostic algorithms has potential for the noninvasive, in vivo diagnosis and detection of gastric neoplasia during clinical gastroscopy.

Raman endoscopy for in vivo differentiation between benign and malignant ulcers in the stomach.

The aim of this study was to evaluate the clinical utility of an image-guided Raman endoscopy technique for in vivo differential diagnosis of benign and malignant ulcerous lesions in the stomach. A rapid-acquisition image-guided Raman endoscopy system with 785 nm laser excitation has been developed to acquire in vivo gastric tissue Raman spectra within 0.5 s during clinical gastroscopic examinations. A total of 1102 in vivo Raman spectra were acquired from 71 gastric patients, in which 924 Raman spectra were from normal tissue, 111 Raman spectra were from benign ulcers whereas 67 Raman spectra were from ulcerated adenocarcinoma. There were distinctive spectral differences in Raman spectra among normal mucosa, benign ulcers and malignant ulcers, particularly in the spectral ranges of 800-900, 1000-1100, 1245-1335, 1440-1450 and 1500-1800 cm(-1), which primarily contain signals related to proteins, DNA, lipids and blood. The malignant ulcerous lesions showed Raman signals to be mainly associated with abnormal nuclear activity and decrease in lipids as compared to benign ulcers. Partial least squares-discriminant analysis (PLS-DA) was employed to generate multi-class diagnostic algorithms for classification of Raman spectra of different gastric tissue types. The PLS-DA algorithms together with leave-one tissue site-out, cross validation technique yielded diagnostic sensitivities of 90.8%, 84.7%, 82.1%, and specificities of 93.8%, 94.5%, 95.3%, respectively, for classification of normal mucosa, benign and malignant ulcerous lesions in the stomach. This work demonstrates that image-guided Raman endoscopy technique associated with PLS-DA diagnostic algorithms has for the first time promising clinical potential for rapid, in vivo diagnosis and detection of malignant ulcerous gastric lesions at the molecular level.

In vivo early diagnosis of gastric dysplasia using narrow-band image-guided Raman endoscopy.

We first report on the implementation of a novel narrow-band image-guided Raman endoscopy technique for in vivo diagnosis of gastric dysplasia. High-quality in vivo Raman spectra can be acquired from normal and dysplastic gastric mucosal tissue within 0.5 sec under narrow-band image (NBI) guidance at gastroscopy. Significant differences are observed in in vivo Raman spectra between normal (n=54) and dysplastic (n=18) gastric tissue from 30 gastric patients, particularly in the spectral ranges of 825 to 950, 1000 to 1100, 1250 to 1500, and 1600 to 1800 cm(-1), which primarily contain signals related to proteins, nucleic acids, and lipids. The multivariate analysis [i.e., principal components analysis (PCA) and linear discriminant analysis (LDA)], together with the leave-one tissue site-out, cross validation on in vivo gastric Raman spectra yields a diagnostic sensitivity of 94.4% (1718) and specificity of 96.3% (5254) for distinction of gastric dysplastic tissue. This study suggests that narrowband image-guided Raman endoscopy associated with PCA-LDA diagnostic algorithms has potential for the noninvasive, in vivo early diagnosis and detection of gastric precancer during clinical gastroscopic examination.