BackgroundStrong proof-of-principle for utilisation of diffuse reflectance spectroscopy, a non-invasive tool for early detection of malignant changes, has emerged recently. The potential of this technique in distinguishing normal tissue from hyperplastic and dysplastic tissues was explored.MethodsDiffuse reflectance (DR) spectra in the 400–700 nm region were obtained from the buccal mucosa of 96 patients and 34 healthy volunteers. The DR spectral data were compared against the gold standard biopsy and histopathology results. A principal-component analysis was performed for dimensional reduction in the normalised spectral data with linear discriminant analysis as the classifying technique. The receiver operator characteristic curve technique was employed for evaluating the performance of the diagnostic test.ResultsDR spectral features for different lesions, such as normal/healthy, hyperplastic, dysplastic and squamous cell carcinoma (SCC), varied significantly according to the intensity of oxygenated haemoglobin absorption. While the classification based on discriminant scores provided an overall sensitivity of 98.5% and specificity of 96.0% for distinguishing SCC from dysplasia, they were 100.0% and 95.0%, respectively, for distinguishing dysplasia from hyperplasia. Similarly, the analysis yielded a sensitivity of 95.0% and specificity of 100.0% for distinguishing hyperplasia from healthy tissue. The areas under the receiver operator characteristic curves were 0.98 (95% CI 0.95 to 1.00) and 0.95 (95% CI 0.90 to 1.00) for distinguishing dysplasia from SCC and hyperplasia from dysplasia, respectively.ConclusionDR spectral data efficiently discriminate healthy tissue from oral malignant lesions. Diagnostic accuracies obtained in this study highlight the potential use of this method for routine clinical practice.

The application of LDA-LOO method on the autofluorescence spectra recorded during a clinical trial in patients was found suitable to discriminate oral mucosal alterations during tissue transformation towards malignancy with improved diagnostic accuracies.

BackgroundDiffusely reflected light is influenced by cytologic and morphologic changes that take place during tissue transformation, such as, nuclear changes, extracellular matrix structure and composition as well as blood flow. Albeit with varying degree of sensitivity and specificity, the properties of diffusely reflected light in discriminating a variety of oral lesions have been demonstrated by our group in multiple studies using point monitoring systems. However, the point monitoring system could not identify the region with the most malignant potential in a single sitting.MethodsIn order to scan the entire lesion, we developed a multi-spectral imaging camera system that records diffuse reflectance (DR) images of the oral lesion at 545 and 575 nm with white light illumination. The diagnostic accuracy of the system for 2-dimensional DR imaging of pre-malignant and malignant changes in the oral cavity was evaluated through a clinical study in 55 patients and 23 healthy volunteers. The DR imaging data were compared with gold standard tissue biopsy and histopathology results.ResultsIn total 106- normal/clinically healthy sites, 20- pre-malignant and 29- malignant (SCC) sites were compared. While the median pixel value of the R545/R575 image ratio for normal/clinically healthy tissue was 0.87 (IQR = 0.82-0.94), they were 1.35 (IQR = 1.13-1.67) and 2.44 (IQR = 1.78-3.80) for pre-malignant and malignant lesions, respectively. Area under the ROC curve to differentiate malignant from normal/clinically healthy [AUC = 0.99 (95% CI: 0.99-1.00)], pre-malignant from normal/clinically healthy [AUC = 0.94 (95% CI: 0.86-1.00)], malignant from pre-malignant [AUC = 0.84 (95% CI: 0.73-0.95)] and pre-malignant and malignant from normal/clinically healthy [AUC = 0.97 (95% CI: 0.94-1.00)] lesions were desirable.ConclusionWe find DR imaging to be very effective as a screening tool in locating the potentially malignant areas of oral lesions with relatively good diagnostic accuracy while comparing it to the gold standard histopathology.

Autofluorescence (AF) and diffuse reflectance (DR) spectroscopic techniques have shown good diagnostic accuracies for noninvasive detection of oral cavity cancer. In the present study, AF and DR spectra recorded in vivo from the same set of sites in 65 patients were analyzed using Principal component analysis (PCA) and linear discriminant analysis (LDA). The effectiveness of these two techniques was assessed by comparison with gold standard and their discrimination efficiency was determined from the area under the receiver operator characteristic (AUC-ROC) curve. Analysis using a DR technique shows a higher AUC-ROC of 0.991 as against 0.987 for AF spectral data.

We present the clinical applicability of fluorescence ratio reference standard (FRRS) to discriminate different stages of dental caries. Toward this, laser-induced autofluorescence emission spectra are recorded in vivo in the 400- to 800-nm spectral range on a miniature fiber optic spectrometer from 65 patients, with a 404-nm diode laser as the excitation source. Autofluorescence spectra of sound teeth consist of a broad emission at 500 nm that is typical of natural enamel, whereas in caries teeth additional peaks are seen at 635 and 680 nm due to emission from porphyrin compounds in oral bacteria. Scatter plots are developed to differentiate sound teeth from enamel caries, sound teeth from dentinal caries, and enamel caries from dentinal caries using the mean fluorescence intensity (FI) and ratios F500F635 and F500F680 measured from 25 sites of sound teeth and 65 sites of carious teeth. The sensitivity and specificity of both the FI and FRRS are determined. It is observed that a diagnostic algorithm based on FRRS scatter plots is able to discriminate enamel caries from sound teeth, dentinal caries from sound teeth, and enamel from dentinal caries with overall sensitivities of 85, 100, and 88% and specificities of 90, 100, and 77%, respectively.

Diffuse reflectance (DR) spectroscopy is a non-invasive, real-time, and cost-effective tool for early detection of malignant changes in squamous epithelial tissues. The present study aims to evaluate the diagnostic power of diffuse reflectance spectroscopy for non-invasive discrimination of cervical lesions in vivo. A clinical trial was carried out on 48 sites in 34 patients by recording DR spectra using a point-monitoring device with white light illumination. The acquired data were analyzed and classified using multivariate statistical analysis based on principal component analysis (PCA) and linear discriminant analysis (LDA). Diagnostic accuracies were validated using random number generators. The receiver operating characteristic (ROC) curves were plotted for evaluating the discriminating power of the proposed statistical technique. An algorithm was developed and used to classify non-diseased (normal) from diseased sites (abnormal) with a sensitivity of 72 % and specificity of 87 %. While low-grade squamous intraepithelial lesion (LSIL) could be discriminated from normal with a sensitivity of 56 % and specificity of 80 %, and high-grade squamous intraepithelial lesion (HSIL) from normal with a sensitivity of 89 % and specificity of 97 %, LSIL could be discriminated from HSIL with 100 % sensitivity and specificity. The areas under the ROC curves were 0.993 (95 % confidence interval (CI) 0.0 to 1) and 1 (95 % CI 1) for the discrimination of HSIL from normal and HSIL from LSIL, respectively. The results of the study show that DR spectroscopy could be used along with multivariate analytical techniques as a non-invasive technique to monitor cervical disease status in real time.

Hydrocarbon fluid inclusions (HCFIs) in mineral grains of source, reservoir, or carrier rocks are of particular interest to the petroleum industry. The minute size of HCFIs warrants a combination of microscopy and spectroscopy for identification and characterization. This article presents fluorescence emission data of pure petroleum oils of known American Petroleum Institute’s gravities (APIG) and proposes an empirical tool for predicting the APIG of oils in micron-sized HCFIs through a noninvasive, nondestructive procedure using microscopy-based fluorescence estimates. It also documents how this empirical tool could be used as a way of inferring the APIG in HCFIs by considering the samples from RV-1 well (Mumbai offshore basin, India) as an example. RV-1 is a nonproducing well from the Mumbai offshore basin, India with proven commercial productivity. Fluorescence emission of 13 crude oil samples with known API gravities were recorded using a diode laser excited at 405 nm in order to estimate the API gravity values of oils trapped as HCFIs. The gathered fluorescence data were fitted in a Gaussian distribution to identify unique emission peaks (i.e., around 500, 560, and 620 nm). Bivariate scatterogram with a smooth line fit using spectral ratio at F620/F560 versus API gravity of crude oil provided a classificatory scheme or an API gravity predictor of oils in hydrocarbon fluid inclusions. Fluorescence emission of oil in HCFIs were recorded in the region of 406–720 nm using the microscopy-based fluorescence technique, and the calculated spectral emission ratios at F620/F560 are given in the scatter plot of API gravity known oils. The APIG of unknown samples (whether they be HCFI’s or otherwise) can be inferred from the algebraic expression linking emission spectra to APIG for known crude oil samples. The methodology developed is reliable in deriving an accurate API (by reference to the calibration of crude oils) so as to estimate the API gravities of minute-sized oil samples in HCFIs and therefore could prove to be a useful tool in the petroleum exploration and industry.

The potential of laser-induced fluorescence (LIF) spectroscopy for the characterization of different stages of dental caries using 404-nm diode laser excitation was investigated. In vitro spectra from 16 sound, 10 noncavitated carious and 10 cavitated carious molar teeth were recorded on a miniature fibre-optic spectrometer. The areas under the receiver operating characteristics (ROC-AUC) were calculated and one-way analysis of variance (ANOVA) was performed. The LIF spectra of the carious teeth showed two peaks at 635 and 680 nm in addition to a broad band seen at 500 nm in sound teeth. The fluorescence intensity ratios, F500/F635 and F500/F680, in carious teeth were always lower than those in sound teeth. The ROC-AUC for discriminating between carious and sound teeth was 0.94, and for discriminating between noncavitated and cavitated carious teeth was 0.87. Statistically significant differences (p<0.001) were seen between sound, noncavitated carious and cavitated carious teeth. The results showed that LIF spectroscopy has the potential to be useful for characterizing different stages of caries in a clinical setting.