Grades Of Precancers Research Articles

Scanning darkfield high-resolution microendoscope for label-free microvascular imaging.

Characterization of microvascular changes during neoplastic progression has the potential to assist in discriminating precancer and early cancer from benign lesions. Here, we introduce a novel high-resolution microendoscope that leverages scanning darkfield reflectance imaging to characterize angiogenesis without exogenous contrast agents. Scanning darkfield imaging is achieved by coupling programmable illumination with a complementary metal-oxide semiconductor (CMOS) camera rolling shutter, eliminating the need for complex optomechanical components and making the system portable, low-cost (<$5,500) and simple to use. Imaging depth is extended by placing a gradient-index (GRIN) lens at the distal end of the imaging fiber to resolve subepithelial microvasculature. We validated the capability of the scanning darkfield microendoscope to visualize microvasculature at different anatomic sites in vivo by imaging the oral cavity of healthy volunteers. Images of cervical specimens resected for suspected neoplasia reveal distinct microvascular patterns in columnar and squamous epithelium with different grades of precancer, indicating the potential of scanning darkfield microendoscopy to aid in efforts to prevent cervical cancer through early diagnosis.

Two dimensional multifractal detrended fluctuation analysis of low coherence images for diagnosis of cervical pre-cancer

We report detection of cervical pre-cancer through their low coherence images by applying two dimensional multifractal detrended fluctuation analysis. Low coherent backscattered images of pre-cancerous cervical tissue sections were captured using a common path interferometric setup. The captured images contain both depth and lateral information of the spatial variation in refractive index (RI) occurring with progression of cervical pre-cancer. A two-dimensional multifractal detrended fluctuation analysis (2D MFDFA) was applied on these low coherent images to study the variations occurring in their fractal nature. Long-range correlations were observed in the RI fluctuations and the strength of multifractality was found to be stronger for higher grades of cervical pre-cancer. A combination of derived multifractal parameters, namely, the generalized Hurst exponent and width of singularity spectrum showed clear differences among the different grades of pre-cancers. Normal, CIN-I and CIN-II were clearly discriminated by application of support vector machine (SVM) using radial Bessel function (RBF) kernel. The specificities and sensitivities between normal and CIN-I, CIN-I and CIN-II and normal and CIN-II were found to be 94%, 88% and 93%, 96% and 98%, 100% respectively.

Probing multifractality in depth-resolved refractive index fluctuations in biological tissues using backscattering spectral interferometry

Fourier domain low coherence interferometry is a promising method for quantification of the depth distribution of the refractive index in a layered scattering medium such as biological tissue. Here, we have explored backscattering spectral interferometric measurement in combination with multifractal detrended fluctuation analysis to probe and quantify multifractality in depth distribution of the refractive index in tissue. The depth resolution of the experimental system was validated on model systems comprising of polystyrene microspheres and mica sheet, and was initially tested on turbid collagen layer, the main building blocks of the connective tissue. Following successful evaluation, the method was applied on ex vivo tissues of human cervix. The derived multifractal parameters of depth-resolved index fluctuations of tissue, namely, the generalized Hurst exponent and the width of the singularity spectrum showed interesting differences between tissues having different grades of precancers. The depth-resolved index fluctuations exhibited stronger multifractality with increasing pathological grades, demonstrating its promise as a potential biomarker for precancer detection.

Detecting cervical cancer progression through extracted intrinsic fluorescence and principal component analysis.

Intrinsic fluorescence spectra of the human normal, cervical intraepithelial neoplasia 1 (CIN1), CIN2, and cervical cancer tissue have been extracted by effectively combining the measured polarized fluorescence and polarized elastic scattering spectra. The efficacy of principal component analysis (PCA) to disentangle the collective behavior from smaller correlated clusters in a dimensionally reduced space in conjunction with the intrinsic fluorescence is examined. This combination unambiguously reveals the biochemical changes occurring with the progression of the disease. The differing activities of the dominant fluorophores, collagen, nicotinamide adenine dinucleotide, flavins, and porphyrin of different grades of precancers are clearly identified through a careful examination of the sectorial behavior of the dominant eigenvectors of PCA. To further classify the different grades, the Mahalanobis distance has been calculated using the scores of selected principal components.