Jaidip Jagtap

Probing multifractality in tissue refractive index: prospects for precancer detection

Multiresolution analysis on the spatial refractive index inhomogeneities in the epithelium and connective tissue regions of a human cervix reveals a clear signature of multifractality. Importantly, the derived multifractal parameters, namely, the generalized Hurst exponent and the width of the singularity spectrum, derived via multifractal detrended fluctuation analysis, shows interesting differences between tissues having different grades of precancers. The refractive-index fluctuations are found to be more anticorrelated, and the strength of multifractality is observed to be considerably stronger in the higher grades of precancers. These observations on the multifractal nature of tissue refractive-index variations may prove to be valuable for developing light-scattering approaches for noninvasive diagnosis of precancer and early-stage cancer.

Quantitative Mueller matrix fluorescence spectroscopy for precancer detection

Quantitative fluorescence spectroscopic Mueller matrix measurements from the connective tissue regions of human cervical tissue reveal intriguing fluorescence diattenuation and polarizance effects. Interestingly, the estimated fluorescence linear diattenuation and polarizance parameters were considerably reduced in the precancerous tissues as compared to the normal ones. These polarimetry effects of the autofluorescence were found to originate from anisotropically organized collagen molecular structures present in the connective tissues. Consequently, the reduction of the magnitude of these polarimetric parameters at higher grades of precancer was attributed to the loss of anisotropic organization of collagen, which was also confirmed by control experiments. These results indicate that fluorescence spectral diattenuation and polarizance parameters may serve as potentially useful diagnostic metrics.

Differing self-similarity in light scattering spectra: a potential tool for pre-cancer detection

The fluctuations in the elastic light scattering spectra of normal and dysplastic human cervical tissues analyzed through wavelet transform based techniques reveal clear signatures of self-similar behavior in the spectral fluctuations. The values of the scaling exponent observed for these tissues indicate the differences in the self-similarity for dysplastic tissues and their normal counterparts. The strong dependence of the elastic light scattering on the size distribution of the scatterers manifests in the angular variation of the scaling exponent. Interestingly, the spectral fluctuations in both these tissues showed multi-fractality (non-stationarity in fluctuations), the degree of multi-fractality being marginally higher in the case of dysplastic tissues. These findings using the multi-resolution analysis capability of the discrete wavelet transform can contribute to the recent surge in the exploration for non-invasive optical tools for pre-cancer detection.

Mueller matrix polarimetry in fluorescence scattering from biological tissues

Mueller matrix polarimetric investigation of normal and diseased human cervical tissue samples in fluorescence scattering yields the possibility of early detection of the disease and a novel probe to monitor morphological changes during disease progression.

Methods for detecting host genetic modifiers of tumor vascular function using dynamic near-infrared fluorescence imaging

Vascular supply is a critical component of the tumor microenvironment (TME) and is essential for tumor growth and metastasis, yet the endogenous genetic modifiers that impact vascular function in the TME are largely unknown. To identify the host TME modifiers of tumor vascular function, we combined a novel genetic mapping strategy [Consomic Xenograft Model] with near-infrared (NIR) fluorescence imaging and multiparametric analysis of pharmacokinetic modeling. To detect vascular flow, an intensified cooled camera based dynamic NIR imaging system with 785 nm laser diode based excitation was used to image the whole-body fluorescence emission of intravenously injected indocyanine green dye. Principal component analysis was used to extract the spatial segmentation information for the lungs, liver, and tumor regions-of-interest. Vascular function was then quantified by pK modeling of the imaging data, which revealed significantly altered tissue perfusion and vascular permeability that were caused by host genetic modifiers in the TME. Collectively, these data demonstrate that NIR fluorescent imaging can be used as a non-invasive means for characterizing host TME modifiers of vascular function that have been linked with tumor risk, progression, and response to therapy.

Vascular Interventional Radiology Guided Photothermal Therapy of Colorectal Cancer Liver Metastasis with Theranostic Gold Nanorods

We report sub-100 nm optical/magnetic resonance (MR)/X-ray contrast-bearing theranostic nanoparticles (TNPs) for interventional image-guided photothermal therapy (PTT) of solid tumors. TNPs were composed of Au@Gd2O3:Ln (Ln = Yb/Er) with X-ray contrast (∼486 HU; 1014 NPs/mL, 0.167 nM) and MR contrast (∼1.1 × 108 mM-1 S-1 at 9.4 T field strength). Although TNPs are deposited in tumors following systemic administration via enhanced permeation and retention effect, the delivered dose to tumors is typically low; this can adversely impact the efficacy of PTT. To overcome this limitation, we investigated the feasibility of site-selective hepatic image-guided delivery of TNPs in rats bearing colorectal liver metastasis (CRLM). The mesenteric vein of tumor-bearing rats was catheterized, and TNPs were infused into the liver by accessing the portal vein for site-selective delivery. The uptake of TNPs with hepatic delivery was compared with systemic administration. MR imaging confirmed that delivery via the hepatic portal vein can double the CRLM tumor-to-liver contrast compared with systemic administration. Photothermal ablation was performed by inserting a 100 μm fiber-optic carrying 808 nm light via a JB1, 3-French catheter for 3 min under DynaCT image guidance. Histological analysis revealed that the thermal damage was largely confined to the tumor region with minimal damage to the adjacent liver tissue. Transmission electron microscopy imaging validated the stability of core-shell structure of TNPs in vivo pre- and post-PTT. TNPs comprising Gd-shell-coated Au nanorods can be effectively employed for the site-directed PTT of CRLM by leveraging interventional radiology methods.

Effective Screening and Classification of Cervical Precancer Biopsy Imagery

Microscope images of biopsy samples of cervical precancers conventionally discriminated by histopathology, the current “gold standard” for cancer detection, showed that their correlation properties are segregated into different classes. The correlation domains clearly indicate increasing cellular clustering in different grades of precancer compared with their normal counterparts. This trend indicates the probability of pixel distribution of the corresponding tissue images. Because the cell density is not uniform in the higher grades, the skewness (asymmetry of a distribution), kurtosis (sharpness of a distribution), entropy (randomness), and standard deviation are affected. A combination of these parameters effectively improves the diagnosis and quantitatively classifies the normal and all the three grades of precancerous cervical tissue sections significantly. Thus, the statistical analysis of microscope images is a promising approach for early stage tumor detection and quantitative classification of precancerous grades; this can effectively supplement the qualitative analysis by the pathologist.

Study and Discrimination of Human Cervical Tissue Images through Multifractal Analysis

We report here a study of confocal microscope images to classify cervical precancers by a multifractal analysis. This study is performed using an inverted confocal microscope with laser scanning fluorescence imaging. The periodic structure of collagen present in the stromal region of cervical tissue gets disordered with progress in grade of dysplasia. This disorder is investigated through the β-exponent of a Discrete Fourier Transform (DFT) of the confocal images, enabling us to discriminate between the lowest and highest grades of dysplasia in human cervical tissue sections. The Holder exponent from 2D images further classifies various grades of dysplasia from normal tissue sections though Gd3 and Gd1 are indistinguishable. DFT however, clearly distinguishes Gd3 from Gd1. In addition to stromal images, epithelial images were also investigated for better classification. The cellular density of epithelium increases with depth for various grades of dysplasia and is not uniform. The Holder exponent, which measures multifractality, is higher for dysplastic tissue sections than for normal ones because of the above morphological differences. Extraction of subtle fluctuations from optical images through multifractal studies promise to be a powerful diagnostic technique.

PCA based polarized fluorescence study for detecting human cervical dysplasia

The two highest principal components of fluorescence spectra in visible region obtained, using Xenon lamp as an excitation source of normal and dysplastic human cervical tissues are analyzed using scatter plots and probability density functions. These yield significant differences between the tissue types.

Grading of Cervical Intraepithelial Neoplasia Using Spatial Frequency for Optical Histology

It is important to detect cervical dysplasia, Cervical Intraepithelial Neoplasia (CIN). CIN is the potentially premalignant and abnormal squamous cells on surface of cervix. In this study, the spatial frequency spectra of pre-cancer cervical tissues are used to detect differences among different grades of human cervical tissues. Seven sets of thick tissue sections of human cervix of normal, CIN 1, CIN 2, and CIN 3 tissues are studied. The confocal microscope images of the stromal region of normal and CIN human tissues were analyzed using Fast Fourier Transform (FFT) to generate the spatial spectra. It is observed that higher frequency components exist in CIN tissues than those in normal tissue, as well as those in higher grade CIN tissue than those in lower grade CIN tissue. The width of the spatial frequency of different types of tissues is used to create a criterion for CIN grading by training a support vector machine (SVM) classifier. The results show that the randomness of tissue structures from normal to different stages of precancer in cervical tissue can be recognized by fingerprints of the spatial frequency. The efficacy of spatial frequency analysis for CIN grading is evaluated as excellent since high AUC (area under the ROC curve), sensitivity and specificity are obtained by the statistics study. This works lays the foundation of using spatial frequency spectra for a histology evaluation.