Tissue multifractality and Born approximation in analysis of light scattering: a novel approach for precancers detection

Quantifying multifractal anisotropy in two dimensional objects

An efficient method of exploring the effects of anisotropy in the fractal properties of 2D surfaces and images is proposed. It can be viewed as a direction-sensitive generalization of the multifractal detrended fluctuation analysis into 2D. It is tested on synthetic structures to ensure its effectiveness, with results indicating consistency. The interdisciplinary potential of this method in describing real surfaces and images is demonstrated, revealing previously unknown directional multifractality in data sets from the Martian surface and the Crab Nebula. The multifractal characteristics of Jackson Pollock's paintings are also analyzed. The results point to their evolution over the time of creation of these works.

Characterizing stroke-induced changes in the variability of lower limb kinematics using multifractal detrended fluctuation analysis

Movement variability reflects the adaptation of the neuromuscular control system to internal or external perturbations, but its relationship to stroke-induced injury is still unclear. In this study, the multifractal detrended fluctuation analysis was used to explore the stroke-induced changes in movement variability by analyzing the joint angles in a treadmill-walking task. Eight healthy subjects and ten patients after stroke participated in the experiment, performing a treadmill-walking task at a comfortable speed. The kinematics data of the lower limbs were collected by the motion-capture system, and two indicators, the degree of multifractality (α) and degree of correlation [h(2)], were used to investigate the mechanisms underlying neuromuscular control. The results showed that the knee and ankle joint angles were multifractal and persistent at various scales, and there was a significant difference in the degree of multifractality and the degree of correlation at the knee and ankle joint angles among the three groups, with the values being ranked in the following order: healthy subjects < non-paretic limb < paretic limb. These observations highlighted increased movement variability and multifractal strength in patients after stroke due to neuromotor defects. This study provided evidence that multifractal detrended analysis of the angles of the knee and ankle joints is useful to investigate the changes in movement variability and multifractal after stroke. Further research is needed to verify and promote the clinical applications.

Fluorescence scattering in between excitation and emission as a depolarizing process: a Mueller matrix viewpoint

A rigorous model has been proposed to qualify fluorescence scattering through the Mueller matrix viewpoint in terms of absorption/excitation, emission, and the process in between them. The process in between the excitation and emission processes of fluorescence, irrespective of the scattering directions, has been modeled as a depolarization process. The absorption/excitation of the fluorophore molecules gets revealed through the first-row elements while the emission of fluorescence has been observed through the first column elements of the fluorescence Mueller matrix. Information of the transitions between the molecular ground and excited states gets encoded into the diagonal elements following the photon selection rule. The other off-diagonal elements of the fluorescence Mueller matrix also exhibit very small nonzero values due to the anisotropic absorption and phase changes that the ground state of the fluorophore molecules imposes on the incident polarized beam while parallelly governing the emitted beam. The comparison of the current model with the earlier model has been discussed in a detailed way. The modeling of the in-between process as the depolarizing one enables us to qualify the fluorescence detected linear and circular dichroism and luminescence and very effectively overcomes the shortcomings in the earlier model.

Engineered Living Hydrogels

Living biological systems, ranging from single cells to whole organisms, can sense, process information, and actuate in response to changing environmental conditions. Inspired by living biological systems, engineered living cells and nonliving matrices are brought together, which gives rise to the technology of engineered living materials. By designing the functionalities of living cells and the structures of nonliving matrices, engineered living materials can be created to detect variability in the surrounding environment and to adjust their functions accordingly, thereby enabling applications in health monitoring, disease treatment, and environmental remediation. Hydrogels, a class of soft, wet, and biocompatible materials, have been widely used as matrices for engineered living cells, leading to the nascent field of engineered living hydrogels. Here, the interactions between hydrogel matrices and engineered living cells are described, focusing on how hydrogels influence cell behaviors and how cells affect hydrogel properties. The interactions between engineered living hydrogels and their environments, and how these interactions enable versatile applications, are also discussed. Finally, current challenges facing the field of engineered living hydrogels for their applications in clinical and environmental settings are highlighted.

Characterization of nanosensitive multifractality in submicron scale tissue morphology and its alteration in tumor progression

SIGNIFICANCE

Assessment of disease using optical coherence tomography is an actively investigated problem, owing to many unresolved challenges in early disease detection, diagnosis, and treatment response monitoring. The early manifestation of disease or precancer is typically associated with subtle alterations in the tissue dielectric and ultrastructural morphology. In addition, biological tissue is known to have ultrastructural multifractality.

AIM

Detection and characterization of nanosensitive structural morphology and multifractality in the tissue submicron structure. Quantification of nanosensitive multifractality and its alteration in progression of tumor.

APPROACH

We have developed a label free nanosensitive multifractal detrended fluctuation analysis(nsMFDFA) technique in combination with multifractal analysis and nanosensitive optical coherence tomography (nsOCT). The proposed method deployed for extraction and quantification of nanosensitive multifractal parameters in mammary fat pad (MFP).

RESULTS

Initially, the nsOCT approach is numerically validated on synthetic submicron axial structures. The nsOCT technique was applied to pathologically characterized MFP of murine breast tissue to extract depth-resolved nanosensitive submicron structures. Subsequently, two-dimensional MFDFA were deployed on submicron structural en face images to extract nanosensitive tissue multifractality. We found that nanosensitive multifractality increases in transition from healthy to tumor.

CONCLUSIONS

This method for extraction of nanosensitive tissue multifractality promises to provide a noninvasive diagnostic tool for early disease detection and monitoring treatment response. The novel ability to delineate the dominant submicron scale nanosensitive multifractal properties may also prove useful for characterizing a wide variety of complex scattering media of non-biological origin.

Fractal nature of groundwater level fluctuations affected by riparian zone vegetation water use and river stage variations

Groundwater systems affected by various factors can exhibit complex fractal behaviors, whose reliable characterization however is not straightforward. This study explores the fractal scaling behavior of the groundwater systems affected by plant water use and river stage fluctuations in the riparian zone, using multifractal detrended fluctuation analysis (MFDFA). The multifractal spectrum based on the local Hurst exponent is used to quantify the complexity of fractal nature. Results show that the water level variations at the riparian zone of the Colorado River, USA, exhibit multifractal characteristics mainly caused by the memory of time series of the water level fluctuations. The groundwater level at the monitoring well close to the river characterizes the season-dependent scaling behavior, including persistence from December to February and anti-persistence from March to November. For the site with high-density plants (Tamarisk ramosissima, which requires direct access to groundwater as its source of water), the groundwater level fluctuation becomes persistent in spring and summer, since the plants have the most significant and sustained influence on the groundwater in these seasons, which can result in stronger memory of the water level fluctuation. Results also show that the high-density plants weaken the complexity of the multifractal property of the groundwater system. In addition, the groundwater level variations at the site close to the river exhibit the most complex multifractality due to the influence of the river stage fluctuation.

Tissue multifractality and hidden Markov model based integrated framework for optimum precancer detection

We report the application of a hidden Markov model (HMM) on multifractal tissue optical properties derived via the Born approximation-based inverse light scattering method for effective discrimination of precancerous human cervical tissue sites from the normal ones. Two global fractal parameters, generalized Hurst exponent and the corresponding singularity spectrum width, computed by multifractal detrended fluctuation analysis (MFDFA), are used here as potential biomarkers. We develop a methodology that makes use of these multifractal parameters by integrating with different statistical classifiers like the HMM and support vector machine (SVM). It is shown that the MFDFA-HMM integrated model achieves significantly better discrimination between normal and different grades of cancer as compared to the MFDFA-SVM integrated model.

Microstructure of nickel nanoparticles embedded in carbon films: case study on annealing effect by micromorphology analysis

The presented study is aimed at analyzing the surface texture of amorphous hydrogenated carbon layers containing nickel nanoparticles (Ni‐NPs@a‐C:H) within their structure, which were deposited by Radio Frequency (RF) sputtering and RF‐Plasma Enhanced Chemical Vapor Deposition (RF‐PECVD) methods on glass substrates. Prepared films were then used as research material following their annealing at two different temperatures of 250 °C and 350 °C in an inert argon atmosphere. Series of height samples were taken with the help of atomic force microscopy (AFM) operating in a non‐contact mode and examined in order to determine their fractal characteristics. Raw AFM data were first plane‐fitted to remove the surface bow exhibiting the so‐called residual surface, and then numerically processed to calculate the Areal Autocorrelation Function (AACF), which was later used to compute the Structure Function (SF). The log–log plots of the latter served for calculation of fractal properties of surfaces under investigation, including fractal dimension D, and pseudo‐topothesy K. The analysis of 3‐D surface texture helps to understand their essential characteristics and their implications as well as graphical models and their implementation in computer simulation. Copyright © 2016 John Wiley & Sons, Ltd.

Mueller matrix approach for probing multifractality in the underlying anisotropic connective tissue

Spatial variation of refractive index (RI) in connective tissues exhibits multifractality, which encodes useful morphological and ultrastructural information about the disease. We present a spectral Mueller matrix (MM)-based approach in combination with multifractal detrended fluctuation analysis (MFDFA) to exclusively pick out the signature of the underlying connective tissue multifractality through the superficial epithelium layer. The method is based on inverse analysis on selected spectral scattering MM elements encoding the birefringence information on the anisotropic connective tissue. The light scattering spectra corresponding to the birefringence carrying MM elements are then subjected to the Born approximation-based Fourier domain preprocessing to extract ultrastructural RI fluctuations of anisotropic tissue. The extracted RI fluctuations are subsequently analyzed via MFDFA to yield the multifractal tissue parameters. The approach was experimentally validated on a simple tissue model comprising of TiO2 as scatterers of the superficial isotropic layer and rat tail collagen as an underlying anisotropic layer. Finally, the method enabled probing of precancer-related subtle alterations in underlying connective tissue ultrastructural multifractality from intact tissues.

Investigation of alterations in multifractality in optical coherence tomographic images of in vivo human retina

Optical coherence tomography (OCT) enables us to monitor alterations in the thickness of the retinal layer as disease progresses in the human retina. However, subtle morphological changes in the retinal layers due to early disease progression often may not lead to detectable alterations in the thickness. OCT images encode depth-dependent backscattered intensity distribution arising due to the depth distributions of the refractive index from tissue microstructures. Here, such depth-resolved refractive index variations of different retinal layers were analyzed using multifractal detrended fluctuation analysis, a special class of multiresolution analysis tools. The analysis extracted and quantified microstructural multifractal information encoded in normal as well as diseased human retinal OCT images acquired <italic<in vivo</italic<. Interestingly, different layers of the retina exhibited different degrees of multifractality in a particular retina, and the individual layers displayed consistent multifractal trends in healthy retinas of different human subjects. In the retinal layers of diabetic macular edema (DME) subjects, the change in multifractality manifested prominently near the boundary of the DME as compared to the normal retinal layers. The demonstrated ability to quantify depth-resolved information on multifractality encoded in OCT images appears promising for the early diagnosis of diseases of the human eye, which may also prove useful for detecting other types of tissue abnormalities from OCT images.

Visible to near-infrared refractive properties of freshly-excised human-liver tissues: marking hepatic malignancies

The refractive index is an optical constant that plays a significant role in the description of light-matter interactions. When it comes to biological media, refraction is understudied despite recent advances in the field of bio-optics. In the present article, we report on the measurement of the refractive properties of freshly excised healthy and cancerous human liver samples, by use of a prism-coupling technique covering the visible and near-infrared spectral range. Novel data on the wavelength-dependent complex refractive index of human liver tissues are presented. The magnitude of the real and imaginary part of the refractive index is correlated with hepatic pathology. Notably, the real index contrast is pointed out as a marker of discrimination between normal liver tissue and hepatic metastases. In view of the current progress in optical biosensor technologies, our findings may be exploited for the development of novel surgical and endoscopic tools.

Fractal propagation method enables realistic optical microscopy simulations in biological tissues

Current simulation methods for light transport in biological media have limited efficiency and realism when applied to three-dimensional microscopic light transport in biological tissues with refractive heterogeneities. We describe here a technique which combines a beam propagation method valid for modeling light transport in media with weak variations in refractive index, with a fractal model of refractive index turbulence. In contrast to standard simulation methods, this fractal propagation method (FPM) is able to accurately and efficiently simulate the diffraction effects of focused beams, as well as the microscopic heterogeneities present in tissue that result in scattering, refractive beam steering, and the aberration of beam foci. We validate the technique and the relationship between the FPM model parameters and conventional optical parameters used to describe tissues, and also demonstrate the method's flexibility and robustness by examining the steering and distortion of Gaussian and Bessel beams in tissue with comparison to experimental data. We show that the FPM has utility for the accurate investigation and optimization of optical microscopy methods such as light-sheet, confocal, and nonlinear microscopy.