Detection of renal biomarkers in chronic kidney disease using microfluidics: progress, challenges and opportunities

Chronic kidney disease (CKD) typically evolves over many years in a latent period without clinical signs, posing key challenges to detection at relatively early stages of the disease. Accurate and timely diagnosis of CKD enable effective management of the disease and may prevent further progression. However, long turn-around times of current testing methods combined with their relatively high cost due to the need for established laboratory infrastructure, specialized instrumentation and trained personnel are drawbacks for efficient assessment and monitoring of CKD, especially in underserved and resource-poor locations. Among the emerging clinical laboratory approaches, microfluidic technology has gained increasing attention over the last two decades due to the possibility of miniaturizing bioanalytical assays and instrumentation, thus potentially improving diagnostic performance. In this article, we review current developments related to the detection of CKD biomarkers using microfluidics. A general trend in this emerging area is the search for novel, sensitive biomarkers for early detection of CKD using technology that is improved by means of microfluidics. It is anticipated that these innovative approaches will be soon adopted and utilized in both clinical and point-of-care settings, leading to improvements in life quality of patients.

Fractal dimension and directional analysis of elastic and collagen fiber arrangement in unsectioned arterial tissues affected by atherosclerosis and aging

Structural proteins like collagen and elastin are major constituents of the extracellular matrix (ECM). ECM degradation and remodeling in diseases significantly impact the microorganization of these structural proteins. Therefore, tracking the changes of collagen and elastin fiber morphological features within ECM impacted by disease progression could provide valuable insight into pathological processes such as tissue fibrosis and atherosclerosis. Benefiting from its intrinsic high-resolution imaging power and superior biochemical specificity, nonlinear optical microscopy (NLOM) is capable of providing information critical to the understanding of ECM remodeling. In this study, alterations of structural fibrillar proteins such as collagen and elastin in arteries excised from atherosclerotic rabbits were assessed by the combination of NLOM images and textural analysis methods such as fractal dimension (FD) and directional analysis (DA). FD and DA were tested for their performance in tracking the changes of extracellular elastin and fibrillar collagen remodeling resulting from atherosclerosis progression/aging. Although other methods of image analysis to study the organization of elastin and collagen structures have been reported, the simplified calculations of FD and DA presented in this work prove that they are viable strategies for extracting and analyzing fiber-related morphology from disease-impacted tissues. Furthermore, this study also demonstrates the potential utility of FD and DA in studying ECM remodeling caused by other pathological processes such as respiratory diseases, several skin conditions, or even cancer. NEW & NOTEWORTHY Textural analyses such as fractal dimension (FD) and directional analysis (DA) are straightforward and computationally viable strategies to extract fiber-related morphological data from optical images. Therefore, objective, quantitative, and automated characterization of protein fiber morphology in extracellular matrix can be realized by using these methods in combination with digital imaging techniques such as nonlinear optical microscopy (NLOM), a highly effective visualization tool for fibrillar collagen and elastic network. Combining FD and DA with NLOM is an innovative approach to track alterations of structural fibrillar proteins. The results illustrated in this study not only prove the effectiveness of FD and DA methods in extracellular protein characterization but also demonstrate their potential value in clinical and basic biomedical research where protein microstructure characterization is critical.

Review of near-infrared methods for wound assessment

Wound management is a challenging and costly problem that is growing in importance as people are living longer. Instrumental methods are increasingly being relied upon to provide objective measures of wound assessment to help guide management. Technologies that employ near-infrared (NIR) light form a prominent contingent among the existing and emerging technologies. We review some of these technologies. Some are already established, such as indocyanine green fluorescence angiography, while we also speculate on others that have the potential to be clinically relevant to wound monitoring and assessment. These various NIR-based technologies address clinical wound management needs along the entire healing trajectory of a wound.

Collagen morphology and texture analysis: from statistics to classification

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage.

Quantitative nonlinear optical assessment of atherosclerosis progression in rabbits

Quantification of atherosclerosis has been a challenging task owing to its complex pathology. In this study, we validated a quantitative approach for assessing atherosclerosis progression in a rabbit model using a numerical matrix, optical index for plaque burden, derived directly from the nonlinear optical microscopic images captured on the atherosclerosis-affected blood vessel. A positive correlation between this optical index and the severity of atherosclerotic lesions, represented by the age of the rabbits, was established based on data collected from 21 myocardial infarction-prone Watanabe heritable hyperlipidemic rabbits with age ranging between new-born and 27 months old. The same optical index also accurately identified high-risk locations for atherosclerotic plaque formation along the entire aorta, which was validated by immunohistochemical fluorescence imaging.

Nonlinear optical microscopy in decoding arterial diseases

Pathological understanding of arterial diseases is mainly attributable to histological observations based on conventional tissue staining protocols. The emerging development of nonlinear optical microscopy (NLOM), particularly in second-harmonic generation, two-photon excited fluorescence and coherent Raman scattering, provides a new venue to visualize pathological changes in the extracellular matrix caused by atherosclerosis progression. These techniques in general require minimal tissue preparation and offer rapid three-dimensional imaging. The capability of label-free microscopic imaging enables disease impact to be studied directly on the bulk artery tissue, thus minimally perturbing the sample. In this review, we look at recent progress in applications related to arterial disease imaging using various forms of NLOM.

Early dental caries detection using a fibre-optic coupled polarization-resolved Raman spectroscopic system

A new fibre-optic coupled polarization-resolved Raman spectroscopic system was developed for simultaneous collection of orthogonally polarized Raman spectra in a single measurement. An application of detecting incipient dental caries based on changes observed in Raman polarization anisotropy was also demonstrated using the developed fibre-optic Raman spectroscopic system. The predicted reduction of polarization anisotropy in the Raman spectra of caries lesions was observed and the results were consistent with those reported previously with Raman microspectroscopy. The capability of simultaneous collection of parallel- and cross-polarized Raman spectra of tooth enamel in a single measurement and the improved laser excitation delivery through fibre-optics demonstrated in this new design illustrates its future clinical potential.

Precision of Raman depolarization and optical attenuation measurements of sound tooth enamel

The demineralization of enamel that is associated with early caries formation affects the optical properties of the enamel. Polarized Raman spectroscopy and optical coherence tomography have been used to detect these changes and potentially offer a means to detect and monitor early caries development. The total optical attenuation coefficient as measured by optical coherence tomography and the polarization anisotropy of the Raman peak arising from the symmetric nu(1) vibration of PO4(3-) at approximately 959 cm(-1) have been demonstrated as being sensitive markers of early caries. This ex vivo study on extracted human teeth demonstrates that these measurements can be made with reasonable precision with concomitantly good repeatability and reproducibility in sound enamel. Such reliability is crucial for these techniques to have a practical clinical value.

Semi-parametric estimation in the compositional modeling of multicomponent systems from Raman spectroscopic data

Identification and quantification of molecular species are central applications of molecular spectroscopy. In complex multicomponent systems like tissue samples, linear parametric models are often used to estimate the relative concentrations of the biochemical components of the sample. In situations where not all of the components of the sample are known or modeled, such parametric models can suffer from omitted variable bias and result in skewed estimates of component concentrations. We propose a semi-parametric approach that tries to avoid this omitted variable bias by effectively including unknown covariates as a non-parametric term in the regression equation. Constituent concentrations estimated with such partial linear models should outperform strict parametric linear models when the user has limited information on the composition of a multi-constituent system.

Detection of early dental caries using polarized Raman spectroscopy

A new technique based on polarized Raman spectroscopy is demonstrated for detecting early dental caries on extracted human teeth. Sound tooth enamel exhibited strong Raman polarization anisotropy whereas early caries consistently showed a lower degree of Raman polarization anisotropy. In particular, for sound enamel, the Raman peak arising from the symmetric nu1 vibration of PO(4) (3-) at 959 cm(-1) is strongly polarized. This is in contrast to the spectra of carious lesions that displayed weaker polarization dependence at 959 cm(-1). Such difference in the degree of Raman polarization anisotropy allows for discrimination between early dental caries and sound enamel.

Ex vivo detection and characterization of early dental caries by optical coherence tomography and Raman spectroscopy

Early dental caries detection will facilitate implementation of nonsurgical methods for arresting caries progression and promoting tooth remineralization. We present a method that combines optical coherence tomography (OCT) and Raman spectroscopy to provide morphological information and biochemical specificity for detecting and characterizing incipient carious lesions found in extracted human teeth. OCT imaging of tooth samples demonstrated increased light backscattering intensity at sites of carious lesions as compared to the sound enamel. The observed lesion depth on an OCT image was approximately 290 microm matching those previously documented for incipient caries. Using Raman microspectroscopy and fiber-optic-based Raman spectroscopy to characterize the caries further, spectral changes were observed in PO4 (3-) vibrations arising from hydroxyapatite of mineralized tooth tissue. Examination of various ratios of PO4 (3-) nu2, nu3, nu4 vibrations against the nu1 vibration showed consistent increases in carious lesions compared to sound enamel. The changes were attributed to demineralization-induced alterations of enamel crystallite morphology and/or orientation. OCT imaging is useful for screening carious sites and determining lesion depth, with Raman spectroscopy providing biochemical confirmation of caries. The combination has potential for development into a new fiber-optic diagnostic tool enabling dentists to identify early caries lesions with greater sensitivity and specificity.