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

Abstract

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.

An Adapted One-dimensional Computational Approach for Irregular ROI Analysis Improves Osteosarcoma Classification

“…It was thereby found that low anisotropy prognosticated axillary lymph node metastasis, larger tumours and higher histological grade 21 . Directional fractal analysis has also been used in investigations of healthy bones with an aim to detect early osteoarthritis by 2-D radiographs 22 and in arterial tissue for monitoring of atherosclerosis progression 23 . The two-dimensional analytical approaches are much better suited for the analysis of histopathology images because of their random orientation and no need to delineate irregular ROI 24 .…”

Optical Microscopy and the Extracellular Matrix Structure: A Review

“…( A – D ) Second-harmonic generation (SHG) optical sections of collagen from the four categories of ovarian tissues [ 55 ]. ( E – H ) Examples of two-photon emission fluorescence (TPEF) images of elastic fibers acquired from the regions along the aorta of myocardial infarction-prone Watanabe heritable hyperlipidemic rabbits [ 56 ]. ( I ) Simultaneous coherent anti-Stokes Raman scattering (CARS) imaging of axonal myelin and TPEF imaging of Oregon green 488 is represented by red and green colors.…”

“…The grayscale inset image is an XZ image showing the cross-section of axons [ 57 ]. Images reproduced with permission from [ 55 , 56 , 57 ].…”

A FIJI macro for quantifying pattern in extracellular matrix

“…Numerous metrics have already been applied to such ECM images. These range from simple abundance and area measurements to more complex textural features such as grey level co-occurrence matrices (7), which measures texture by analysing the variation in pixel intensity value, and boxcounting fractal dimension (8), which measures how an image is sampled in "boxes" of decreasing size. One commonly used metric is matrix fibre alignment, which is known to be a promoter of cancer cell invasion (9,10,11).…”