Monitoring tissue development in acellular matrix‐based regeneration for bladder tissue engineering: Multiexponential diffusion and T2* for improved specificity

Abstract

Cell-seeded acellular matrices (ACMs) are a promising approach for the tissue engineering of soft tissues and organs, such as the urinary bladder. ACM contains site-preferred structural and functional molecules, and degradation products derived from ACM play important roles in tissue remodeling. Regeneration proceeds along concurrent trajectories of cell growth and matrix degradation, characterized by evolving biophysical and biochemical properties. The assessment of tissue development through a noninvasive imaging technique, such as MRI, must therefore be capable of distinguishing these concurrent biophysical and biochemical changes. However, although MRI provides exquisite sensitivity to tissue microstructure, composition and function, specificity remains limited. In this study, multiexponential diffusion and the effective transverse relaxation time T(2)* were investigated for their ability to assess cell growth and tissue composition, respectively. Bladder ACMs prepared with and without hyaluronic acid, and ACMs seeded with smooth muscle cells, were assessed on MRI. The slow diffusion fraction from multiexponential diffusion analysis demonstrated the best correlation with cellularity, with minimal influence from underlying matrix degradation. T(2)* measurements were sensitive to macromolecular content, specifically the presence of hyaluronic acid, without confounding influence from tissue hydration. T(2)* also appeared to be sensitive to cell filling of the matrix pore space. Compared with these metrics, commonly used MRI parameters, such as T(1), T(2) and single diffusion coefficients, were more limited in specificity. The use of T(2) to measure tissue structure and composition is limited by its large dependence on water content, and single diffusion can only reflect the overall characteristics of the extra- and intracellular environment. These findings are important for further development of more specific MRI methods for the monitoring of regeneration in tissue-engineered systems.