Concise Review: Intraoperative Strategies for Minimal Manipulation of Autologous Adipose Tissue for Cell- and Tissue-Based Therapies

The stromal vascular fraction (SVF) is a heterogeneous population of stem/stromal cells isolated from perivascular and extracellular matrix (ECM) of adipose tissue complex (ATC). Administration of SVF holds a strong therapeutic potential for regenerative and wound healing medicine applications aimed at functional restoration of tissues damaged by injuries or chronic diseases. SVF is commonly divided into cellular stromal vascular fraction (cSVF) and tissue stromal vascular fraction (tSVF). Cellular SVF is obtained from ATC by collagenase digestion, incubation/isolation, and pelletized by centrifugation. Enzymatic disaggregation may alter the relevant biological characteristics of adipose tissue, while providing release of complex, multiattachment of cell-to-cell and cell-to-matrix, effectively eliminating the bioactive ECM and periadventitial attachments. In many countries, the isolation of cellular elements is considered as a more than minimal manipulation, and is most often limited to controlled clinical trials and subject to regulatory review. Several alternative, nonenzymatic methods of adipose tissue processing have been developed to obtain via minimal mechanical manipulation an autologous tSVF product intended for delivery, reducing the procedure duration, lowering production costs, decreasing regulatory burden, and shortening the translation into the clinical setting. Ideally, these procedures might allow for the integration of harvesting and processing of adipose tissue for ease of injection, in a single procedure utilizing a nonexpanded cellular product at the point of care, while permitting intraoperative autologous cellular and tissue-based therapies. Here, we review and discuss the options, advantages, and limitations of the major strategies alternative to enzymatic processing currently developed for minimal manipulation of adipose tissue. Stem Cells Translational Medicine 2019