A Prospective Pilot Study Comparing Rate of Processing Techniques in Autologous Fat Grafting. (25th June 2018)

• Record Type: Journal Article
• Authors: Hanson, Summer E; Garvey, Patrick B; Chang, Edward I; Reece, Gregory; Liu, Jun; Butler, Charles E
• Is Part Of: Aesthetic surgery journal. Volume 39:Number 3(2019)
• Page Start: 331
• Page End: 337
• Publication Date: 2018-06-25
• Subjects: Surgery, Plastic -- Periodicals; 617.95
• DOI: 10.1093/asj/sjy154
• Languages: English
• ISSNs: 1090-820X

Abstract

Abstract: Background: Autologous fat grafting (AFG) is increasing in popularity to address a variety of defects. There is interest in developing techniques to harvest, process, and inject fat to improve clinical outcomes as well as operative efficiency. Objectives: The purpose of this pilot study is to compare the rate of graft processing of two commercially available systems for graft preparation. Methods: Twenty consecutive cases using an active filtration system (system-AF) were observed followed by 20 consecutive cases using a passive filtration system (system-PF) to compare efficiency rate. Fat processing rate was quantified in milliliters/minute. Results: Forty patients underwent AFG with no differences in patient characteristics between the groups. There was 1 incidence of palpable fat necrosis per group (5%). For all patients, this was the first fat grafting procedure; 20% of patients (n = 4 per group) had additional fat grafting. Overall, the rate of adipose tissue preparation was significantly higher with system-AF compared to system-PF (19.8 mL/min vs 5.3 mL/min, P ≤ 0.001). The resulting percent of graftable fat was comparable (AF: 41% vs PF: 42%; P = 0.83). Conclusions: Time and motion studies such as this provide a means to systematically document each of the steps involved in fat grafting in a reliable fashion. The authors demonstrate a significantly higher rate of lipoaspirate processing using an active filtration system compared to a passive system. Further large-scale studies of the efficacy and cost analysis of AFG are a necessary component of determining best practices in the field. Level of Evidence: 2: