Michael Atlan1, Gina Nuti2, Hongpeng Wang3, Sherri Decker4, TracyAnn Perry5. 1. APHP Hopital Tenon, Université Pierre et Marie Curie Paris VI, Maitre de conférence des Universités Praticien Hospitalier, 4 rue de la Chine, 75020 Paris, France. Electronic address: drmichaelatlan@gmail.com. 2. Allergan plc, 2525 Dupont Dr, Irvine, CA, USA. Electronic address: Nuti_Gina@Allergan.com. 3. Allergan plc, 2525 Dupont Dr, Irvine, CA, USA. Electronic address: Wang_Hongpeng@Allergan.com. 4. Allergan plc, 2525 Dupont Dr, Irvine, CA, USA. Electronic address: Sherri.Decker-Gragson@Allergan.com. 5. Allergan plc, 2525 Dupont Dr, Irvine, CA, USA. Electronic address: tracyann.perry07@gmail.com.
Abstract
BACKGROUND: Surface texture of a breast implant influences tissue response and ultimately device performance. Characterizing differences among available surface textures is important for predicting and optimizing performance. METHODS: Scanning electron microscopy (SEM) and X-ray computed tomography (CT)-imaging were used to characterize the topography and surface area of 12 unique breast implant surface textures from seven different manufacturers. Samples of these surface textures were implanted in rats, and tissue response was analyzed histologically. In separate experiments, the force required to separate host tissue from the implant surface texture was used as a measure of tissue adherence. RESULTS: SEM imaging of the top and cross section of the implant shells showed that the textures differed qualitatively in evenness of the surface, presence of pores, size and openness of the pores, and the depth of texturing. X-ray CT imaging reflected these differences, with the texture surface area of the anterior of the shells ranging from 85 to 551 mm2, which was 8-602% greater than that of a flat surface. General similarities based on the physical structure of the surfaces were noted among groups of textures. In the rat models, with increasing surface texture complexity, there was increased capsule disorganization, tissue ingrowth, and tissue adherence. CONCLUSIONS: Surface area and topography of breast implant textures are important factors contributing to tissue ingrowth and adherence. Based on surface area characteristics and measurements, it is possible to group the textures into four classifications: smooth/nanotexture (80-100 mm2), microtexture (100-200 mm2), macrotexture (200-300 mm2), and macrotexture-plus (> 300 mm2).
BACKGROUND: Surface texture of a breast implant influences tissue response and ultimately device performance. Characterizing differences among available surface textures is important for predicting and optimizing performance. METHODS: Scanning electron microscopy (SEM) and X-ray computed tomography (CT)-imaging were used to characterize the topography and surface area of 12 unique breast implant surface textures from seven different manufacturers. Samples of these surface textures were implanted in rats, and tissue response was analyzed histologically. In separate experiments, the force required to separate host tissue from the implant surface texture was used as a measure of tissue adherence. RESULTS: SEM imaging of the top and cross section of the implant shells showed that the textures differed qualitatively in evenness of the surface, presence of pores, size and openness of the pores, and the depth of texturing. X-ray CT imaging reflected these differences, with the texture surface area of the anterior of the shells ranging from 85 to 551 mm2, which was 8-602% greater than that of a flat surface. General similarities based on the physical structure of the surfaces were noted among groups of textures. In the rat models, with increasing surface texture complexity, there was increased capsule disorganization, tissue ingrowth, and tissue adherence. CONCLUSIONS: Surface area and topography of breast implant textures are important factors contributing to tissue ingrowth and adherence. Based on surface area characteristics and measurements, it is possible to group the textures into four classifications: smooth/nanotexture (80-100 mm2), microtexture (100-200 mm2), macrotexture (200-300 mm2), and macrotexture-plus (> 300 mm2).
Authors: Mark R Magnusson; Tony Connell; Michael Miroshnik; Craig Layt; Mark Ashton; Anand K Deva; Hamish Farrow; Janek Januszkiewicz Journal: Plast Reconstr Surg Glob Open Date: 2019-05-01
Authors: Smrithi Padmakumar; Gregory Jones; Olga Khorkova; Jane Hsiao; Jonghan Kim; Benjamin S Bleier; Mansoor M Amiji Journal: Biomaterials Date: 2021-06-30 Impact factor: 12.479