Computer assisted planning of autologous fat grafting in breast. (January 2013)

• Record Type: Journal Article
• Authors: Patete, Paolo; Rigotti, Gino; Marchi, Alessandra; Baroni, Guido
• Is Part Of: Computer aided surgery. Volume 18:Number 1/2(2013:Jan.)
• Page Start: 10
• Page End: 18
• Publication Date: 2013-01
• Subjects: Computer-assisted surgery -- Periodicals; Imaging systems in medicine -- Periodicals; Surgery, Operative -- Computer simulation -- Periodicals; Surgical technology -- Periodicals; Medical technology -- Periodicals; 617.90285
• DOI: 10.3109/10929088.2012.745169
• Languages: English
• ISSNs: 1092-9088

Abstract

<abstract> <title> <x xml:space="preserve">Abstract</x> </title> <p>Autologous fat grafting is an emerging and promising surgical technique in regenerative medicine, and its application is quickly spreading in plastic and reconstructive surgery of the breast. However, despite the advantages of the technique, surgical complications may occur, such as implanted tissue necrosis and resorption and onset of microcalcifications. In view of the hypothesis that the uniformity of the lipoaspirate transplantation is related to graft survival and a lower probability of complications, we developed an interactive lipomodeling planning software application based on a genetic algorithm that allows automatic optimization of the uniformity of fat tissue distribution. The input dataset consists of a 3D model of the patient's thorax, created from MRI scans, on which relevant structures are segmented. The developed software was tested starting from either an automatically generated plan or an initial guess of the optimal surgical plan, and in both cases the application yielded a consistent improvement in the planned fat tissue distribution by optimizing the position of the insertion points and the direction of the insertion pathways. On the basis of the simulations performed, the use of genetic algorithms for optimization of the geometry of autologous fat transfer in the breast proved to be effective. These results will foster further activities focused on the comparison of predicted optimized geometries and those obtained in real surgical cases as a means of obtaining a deeper knowledge of the potential influence of a uniform fat tissue distribution on the quality of the surgical outcome. The presented application is also put forward as representing a noteworthy step towards the clinical application of computer assisted planning tools in breast surgery.</p> </abstract>