Development of an average chest shape for objective evaluation of the aesthetic outcome in the nuss procedure planning process

Abstract

The Nuss procedure is a minimally invasive surgery for correcting pectus excavatum. Pectus excavatum (PE), also called sunken or funnel chest, is a congenital chest wall deformity which is characterized by a deep depression of the sternum. This condition affects primarily children and young adults and is responsible for about 90% of congenital chest wall abnormalities. Among various PE treatments options, the Nuss procedure has been proven to have a high success rate and satisfactory aesthetic outcome. Although the Nuss procedure is routinely performed, the outcome depends mostly on the correct placement of the bar. Therefore, a Nuss procedure surgical planner would be an invaluable planning tool ensuring the optimal aesthetic outcome. Unlike what is done today, the planner will require a means to evaluate the aesthetic results objectively. Therefore, we have developed a methodology to generate an average shape of the chest for comparison with results of the Nuss procedure planning process. Since a method is based on a sample of normal chests obtained from the male population using laser surface scanning, a challenging aspect is data processing of the sample. This includes hole-filling, scan registration, ensuring consistency among scans, and shape vector creation. In our case, the first problem is solved using radial basis function approximation of the surface optionally implemented in the scanning software. After registration of all scans, they are processed in order to meet requirements of statistical shape analysis, which includes creation of a surface interpolant for each dataset that allows controlling consistency among scans and their resolution. If hole-filling cannot be initially performed, we propose a cross-section of scans with parallel planes and then sampling points from fitted polynomials. As a result an average shape of the chest is obtain with statistical shape analysis performed, disclosing directions in which the largest variability occurs. © 2010 Springer-Verlag.