Computed Tomography Image Quality Analysis Using Reverse Engineering for Prosthesis Design

Abstract

Introduction. Various diseases and accidents cause facial deformities in people. These deformities are mostly caused by cancer and traumatic events such as motor vehicle accidents, assaults and burn injuries. Patients with severe facial disfigurements suffer physiological trauma and social rejection. To improve their facial appearance, these patients often require facial reconstructive surgery and the placement of custom-made prostheses. A facial prosthesis requires accurate patient anatomy obtained through computed tomography (CT) imaging for the 3D printing of prosthesis. Suboptimal CT images could result in incorrectly sized, ill-fitting prostheses, which may cause additional trauma, repeat imaging, and additional radiation exposure and cost. CT scans must be of high quality so that optimal stereolithography files (STLs) can be produced from the scans to ensure the design of correctly sized prostheses, thereby reducing trauma and cost. The aim of this study was to evaluate the image quality of CT scans. The Centre for Rapid Prototyping and Manufacturing (CRPM) supplied 35 STL files previously used for prosthesis manufacturing derived from original CT scans. Because access to the original CT scans (DICOM files) was impossible, an innovative approach to image quality analysis was devised by reverse engineering existing STL files to produce representative CT scans. Materials and methods