While use of advanced visualization in radiology is instrumental in diagnosis and communication with referring clinicians, there is an unmet need to render Digital Imaging and Communications in Medicine (DICOM) images as three-dimensional (3D) printed models capable of providing both tactile feedback and tangible depth information about anatomic and pathologic states. Three-dimensional printed models, already entrenched in the nonmedical sciences, are rapidly being embraced in medicine as well as in the lay community. Incorporating 3D printing from images generated and interpreted by radiologists presents particular challenges, including training, materials and equipment, and guidelines. The overall costs of a 3D printing laboratory must be balanced by the clinical benefits. It is expected that the number of 3D-printed models generated from DICOM images for planning interventions and fabricating implants will grow exponentially. Radiologists should at a minimum be familiar with 3D printing as it relates to their field, including types of 3D printing technologies and materials used to create 3D-printed anatomic models, published applications of models to date, and clinical benefits in radiology. Online supplemental material is available for this article.

Despite the rapid growth of three-dimensional (3D) printing applications in medicine, the accuracy and reproducibility of 3D printed medical models have not been thoroughly investigated. Although current technologies enable 3D models to be created with accuracy within the limits of clinical imaging spatial resolutions, this is not always achieved in practice. Inaccuracies are due to errors that occur during the imaging, segmentation, postprocessing, and 3D printing steps. Radiologists' understanding of the factors that influence 3D printed model accuracy and the metrics used to measure this accuracy is key in directing appropriate practices and establishing reference standards and validation procedures. The authors review the various factors in each step of the 3D model printing process that contribute to model inaccuracy, including the intrinsic limitations of each printing technology. In addition, common sources of model inaccuracy are illustrated. Metrics involving comparisons of model dimensions and morphology that have been developed to quantify differences between 3D models also are described and illustrated. These metrics can be used to define the accuracy of a model, as compared with the reference standard, and to measure the variability of models created by different observers or using different workflows. The accuracies reported for specific indications of 3D printing are summarized, and potential guidelines for quality assurance and workflow assessment are discussed. Online supplemental material is available for this article. RSNA, 2017.