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.

is an essential component of nearly all diagnostic US procedures. In this era of increased awareness of the effects of ionizing radiation and the side effects of iodine-and gadolinium-based contrast agents, Doppler US is poised to play an even bigger role in medical imaging. It is safe, cost-effective, portable, and highly accurate when performed by an experienced operator. The sensitivities and specificities of Doppler US for detecting blood flow and determining the direction and velocity of blood flow in various organs and vascular systems have increased dramatically in the past decade. With use of advanced flow techniques that are available for use with most modern equipment, US can provide vascular information that is comparable to or even more accurate than that obtained with other cross-sectional and interventional modalities. However, there remains concern that US (including newer more advanced flow-evaluating techniques) will not be used to its full potential owing to dependence on operator skill and expertise. Thorough understanding of image optimization techniques and expanded knowledge of the physical principles, instrumentation, application, advantages, and limitations of this modality are of utmost importance. The authors provide a simple practical guide for optimizing images for vascular flow detection by reviewing various cases and focusing on the parameters that should be optimized.