Three-Dimensional Printing: An Enabling Technology for IR.

Rapid prototyping, also known as three-dimensional (3D) printing, is a recent technologic advancement with tremendous potential for advancing medical device design. A wide range of raw materials can be incorporated into complex 3D structures, including plastics, metals, biocompatible polymers, and even living cells. With its promise of highly customized, adaptable, and personalized device design at the point of care, 3D printing stands to revolutionize medical care. The present review summarizes the methods for 3D printing and their current and potential roles in medical device design, with an emphasis on their potential relevance to interventional radiology.

Private Equity and Radiology: Productive Partnership or Inherently Misaligned?

Private equity acquisition of medical groups and health care organizations is becoming increasingly important in medicine and is a trend that is likely to continue for the foreseeable future. Some question the ethical implications of private equity acquisitions, since the clear goal of such organizations is maximizing profitability, which may or may not be in the best interests of either the patient population or the provider group. This article will describe the role of private equity in the medical marketplace, with a focus on the role of private equity in radiology and interventional radiology specifically. Additionally, this article will explore this growing trend in the radiology marketplace and its anticipated effects upon patient care and professional satisfaction for radiologists.

Leveraging Artificial Intelligence to Enhance Peer Review: Missed Liver Lesions on Computed Tomographic Pulmonary Angiography.

PURPOSE: The aim of this study was to use artificial intelligence (AI) to facilitate peer review for detection of missed suspicious liver lesions (SLLs) on CT pulmonary angiographic (CTPA) examinations. METHODS: This retrospective study included 1 month of consecutive CTPA examinations from a multisite teleradiology practice. Visual classification (VC) software analyzed images for the presence (+) or absence (-) of SLLs (>1 cm, >20 Hounsfield units). Separately, a natural language processing (NLP) algorithm evaluated corresponding reports for description (+) of an SLL or lack thereof (-). Studies containing possible missed SLLs (VC+/NLP-) were reviewed by three abdominal radiologists in a two-step adjudication process to confirm if an SLL was missed by the interpreting radiologist. The number of VC+/NLP- cases, the number of images needing radiologist review, and the number of cases with confirmed missed SLLs were recorded. Interobserver agreement for SLLs was calculated for the radiologist readers. RESULTS: A total of 2,573 CTPA examinations were assessed, and 136 were classified as potentially containing missed SLLs (VC+/NLP-). After radiologist review, 13 cases with missed SLLs were confirmed, representing 0.5% of analyzed CT studies. Using AI, the ratio of CT studies requiring review to missed SLLs identified was 10:1; the ratio without the help of AI would be at least 66:1. Among the 136 cases reviewed by radiologists, interobserver agreement for SLLs was excellent (κ = 0.91). CONCLUSIONS: AI can accelerate meaningful peer review by rapidly assessing thousands of examinations to identify potentially clinically significant errors. Although radiologist involvement is necessary, the amount of effort required after initial AI screening is dramatically reduced.

If You Build It, They Will Come: How to Establish an Academic Innovation Enterprise.

The rapid growth of minimally invasive, image-guided intervention has redefined the procedural management of multiple disease entities. The process of innovation which has characterized the growth of interventional radiology can be best described as "needs-based," whereby practicing interventionalists identify unmet clinical needs and subsequently invent solutions to achieve desired technical and clinical outcomes. Historically, catheters and other percutaneous devices were developed with rudimentary manufacturing techniques and subsequently translated to patients with relatively little regulatory oversight. Since then, the resources required and financial costs of interventional technology development have grown exponentially. Fortunately, advances in software development, new methods of rapid prototyping, and commoditization of hardware components have made in-house engineering feasible once again. This has created an opportunity for academic medical centers to translate their research into testable prototypes in humans sooner and at reduced costs, and academic interventional radiology divisions are now leveraging these developments to create collaborative centers of innovation. This article describes five such organizational formats for collaboration and innovation in the academic setting, describing the structure, opportunities, requirements, and caveats of each model.