To evaluate the diagnostic efficacy of artificial intelligence (AI) software in detecting incidental pulmonary embolism (IPE) at CT and shorten the time to diagnosis with use of radiologist reading worklist prioritization. In this study with historical controls and prospective evaluation, regulatory-cleared AI software was evaluated to prioritize IPE on routine chest CT scans with intravenous contrast agent in adult oncology patients. Diagnostic accuracy metrics were calculated, and temporal end points, including detection and notification times (DNTs), were assessed during three time periods (April 2019 to September 2020): routine workflow without AI, human triage without AI, and worklist prioritization with AI. In total, 11 736 CT scans in 6447 oncology patients (mean age, 63 years ± 12 [SD]; 3367 men) were included. Prevalence of IPE was 1.3% (51 of 3837 scans), 1.4% (54 of 3920 scans), and 1.0% (38 of 3979 scans) for the respective time periods. The AI software detected 131 true-positive, 12 false-negative, 31 false-positive, and 11 559 true-negative results, achieving 91.6% sensitivity, 99.7% specificity, 99.9% negative predictive value, and 80.9% positive predictive value. During prospective evaluation, AI-based worklist prioritization reduced the median DNT for IPE-positive examinations to 87 minutes (vs routine workflow of 7714 minutes and human triage of 4973 minutes). Radiologists’ missed rate of IPE was significantly reduced from 44.8% (47 of 105 scans) without AI to 2.6% (one of 38 scans) when assisted by the AI tool (P < .001). AI-assisted workflow prioritization of IPE on routine CT scans in oncology patients showed high diagnostic accuracy and significantly shortened the time to diagnosis in a setting with a backlog of examinations. Keywords: CT, Computer Applications, Detection, Diagnosis, Embolism, Thorax, Thrombosis Supplemental material is available for this article . © RSNA, 2023 See also the commentary by Elicker in this issue.

An observer study showed that two of the three top-performing algorithms from a public competition (Kaggle Data Science Bowl 2017) attained performances that were not significantly worse than that ... Purpose To determine whether deep learning algorithms developed in a public competition could identify lung cancer on low-dose CT scans with a performance similar to that of radiologists. Materials...

Objectives To obtain an overview of teleradiology usage within Europe, to evaluate the current opinion and future vision about this technique. Methods A web-based survey targeted at active radiologists throughout Europe. Results A total of 368 radiology professionals participated in the survey. Among them 65 % currently use teleradiology. The main usages are in-house image distribution (71 %) and on-call readings from home (44 %). The major advantages are improved collaboration with other radiologists (46 %) and efficient distribution of workload (38 %). Outsourcing is performed by 35 % of the participants, among them 68 % use commercial services. The major advantages of outsourcing are availability of second opinions (82 %) and additional capacity for on-call services (71 %). The major disadvantages are insufficient integration of patient history and priors (69 %), and limited communication with clinicians (68 %). The majority expressed a positive opinion regarding the future of teleradiology (80 %) predicting a growing importance (46 %). Opportunities ought to be found in emergency reading services, flexible support of small practices and in collaborative platforms. Conclusions A wide usage of teleradiology throughout Europe is perceived; however usage of commercial services is relatively limited. Regarding cross-border services, there is a great demand for a focused Pan-European legislation, an adapted price regulation and a quality assurance framework. Main Messages • A wide variety of teleradiology applications exist in Europe • Implementation mainly occurs in countries with a high concentration of networked PACS • Usage of commercial teleradiology services in Europe is relatively limited • Language is an unsolved issue and limiting factor for further deployment of services • There is a demand for a Pan-European legislation, price regulation and quality assurance framework