Tessa S. Cook MD, PhD, Presenter: Nothing to Disclose

Christopher Aquino MD, Abstract Co-Author: Nothing to Disclose

Alexander C. Mamourian MD, Abstract Co-Author: Nothing to Disclose

William W. Boonn MD, Abstract Co-Author: Research Grant, Siemens AG Founder, Montage Healthcare Solutions, Inc Shareholder, Montage Healthcare Solutions, Inc Medical Advisory Board, Merge Healthcare Incorporated Stock options, Merge Healthcare Incorporated

Woojin Kim MD, Abstract Co-Author: Principal, Montage Healthcare Solutions, Inc Shareholder, Montage Healthcare Solutions, Inc Consultant, Amirsys, Inc Consultant, Infiniti Medical, LLC Speaker, Terumo Corporation Principal, iVirtuoso, Inc Shareholder, iVirtuoso, Inc

Educational materials in radiology take many forms--teaching files, formal presentations, collections of interesting cases. But they typically only provide a small subset of images that features the salient findings. While this is a conventional method of teaching, it is contrary to regular clinical practice, during which stacks of images must be reviewed to make a diagnosis. To realistically test the ability of trainees to recognize abnormalities on head CTs, we have developed a mobile application that mixes normal cases with abnormal exams. All cases are presented as scrollable image stacks, to replicate the way they would be viewed on a PACS workstation. However, the convenience of a mobile platform enables radiology trainees to practice on the go, while still simulating the nature of daily practice.

Giving radiology trainees additional opportunities to practice their diagnostic skills outside the reading room is important, and this mobile application is an initial approach. The app can be modified to serve as a performance tracker during residency or fellowship, as well as being extended to other modalities and subspecialties.

We have created a test of visual perception for neuroimaging that presents head CTs as they would be viewed on a PACS workstation, with the added convenience of a mobile platform for review.

Axial image stacks from normal and abnormal normal head CT scans (divided into basic and advanced cases) are randomly presented in a scrollable image viewer. For each case, the app allows the user to scroll through the image stack just as he/she would when reviewing at a workstation. Once the images have been reviewed, the possible diagnoses can be revealed as a multiple-choice quiz, but only after the case images are hidden! This is intended to simulate daily practice, during which each patient’s study does not arrive with a multiple-choice list of possible diagnoses which can sequentially be eliminated. A running score is tallied as the trainee reviews each case, and high scores can be tracked by the app. At the end of the quiz, the answers are revealed, with additional supporting cross-sectional images or reformats provided by way of explanation.

Cook, T, Aquino, C, Mamourian, A, Boonn, W, Kim, W, Learning Neuroradiology on the Go: PACS-like Testing of Both Recognition and Interpretive Skills on the iPad.  Radiological Society of North America 2012 Scientific Assembly and Annual Meeting, November 25 - November 30, 2012 ,Chicago IL. http://archive.rsna.org/2012/12025732.html