J Korean Soc Radiol.  2015 Nov;73(5):312-322. 10.3348/jksr.2015.73.5.312.

Development of an Online Radiology Case Review System Featuring Interactive Navigation of Volumetric Image Datasets Using Advanced Visualization Techniques

• Yang HK
• Woo H
• Jo J
• Lee MH
• Kim B
• Seo J
• Jung JH
• Kang HS
• Lee KH

• KMID: 2079566
• DOI: http://doi.org/10.3348/jksr.2015.73.5.312

Abstract

PURPOSE
To develop an online radiology case review system that allows interactive navigation of volumetric image datasets using advanced visualization techniques.
MATERIALS AND METHODS
Our Institutional Review Board approved the use of the patient data and waived the need for informed consent. We determined the following system requirements: volumetric navigation, accessibility, scalability, undemanding case management, trainee encouragement, and simulation of a busy practice. The system comprised a case registry server, client case review program, and commercially available cloud-based image viewing system.
RESULTS
In the pilot test, we used 30 cases of low-dose abdomen computed tomography for the diagnosis of acute appendicitis. In each case, a trainee was required to navigate through the images and submit answers to the case questions. The trainee was then given the correct answers and key images, as well as the image dataset with annotations on the appendix. After evaluation of all cases, the system displayed the diagnostic accuracy and average review time, and the trainee was asked to reassess the failed cases. The pilot system was deployed successfully in a hands-on workshop course.
CONCLUSION
We developed an online radiology case review system that allows interactive navigation of volumetric image datasets using advanced visualization techniques.

MeSH Terms

Abdomen
Appendicitis
Appendix
Case Management
Dataset*
Diagnosis
Education
Ethics Committees, Research
Humans
Informed Consent
Internet

Figure

• 

  Fig. 1 Diagram showing overall architecture of the system. The system comprised a case registry server, cloud image server, client case review program, and client case image viewer.

• 

  Fig. 2 Screenshots of the client case review program. A. A question page shows brief clinical findings (red underline), case questions (green box), diagnostic criteria for appendicitis (blue box), and the time spent reviewing each case (orange box). B. A feedback page shows the submitted answers (red box), correct answers (green box), and annotated key images (blue box). The trainee can open the annotated image dataset in the client image viewer by clicking the 'Open Annotated Images' button (orange box). C. A training record page shows the trainee's diagnostic accuracy and average review time per case (red box). The trainees can reassess their failed cases by clicking 'Review' buttons (blue box).

• 

  Fig. 3 Sequence diagram showing interactions during a case review cycle. In each case review, the client case review program retrieved the case data, including brief clinical findings, case questions, and the identification number of the image dataset (the first copy without annotations), from the case registry server and displayed the brief clinical findings to the trainee. After receiving the trainee's request, the client case review program sent a command that included the identification number of the image dataset to the client image viewer, and the client image viewer then displayed the processed images received from the cloud image server for the trainee to review. During the review process, the client case review program displayed the time spent reviewing each case. The review time and answers submitted for each case were stored in the case registry server. After the trainee submitted the answers for each case, the client case review program received the correct answers and key images from the case registry server, and displayed them to the trainee as feedback. Following the trainee's request, the client case review program sent a command containing the identification number of the annotated image dataset (the second copy with the annotations for the appendix and other important image findings) to the client image viewer, and the trainee could navigate through the annotated image dataset using the client image viewer. The boxes with dashed vertical lines represent lifelines of the four components of the system and a trainee. The vertical gray bars on the lifelines represent executions. The solid horizontal arrows represent messages between the lifelines and dotted horizontal arrows represent reply messages. ID = identification number

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