E-learn computed tomographic angiography: a proposed educational tool for computed tomographic angiography in acute...

Area of Science:

• Medical Education
• Radiology
• Neurology

Background:

• Computed tomographic angiography (CTA) is a key tool for evaluating acute stroke in emergency settings.
• Standardizing CTA interpretation and training new readers are crucial for effective stroke management.
• An e-learning program was developed to address these needs using a test-teach-retest approach.

Purpose of the Study:

• To assess the effectiveness of a novel 3-step e-learning tool in improving physicians' diagnostic accuracy and confidence in interpreting CTA for acute stroke.
• To evaluate the program's impact on identifying specific acute stroke indicators: vascular occlusion and the "spot sign" in intracerebral hemorrhage.
• To determine if the e-learning tool benefits physicians across different experience levels.

Main Methods:

• An HTML-based e-learning program was created, featuring a teaching module and two corresponding test modules.
• Participants completed tests before and after the teaching segment to measure changes in diagnostic accuracy and confidence.
• Diagnostic accuracy and self-reported confidence were assessed and compared using statistical analysis (Wilcoxon rank sum test).

Main Results:

• The e-learning program significantly improved diagnostic accuracy for vascular occlusion (42% to 68%, P = .005) and "spot sign" detection (69% to 92%, P = .009).
• Neurologic consultants showed marked improvement in vascular occlusion detection (50% to 75%, P = .027), while residents showed a positive trend (33% to 60%, P = .081).
• Self-perceived diagnostic certainty increased significantly for "spot sign" detection (50% to 75%, P = .030), but not for vascular occlusion.

Conclusions:

• The developed e-learning tool is an effective educational resource for enhancing CTA interpretation skills in acute stroke.
• The program demonstrably improves diagnostic accuracy and confidence among physicians with varying levels of experience.
• This digital learning approach offers a valuable method for standardizing and advancing the interpretation of critical neuroimaging findings.