Keywords: Diagnosis/Prediction, Machine Learning/Artificial Intelligence
Motivation: Inexperienced junior radiologists faced difficulty in identifying the activity of liver post-treatment lesions with multiple therapeutic techniques.
Goal(s): Commercial liver MRI AI software is promising in improving the accuracy of junior radiologists in judging the activity of lesions after treatment.
Approach: Two senior radiologists used the 5-point scale to evaluate the malignancy of liver lesions as the reference standard. A junior radiologist was evaluated without and with the assistance of AI software to test the diagnostic performance.
Results: AI software performs better in sensitivity and negative predictive value. With the help of AI, the diagnostic efficacy of junior radiologists has been significantly improved.
Impact: Accurate identification of liver lesion malignancy is essential for determining effective treatment regimens. AI software can support junior radiologists in assessing malignancy in post-treatment lesions, regardless of the familiarity with specific treatment techniques.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords