Meeting Banner
Abstract #0777

Improved Detection, Description and Efficiency of Multiple Sclerosis Lesions’ Assessment using a Dedicated Software

Christian Federau1, Guangming Zhu2, Nicolin Hainc3, Silvio Paganucci1, Lukas Kipp2, and Max Wintermark2
1AI Medical, Zollikon, Switzerland, 2Stanford University, Stanford, CA, United States, 3University Zürich, Zürich, Switzerland


Yearly multiple sclerosis MRI follow-ups require the tedious and time-consuming manual comparing and counting of multiple demyelinating lesions, which can reach hundreds in some cases. We evaluated a semi-automatic software for the efficient assessment of such images, and found that a significant increase in the number of reported new multiple sclerosis lesions can be achieved in two-and-a-half minutes reading on average per case. In contrast, current standard reports missed 80% of the new lesions. In addition, The Jazz software permits the efficient reporting of slowly evolving lesions, an entity growing in clinical relevance and typically overlooked in current reporting.

This abstract and the presentation materials are available to members only; a login is required.

Join Here