Meeting Banner
Abstract #4014

Optimizing Temporal Resolution of Dynamic Contrast Enhanced Abdominal MRI Using Deep Learning Reconstruction

Eugene Milshteyn1, Soumyadeep Ghosh2, Nabih Nakrour2, Rory L. Cochran2, Nathaniel Mercaldo2, Xinzeng Wang3, Leo L. Tsai2, Arnaud Guidon1, and Mukesh G. Harisinghani2
1GE HealthCare, Boston, MA, United States, 2Department of Radiology, Massachusetts General Hospital, Boston, MA, United States, 3GE HealthCare, Houston, TX, United States

Synopsis

Keywords: Liver, DSC & DCE Perfusion, DISCO-Star, DL Stack-of-stars, Double Wash-in phase

Motivation: Free breathing DCE imaging is beneficial for patients who have difficulty holding their breath, but can be susceptible to artifacts and suboptimal contrast bolus timing, which may compromise diagnostic accuracy.

Goal(s): Our goal was to validate application of deep learning to 3D DISCO-Star imaging in the abdomen after doubling the number of wash-in phases via spoke reordering.

Approach: 8 and 16 wash-in phase images were assessed by two radiologists across different IQ attributes. Noise characteristics were evaluated and AUC was calculated.

Results: The radiologists preferred DL enhanced 16 wash-in phase across many of the IQ attributes, with higher SNR and decreased streaks.

Impact: The ability to double the wash-in phases in DISCO-Star DCE imaging without compromising image quality via deep learning will provide enhanced diagnostic quality, and has the potential to improve patient care.

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.

Click here for more information on becoming a member.

Keywords