Abstract #1659
Automated classification of vessel disease based on high-resolution intravascular multi-parametric mapping MRI
Guan Wang 1,2 , M. Arcan Erturk 3 , Shashank Sathyanarayana Hegde 2 , and Paul A. Bottomley 1,2
1
Dept. of Electrical & Computer Engineering,
Johns Hopkins University, Baltimore, MD, United States,
2
Russell
H. Morgan Dept. of Radiology & Radiological Sciences,
Johns Hopkins University, Baltimore, MD, United States,
3
Center
for Magnetic Resonance Research, University of
Minnesota, Minneapolis, MN, United States
The ability to characterize atheroma components is
central to assessing the status of vessel disease, its
progression and response to interventions, diet, etc,
but is poorly served by existing modalities. To test
whether high-field, high-resolution intravascular MRI
(IVMRI) combined with quantitative T1, T2, proton
density and mobile lipid mapping could be used to stage
vessel disease, we applied 200m resolution
multi-parametric 3T MRI to diseased human artery
specimens. The results were used to train an automatic
machine-learning-based classifier to classify disease,
and the performance was compared with histology.
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.
