Abstract #4092

Iterative decomposition of multi-compartment relaxometry with least square estimations (IDMCR) for UTE relaxometry in brain

Jingwen Yao¹, Nikhil Deveshwar^1,2, and Peder E. Z. Larson¹

¹Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, ²Graduate Program in Bioengineering, UCSF/UC Berkeley, San Francisco, CA, United States

Synopsis

To improve the fitting performance of a UTE relaxometry model, we proposed an iterative decomposition method of multi-compartment relaxometry with least square estimations (IDMCR), based on Gauss-Newton estimations and incorporating spatial constraints. Monte Carlo simulation showed that IDMCR provided robust and unbiased estimation of ultra-short T₂* myelin fraction, which was further improved by adding spatial constraints. We examined the fitting algorithm in one healthy volunteer UTE relaxometry data and showed clear contrast of gray and white matter on the fitted myelin fraction map. The framework of IDMCR could also be easily adapted for other nonlinear parameter fitting problems.

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.