Meeting Banner
Abstract #0643

Unbiasing the spherical variance of a diffusion-weighted MR signal: An application to intra-axonal T2 estimation

Tomasz Pieciak1, Guillem París1,2, Antonio Tristán Vega1, and Santiago Aja-Fernández1
1Laboratorio de Procesado de Imagen (LPI), ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain, 2Department of Radiology, Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States

Synopsis

Keywords: Diffusion Modeling, Diffusion/other diffusion imaging techniques, intra-axonal T2, spherical variance, Rician bias

Motivation: The spherical variance (SV) from multiparametric diffusion MRI acquisitions enables the estimation of the axonal T2 relaxation time. The SV is prone to a noise-induced bias due to positively skewed Rician statistics, leading to overestimation in the axonal T2 parameter.

Goal(s): To derive a method to mitigate the Rician bias in the SV parameter map.

Approach: A closed-form formula to remove the Rician bias from the SV has been analytically derived and verified with in silico and in vivo data.

Results: The bias-corrected SV reduces the estimation error compared to the SV, translating to a less pronounced misestimation in the axonal T2 parameter.

Impact: The SV is a practical parameter to infer the properties of restricted compartments with diffusion MRI. This work shows a formula to remove the Rician bias from the SV. The correction can be used for other SV-based diffusion MRI measures.

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