Meeting Banner
Abstract #0194

Early Brain Tumor Detection by Active-Feedback MRI

Zhao Li1, Chaohsiung Hsu1, Ryan Quiroz1, and Yung-Ya Lin1

1Department of Chemistry and Biochemistry, UCLA, Los Angeles, CA, United States

Early detection of high-grade malignancy, such as glioblastoma multiforme (GBM), using enhanced MRI techniques significantly increases not only the treatment options available, but also the patients’ survival rate. For this purpose, a conceptually new approach, termed “Active-Feedback MRI”, was developed. An active feedback electronic device was homebuilt to implement active-feedback pulse sequences to generate avalanching spin amplification and fixed-point spin dynamics, which enhances the local magnetic-field gradient variations due to irregular water contents and deoxyhemoglobin concentration in early GBM. Statistical results (N=22) for in vivo orthotopic xenografts GBM mouse models at various cancer stages validate the superior contrast and robustness of this approach (tumor time constant differs from that of the healthy brain tissue by +24%) towards early GBM detection than conventional T1-weighted (+2.6%) and T2-weighted images (-3.1%). This novel approach provides 4-8 times of improvements in early GBM tumor contrast, as measured by "tumor to normal tissue contrast", “contrast-to-noise ratio” (CNR) or “Visibility”.

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