Meeting Banner
Abstract #3217

Cerebrovascular Reactivity Measurements using Simultaneous 15O-Water PET and Deep-Learning Synthesized Multi-PLD PCASL

Brandon C. Ho1, Donghoon Kim1, Ashwin Kumar1, Moss Zhao1, Audrey Fan2, Youngkyoo Jung3, and Greg Zaharchuk1
1Department of Radiology, Stanford University, Stanford, CA, United States, 2Department of Neurology, University of California, Davis, Davis, CA, United States, 3Department of Radiology, University of California, Davis, Davis, CA, United States

Synopsis

Keywords: AI/ML Image Reconstruction, AI/ML Image Reconstruction

Motivation: Arterial spin labeling offers a less invasive alternative to measure cerebrovascular reactivity (CVR) compared to 15O-water PET.

Goal(s): To provide validation of deep learning methods to estimate CVR from a single PLD of multi-PLD data.

Approach: Using 1 PWI and M0 image from multi-PLD PCASL data as input, a 3D H-CNN estimated CBF maps at baseline and post-acetazolamide vasodilation. CBF and CVR measures by 15O-water PET, single-PLD, multi-PLD, and synthesized multi-PLD ASL were compared.

Results: Synthesized CBF and CVR were similar to the ground truth multi-PLD ASL estimates and significantly closer to the gold standard 15O-water PET in comparison to single-PLD ASL.

Impact: Though single-PLD ASL offers shorter scan durations, it largely underestimates CVR. Using deep learning models to synthesize multi-PLD ASL even from a single PLD may allow for more robust CVR estimates while potentially matching the shorter scan times.

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