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Abstract #3192

Inter-Scanner Variability and Evaluation of T2-FLAIR Harmonization in Alzheimer’s Neuroimaging

Brandon C. Ho1, Donghoon Kim1, Ashwin Kumar1, Skylar Weiss2, Hillary Vossler2, Andrew Dreisbach1, Dawn Holley1, Mehdi Khalighi1, Elizabeth Mormino2, and Greg Zaharchuk1
1Department of Radiology, Stanford University, Stanford, CA, United States, 2Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, United States

Synopsis

Keywords: Data Acquisition, Acquisition Methods, T2-FLAIR, Harmonization

Motivation: Standardized protocols for multi-center imaging studies like ADNI attempt to harmonize imaging data, but evaluating image quality is essential to assess differences between sites.

Goal(s): To highlight visual and quantitative differences in ADNI-protocol T2-FLAIR images across scanner manufacturers.

Approach: ADNI3 T2-FLAIR images from three manufacturers were compared via gray matter/white matter contrast ratio (GM/WM). Additionally, we compared the ADNI-protocol and a GM/WM optimized T2-FLAIR sequence in a single scan session for 3 subjects.

Results: ADNI3 GM/WM ratio was significantly different across manufacturers, with GE having the lowest GM/WM contrast. For this manufacturer, we found that a GM/WM optimized T2-FLAIR can improve inter-scanner harmonization.

Impact: T2-FLAIR is an instrumental imaging sequence to visualize gray-white matter contrast and white matter abnormalities. However, inter-scanner variability may hinder analysis involving multi-site imaging datasets. Thus, we evaluated protocol changes that can improve harmonization of T2-FLAIR images across scanners.

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Keywords