Abstract #0473

Assessment of Slow Flow in the Brain using SCIMI and q-aMRI on a High-Performance Gradient System: Comparison of Phase and Magnitude-based Methods

Afis Ajala¹, Itamar Terem², Isabelle Heukensfeldt Jansen¹, Nastaren Abad¹, Chitresh Bhushan¹, Thomas K. F. Foo¹, J Kevin DeMarco^3,4, Robert Y. Shih^3,4, Gail Kohls⁴, H Doug Morris³, Angeliki Pollatou³, Haymanot Yalewayker³, Maureen N. Hood^3,4, Sonja Skeete^3,4, Elizabeth Metzger^3,4, Vincent B Ho^3,4, Samantha Holdsworth⁵, J Kent Warner³, Kawin Setsompop⁶, and Luca Marinelli¹

¹GE HealthCare, Niskayuna, NY, United States, ²Department of Electrical Engineering, Stanford University, Stanford, CA, United States, ³Uniformed Services University of the Health Sciences, Bethesda, MD, United States, ⁴Walter Reed National Military Medical Center, Bethesda, MD, United States, ⁵Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand, ⁶Department of Radiology, Stanford University, Stanford, CA, United States

Synopsis

Keywords: Neurofluids, Neurofluids, Simultaneous coherent and incoherent Imaging, Slow flow, quantitative amplified MRI, High performance gradients.

Motivation: The physiology and function of slow flows in the brain parenchyma is poorly understood and remains an on-going research subject.

Goal(s): To compare displacement fields of the simultaneous coherent and incoherent motion imaging (SCIMI) method (phase-based) and the 3D quantitative amplified MRI (q-aMRI) method (magnitude-based) with the view to jointly validate both methods.

Approach: Displacement fields (Lagrangian perspective) of SCIMI and q-aMRI acquisitions were obtained from four healthy volunteers and compared using correlation and Bland Altman (BA) plots.

Results: Correlation r²as high as 0.93 and mean differences in BA analyses as low as 0 were observed between SCIMI and q-aMRI displacement estimations.

Impact: This study independently compared the measured displacement fields due to brain parenchymal fluid flow obtained from the SCIMI and q-aMRI methods and the correlation of both estimations, thereby validating both methods and providing deeper insights for applications in neurodegenerative pathologies.

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