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Abstract #4325

A Flexible Computational Framework for Characterization of Dynamic Cerebrovascular Response to Global Hemodynamic Stimuli  

Siddhant Dogra1, Xiuyuan Wang2, Jelle Veraart3, Alejandro Gupta3, Koto Ishida3, Deqiang Qiu4, and Seena Dehkharghani3
1Radiology, New York University Langone Health, New York, NY, United States, 2Weill Cornell, New York, NY, United States, 3New York University Langone Health, New York, NY, United States, 4Emory University, Atlanta, GA, United States

Cerebrovascular reactivity (CVR) is conventionally assessed by comparing discrete cerebral blood flow measurements obtained prior to and following a hemodynamic stimulus. Blood-oxygen-level-dependent (BOLD)-MRI provides potentially continuous, dynamic CVR characterization when coupled to stimuli such as acetazolamide (ACZ), but poor signal-to-noise generally limits its analysis to an analogous comparison of arbitrarily defined terminal BOLD signals relative to baseline. We present a novel framework incorporating temporal and spatial denoising to pre-condition the dynamic time-signal course for robust voxel-level maximal and terminal CVR, and novel CVR time-to-peak and related kinetic features, disambiguating confounders related to potentially non-optimal terminal CVR assignment in conventional use.

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