Friday, May 9, 2025
5/9/2025
Silent Functional MRI Using Looping Star - Project Summary: Silent Functional MRI using Looping Star Functional brain imaging using MRI (functional MRI or fMRI) has grown rapidly in use over the past 30 years and is now widely used for basic cognitive neuroscience research and for presurgical planning. It is increasingly being used for developing biomarkers for neurological and psychiatric disorders and for population-based studies of, for example, normal and abnormal development and aging. While there have been numerous advances to fMRI technology that have improved the sensitivity and specificity of the method, many practical challenges remain, for example, the impact of acoustic noise and head movement. The presence of acoustic noise is problematic for fMRI studies in a number of ways. Most obviously are the unpleasant aspects of the loud MRI scanner that can create issues for studies of children and patients with dementia. Studies requiring precise hearing, such as studies of auditory discrimination and processing of natural language are greatly influenced by loud scanner noises. In addition, numerous studies have shown alterations in brain activity in ordinary fMRI studies due to the presence of acoustic noise. The overarching goal of this project is to develop a silent, whole-brain fMRI acquisition that is capable of commonly used spatial and temporal resolutions. Our general approach builds off of a class of very quiet MRI acquisition methods that use very slowly changing gradient waveforms, specifically, a method known as Looping Star. In our project, we will carefully address the critical needs of SNR, spatial and temporal resolution, physiological noise and motion, and susceptibility-related distortions through a combination of novel image acquisition, reconstruction, and processing methods. Our preliminary data suggest that we should be able to achieve substantial parallel imaging accelerations and improvements in SNR and artifact robustness over current methods. The project has four main aims: (1) design and optimize image acquisition for improved SNR, improved spatiotemporal resolution, and reduced undersampling artifact for LS fMRI acquisitions, (2) develop novel dynamic image reconstruction methods for improved spatiotemporal resolution in LS fMRI, (3) integrate corrections into the image reconstruction for physiological noise, head motion, and off-resonance corrections, and (4), evaluate the looping star fMRI approach in comparison to state-of-the-art simultaneous multislice acquisition methods in phantoms and in human subjects using both task fMRI and connectivity. Success in this project will allow quiet, motion and artifact-robust fMRI for studies of children, patients with dementia, hearing, naturalistic speech, amongst other areas. In addition, we believe it is possible that our optimized LS fMRI will be robust for most routine fMRI studies in clinical and research environments.
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