Hesamoddin Jahanian1, Samantha Holdsworth2, Thomas Christen3, Hua Wu4, Kangrong Zhu5, Adam B Kerr5, Matthew J Middione6, Robert F Dougherty4, Michael Moseley3, Greg Zaharchuk3. 1. Departmment of Radiology, University of Washington, Seattle, WA, United States. Electronic address: hesamj@uw.edu. 2. Department of Anatomy and Medical Imaging & Centre for Brain Research, University of Auckland, Auckland, New Zealand. 3. Departmment of Radiology, Stanford University, CA, United States. 4. Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA, United States. 5. Department of Electrical Engineering, Stanford University, Stanford, CA, United States. 6. Applied Sciences Laboratory West, GE Healthcare, Menlo Park, CA, United States.
Abstract
BACKGROUND: Recent advancements in simultaneous multi-slice (SMS) imaging techniques have enabled whole-brain resting-state fMRI (rs-fMRI) scanning at sub-second temporal resolution, providing spectral ranges much wider than the typically used range of 0.01-0.1 Hz. However, the advantages of this accelerated acquisition for rs-fMRI have not been evaluated. NEW METHOD: In this study, we used SMS Echo Planar Imaging (EPI) to probe whole-brain functional connectivity with a short repetition time (TR = 350 ms) and compared it with standard EPI with a longer TR of 2000 ms. We determined the effect of scan length and investigated the temporal filtration strategies that optimize results based on metrics of signal-noise separation and test-retest reliability using both seed-based and independent component analysis (ICA). RESULTS: We found that use of either the entire frequency range of 0.01-1.4 Hz or the entire frequency range with the exclusion of typical cardiac and respiratory frequency values tended to provide the best functional connectivity maps. COMPARISON WITH EXISTING METHODS: We found that the SMS-acquired rs-fMRI scans had improved the signal-noise separation, while preserving the same level of test-retest reliability compared to conventional EPI, and enabled the detection of reliable functional connectivity networks with scan times as short as 3 min. CONCLUSIONS: Our findings suggest that whole-brain rs-fMRI studies may benefit from the increased temporal resolution enabled by the SMS-EPI acquisition, leading to drastic scan time reductions, which in turn should enable the more widespread use of rs-fMRI in clinical research protocols.
BACKGROUND: Recent advancements in simultaneous multi-slice (SMS) imaging techniques have enabled whole-brain resting-state fMRI (rs-fMRI) scanning at sub-second temporal resolution, providing spectral ranges much wider than the typically used range of 0.01-0.1 Hz. However, the advantages of this accelerated acquisition for rs-fMRI have not been evaluated. NEW METHOD: In this study, we used SMS Echo Planar Imaging (EPI) to probe whole-brain functional connectivity with a short repetition time (TR = 350 ms) and compared it with standard EPI with a longer TR of 2000 ms. We determined the effect of scan length and investigated the temporal filtration strategies that optimize results based on metrics of signal-noise separation and test-retest reliability using both seed-based and independent component analysis (ICA). RESULTS: We found that use of either the entire frequency range of 0.01-1.4 Hz or the entire frequency range with the exclusion of typical cardiac and respiratory frequency values tended to provide the best functional connectivity maps. COMPARISON WITH EXISTING METHODS: We found that the SMS-acquired rs-fMRI scans had improved the signal-noise separation, while preserving the same level of test-retest reliability compared to conventional EPI, and enabled the detection of reliable functional connectivity networks with scan times as short as 3 min. CONCLUSIONS: Our findings suggest that whole-brain rs-fMRI studies may benefit from the increased temporal resolution enabled by the SMS-EPI acquisition, leading to drastic scan time reductions, which in turn should enable the more widespread use of rs-fMRI in clinical research protocols.
Authors: Andrew W Russo; Kirsten E Stockel; Sean M Tobyne; Chanon Ngamsombat; Kristina Brewer; Aapo Nummenmaa; Susie Y Huang; Eric C Klawiter Journal: Brain Struct Funct Date: 2022-05-10 Impact factor: 3.270
Authors: Daehun Kang; Hang Joon Jo; Myung-Ho In; Uten Yarach; Nolan K Meyer; Lydia J Bardwell Speltz; Erin M Gray; Joshua D Trzasko; John Huston Iii; Matt A Bernstein; Yunhong Shu Journal: Phys Med Biol Date: 2020-11-27 Impact factor: 3.609
Authors: Przemysław Podgórski; Marta Waliszewska-Prosół; Anna Zimny; Marek Sąsiadek; Joanna Bladowska Journal: Front Neurol Date: 2021-07-12 Impact factor: 4.003