Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact
Fan, Qiuyun; Eichner, Cornelius; Afzali, Maryam; Mueller, Lars; Tax, Chantal M.W.; Davids, Mathias; Mahmutovic, Mirsad; Keil, Boris; Bilgic, Berkin; Setsompop, Kawin; Lee, Hong Hsi; Tian, Qiyuan; Maffei, Chiara; Ramos-Llordén, Gabriel; Nummenmaa, Aapo; Witzel, Thomas; Yendiki, Anastasia; Song, Yi Qiao; Huang, Chu Chung; Lin, Ching Po; Weiskopf, Nikolaus; Anwander, Alfred; Jones, Derek K.; Rosen, Bruce R.; Wald, Lawrence L.; Huang, Susie Y.
(2022) NeuroImage, volume 254, pp. 1 - 24
(Article)
Abstract
Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General
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Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide – one in the United Kingdom in Cardiff, Wales, another in continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength diffusion MRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for diffusion MRI and where the field is headed in the coming years.
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Keywords: axon diameter, brain, clinical applications, data sharing, Diffusion MRI, fiber tracking, high b-value, Human Connectome Project (HCP), human connectome scanner, peripheral nerve stimulation, preprocessing, radio frequency coil, sequence, tissue microstructure, white matter, Humans, Connectome/methods, Brain/diagnostic imaging, China, Diffusion Magnetic Resonance Imaging/methods, Diffusion Tensor Imaging/methods, Neurology, Cognitive Neuroscience, Review, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, Non-P.H.S., Journal Article, Research Support, N.I.H., Extramural
ISSN: 1053-8119
Publisher: Academic Press Inc.
Note: Funding Information: Beyond the whole-body design of the original Connectom system, head-only gradient designs have been advanced by several separate research projects in an effort to achieve high G max and fast slew rates. For example, the MAGNUS (Microstructure Anatomy Gradient for Neuroimaging with Ultrafast Scanning) was developed as part of the Congressional Directed Medical Research Programs (CDMRP) supported by the U.S. Department of Defense. MAGNUS achieves up to G max of 200 mT/m and 500 T/m/s slew rate ( Foo et al., 2020 ). The 7T Impulse gradient ( Feinberg et al., 2021 ), developed by Siemens Healthineers in collaboration with the University of California, Berkeley, and MGH is also specifically designed as a head gradient for brain imaging. The Impulse gradient is capable of up to 200 mT/m maximum gradient strength with a maximum slew rate of 900 T/m/s per axis. In addition, a next-generation human Connectome MRI scanner (Connectome 2.0) targeting a maximum gradient strength of 500 mT/m and 600 T/m/s is being engineered with a head-only design in collaboration with Siemens Healthineers and will be brought online to replace the current Connectome scanner at MGH ( Huang et al., 2021b ; Yendiki et al., 2020 ). In comparison to the body gradient design, the head-only design offers several advantages from an engineering perspective. First, head-only gradients allow for higher gradient performance due to the smaller bore size. Less stringent constraints arising from peripheral and cardiac nerve stimulation are expected due to less exposure of the body to the gradient field. Moreover, head-only gradients can be developed to be synergistic with higher field strengths by taking advantage of the smaller bore sizes and higher SNR afforded by stronger static magnetic fields. As an emerging trend, the head-only design represents a promising long-term direction for the development of future high gradient strength systems. Funding Information: This work was funded by an NIH Blueprint for Neuroscience Research Grant: U01MH093765 , as well as NIH funding from U01-EB026996 , P41-EB030006 , K23-NS096056 , R01-EB028797 , U01-EB025162 , R03-EB031175 , R01-EB020613 , R01-MH116173 , R01-EB019437 , R01-EB016695 , R01-NS118187, and NIH Office of the Director DP5OD031854 . Funding support was also received from the National Natural Science Foundation of China (No. 82071994 ), Shanghai Municipal Science and Technology Major Project (No. 2018SHZDZX01 ), ZJ Lab, and Shanghai Center for Brain Science and Brain-Inspired Technology (CPL). CMWT was supported by a Veni grant (17331) from the Dutch Research Council (NWO) and a Sir Henry Wellcome Fellowship (215944/Z/19/Z). CE and AA are supported by the SPP 2041 ‘Computational Connectomics’ of the German Research Foundation, DFG. MA and LM are supported by Wellcome Trust Investigator Award ( 219536/Z/19/Z ). NW received funding from the European Research Council under the European Union 's Seventh Framework Programme ( FP7/2007–2013 ) / ERC grant agreement No 616905 , from the NISCI project funded by the European Union's Horizon 2020 research and innovation program under the grant agreement No 681094 , and the BMBF ( 01EW1711A & B) in the framework of ERA-NET NEURON. YS thanks Dr. Isik Kizilyalli, program director of the Advanced Research Projects Agency-Energy (ARPA-E), for the partial support of this research under contract DE-AR0001063 . Publisher Copyright: © 2022
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