Evidence map›Paper›PMID 35217204›Full record

ReviewNeuroImage2022

Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact.

Qiuyun Fan, Cornelius Eichner, Maryam Afzali, Lars Mueller, Chantal M W Tax, Mathias Davids, Mirsad Mahmutovic, Boris Keil, Berkin Bilgic, Kawin Setsompop and 16 more

Registry-linked trialOpen access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06244680 (Super-fast 3T Prostate MRI Using High Gradient Strength and Deep Learning), which is not on this map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
6.5field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06244680 completednot on this mapstarted 2023, after this paper: background citation

Super-fast 3T Prostate MRI Using High Gradient Strength and Deep Learning: Initial Experience

TypeobservationalSponsorUniversity Hospital, BonnRan2023 to 2023Enrolled77ConditionsProstate CancerArmsMRI of the prostate
3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Axon Diameter Mapping From Myelin Water Diffusion MRI.IEEE transactions on medical imaging · 2026
    Article
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  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

26 authors at 10 institutions in 7 countries.

Qiuyun FanDepartment of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA.
Cornelius EichnerMax Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany.
Maryam AfzaliCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK; Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9JT, UK.
Lars MuellerLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9JT, UK.
Chantal M W TaxCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK; Image Sciences Institute, University Medical Center (UMC) Utrecht, Utrecht, the Netherlands.
Mathias DavidsAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Mirsad MahmutovicInstitute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany.
Boris KeilInstitute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany.
Berkin BilgicAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
Kawin SetsompopDepartment of Radiology, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
Hong-Hsi LeeAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA.
Qiyuan TianAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA.
Chiara MaffeiAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA.
Gabriel Ramos-LlordénAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA.
Aapo NummenmaaAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA.
Thomas WitzelQ bio Inc., San Carlos, CA, USA.
Anastasia YendikiAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA.
Yi-Qiao SongAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA USA.
Chu-Chung HuangKey Laboratory of Brain Functional Genomics (MOE & STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Shanghai Changning Mental Health Center, Shanghai, China.
Ching-Po LinInstitute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Nikolaus WeiskopfDepartment of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany.
Alfred AnwanderMax Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany.
Derek K JonesCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK.
Bruce R RosenAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
Lawrence L WaldAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
Susie Y HuangAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA. Electronic address: susie.huang@mgh.harvard.edu.
Harvard University · USMax Planck Institute for Human Cognitive and Brain Sciences · DETechnische Hochschule Mittelhessen · DEUniversity of Leeds · GBAthinoula A. Martinos Center for Biomedical Imaging · USCardiff University · GBNational Yang Ming Chiao Tung University · TWShanghai Changning Mental Health Center · CNStanford University · USUniversity Medical Center Utrecht · NL

Funding

CONNECTOME 2.0: DEVELOPING THE NEXT GENERATION HUMAN MRI SCANNER FOR BRIDGING STUDIES OF THE MICRO-, MESO- AND MACRO-CONNECTOMEU01EB026996 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI BASSER, PETER J., HUANG, SUSIE YI · 2018 to 2022
$14.2M
MRI CORTICOGRAPHY: DEVELOPING NEXT GENERATION MICROSCALE HUMAN CORTEX MRI SCANNERU01EB025162 · NIBIB · UNIVERSITY OF CALIFORNIA BERKELEY · PI FEINBERG, DAVID ALAN, LIU, CHUNLEI · 2017 to 2021
$13.4M
The Human Connectome Project (HCP)U01MH093765 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2010 to 2014
$12.1M
Training and Dissemination CoreP41EB030006 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI BRUCE R ROSEN · 2020 to 2026
$10.9M
Project 4P41EB015896 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2012 to 2018
$9.8M
Next generation in-vivo diffusion imaging at submillimeter resolutionR01MH116173 · NIMH · STANFORD UNIVERSITY · PI Yogesh Rathi, Kawin Setsompop · 2018 to 2026
$6.2M
fMRI Technologies for Imaging at the Limit of Biological Spatiotemporal Resolution: Administrative SupplementR01EB019437 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI POLIMENI, JONATHAN RIZZO, SETSOMPOP, KAWIN · 2015 to 2024
$5.5M
Three-Dimensional Patient-Tailored RF Pulses for Spin Echo Neuroimaging at 7 TR01EB016695 · NIBIB · VANDERBILT UNIVERSITY · PI GRISSOM, WILLIAM A · 2014 to 2021
$3.8M
MRI technology for restoring brain image quality for pediatric patients with metallic orthodontic hardwareR01EB028797 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Berkin Bilgic, Jason P Stockmann · 2020 to 2026
$3.0M
Toward a Validated in Vivo Imaging Marker of Axonal Damage Predictive of Progressive Disability in Multiple SclerosisR01NS118187 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI HUANG, SUSIE YI · 2021 to 2025
$2.8M
Rapid MRI acquisition for pediatric low-grade gliomasR01EB020613 · NIBIB · STANFORD UNIVERSITY · PI SETSOMPOP, KAWIN · 2016 to 2019
$2.5M
Revealing tissue microstructure in the brain gray matter in Alzheimer's disease using in vivo high-gradient diffusion MRIDP5OD031854 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI LEE, HONG HSI · 2021 to 2025
$2.1M
NIBIB NIH HHS P41 EB015896NIBIB NIH HHS P41 EB030006NIBIB NIH HHS R01 EB016695NIBIB NIH HHS R01 EB019437NIBIB NIH HHS R01 EB020613NIBIB NIH HHS R01 EB028797NIBIB NIH HHS R03 EB031175NIBIB NIH HHS U01 EB025162NIBIB NIH HHS U01 EB026996NIH HHS DP5 OD031854NIMH NIH HHS R01 MH116173NIMH NIH HHS U01 MH093765NINDS NIH HHS K23 NS096056NINDS NIH HHS R01 NS118187Wellcome TrustWellcome Trust 215944/Z/19/ZWellcome Trust 219536/Z/19/Z
6 · The paper itself

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 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.

Indexed as

ConnectomeBrainChinaDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingHumansaxon diameterbrainclinical applicationsdata sharingDiffusion MRIfiber trackinghigh b-valueHuman Connectome Project (HCP)human connectome scannerperipheral nerve stimulationpreprocessingradio frequency coilsequencetissue microstructurewhite matter

Identifiers

PMID35217204
PMCPMC9121330
OpenAlexW4214569963

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.