Evidence map›Paper›PMID 34464739›Full record

ReviewNeuroImage2021

Connectome 2.0: Developing the next-generation ultra-high gradient strength human MRI scanner for bridging studies of the micro-, meso- and macro-connectome.

Susie Y Huang, Thomas Witzel, Boris Keil, Alina Scholz, Mathias Davids, Peter Dietz, Elmar Rummert, Rebecca Ramb, John E Kirsch, Anastasia Yendiki and 25 more

Registry-linked trialAbstract readReview
In one paragraph

Review in NeuroImage, 2021. 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 115 papers.

0numbers the graph read from it
0cells of the map it votes in
115citing papers in PubMed
–field-weighted citation impact
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

115 citing papers in PubMed.

  1. Article
  2. Article
  3. Group-Patch Joint Compression: Compressing Dynamic BMagnetic resonance in medicine · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Axon Diameter Mapping From Myelin Water Diffusion MRI.IEEE transactions on medical imaging · 2026
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. A human subcortical connectome at 400 μm resolution.bioRxiv : the preprint server for biology · 2026
    Article
  20. Article

55 more citing papers are in PubMed but not listed here.

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

35 authors.

Susie Y HuangAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: Susie.Huang@MGH.HARVARD.EDU.
Thomas WitzelQ bio Inc., San Carlos, CA, USA.
Boris KeilInstitute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany.
Alina ScholzInstitute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany.
Mathias DavidsAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Peter DietzSiemens Healthineers, Erlangen, Germany.
Elmar RummertSiemens Healthineers, Erlangen, Germany.
Rebecca RambSiemens Healthineers, Erlangen, Germany.
John E KirschAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Anastasia YendikiAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Qiuyun FanAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Qiyuan TianAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Gabriel Ramos-LlordénAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Hong-Hsi LeeAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Aapo NummenmaaAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Berkin BilgicAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Kawin SetsompopRadiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA, USA.
Fuyixue WangAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Alexandru V AvramEunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
Michal KomloshEunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
Dan BenjaminiEunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
Kulam Najmudeen MagdoomEunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
Sudhir PathakLearning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA.
Walter SchneiderLearning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA.
Dmitry S NovikovCenter for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, USA.
Els FieremansCenter for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, USA.
Slimane TounektiAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Choukri MekkaouiAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Jean AugustinackAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Daniel BergerDepartment of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA.
Alexander Shapson-CoeDepartment of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA.
Jeff LichtmanDepartment of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA.
Peter J BasserEunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
Lawrence L WaldAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Bruce R RosenAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Riccardo Lattanzi · 2014 to 2026
$19.3M
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
Training and Dissemination CoreP41EB030006 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Susie Yi Huang · 2020 to 2026
$10.9M
Mesoscopic Biomarkers of Neurodegeneration with Diffusion MRIR01NS088040 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FIEREMANS, ELS, NOVIKOV, DMITRY S · 2014 to 2023
$5.2M
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
Random Matrix Theory-Based Noise Removal in MRIR01EB027075 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FIEREMANS, ELS, NOVIKOV, DMITRY S · 2019 to 2022
$2.7M
Free-Breathing Diffusion Tensor MRI in Patients Following Myocardial InfarctionR01HL131635 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI MEKKAOUI, CHOUKRI · 2016 to 2020
$2.1M
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
Characterizing axonal damage in multiple sclerosis using TractCaliber MRIK23NS096056 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI HUANG, SUSIE YI · 2016 to 2020
$877k
NHLBI NIH HHS R01 HL131635NIBIB NIH HHS P41 EB017183NIBIB NIH HHS P41 EB030006NIBIB NIH HHS R01 EB027075NIBIB NIH HHS R01 EB028797NIBIB NIH HHS U01 EB025162NIBIB NIH HHS U01 EB026996NIH HHS DP5 OD031854NINDS NIH HHS K23 NS096056NINDS NIH HHS R01 NS088040NINDS NIH HHS R01 NS118187
6 · The paper itself

Abstract

The first phase of the Human Connectome Project pioneered advances in MRI technology for mapping the macroscopic structural connections of the living human brain through the engineering of a whole-body human MRI scanner equipped with maximum gradient strength of 300 mT/m, the highest ever achieved for human imaging. While this instrument has made important contributions to the understanding of macroscale connectional topology, it has also demonstrated the potential of dedicated high-gradient performance scanners to provide unparalleled in vivo assessment of neural tissue microstructure. Building on the initial groundwork laid by the original Connectome scanner, we have now embarked on an international, multi-site effort to build the next-generation human 3T Connectome scanner (Connectome 2.0) optimized for the study of neural tissue microstructure and connectional anatomy across multiple length scales. In order to maximize the resolution of this in vivo microscope for studies of the living human brain, we will push the diffusion resolution limit to unprecedented levels by (1) nearly doubling the current maximum gradient strength from 300 mT/m to 500 mT/m and tripling the maximum slew rate from 200 T/m/s to 600 T/m/s through the design of a one-of-a-kind head gradient coil optimized to minimize peripheral nerve stimulation; (2) developing high-sensitivity multi-channel radiofrequency receive coils for in vivo and ex vivo human brain imaging; (3) incorporating dynamic field monitoring to minimize image distortions and artifacts; (4) developing new pulse sequences to integrate the strongest diffusion encoding and highest spatial resolution ever achieved in the living human brain; and (5) calibrating the measurements obtained from this next-generation instrument through systematic validation of diffusion microstructural metrics in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales with accompanying diffusion simulations in histology-based micro-geometries. We envision creating the ultimate diffusion MRI instrument capable of capturing the complex multi-scale organization of the living human brain - from the microscopic scale needed to probe cellular geometry, heterogeneity and plasticity, to the mesoscopic scale for quantifying the distinctions in cortical structure and connectivity that define cyto- and myeloarchitectonic boundaries, to improvements in estimates of macroscopic connectivity.

Indexed as

BrainConnectomeDiffusion Magnetic Resonance ImagingFemaleHumansMaleNeuroimagingPhantoms, ImagingAxon diameterConnectomeDiffusion MRIGray matterHead gradientMulti-scale modelingPeripheral nerve stimulationTissue microstructureValidation

Identifiers

PMID34464739
PMCPMC8863543

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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.