Evidence map›Paper›PMID 32745680›Full record

ArticleNeuroImage2020

Axon diameter index estimation independent of fiber orientation distribution using high-gradient diffusion MRI.

Qiuyun Fan, Aapo Nummenmaa, Thomas Witzel, Ned Ohringer, Qiyuan Tian, Kawin Setsompop, Eric C Klawiter, Bruce R Rosen, Lawrence L Wald, Susie Y Huang

Open access · goldAbstract read
In one paragraph

Article in NeuroImage, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
5.6field-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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed, 76 citations in OpenAlex.

  1. Article
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  7. Axon Diameter Mapping From Myelin Water Diffusion MRI.IEEE transactions on medical imaging · 2026
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  11. ArXiv · 2025
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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

10 authors at 5 institutions in 1 country.

Qiuyun FanAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States. Electronic address: qiuyun.fan@mgh.harvard.edu.
Aapo NummenmaaAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States.
Thomas WitzelAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States.
Ned OhringerAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States.
Qiyuan TianAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States.
Kawin SetsompopAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States.
Eric C KlawiterHarvard Medical School, Boston, MA, United States; Department of Neurology, Massachusetts General Hospital, Boston, MA, United States.
Bruce R RosenAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States.
Lawrence L WaldAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States.
Susie Y HuangAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States.
Harvard University · USHarvard–MIT Division of Health Sciences and Technology · USAthinoula A. Martinos Center for Biomedical Imaging · USMassachusetts General Hospital · USMassachusetts Institute of Technology · US

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
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 Aapo Nummenmaa · 2020 to 2026
$10.9M
Project 4P41EB015896 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2012 to 2018
$9.8M
Parallel Excitation Methods for High Field MRIR01EB006847 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI WALD, LAWRENCE L · 2007 to 2020
$5.4M
A Storage Area Network for Structural and Functional Image AnalysisS10RR023401 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2009 to 2009
$2.0M
SILICON GRAPHICS PRISM EXTREME 128P/1TBS10RR023043 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI SORENSEN, ALMA GREGORY · 2006 to 2006
$1.5M
Disconnection as a model for cognitive dysfunction in multiple sclerosisK23NS078044 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI KLAWITER, ERIC · 2012 to 2016
$956k
Characterizing axonal damage in multiple sclerosis using TractCaliber MRIK23NS096056 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI HUANG, SUSIE YI · 2016 to 2020
$877k
Modeling TMS-induced Cortical Network ActivityR00EB015445 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI NUMMENMAA, AAPO · 2015 to 2017
$747k
Computeserver Structural &Functional Image AnalysisS10RR019307 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2004 to 2004
$496k
NCRR NIH HHS S10 RR019307NCRR NIH HHS S10 RR023043NCRR NIH HHS S10 RR023401NIBIB NIH HHS P41 EB015896NIBIB NIH HHS P41 EB030006NIBIB NIH HHS R00 EB015445NIBIB NIH HHS R01 EB006847NIBIB NIH HHS U01 EB026996NIMH NIH HHS U01 MH093765NINDS NIH HHS K23 NS078044NINDS NIH HHS K23 NS096056
6 · The paper itself

Abstract

Axon diameter mapping using high-gradient diffusion MRI has generated great interest as a noninvasive tool for studying trends in axonal size in the human brain. One of the main barriers to mapping axon diameter across the whole brain is accounting for complex white matter fiber configurations (e.g., crossings and fanning), which are prevalent throughout the brain. Here, we present a framework for generalizing axon diameter index estimation to the whole brain independent of the underlying fiber orientation distribution using the spherical mean technique (SMT). This approach is shown to significantly benefit from the use of real-valued diffusion data with Gaussian noise, which reduces the systematic bias in the estimated parameters resulting from the elevation of the noise floor when using magnitude data with Rician noise. We demonstrate the feasibility of obtaining whole-brain orientationally invariant estimates of axon diameter index and relative volume fractions in six healthy human volunteers using real-valued diffusion data acquired on a dedicated high-gradient 3-Tesla human MRI scanner with 300 mT/m maximum gradient strength. The trends in axon diameter index are consistent with known variations in axon diameter from histology and demonstrate the potential of this generalized framework for revealing coherent patterns in axonal structure throughout the living human brain. The use of real-valued diffusion data provides a viable solution for eliminating the Rician noise floor and should be considered for all spherical mean approaches to microstructural parameter estimation.

Indexed as

AdultAxonsDiffusion Magnetic Resonance ImagingFemaleHumansNeuroimagingWhite MatterYoung AdultAxon diameterDiffusion MRIHigh b-valueHuman Connectome Project (HCP)Human connectome scannerSpherical mean technique (SMT)Tissue microstructureWhite matter

Identifiers

PMID32745680
PMCPMC7736138
OpenAlexW3046919835

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

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.