Evidence map›Paper›PMID 28371107›Full record

ArticleHuman brain mapping2017

Using clinically acquired MRI to construct age-specific ADC atlases: Quantifying spatiotemporal ADC changes from birth to 6-year old.

Yangming Ou, Lilla Zöllei, Kallirroi Retzepi, Victor Castro, Sara V Bates, Steve Pieper, Katherine P Andriole, Shawn N Murphy, Randy L Gollub, Patricia Ellen Grant

Abstract read
In one paragraph

Article in Human brain mapping, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

29 citing papers in PubMed, 36 citations in OpenAlex.

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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 3 institutions in 1 country.

Yangming OuPsychiatric Neuroimaging, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.ORCID 0000-0002-7726-6208
Lilla ZölleiLaboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.
Kallirroi RetzepiPsychiatric Neuroimaging, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.
Victor CastroResearch Computing, Partners Healthcare, 1 Constitution Center, Charlestown, Massachusetts.
Sara V BatesDivision of Newborn Medicine, Department of Pediatrics, Massachusetts General Hospital for Children, Harvard Medical School, Boston, Massachusetts.
Steve Piepersomics Inc, Cambridge, Massachusetts.
Katherine P AndrioleDepartment of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Shawn N MurphyResearch Computing, Partners Healthcare, 1 Constitution Center, Charlestown, Massachusetts.
Randy L GollubPsychiatric Neuroimaging, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts.
Patricia Ellen GrantFetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
Harvard University · USBoston Children's Hospital · USBrigham and Women's Hospital · US

Funding

Training and DisseminationP41EB015902 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI WELLS, WILLIAM M. · 2012 to 2022
$20.9M
Mouse Neurodevelopmental Behavior CoreU54HD090255 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI POMEROY, SCOTT LOREN · 2016 to 2020
$5.2M
Career Development Program in Substance Use and Addiction MedicineK12DA043490 · NIDA · MASSACHUSETTS GENERAL HOSPITAL · PI A EDEN EVINS, NANCY A RIGOTTI · 2017 to 2026
$4.7M
mi2b2 Enabled Pediatric Radiological Decision SupportR01EB014947 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI GRANT, PATRICIA ELLEN, HIRSCHTICK, RANDY L · 2012 to 2015
$2.8M
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
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 EB015902NIBIB NIH HHS R01 EB014947NICHD NIH HHS U54 HD090255NIDA NIH HHS K12 DA043490
6 · The paper itself

Abstract

Diffusion imaging is critical for detecting acute brain injury. However, normal apparent diffusion coefficient (ADC) maps change rapidly in early childhood, making abnormality detection difficult. In this article, we explored clinical PACS and electronic healthcare records (EHR) to create age-specific ADC atlases for clinical radiology reference. Using the EHR and three rounds of multiexpert reviews, we found ADC maps from 201 children 0-6 years of age scanned between 2006 and 2013 who had brain MRIs with no reported abnormalities and normal clinical evaluations 2+ years later. These images were grouped in 10 age bins, densely sampling the first 1 year of life (5 bins, including neonates and 4 quarters) and representing the 1-6 year age range (an age bin per year). Unbiased group-wise registration was used to construct ADC atlases for 10 age bins. We used the atlases to quantify (a) cross-sectional normative ADC variations; (b) spatiotemporal heterogeneous ADC changes; and (c) spatiotemporal heterogeneous volumetric changes. The quantified age-specific whole-brain and region-wise ADC values were compared to those from age-matched individual subjects in our study and in multiple existing independent studies. The significance of this study is that we have shown that clinically acquired images can be used to construct normative age-specific atlases. These first of their kind age-specific normative ADC atlases quantitatively characterize changes of myelination-related water diffusion in the first 6 years of life. The quantified voxel-wise spatiotemporal ADC variations provide standard references to assist radiologists toward more objective interpretation of abnormalities in clinical images. Our atlases are available at https://www.nitrc.org/projects/mgh_adcatlases. Hum Brain Mapp 38:3052-3068, 2017. © 2017 Wiley Periodicals, Inc.

Indexed as

Brain MappingDiffusion Magnetic Resonance ImagingAdultBrainBrain InjuriesChildChild, PreschoolCohort StudiesCross-Sectional StudiesElectronic Health RecordsHumansImage Processing, Computer-AssistedInfantInfant, NewbornYoung Adultatlas constructionbig data informaticsclinical imagesdiffusion MRIneurodevelopment

Identifiers

PMID28371107
PMCPMC5426959
OpenAlexW2601330826

What OpenQuestion holds

Textmetadata
LicenceTDM
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.