Evidence map›Paper›PMID 33772083›Full record

ArticleScientific reports2021

Free-water diffusion tensor imaging improves the accuracy and sensitivity of white matter analysis in Alzheimer's disease.

Maurizio Bergamino, Ryan R Walsh, Ashley M Stokes

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05804643 (Development and Optimization of Novel MRI Techniques on Evaluation of Therapeutic Effects for Lymphedema Secondary to Breast Cancer Treatment), which is not on this map. Cited by 71 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed, 3 pooled it
10.4field-weighted citation impact, top 1% 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.

NCT05804643 recruitingnot on this mapstarted 2023, after this paper: background citation

Development and Optimization of Novel MRI Techniques on Evaluation of Therapeutic Effects for Lymphedema Secondary to Breast Cancer Treatment: An Integrated Study of Pre-clinical Animal Models and Clinical Follow-up

TypeobservationalSponsorNational Taiwan University HospitalRan2023 to 2026Enrolled210ConditionsLymphedema of Upper LimbArmsDiffusion magnetic resonance imaging
3 · Its place in the literature

Who cites it

71 citing papers in PubMed, 3 syntheses or guidelines pooled it, 114 citations in OpenAlex.

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  3. Predicting glioblastoma progression using MR diffusion tensor imaging: A systematic review.Journal of neuroimaging : official journal of the American Society of Neuroimaging
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11 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

3 authors at 1 institution in 1 country.

Maurizio BergaminoDivision of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, 85013, USA.
Ryan R WalshMuhammad Ali Parkinson Center, Barrow Neurological Institute, Phoenix, AZ, 85013, USA.
Ashley M StokesDivision of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, 85013, USA. ashley.stokes@barrowneuro.org.
Barrow Neurological Institute · US

Funding

Smartphone-Based "Burst" Cognitive AssessmentsP01AG003991 · NIA · WASHINGTON UNIVERSITY · PI JOHN MORRIS · 1985 to 2026
$69.5M
WASHINGTON UNIVERSITY ALZHEIMERS DISEASE RESEARCH CENTERP50AG005681 · NIA · WASHINGTON UNIVERSITY · PI FAGAN, ANNE · 1985 to 2019
$52.1M
Research Education ComponentP30AG066444 · NIA · WASHINGTON UNIVERSITY · PI DAVID M. HOLTZMAN · 2020 to 2026
$28.7M
MORPHOMETRY BIOMEDICAL INFORMATICS RESEARCH NETWORKU24RR021382 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2004 to 2008
$24.1M
STRUCTURE, FUNCTION AND COGNITION IN SCHIZOPHRENIAP50MH071616 · NIMH · WASHINGTON UNIVERSITY · PI BARCH, DEANNA · 2004 to 2008
$11.2M
Functional-anatomic exploration of cognitive controlR01AG021910 · NIA · WASHINGTON UNIVERSITY · PI BUCKNER, RANDY L · 2005 to 2009
$1.2M
NCRR NIH HHS U24 RR021382NIA NIH HHS P01 AG003991NIA NIH HHS P30 AG066444NIA NIH HHS P50 AG005681NIA NIH HHS R01 AG021910NIMH NIH HHS P50 MH071616
6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) based diffusion tensor imaging (DTI) can assess white matter (WM) integrity through several metrics, such as fractional anisotropy (FA), axial/radial diffusivities (AxD/RD), and mode of anisotropy (MA). Standard DTI is susceptible to the effects of extracellular free water (FW), which can be removed using an advanced free-water DTI (FW-DTI) model. The purpose of this study was to compare standard and FW-DTI metrics in the context of Alzheimer's disease (AD). Data were obtained from the Open Access Series of Imaging Studies (OASIS-3) database and included both healthy controls (HC) and mild-to-moderate AD. With both standard and FW-DTI, decreased FA was found in AD, mainly in the corpus callosum and fornix, consistent with neurodegenerative mechanisms. Widespread higher AxD and RD were observed with standard DTI; however, the FW index, indicative of AD-associated neurodegeneration, was significantly elevated in these regions in AD, highlighting the potential impact of free water contributions on standard DTI in neurodegenerative pathologies. Using FW-DTI, improved consistency was observed in FA, AxD, and RD, and the complementary FW index was higher in the AD group as expected. With both standard and FW-DTI, higher values of MA coupled with higher values of FA in AD were found in the anterior thalamic radiation and cortico-spinal tract, most likely arising from a loss of crossing fibers. In conclusion, FW-DTI better reflects the underlying pathology of AD and improves the accuracy of DTI metrics related to WM integrity in Alzheimer's disease.

Indexed as

AgedAged, 80 and overAlzheimer DiseaseAnisotropyBiomarkersCognitive DysfunctionDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingHumansMiddle AgedWhite MatterBiomarkers

Identifiers

PMID33772083
PMCPMC7998032
OpenAlexW3137667308

What OpenQuestion holds

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LicenceCC BY
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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.