Evidence map›Paper›PMID 38073070›Full record

ArticleMagnetic resonance in medicine2024

Facilitating diffusion tensor imaging of the brain during continuous gross head motion with first and second order motion compensating diffusion gradients.

Danielle Kara, Katherine Koenig, Mark Lowe, Christopher T Nguyen, Ken Sakaie

Open access · hybridAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
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

5 authors at 1 institution in 1 country.

Danielle KaraCardiovascular Innovation Research Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA.ORCID 0000-0001-8369-798X
Katherine KoenigImaging Sciences, Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Mark LoweImaging Sciences, Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Christopher T NguyenCardiovascular Innovation Research Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA.ORCID 0000-0003-1475-2329
Ken SakaieImaging Sciences, Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Cleveland Clinic · US

Funding

Serial evaluation of cardioprotective effects of exercise training in heart failure using cardiac diffusion tensor MRIR01HL151704 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI NGUYEN, CHRISTOPHER T · 2020 to 2024
$3.4M
Microstructural Response of the Myocardium to Mechanical LoadR01HL159010 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI MEKKAOUI, CHOUKRI, NGUYEN, CHRISTOPHER T · 2021 to 2024
$3.2M
Modeling, measurement and prediction of cardiac magneto-stimulation thresholdsR01EB033853 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Bastien Guerin, Christopher T Nguyen · 2023 to 2026
$2.4M
NHLBI NIH HHS R01 HL151704NHLBI NIH HHS R01 HL159010NIBIB NIH HHS R01 EB033853NIH HHS R01 EB033853NIH HHS R01 HL151704NIH HHS R01 HL159010
6 · The paper itself

Abstract

purposeTo demonstrate the feasibility of motion compensating diffusion gradient schemes in the acquisition of quality diffusion tensor images (DTI) of the brain during continuous gross head motion.

methodsFive healthy subjects were scanned using a clinical 3 T MRI with and without continuous head motion. For one volunteer, DTI data was acquired using standard (M0) diffusion-weighted (DW) gradients, and first (M1) and second (M2) order gradient schemes that were previously developed for use in cardiac DTI. In four additional volunteers, DTI data was acquired with M0 and M2 gradients. DTI parameters were calculated and compared with established retrospective motion corrections.

resultsIn the absence of motion, DTI parameters calculated from M0, M1, and M2 data were consistent. In the presence of motion, up to 44% of DW images acquired with M0 gradients were corrupted by signal dropout, compared to 0% of the M2 images. In voxelwise comparisons, DTI parameters calculated using motion-M0 data were elevated compared to reference data. Retrospective corrections for extreme motion applied to motion-M0 data did not improve consistency with reference data in cases where motion corrupted >15% of DW images. In contrast, DTI parameters calculated with motion-M2 data were consistent with reference data.

conclusionThis proof-of-principle study demonstrates that motion compensating diffusion gradients can mitigate artifacts because of continuous motion in DTI of the brain and offers promise for improved DTI accessibility. Further study will be necessary to determine the robustness of the approach in patient populations with high susceptibility to head motion.

Indexed as

BrainDiffusion Tensor ImagingDiffusion Magnetic Resonance ImagingHumansMagnetic Resonance ImagingMotionRetrospective Studiesbraindiffusion tensor imagingmotion compensation

Identifiers

PMID38073070
PMCPMC10872734
OpenAlexW4389570297

What OpenQuestion holds

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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.