Evidence map›Paper›PMID 37501362›Full record

ArticleAnnals of clinical and translational neurology2023

Predictive values of spinal cord diffusion magnetic resonance imaging to characterize outcomes after contusion injury.

Rakib Uddin Ahmed, Daniel Medina-Aguinaga, Shawns Adams, Chase A Knibbe, Monique Morgan, Destiny Gibson, Joo-Won Kim, Mayur Sharma, Manpreet Chopra, Steven Davison and 8 more

Open access · goldAbstract read
In one paragraph

Article in Annals of clinical and translational neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

18 authors at 4 institutions in 1 country.

Rakib Uddin AhmedDepartment of Neurological Surgery and Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, Kentucky, USA.ORCID 0000-0002-8985-3717
Daniel Medina-AguinagaDepartment of Anatomical Sciences and Neurobiology, University of Louisville, Louisville, Kentucky, USA.
Shawns AdamsDepartment of Neurosurgery, Duke University, Raleigh, North Carolina, USA.
Chase A KnibbeDepartment of Neurological Surgery and Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, Kentucky, USA.
Monique MorganDepartment of Neurological Surgery and Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, Kentucky, USA.
Destiny GibsonDepartment of Neurological Surgery and Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, Kentucky, USA.
Joo-Won KimDepartment of Radiology, Baylor College of Medicine, Houston, Texas, USA.
Mayur SharmaDepartment of Neurological Surgery and Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, Kentucky, USA.
Manpreet ChopraDepartment of Neurological Surgery and Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, Kentucky, USA.
Steven DavisonComparative Medicine Research Unit, University of Louisville, Louisville, Kentucky, USA.
Leslie C SherwoodComparative Medicine Research Unit, University of Louisville, Louisville, Kentucky, USA.
M J NegahdarDepartment of Radiology, University of Louisville, Louisville, Kentucky, USA.
Robert BertDepartment of Radiology, University of Louisville, Louisville, Kentucky, USA.
Beatrice UgiliwenezaDepartment of Neurological Surgery and Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, Kentucky, USA.
Charles HubscherDepartment of Anatomical Sciences and Neurobiology, University of Louisville, Louisville, Kentucky, USA.
Matthew D BuddeDepartment of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Junqian XuDepartment of Radiology, Baylor College of Medicine, Houston, Texas, USA.ORCID 0000-0001-8438-2066
Maxwell BoakyeDepartment of Neurological Surgery and Kentucky Spinal Cord Injury Research Center, University of Louisville, Louisville, Kentucky, USA.
University of Louisville · USBaylor College of Medicine · USDuke University · USMedical College of Wisconsin · US

Funding

Combined DDE MRI and Electrophysiology Prediction of Spinal Cord InjuryR21NS114982 · NINDS · UNIVERSITY OF LOUISVILLE · PI BOAKYE, MAXWELL · 2020 to 2020
$444k
NINDS NIH HHS R21 NS114982
6 · The paper itself

Abstract

objectivesTo explore filtered diffusion-weighted imaging (fDWI), in comparison with conventional magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI), as a predictor for long-term locomotor and urodynamic (UD) outcomes in Yucatan minipig model of spinal cord injury (SCI). Additionally, electrical conductivity of neural tissue using D-waves above and below the injury was measured to assess correlations between fDWI and D-waves data.

methodsEleven minipigs with contusion SCI at T8-T10 level underwent MRI at 3T 4 h. post-SCI. Parameters extracted from region of interest analysis included D

resultsTwo groups of pigs were found based on the PTIBS at week 12 (p < 0.0001) post-SCI and were labeled "poor" and "good" recovery. D-waves amplitude decreased below injury and increased above injury. UD outcomes pre/post SCI changed significantly. Conventional MRI metrics from T

interpretationSimilar to small animal studies, fDWI from acute imaging after SCI is a promising predictor for functional outcomes in large animals.

Indexed as

ContusionsSpinal Cord InjuriesAnimalsDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingSwineSwine, Miniature

Identifiers

PMID37501362
PMCPMC10502634
OpenAlexW4385330378

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.