Evidence map›Paper›PMID 34855576›Full record

ArticleThe journal of spinal cord medicine2023

Correlations of diffusion tensor imaging and clinical measures with spinal cord cross-sectional area measurements in pediatric spinal cord injury patients.

Devon M Middleton, Shiva Shahrampour, Laura Krisa, Winston Liu, Govind Nair, Steven Jacobson, Chris J Conklin, Mahdi Alizadeh, Scott H Faro, M J Mulcahey and 1 more

Abstract read
In one paragraph

Article in The journal of spinal cord medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

11 authors.

Devon M MiddletonDepartment of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.
Shiva ShahrampourDepartment of Bioengineering, Temple University, Philadelphia, Pennsylvania, USA.
Laura KrisaCollege of Rehabilitation Sciences, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.
Winston LiuSchool of Medicine, Duke University, Durham, North Carolina, USA.
Govind NairNational Institutes of Health, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA.
Steven JacobsonNational Institutes of Health, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA.
Chris J ConklinBioclinica, Princeton, New Jersey, USA.
Mahdi AlizadehDepartment of Neurosurgery, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.
Scott H FaroDepartment of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.
M J MulcaheyCollege of Rehabilitation Sciences, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.
Feroze B MohamedDepartment of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.

Funding

Medical Scientist Training Program Training GrantT32GM145449 · NIGMS · DUKE UNIVERSITY · PI Christopher D Kontos · 2022 to 2026
$6.6M
Neuroimaging based on DTI as a biomarker for spinal cord injury in children.R01NS079635 · NINDS · THOMAS JEFFERSON UNIVERSITY · PI MOHAMED, FEROZE B, MULCAHEY-HERSHEY, MARYJANE · 2013 to 2017
$1.7M
NIGMS NIH HHS T32 GM145449NINDS NIH HHS R01 NS079635
6 · The paper itself

Abstract

purposeThe purpose of this work was to employ a semi-automatic method for measuring spinal cord cross-sectional area (SCCSA) and investigate the correlations between diffusion tensor imaging (DTI) metrics and SCCSA for the cervical and thoracic spinal cord for typically developing pediatric subjects and pediatric subject with spinal cord injury.

methodsTen typically developing (TD) pediatric subjects and ten pediatric subjects with spinal cord injury (SCI) were imaged using a Siemens Verio 3 T MR scanner to acquire DTI and high-resolution anatomic scans covering the cervical and thoracic spinal cord (C1-T12). SCCSA was measured using a semi-automated edge detection algorithm for the entire spinal cord. DTI metrics were obtained from whole cord axial ROIs at each vertebral level. SCCSA measures were compared to DTI metrics by vertebral level throughout the entire cord, and above and below the injury site. Correlation analysis was performed to compare SCCSA, DTI and clinical measures as determined by the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) examination.

resultsIn subjects with SCI, FA and SCCSA had a positive correlation (r = 0.81,

conclusionThe ability to quickly and effectively measure SCCSA in subjects with SCI has the potential to allow for a better understanding of the progression of atrophy following a SCI. Correlations between cord cross section and DTI metrics by vertebral level suggest that imaging inferior and superior to lesion may yield useful information for diagnosis and prognosis.

Indexed as

Spinal Cord InjuriesChildDiffusion Tensor ImagingHumansPrognosisSpinal CordDiffusion imagingPediatric spine imagingSCCSASCI

Identifiers

PMID34855576
PMCPMC10653768

What OpenQuestion holds

Textmetadata
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.