Evidence map›Paper›PMID 22749050›Full record

SynthesisAcademic radiology2012

Diagnostic accuracy using diffusion tensor imaging in the diagnosis of ALS: a meta-analysis.

Bradley R Foerster, Ben A Dwamena, Myria Petrou, Ruth C Carlos, Brian C Callaghan, Martin G Pomper

Abstract readMeta-Analysis
In one paragraph

Synthesis in Academic radiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
5.7field-weighted citation impact, top 4% 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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 50 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. MR Biomarkers of Degenerative Brain Disorders Derived From Diffusion Imaging.Journal of magnetic resonance imaging : JMRI · 2020
    Review
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Neuroimaging Endpoints in Amyotrophic Lateral Sclerosis.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2017
    Review
  14. Article
  15. Review
  16. Neuroimaging as a New Diagnostic Modality in Amyotrophic Lateral Sclerosis.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2015
    Review
  17. Diffusion tensor MRI of the corpus callosum in amyotrophic lateral sclerosis.Journal of magnetic resonance imaging : JMRI · 2014
    Article
  18. Article
  19. Multimodal MRI as a diagnostic biomarker for amyotrophic lateral sclerosis.Annals of clinical and translational neurology · 2014
    Article
  20. 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

6 authors at 2 institutions in 1 country.

Bradley R FoersterRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA. compfun@umich.edu
Ben A Dwamena
Myria Petrou
Ruth C Carlos
Brian C Callaghan
Martin G Pomper
University of Michigan–Ann Arbor · USJohns Hopkins University · US

Funding

Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI Rosalie Wollett · 1985 to 2026
$208.6M
NCI NIH HHS P30 CA006973
6 · The paper itself

Abstract

RATIONALE AND

objectivesA number of studies have reported decreases in fractional anistropy (FA) in amyotrophic lateral sclerosis using diffusion tensor imaging (DTI). The purpose of this study was to perform a meta-analysis in order to estimate the diagnostic test accuracy measures of DTI for the diagnosis of amyotrophic lateral sclerosis (ALS). MATERIALS AND

methodsWe searched MEDLINE (1966-April 2011), EMBASE (1999-April 2011), CINAHL (1999-April 2011), and Cochrane (2005-April 2011) databases to identify studies that measured FA in ALS subjects. Human, single-center studies using a DTI region of interest (ROI) or tractography techniques were used to compare FA values along the brain corticospinal tracts between ALS subjects and healthy controls. There were no language restrictions. Independent extraction of articles by 2 authors using predefined data fields including study quality indicators. We identified 30 case-control studies that used region of interest or tractography DTI techniques. We applied binormal receiver operative characteristic (ROC) curve analysis to assign specificity and sensitivity for each study. We applied the bivariate mixed-effects regression model using the Markov Chain Monte Carlo Simulation to calculate summary estimates for the sensitivity and specificity. We used the metan module in Stata, version 11.0, to calculate the area under the ROC curve, diagnostic odds ratio and the test effectiveness summary estimates.

resultsThe pooled sensitivity was 0.65 (95% CI 0.61-0.69); the pooled specificity, 0.67 (95% CI 0.63-0.72); the pooled diagnostic odds ratio, 1.88 (95% CI 1.46-2.30); the pooled test effectiveness, 1.04 (95% CI 0.81-1.27); and the pooled area under the ROC curve, 0.76 (95% CI 0.71-0.81). Subanalyses comparing magnetic resonance imaging (MRI) field strength (1.5T vs. 3.0T) and brain location (corticospinal tract average vs. internal capsule) revealed no significant differences in the test accuracy measures. Reference standard used for the diagnosis of ALS was the El Escorial criteria. There was at least moderate heterogeneity between the studies. True study quality is uncertain.

conclusionThe discriminatory capability of DTI to make a diagnosis of ALS is only modest. There were no significant differences in the diagnostic test accuracy summary estimates with respect to MRI field strength or brain location.

Indexed as

Amyotrophic Lateral SclerosisAnisotropyDiffusion Tensor ImagingHumansMonte Carlo MethodROC CurveSensitivity and Specificity

Identifiers

PMID22749050
PMCPMC4337857
OpenAlexW99998899

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.