Evidence map›Paper›PMID 31692763›Full record

ArticleThe Eurasian journal of medicine2019

Is It Possible to Discriminate Active MS Lesions with Diffusion Weighted Imaging?

Sena Unal, Elif Peker, Seyda Erdogan, Memet Ilhan Erden

Abstract read
In one paragraph

Article in The Eurasian journal of medicine, 2019. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Sena UnalDepartment of Radiology, Ankara University School of Medicine, Ankara, Turkey.ORCID 0000-0001-6680-0789
Elif PekerDepartment of Radiology, Ankara University School of Medicine, Ankara, Turkey.ORCID 0000-0003-3585-6848
Seyda ErdoganDepartment of Neurology, Ankara University School of Medicine, Ankara, Turkey.ORCID 0000-0002-4113-2080
Memet Ilhan ErdenDepartment of Radiology, Ankara University School of Medicine, Ankara, Turkey.ORCID 0000-0002-6274-3841

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivePatients with multiple sclerosis (MS) are at a risk of gadolinium deposition because of multiple control imaging. Therefore, it is important to determine biomarkers that can differentiate active and chronic lesions without using contrast agent. This study aimed to assess mean apparent diffusion coefficient (ADC) values and signal intensities (SI) on diffusion weighted imaging (DWI) values of active and nonactive lesions. MATERIALS AND

methodsWe included 25 patients in this study. We measured mean ADC values and SI on DWI of the randomly selected active and nonactive lesions and normal appearing white matter (NAWM) for all patients with MS. SI on DWI and ADC values were normalized to the SI of the CSF. We compared all of the measurements between active and nonactive lesions, active lesions and NAWM, and nonactive lesions and NAWM. SI on DWI and mean ADC values of normal healthy white matter (NHWM) of control group were measured. A comparison was made between NHWM and NAWM.

resultsFor patients with active lesions, the mean nADC value was 0.35±0.06 for active lesions and 0.30±0.07 for nonactive lesions (p>0.050). The mean nDWI-SI value was 3.69±0.68 for active lesions was 3.39±0.68 for nonactive lesions (p<0.050). When patients with and without active lesions were compared, both nDWI values and nADC values for active and nonactive lesions were statistically insignificant (p>0.050). DISCUSSION: In MS lesions, diffusion alternations can be quantitatively evaluated with ADC mapping. Lesions seen in patients with MS have higher mean ADC values than NAWM and NHWM.

Indexed as

activeapparent diffusion coefficientDiffusionmultiple sclerosis

Identifiers

PMID31692763
PMCPMC6812928

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.