Evidence map›Paper›PMID 24778769›Full record

ReviewWorld journal of radiology2014

Clinical decision support systems for brain tumor characterization using advanced magnetic resonance imaging techniques.

Evangelia Tsolaki, Evanthia Kousi, Patricia Svolos, Efthychia Kapsalaki, Kyriaki Theodorou, Constastine Kappas, Ioannis Tsougos

Abstract readReview
In one paragraph

Review in World journal of radiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

7 authors.

Evangelia TsolakiEvangelia Tsolaki, Evanthia Kousi, Patricia Svolos, Kyriaki Theodorou, Constastine Kappas, Ioannis Tsougos, Medical Physics Department, University of Thessaly, Biopolis, 41110 Larissa, Greece.
Evanthia KousiEvangelia Tsolaki, Evanthia Kousi, Patricia Svolos, Kyriaki Theodorou, Constastine Kappas, Ioannis Tsougos, Medical Physics Department, University of Thessaly, Biopolis, 41110 Larissa, Greece.
Patricia SvolosEvangelia Tsolaki, Evanthia Kousi, Patricia Svolos, Kyriaki Theodorou, Constastine Kappas, Ioannis Tsougos, Medical Physics Department, University of Thessaly, Biopolis, 41110 Larissa, Greece.
Efthychia KapsalakiEvangelia Tsolaki, Evanthia Kousi, Patricia Svolos, Kyriaki Theodorou, Constastine Kappas, Ioannis Tsougos, Medical Physics Department, University of Thessaly, Biopolis, 41110 Larissa, Greece.
Kyriaki TheodorouEvangelia Tsolaki, Evanthia Kousi, Patricia Svolos, Kyriaki Theodorou, Constastine Kappas, Ioannis Tsougos, Medical Physics Department, University of Thessaly, Biopolis, 41110 Larissa, Greece.
Constastine KappasEvangelia Tsolaki, Evanthia Kousi, Patricia Svolos, Kyriaki Theodorou, Constastine Kappas, Ioannis Tsougos, Medical Physics Department, University of Thessaly, Biopolis, 41110 Larissa, Greece.
Ioannis TsougosEvangelia Tsolaki, Evanthia Kousi, Patricia Svolos, Kyriaki Theodorou, Constastine Kappas, Ioannis Tsougos, Medical Physics Department, University of Thessaly, Biopolis, 41110 Larissa, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, advanced magnetic resonance imaging (MRI) techniques, such as magnetic resonance spectroscopy, diffusion weighted imaging, diffusion tensor imaging and perfusion weighted imaging have been used in order to resolve demanding diagnostic problems such as brain tumor characterization and grading, as these techniques offer a more detailed and non-invasive evaluation of the area under study. In the last decade a great effort has been made to import and utilize intelligent systems in the so-called clinical decision support systems (CDSS) for automatic processing, classification, evaluation and representation of MRI data in order for advanced MRI techniques to become a part of the clinical routine, since the amount of data from the aforementioned techniques has gradually increased. Hence, the purpose of the current review article is two-fold. The first is to review and evaluate the progress that has been made towards the utilization of CDSS based on data from advanced MRI techniques. The second is to analyze and propose the future work that has to be done, based on the existing problems and challenges, especially taking into account the new imaging techniques and parameters that can be introduced into intelligent systems to significantly improve their diagnostic specificity and clinical application.

Indexed as

Decision support systemsDiffusion tensor imagingDiffusion weighted imagingMagnetic resonance imagingMagnetic resonance spectroscopyPattern recognitionPerfusion weighted imaging

Identifiers

PMID24778769
PMCPMC4000611

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.