Evidence map›Paper›PMID 27242476›Full record

ReviewFrontiers in human neuroscience2016

Studying Autism Spectrum Disorder with Structural and Diffusion Magnetic Resonance Imaging: A Survey.

Marwa M T Ismail, Robert S Keynton, Mahmoud M M O Mostapha, Ahmed H ElTanboly, Manuel F Casanova, Georgy L Gimel'farb, Ayman El-Baz

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in human neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
6.7field-weighted citation impact, top 3% 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

41 citing papers in PubMed, 1 synthesis or guideline pooled it, 101 citations in OpenAlex.

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  19. The Role of Structure MRI in Diagnosing Autism.Diagnostics (Basel, Switzerland) · 2022
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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 at 3 institutions in 2 countries.

Marwa M T IsmailBioImaging Laboratory, Department of Bioengineering, University of Louisville Louisville, KY, USA.
Robert S KeyntonBioImaging Laboratory, Department of Bioengineering, University of Louisville Louisville, KY, USA.
Mahmoud M M O MostaphaBioImaging Laboratory, Department of Bioengineering, University of Louisville Louisville, KY, USA.
Ahmed H ElTanbolyBioImaging Laboratory, Department of Bioengineering, University of Louisville Louisville, KY, USA.
Manuel F CasanovaDepartments of Pediatrics and Biomedical Sciences, University of South Carolina Columbia, SC, USA.
Georgy L Gimel'farbDepartment of Computer Science, University of Auckland Auckland, New Zealand.
Ayman El-BazBioImaging Laboratory, Department of Bioengineering, University of Louisville Louisville, KY, USA.
University of Louisville · USUniversity of Auckland · NZUniversity of South Carolina · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics.

Indexed as

autismdiffusion tensor MRIlife stagesmulti-modal approachesstructural MRI

Identifiers

PMID27242476
PMCPMC4862981
OpenAlexW2398481640

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.