Evidence map›Paper›PMID 35527877›Full record

ReviewRSC advances2019

Current and future functional imaging techniques for post-traumatic stress disorder.

Alisha Prasad, Ardalan Chaichi, D Parker Kelley, Joseph Francis, Manas Ranjan Gartia

Open access · goldAbstract readReview
In one paragraph

Review in RSC advances, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

14 citing papers in PubMed, 30 citations in OpenAlex.

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  11. Advances in translational imaging of the microcirculation.Microcirculation (New York, N.Y. : 1994) · 2021
    Review
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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

5 authors at 1 institution in 1 country.

Alisha PrasadDepartment of Mechanical and Industrial Engineering, Louisiana State University Baton Rouge LA 70803 USA mgartia@lsu.edu.ORCID https://orcid.org/0000-0002-2583-7427
Ardalan ChaichiDepartment of Mechanical and Industrial Engineering, Louisiana State University Baton Rouge LA 70803 USA mgartia@lsu.edu.
D Parker KelleyComparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University Baton Rouge LA 70803 USA jfrancis@lsu.edu.ORCID https://orcid.org/0000-0001-8492-2704
Joseph FrancisComparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University Baton Rouge LA 70803 USA jfrancis@lsu.edu.ORCID https://orcid.org/0000-0002-9502-4579
Manas Ranjan GartiaDepartment of Mechanical and Industrial Engineering, Louisiana State University Baton Rouge LA 70803 USA mgartia@lsu.edu.ORCID https://orcid.org/0000-0001-6243-6780
Louisiana State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Posttraumatic stress disorder (PTSD) is a trauma and stressor related psychiatric disorder associated with structural, metabolic, and molecular alternations in several brain regions including diverse cortical areas, neuroendocrine regions, the striatum, dopaminergic, adrenergic and serotonergic pathways, and the limbic system. We are in critical need of novel therapeutics and biomarkers for PTSD and a deep understanding of cutting edge imaging and spectroscopy methods is necessary for the development of promising new approaches to better diagnose and treat the disorder. According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) criterion, all forms of traumatic stress-induced disorder are considered acute stress disorder for the first month following the stressor. Only after symptoms do not remit for one month can the disorder be deemed PTSD. It would be particularly useful to differentiate between acute stress disorder and PTSD during the one month waiting period so that more intensive treatments can be applied early on to patients with a high likelihood of developing PTSD. This would potentially enhance treatment outcomes and/or prevent the development of PTSD. Comprehension of the qualities and limitations of currently applied methods as well as the novel emerging techniques provide invaluable knowledge for fast paced development. Conventional methods of studying PTSD have proven to be insufficient for diagnosis, measurement of treatment efficacy, and monitoring disease progression. As the field currently stands, there is no diagnostic biomarker available for any psychiatric disease, PTSD included. Currently, emerging and available technologies are not utilized to their full capacity and in appropriate experimental designs for the most fruitful possible studies in this area. Therefore, there is an apparent need for improved methods in PTSD research. This review demonstrates the current state of the literature in PTSD, including molecular, cellular, and behavioral indicators, possible biomarkers and clinical and pre-clinical imaging techniques relevant to PTSD, and through this, elucidate the void of current practical imaging and spectroscopy methods that provide true biomarkers for the disorder and the significance of devising new techniques for future investigations. We are unlikely to develop a single biomarker for any psychiatric disorder however. As psychiatric disorders are incomparably complex compared to other medical diagnoses, its most likely that transcriptomic, metabolomic and structural and connectomic imaging data will have to be analyzed in concert in order to produce a dependable non-behavioral marker of PTSD. This can explain the necessity of bridging conventional approaches to novel technologies in order to create a framework for further discoveries in the treatment of PTSD.

Identifiers

PMID35527877
PMCPMC9069787
OpenAlexW2967433009

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.