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2000
Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
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Abstract

Background

Neuroimaging has helped us learn about the stages of brain development from infancy to maturity. Neuroimaging helps physicians diagnose mental illnesses and find novel treatments for them. It can distinguish depression from neurodegenerative diseases or brain tumors, and it can reveal structural defects that cause psychosis. Psychosis has been linked to lesions in the frontal or temporal lobes of the brain, as well as the thalamus and hypothalamus, which can be detected using a brain scan for mental illnesses. Neuroimaging uses quantitative and computational methods to explore the central nervous system. It can detect brain injuries and psychological illnesses. Thus, a systematic review and meta-analysis of randomized controlled trials using neuroimaging to detect psychiatric disorders assessed their efficacy and benefits.

Materials and Methods

Appropriate articles were searched from PubMed, MEDLINE, and CENTRAL databases using the appropriate keywords as per the PRISMA guidelines. Randomized controlled trials and open-label studies were included as per the predefined PICOS criteria. Meta-analysis was performed using the RevMan software, and statistical parameters like odds ratio and risk difference were calculated.

Results

Twelve randomized controlled clinical trials with a total of 655 psychiatric patients were included following the criteria from the year 2000 to 2022. We included studies that use different neuroimaging techniques for the detection of organic brain lesions that would help diagnose psychiatric disorders. The primary outcome was detecting brain abnormalities in diverse psychiatric illnesses with neuroimaging versus conventional methods. We found the odds ratio value of 2.29 (95% CI 1.49-3.51). The results were heterogeneous with a 2 value of 0.38, 2 value of 35.48, df value of 11, I2 value of 69%, the z value of 3.78, and p-value less than 0.05. The risk difference is 0.20 (95% CI 0.09 -0.31) with heterogeneity of Tau2 value of 0.03, chi2 value of 50, df value of 11, I2 value of 78%, the z value of 3.49, and p-value less than 0.05.

Conclusion

The present meta-analysis strongly recommends the use of neuroimaging techniques for the detection of psychiatric disorders.

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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2023-01-01
2024-11-26
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References

  1. CastagniniA. BerriosG.E. Acute and transient psychotic disorders (ICD-10 F23): a review from a European perspective.Eur. Arch. Psychiatry Clin. Neurosci.2009259843344310.1007/s00406‑009‑0008‑219381705
    [Google Scholar]
  2. KarilaL PetitA PhanO ReynaudM Cocaine induced psychotic disorders: a review.Rev Med Liege20106511623627
    [Google Scholar]
  3. HartzS.M. PatoC.N. MedeirosH. Cavazos-RehgP. SobellJ.L. KnowlesJ.A. BierutL.J. PatoM.T. Genomic Psychiatry Cohort Consortium Comorbidity of severe psychotic disorders with measures of substance use.JAMA Psychiatry201471324825410.1001/jamapsychiatry.2013.372624382686
    [Google Scholar]
  4. Harkavy-FriedmanJ.M. NelsonE.A. VenardeD.F. MannJ.J. Suicidal behavior in schizophrenia and schizoaffective disorder: examining the role of depression.Suicide Life Threat. Behav.2004341667610.1521/suli.34.1.66.2777015106889
    [Google Scholar]
  5. MaloneK.M. OquendoM.A. HaasG.L. EllisS.P. LiS. MannJ.J. Protective factors against suicidal acts in major depression: reasons for living.Am. J. Psychiatry200015771084108810.1176/appi.ajp.157.7.108410873915
    [Google Scholar]
  6. MukamelR. GelbardH. ArieliA. HassonU. FriedI. MalachR. Coupling between neuronal firing, field potentials, and FMRI in human auditory cortex.Science2005309573695195410.1126/science.111091316081741
    [Google Scholar]
  7. ScheerenT.W.L. SchoberP. SchwarteL.A. Monitoring tissue oxygenation by near infrared spectroscopy (NIRS): background and current applications.J. Clin. Monit. Comput.201226427928710.1007/s10877‑012‑9348‑y22467064
    [Google Scholar]
  8. FujiiD. AhmedI. Characteristics of psychotic disorder due to traumatic brain injury: an analysis of case studies in the literature.J. Neuropsychiatry Clin. Neurosci.200214213014010.1176/jnp.14.2.13011983787
    [Google Scholar]
  9. FreireR.C. CirilloP.C. NardiA.E. Clinical application of neurostimulation in depression. IN Understanding Depression.SingaporeSpringer201827728810.1007/978‑981‑10‑6577‑4_20
    [Google Scholar]
  10. BusattoG.F. Structural and functional neuroimaging studies in major depressive disorder with psychotic features: a critical review.Schizophr. Bull.201339477678610.1093/schbul/sbt05423615813
    [Google Scholar]
  11. ColeJ.C. Green BernackiC. HelmerA. PinnintiN. O’reardonJ.P. Efficacy of Transcranial Magnetic Stimulation (TMS) in the treatment of schizophrenia: A review of the literature to date.Innov. Clin. Neurosci.2015127-8121926351619
    [Google Scholar]
  12. SmieskovaR. Fusar-PoliP. AllenP. BendfeldtK. StieglitzR.D. DreweJ. RadueE.W. McGuireP.K. Riecher-RösslerA. BorgwardtS.J. Neuroimaging predictors of transition to psychosis-a systematic review and meta-analysis.Neurosci. Biobehav. Rev.20103481207122210.1016/j.neubiorev.2010.01.01620144653
    [Google Scholar]
  13. PidgeonL.M. GrealyM. DuffyA.H.B. HayL. McTeagueC. VuleticT. CoyleD. GilbertS.J. Functional neuroimaging of visual creativity: a systematic review and meta-analysis.Brain Behav.2016610e0054010.1002/brb3.54027781148
    [Google Scholar]
  14. Fusar-PoliP. HowesO. BechdolfA. BorgwardtS. Mapping vulnerability to bipolar disorder: a systematic review and meta-analysis of neuroimaging studies.J. Psychiatry Neurosci.201237317018410.1503/jpn.11006122297067
    [Google Scholar]
  15. QuaakM. van de MortelL. ThomasR.M. van WingenG. Deep learning applications for the classification of psychiatric disorders using neuroimaging data: Systematic review and meta-analysis.Neuroimage Clin.20213010258410.1016/j.nicl.2021.10258433677240
    [Google Scholar]
  16. SlotemaC. W. BlomJ. D. Can low-frequency repetitive transcranial magnetic stimulation really relieve medication-resistant auditory verbal hallucinations? Negative results from a large randomized controlled trial.Biol Psych.201069545045610.1016/j.biopsych.2010.09.051
    [Google Scholar]
  17. Ishii-TakahashiA. TakizawaR. NishimuraY. KawakuboY. KuwabaraH. MatsubayashiJ. HamadaK. OkuhataS. YahataN. IgarashiT. KawasakiS. YamasueH. KatoN. KasaiK. KanoY. Prefrontal activation during inhibitory control measured by near-infrared spectroscopy for differentiating between autism spectrum disorders and attention deficit hyperactivity disorder in adults.Neuroimage Clin.20144536310.1016/j.nicl.2013.10.00224298446
    [Google Scholar]
  18. BaisL. VercammenA. StewartR. van EsF. VisserB. AlemanA. KnegteringH. Short and long term effects of left and bilateral repetitive transcranial magnetic stimulation in schizophrenia patients with auditory verbal hallucinations: a randomized controlled trial.PLoS One2014910e10882810.1371/journal.pone.010882825329799
    [Google Scholar]
  19. Ishii-TakahashiA TakizawaR NishimuraY Neuroimaging-aided prediction of the effect of methylphenidate in children with attention-deficit hyperactivity disorder: A randomized controlled trial.Neuropsychopharmacology201540122676268110.1038/npp.2015.154
    [Google Scholar]
  20. JavittD.C. CarterC.S. KrystalJ.H. KantrowitzJ.T. GirgisR.R. KegelesL.S. RaglandJ.D. MaddockR.J. LeshT.A. TanaseC. CorlettP.R. RothmanD.L. MasonG. QiuM. RobinsonJ. PotterW.Z. CarlsonM. WallM.M. ChooT.H. GrinbandJ. LiebermanJ.A. Utility of imaging-based biomarkers for glutamate-targeted drug development in psychotic disorders.JAMA Psychiatry2018751111910.1001/jamapsychiatry.2017.357229167877
    [Google Scholar]
  21. PetersenJ.Z. SchmidtL.S. VinbergM. JørgensenM.B. HagemanI. EhrenreichH. KnudsenG.M. KessingL.V. MiskowiakK.W. Effects of recombinant human erythropoietin on cognition and neural activity in remitted patients with mood disorders and first-degree relatives of patients with psychiatric disorders: a study protocol for a randomized controlled trial.Trials201819161110.1186/s13063‑018‑2995‑730400939
    [Google Scholar]
  22. SutokoS. MondenY. TokudaT. IkedaT. NagashimaM. KiguchiM. MakiA. YamagataT. DanI. Distinct methylphenidate-evoked response measured using functional near-infrared spectroscopy during go/no-go task as a supporting differential diagnostic tool between attention-deficit/hyperactivity disorder and autism spectrum disorder comorbid children.Front. Hum. Neurosci.201913710.3389/fnhum.2019.0000730800062
    [Google Scholar]
  23. Harika-GermaneauG. HeitD. ChatardA. ThiriouxB. LangbourN. JaafariN. Treating refractory obsessive–compulsive disorder with transcranial direct current stimulation: An open label study.Brain Behav.2020107e0164810.1002/brb3.164832406608
    [Google Scholar]
  24. BationR. MondinoM. Le CamusF. SaoudM. BrunelinJ. Transcranial direct current stimulation in patients with obsessive compulsive disorder: A randomized controlled trial.Eur. Psychiatry201962384410.1016/j.eurpsy.2019.08.01131525581
    [Google Scholar]
  25. VoineskosA.N. MulsantB.H. DickieE.W. NeufeldN.H. RothschildA.J. WhyteE.M. MeyersB.S. AlexopoulosG.S. HoptmanM.J. LerchJ.P. FlintA.J. Effects of antipsychotic medication on brain structure in patients with major depressive disorder and psychotic features.JAMA Psychiatry202077767468310.1001/jamapsychiatry.2020.003632101271
    [Google Scholar]
  26. SilvaR.M.F. BrunoniA.R. GoerigkS. BatistuzzoM.C. CostaD.L.C. DinizJ.B. PadbergF. D’UrsoG. MiguelE.C. ShavittR.G. Efficacy and safety of transcranial direct current stimulation as an add-on treatment for obsessive-compulsive disorder: a randomized, sham-controlled trial.Neuropsychopharmacology20214651028103410.1038/s41386‑020‑00928‑w33452434
    [Google Scholar]
  27. PiguetC. KlauserP. CelenZ. James MurrayR. Magnus SmithM. MerglenA. Randomized controlled trial of a mindfulness‐based intervention in adolescents from the general population: The Mindfulteen neuroimaging study protocol.Early Interv. Psychiatry202216889190110.1111/eip.1323534734463
    [Google Scholar]
  28. KimberleyT.J. LewisS.M. Understanding Neuroimaging.Phys. Ther.200787667068310.2522/ptj.2006014917429004
    [Google Scholar]
  29. WilliamsN. HensonR.N. Recent advances in functional neuroimaging analysis for cognitive neuroscience.Brain Neurosci. Adv.2018210.1177/239821281775272732285010
    [Google Scholar]
  30. LorenzettiD.L. GhaliW.A. Reference management software for systematic reviews and meta-analyses: an exploration of usage and usability.BMC Med. Res. Methodol.201313114110.1186/1471‑2288‑13‑14124237877
    [Google Scholar]
  31. HannemanS.K. Design, analysis, and interpretation of method-comparison studies.AACN Adv. Crit. Care200819222323410.1097/01.AACN.0000318125.41512.a318560291
    [Google Scholar]
  32. SimmondsM. Quantifying the risk of error when interpreting funnel plots.Syst. Rev.2015412410.1186/s13643‑015‑0004‑825875027
    [Google Scholar]
  33. SaaiqM. AshrafB. Modifying “pico” question into “picos” model for more robust and reproducible presentation of the methodology employed in a scientific study.World J. Plast. Surg.20176339039229218294
    [Google Scholar]
  34. HayashinoY. NoguchiY. FukuiT. Systematic evaluation and comparison of statistical tests for publication bias.J. Epidemiol.200515623524310.2188/jea.15.23516276033
    [Google Scholar]
  35. HuppertF.A. Psychological well‐being: Evidence regarding its causes and consequences.Appl. Psychol. Health Well-Being20091213716410.1111/j.1758‑0854.2009.01008.x
    [Google Scholar]
  36. BuccinoG. AmoreM. Mirror neurons and the understanding of behavioural symptoms in psychiatric disorders.Curr. Opin. Psychiatry200821328128510.1097/YCO.0b013e3282fbcd3218382228
    [Google Scholar]
  37. CanarioE. ChenD. BiswalB. A review of resting-state fMRI and its use to examine psychiatric disorders.Psychoradiology202111425310.1093/psyrad/kkab003
    [Google Scholar]
  38. FerreriL. BigandE. PerreyS. BugaïskaA. The promise of Near-Infrared Spectroscopy (NIRS) for psychological research: A brief review.Annee Psychol.2014114353756910.3917/anpsy.143.0537
    [Google Scholar]
  39. AgzarianM.J. ChryssidisS. DaviesR.P. PozzaC.H. Use of routine computed tomography brain scanning of psychiatry patients.Australas. Radiol.2006501272810.1111/j.1440‑1673.2005.01542.x16499723
    [Google Scholar]
  40. WuC.L. LinT.J. ChiouG.L. LeeC.Y. LuanH. TsaiM.J. PotvinP. TsaiC.C. A systematic review of mri neuroimaging for education research.Front. Psychol.20211261759910.3389/fpsyg.2021.61759934093308
    [Google Scholar]
  41. AnthonyM. LinF. A systematic review for functional neuroimaging studies of cognitive reserve across the cognitive aging spectrum.Arch. Clin. Neuropsychol.201833893794810.1093/arclin/acx12529244054
    [Google Scholar]
  42. TalwarP. KushwahaS. ChaturvediM. MahajanV. Systematic review of different neuroimaging correlates in mild cognitive impairment and alzheimer’s disease.Clin. Neuroradiol.202131495396710.1007/s00062‑021‑01057‑734297137
    [Google Scholar]
  43. AhmadzadehM. ChristieG.J. CoscoT.D. MorenoS. Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer’s disease: protocol for a rapid systematic review.Syst. Rev.2020917110.1186/s13643‑020‑01332‑732241302
    [Google Scholar]
  44. CummingsP. The relative merits of risk ratios and odds ratios.Arch. Pediatr. Adolesc. Med.2009163543844510.1001/archpediatrics.2009.3119414690
    [Google Scholar]
  45. RichardsonT.S. RobinsJ.M. WangL. On modeling and estimation for the relative risk and risk difference.J. Am. Stat. Assoc.20171125191121113010.1080/01621459.2016.1192546
    [Google Scholar]
  46. MittlböckM. HeinzlH. A simulation study comparing properties of heterogeneity measures in meta-analyses.Stat. Med.200625244321433310.1002/sim.269216991104
    [Google Scholar]
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PRISMA checklist is available as supplementary material on the publisher’s website along with the published article. Supplementary material is available on the publisher’s website along with the published article.

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