Diagnosis of Autism Spectrum Disorder: A Review of Three Focused Interventions
Autism is a neurological developmental disorder that impacts a person’s physical, social, and emotional behavior. This disorder develops over time and is characterized by social deficits and repetitive behavior. Although there is no cure for this disorder, an early diagnosis and intervention can do...
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| Published in | SN computer science Vol. 4; no. 2; p. 139 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Singapore
Springer Nature Singapore
01.03.2023
Springer Nature B.V |
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| Online Access | Get full text |
| ISSN | 2661-8907 2662-995X 2661-8907 |
| DOI | 10.1007/s42979-022-01584-1 |
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| Abstract | Autism is a neurological developmental disorder that impacts a person’s physical, social, and emotional behavior. This disorder develops over time and is characterized by social deficits and repetitive behavior. Although there is no cure for this disorder, an early diagnosis and intervention can do significant wonders and can help the subject to become active functioning members of the family and society. The aim of this study is to minimize the diagnostic period by finding an optimal diagnosis procedure from the existing diagnosis tools. The diagnosis of autism can be done in three ways: 1. clinical evaluation; 2. screening tools; 3. brain images. In this review paper, we have thoroughly gone through all three types of diagnostic procedures and found that there was no single diagnostic tool to confirm the disorder. We also found that the diagnosis period was too long. As the result of this review, we found an ASD diagnosis triad which helps to choose the right diagnosis procedure based on the subjects age which reduces the diagnostic period and helps to aid early diagnosis by eliminating the chaos in choosing the diagnostic tools. |
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| AbstractList | Autism is a neurological developmental disorder that impacts a person’s physical, social, and emotional behavior. This disorder develops over time and is characterized by social deficits and repetitive behavior. Although there is no cure for this disorder, an early diagnosis and intervention can do significant wonders and can help the subject to become active functioning members of the family and society. The aim of this study is to minimize the diagnostic period by finding an optimal diagnosis procedure from the existing diagnosis tools. The diagnosis of autism can be done in three ways: 1. clinical evaluation; 2. screening tools; 3. brain images. In this review paper, we have thoroughly gone through all three types of diagnostic procedures and found that there was no single diagnostic tool to confirm the disorder. We also found that the diagnosis period was too long. As the result of this review, we found an ASD diagnosis triad which helps to choose the right diagnosis procedure based on the subjects age which reduces the diagnostic period and helps to aid early diagnosis by eliminating the chaos in choosing the diagnostic tools. |
| ArticleNumber | 139 |
| Author | Augustine, D. Peter Sujana, D. Swainson |
| Author_xml | – sequence: 1 givenname: D. Swainson orcidid: 0000-0002-5655-3136 surname: Sujana fullname: Sujana, D. Swainson email: d.sujana@res.christuniversity.in organization: Christ University – sequence: 2 givenname: D. Peter orcidid: 0000-0002-8350-5201 surname: Augustine fullname: Augustine, D. Peter organization: Department of Computer Science, Christ University |
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| Cites_doi | 10.1016/j.pnpbp.2018.11.002 10.1016/j.ensci.2019.100188 10.1016/j.jpeds.2016.07.052 10.1186/s43045-022-00220-1 10.1080/17538157.2017.1399132 10.1007/s10278-018-0093-8 10.1002/aur.2643 10.1186/s13229-021-00480-4 10.1542/peds.2013-1813 10.1007/s10803-020-04839-z 10.4103/jnrp.jnrp_329_16 10.1038/nrneurol.2013.276 10.23950/jcmk/11041 10.1007/s10278-019-00196-1 10.1146/annurev-neuro-071013-014111 10.3389/fpsyt.2019.00392 10.3390/brainsci10030180 10.1007/s10803-016-2876-4 10.1016/j.nicl.2017.08.017 10.1002/aur.2014 10.1016/j.spen.2020.100831 10.1016/j.compbiomed.2022.105854 10.1186/s13229-022-00489-3 10.1001/jamapsychiatry.2019.1411 10.1038/pr.2018.23 10.1016/j.annepidem.2011.12.006 10.3988/jcn.2018.14.2.129 10.1016/j.jneumeth.2020.108799 10.1002/aur.2033 10.1097/dbp.0000000000000194 10.1037/neu0000494 10.1007/s11065-015-9278-9 10.1002/aur.2212 10.1186/s13229-022-00506-5 |
| ContentType | Journal Article |
| Copyright | The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Keywords | ASD MRIs Developmental delay Screening tools Machine learning |
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| References | KimSYOhMBongGSongDYYoonNHKimJHYooHJDiagnostic validity of autism diagnostic observation schedule second edition (K-ADOS-2) in the Korean populationMol Autism202210.1186/s13229-022-00506-5 SchjølbergSShicFVolkmarFRNordahl-HansenAStenbergNTorskeTLarsenKRileyKSukhodolskyDGLeckmanJFChawarskaKØienRAWhat are we optimizing for in autism screening? Examination of algorithmic changes in the M-CHATAutism Res202115229630410.1002/aur.2643 LebersfeldJBSwansonMClesiCDSystematic review and meta-analysis of the clinical utility of the ADOS-2 and the ADI-R in diagnosing autism spectrum disorders in childrenJ Autism Dev Disord2021514101411410.1007/s10803-020-04839-z MargolisAEPagliaccioDThomasLBankerSMarshRSalience network connectivity and social processing in children with nonverbal learning disability or autism spectrum disorderNeuropsychology201933113514310.1037/neu0000494 LiYZhuYNguchuBAWangYWangHQiuBWangXDynamic functional connectivity reveals abnormal variability and hyper-connected pattern in autism spectrum disorderAutism Res201913223024310.1002/aur.2212 HillmanEMCoupling mechanism and significance of the BOLD signal: a status reportAnnu Rev Neurosci20143716118110.1146/annurev-neuro-071013-014111PMID:25032494; PMCID:PMC4147398 EckerCMurphyDNeuroimaging in autism—from basic science to translational researchNat Rev Neurol2014102829110.1038/nrneurol.2013.276 LiuGShiLQiuJLuWTwo neuroanatomical subtypes of males with autism spectrum disorder revealed using semi-supervised machine learningMol Autism202210.1186/s13229-022-00489-3 AghdamMASharifiAPedramMMDiagnosis of autism spectrum disorders in young children based on resting-state functional magnetic resonance imaging data using convolutional neural networksJ Digit Imaging201932689991810.1007/s10278-019-00196-1 WeitlaufASVehornACStoneWLFeinDWarrenZEUsing the M-CHAT-R/F to identify developmental concerns in a high-risk 18-month-old sibling sampleJ Dev Behav Pediatr201536749750210.1097/dbp.0000000000000194 JansenAGMousSEWhiteTPosthumaDPoldermanTJCWhat twin studies tell us about the heritability of brain development, morphology, and function: a reviewNeuropsychol Rev2015251274610.1007/s11065-015-9278-9 JohnOMeta-analysis of diagnostic accuracy of M-CHAT by categorical rank of clinical diagnosisThesis2020Georgia State University RobinsDLCasagrandeKBartonMChenCMADumont-MathieuTFeinDValidation of the modified checklist for autism in toddlers, revised with follow-up (M-CHAT-R/F)Pediatrics20131331374510.1542/peds.2013-1813 Ruby Grace D, Immaculate. International Journal of Emerging Technology and Innovative Engineering, 2015; 1(3). VoorhiesWDajaniDRVijSGShankarSTuranTOUddinLQAberrant functional connectivity of inhibitory control networks in children with autism spectrum disorderAutism Res201811111468147810.1002/aur.2014 SrisinghasongkramPPruksananondaCChonchaiyaWTwo-step screening of the modified checklist for autism in toddlers in Thai children with language delay and typically developing childrenJ Autism Dev Disord201646103317332910.1007/s10803-016-2876-4 McCartyPFryeREEarly detection and diagnosis of autism spectrum disorder: why is it so difficult?Semin Pediatr Neurol20203510083110.1016/j.spen.2020.100831 BilgenIGuvercinGRekikIMachine learning methods for brain network classification: application to autism diagnosis using cortical morphological networksJ Neurosci Methods202034310879910.1016/j.jneumeth.2020.108799 PetrocchiSLevanteALeccisoFSystematic review of level 1 and level 2 screening tools for autism spectrum disorders in toddlersBrain Sci202010318010.3390/brainsci10030180 ParnerETBaron-CohenSLauritsenMBJørgensenMSchieveLAYeargin-AllsoppMObelCParental age and autism spectrum disordersAnn Epidemiol201222314315010.1016/j.annepidem.2011.12.006 NukeshtayevaKLubchenkoMOmarkulovBDeLellisNValidation non-English version of modified checklist for autism in toddlers-revised with follow-upJ Clin Med Kazakhstan202118441110.23950/jcmk/11041 TaeWSHamBJPyunSBKangSHKimBJCurrent clinical applications of diffusion-tensor imaging in neurological disordersJ Clin Neurol201814212910.3988/jcn.2018.14.2.129 KimSHJosephRMFrazierJAO’SheaTMChawarskaKAllredENLevitonAKubanKKExtremely Low Gestational Age Newborn (ELGAN) Study InvestigatorsPredictive validity of the modified checklist for autism in toddlers (M-CHAT) born very pretermJ Pediatr2016178101107.e210.1016/j.jpeds.2016.07.052 SturnerRHowardBBergmannPAttarSStewart-ArtzLBetKAllisonCBaron-CohenSAutism screening at 18 months of age: a comparison of the Q-CHAT-10 and M-CHAT screenersMol Autism202210.1186/s13229-021-00480-4 HeinsfeldASFrancoARCraddockRCBuchweitzAMeneguzziFIdentification of autism spectrum disorder using deep learning and the ABIDE datasetNeuroImage Clin201817162310.1016/j.nicl.2017.08.017 Khadem-RezaZKZareHAutomatic detection of autism spectrum disorder (ASD) in children using structural magnetic resonance imaging with machine vision systemMiddle East Curr Psychiatry2022295410.1186/s43045-022-00220-1 Bai D, Yip BHK, Windham GC, et al. Association of Genetic and Environmental Factors With Autism in a 5-Country Cohort. JAMA Psychiatry. 2019;76(10):1035–43. https://doi.org/10.1001/jamapsychiatry.2019.1411 Immaculate RGD. A comparison on performance evaluation of various image fusion techniques. Int J Emerg Technol Innovative Eng. 2015;1(3). ISSN: 2394-6598 SangareMToureHBToureAKarembeADoloHCoulibalyYIKouyateMTraoreKDiakitéSACoulibalySTogoraAGuintoCOAwandareGADoumbiaSDiakiteMGeschwindDHValidation of two parent-reported autism spectrum disorders screening tools M-CHAT-R and SCQ in Bamako, MaliENeurological Sci20191510018810.1016/j.ensci.2019.100188 Hisle-GormanESusiAStokesTGormanGErdie-LalenaCNylundCMPrenatal, perinatal, and neonatal risk factors of autism spectrum disorderPediatr Res201884219019810.1038/pr.2018.23 Centres for Disease Control and Prevention. Autism Spectrum Disorder (ASD). Data and Statistics. 2022. https://www.cdc.gov/ncbddd/autism/data.html (Accessed on 31st Mar 2022) DekhilOAliMEl-NakiebYShalabyASolimanASwitalaAMahmoudAGhazalMHajjdiabHCasanovaMFElmaghrabyAKeyntonREl-BazABarnesGA personalized autism diagnosis CAD system using a fusion of structural MRI and resting-state functional MRI dataFront Psych201910.3389/fpsyt.2019.00392 GottsSJRamotMJasminKMartinAAltered resting-state dynamics in autism spectrum disorder: Causal to the social impairment?Prog Neuropsychopharmacol Biol Psychiatry201990283610.1016/j.pnpbp.2018.11.002 Akhavan AghdamMSharifiAPedramMMCombination of rs-fMRI and sMRI data to discriminate autism spectrum disorders in young children using deep belief networkJ Digit Imaging201831689590310.1007/s10278-018-0093-8 MarlowMServiliCTomlinsonMA review of screening tools for the identification of autism spectrum disorders and developmental delay in infants and young children: recommendations for use in low- and middle-income countriesAutism Res201912217619910.1002/aur.2033 Centres for Disease Control and Prevention. Autism Spectrum Disorder (ASD). Screening and diagnosis. 2022. https://www.cdc.gov/ncbddd/autism/hcp-screening.html (Accessed on 6th Apr 2022) ThabtahFMachine learning in autistic spectrum disorder behavioral research: a review and ways forwardInform Health Soc Care201844327829710.1080/17538157.2017.1399132 Centres for Disease Control and Prevention. Autism Spectrum Disorder (ASD). Screening and diagnosis. 2022. https://www.cdc.gov/ncbddd/autism/screening.html (Accessed on 31st Mar 2022) ZhangFWeiYLiuJWangYXiWPanYIdentification of Autism spectrum disorder based on a novel feature selection method and variational autoencoderComput Biol Med202214810585410.1016/j.compbiomed.2022.105854 RainaSKChanderVBhardwajAKKumarDSharmaSKashyapVSinghMBhardwajAPrevalence of Autism Spectrum Disorder among Rural, Urban, and Tribal Children (1–10 Years of Age)J Neurosci Rural Pract2017080336837410.4103/jnrp.jnrp_329_16 WS Tae (1584_CR23) 2018; 14 SJ Gotts (1584_CR26) 2019; 90 AG Jansen (1584_CR20) 2015; 25 1584_CR01 1584_CR21 F Thabtah (1584_CR30) 2018; 44 M Marlow (1584_CR39) 2019; 12 S Petrocchi (1584_CR14) 2020; 10 EM Hillman (1584_CR22) 2014; 37 ET Parner (1584_CR2) 2012; 22 M Akhavan Aghdam (1584_CR32) 2018; 31 C Ecker (1584_CR38) 2014; 10 AS Weitlauf (1584_CR13) 2015; 36 G Liu (1584_CR29) 2022 AS Heinsfeld (1584_CR34) 2018; 17 1584_CR8 W Voorhies (1584_CR28) 2018; 11 1584_CR3 1584_CR4 O John (1584_CR6) 2020 F Zhang (1584_CR24) 2022; 148 O Dekhil (1584_CR35) 2019 M Sangare (1584_CR10) 2019; 15 I Bilgen (1584_CR31) 2020; 343 SY Kim (1584_CR17) 2022 Y Li (1584_CR27) 2019; 13 MA Aghdam (1584_CR33) 2019; 32 E Hisle-Gorman (1584_CR1) 2018; 84 R Sturner (1584_CR12) 2022 ZK Khadem-Reza (1584_CR36) 2022; 29 JB Lebersfeld (1584_CR18) 2021; 51 K Nukeshtayeva (1584_CR16) 2021; 18 P Srisinghasongkram (1584_CR9) 2016; 46 AE Margolis (1584_CR25) 2019; 33 SH Kim (1584_CR5) 2016; 178 S Schjølberg (1584_CR7) 2021; 15 SK Raina (1584_CR37) 2017; 08 DL Robins (1584_CR11) 2013; 133 1584_CR19 P McCarty (1584_CR15) 2020; 35 |
| References_xml | – reference: PetrocchiSLevanteALeccisoFSystematic review of level 1 and level 2 screening tools for autism spectrum disorders in toddlersBrain Sci202010318010.3390/brainsci10030180 – reference: RainaSKChanderVBhardwajAKKumarDSharmaSKashyapVSinghMBhardwajAPrevalence of Autism Spectrum Disorder among Rural, Urban, and Tribal Children (1–10 Years of Age)J Neurosci Rural Pract2017080336837410.4103/jnrp.jnrp_329_16 – reference: SturnerRHowardBBergmannPAttarSStewart-ArtzLBetKAllisonCBaron-CohenSAutism screening at 18 months of age: a comparison of the Q-CHAT-10 and M-CHAT screenersMol Autism202210.1186/s13229-021-00480-4 – reference: MarlowMServiliCTomlinsonMA review of screening tools for the identification of autism spectrum disorders and developmental delay in infants and young children: recommendations for use in low- and middle-income countriesAutism Res201912217619910.1002/aur.2033 – reference: VoorhiesWDajaniDRVijSGShankarSTuranTOUddinLQAberrant functional connectivity of inhibitory control networks in children with autism spectrum disorderAutism Res201811111468147810.1002/aur.2014 – reference: DekhilOAliMEl-NakiebYShalabyASolimanASwitalaAMahmoudAGhazalMHajjdiabHCasanovaMFElmaghrabyAKeyntonREl-BazABarnesGA personalized autism diagnosis CAD system using a fusion of structural MRI and resting-state functional MRI dataFront Psych201910.3389/fpsyt.2019.00392 – reference: RobinsDLCasagrandeKBartonMChenCMADumont-MathieuTFeinDValidation of the modified checklist for autism in toddlers, revised with follow-up (M-CHAT-R/F)Pediatrics20131331374510.1542/peds.2013-1813 – reference: Centres for Disease Control and Prevention. Autism Spectrum Disorder (ASD). Screening and diagnosis. 2022. https://www.cdc.gov/ncbddd/autism/hcp-screening.html (Accessed on 6th Apr 2022) – reference: EckerCMurphyDNeuroimaging in autism—from basic science to translational researchNat Rev Neurol2014102829110.1038/nrneurol.2013.276 – reference: Akhavan AghdamMSharifiAPedramMMCombination of rs-fMRI and sMRI data to discriminate autism spectrum disorders in young children using deep belief networkJ Digit Imaging201831689590310.1007/s10278-018-0093-8 – reference: Bai D, Yip BHK, Windham GC, et al. Association of Genetic and Environmental Factors With Autism in a 5-Country Cohort. JAMA Psychiatry. 2019;76(10):1035–43. https://doi.org/10.1001/jamapsychiatry.2019.1411 – reference: ParnerETBaron-CohenSLauritsenMBJørgensenMSchieveLAYeargin-AllsoppMObelCParental age and autism spectrum disordersAnn Epidemiol201222314315010.1016/j.annepidem.2011.12.006 – reference: Centres for Disease Control and Prevention. Autism Spectrum Disorder (ASD). Data and Statistics. 2022. https://www.cdc.gov/ncbddd/autism/data.html (Accessed on 31st Mar 2022) – reference: WeitlaufASVehornACStoneWLFeinDWarrenZEUsing the M-CHAT-R/F to identify developmental concerns in a high-risk 18-month-old sibling sampleJ Dev Behav Pediatr201536749750210.1097/dbp.0000000000000194 – reference: McCartyPFryeREEarly detection and diagnosis of autism spectrum disorder: why is it so difficult?Semin Pediatr Neurol20203510083110.1016/j.spen.2020.100831 – reference: Ruby Grace D, Immaculate. International Journal of Emerging Technology and Innovative Engineering, 2015; 1(3). – reference: LebersfeldJBSwansonMClesiCDSystematic review and meta-analysis of the clinical utility of the ADOS-2 and the ADI-R in diagnosing autism spectrum disorders in childrenJ Autism Dev Disord2021514101411410.1007/s10803-020-04839-z – reference: Centres for Disease Control and Prevention. Autism Spectrum Disorder (ASD). Screening and diagnosis. 2022. https://www.cdc.gov/ncbddd/autism/screening.html (Accessed on 31st Mar 2022) – reference: SangareMToureHBToureAKarembeADoloHCoulibalyYIKouyateMTraoreKDiakitéSACoulibalySTogoraAGuintoCOAwandareGADoumbiaSDiakiteMGeschwindDHValidation of two parent-reported autism spectrum disorders screening tools M-CHAT-R and SCQ in Bamako, MaliENeurological Sci20191510018810.1016/j.ensci.2019.100188 – reference: LiYZhuYNguchuBAWangYWangHQiuBWangXDynamic functional connectivity reveals abnormal variability and hyper-connected pattern in autism spectrum disorderAutism Res201913223024310.1002/aur.2212 – reference: GottsSJRamotMJasminKMartinAAltered resting-state dynamics in autism spectrum disorder: Causal to the social impairment?Prog Neuropsychopharmacol Biol Psychiatry201990283610.1016/j.pnpbp.2018.11.002 – reference: SrisinghasongkramPPruksananondaCChonchaiyaWTwo-step screening of the modified checklist for autism in toddlers in Thai children with language delay and typically developing childrenJ Autism Dev Disord201646103317332910.1007/s10803-016-2876-4 – reference: HillmanEMCoupling mechanism and significance of the BOLD signal: a status reportAnnu Rev Neurosci20143716118110.1146/annurev-neuro-071013-014111PMID:25032494; PMCID:PMC4147398 – reference: SchjølbergSShicFVolkmarFRNordahl-HansenAStenbergNTorskeTLarsenKRileyKSukhodolskyDGLeckmanJFChawarskaKØienRAWhat are we optimizing for in autism screening? 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| Title | Diagnosis of Autism Spectrum Disorder: A Review of Three Focused Interventions |
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