Computer-vision analysis of craniofacial dysmorphology in 22q11.2 deletion syndrome and psychosis spectrum disorders / David R. ROALF in Journal of Neurodevelopmental Disorders, 16 (2024)  

Public ISBD [article]  inJournal of Neurodevelopmental Disorders > 16 (2024) Titre : Computer-vision analysis of craniofacial dysmorphology in 22q11.2 deletion syndrome and psychosis spectrum disorders Type de document : texte imprimé Auteurs : David R. ROALF, Auteur ; Donna M. MCDONALD-MCGINN, Auteur ; Joelle JEE, Auteur ; Mckenna KRALL, Auteur ; T Blaine CROWLEY, Auteur ; Paul J. MOBERG, Auteur ; Christian KOHLER, Auteur ; Monica E. CALKINS, Auteur ; Andrew J.D. CROW, Auteur ; Nicole FLEISCHER, Auteur ; R. Sean GALLAGHER, Auteur ; Virgilio GONZENBACH, Auteur ; Kelly CLARK, Auteur ; Ruben C. GUR, Auteur ; Emily MCCLELLAN, Auteur ; Daniel E. MCGINN, Auteur ; Arianna MORDY, Auteur ; Kosha RUPAREL, Auteur ; Bruce I. TURETSKY, Auteur ; Russell T. SHINOHARA, Auteur ; Lauren WHITE, Auteur ; Elaine ZACKAI, Auteur ; Raquel E. GUR, Auteur Langues : Anglais (eng) Mots-clés : Humans  DiGeorge Syndrome/genetics/physiopathology  Psychotic Disorders/genetics  Female  Male  Adolescent  Child  Craniofacial Abnormalities/genetics  Young Adult  Adult  Machine Learning  Image Processing, Computer-Assisted  22q11.2 deletion syndrome  Clinical high-risk psychosis  Computer-vision  Face  Minor physical anomalies  Psychosis  Schizophrenia  to provide F2G Gestalt data for facial photographs. She was not involved in  project design, implementation, or data analysis. She reviewed and edited the  final manuscript. No other authors have any competing interest to report. Index. décimale : PER Périodiques Résumé : BACKGROUND: Minor physical anomalies (MPAs) are congenital morphological abnormalities linked to disruptions of fetal development. MPAs are common in 22q11.2 deletion syndrome (22q11DS) and psychosis spectrum disorders (PS) and likely represent a disruption of early embryologic development that may help identify overlapping mechanisms linked to psychosis in these disorders. METHODS: Here, 2D digital photographs were collected from 22q11DS (n = 150), PS (n = 55), and typically developing (TD; n = 93) individuals. Photographs were analyzed using two computer-vision techniques: (1) DeepGestalt algorithm (Face2Gene (F2G)) technology to identify the presence of genetically mediated facial disorders, and (2) Emotrics-a semi-automated machine learning technique that localizes and measures facial features. RESULTS: F2G reliably identified patients with 22q11DS; faces of PS patients were matched to several genetic conditions including FragileX and 22q11DS. PCA-derived factor loadings of all F2G scores indicated unique and overlapping facial patterns that were related to both 22q11DS and PS. Regional facial measurements of the eyes and nose were smaller in 22q11DS as compared to TD, while PS showed intermediate measurements. CONCLUSIONS: The extent to which craniofacial dysmorphology 22q11DS and PS overlapping and evident before the impairment or distress of sub-psychotic symptoms may allow us to identify at-risk youths more reliably and at an earlier stage of development. En ligne : https://dx.doi.org/10.1186/s11689-024-09547-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=575 [article] Computer-vision analysis of craniofacial dysmorphology in 22q11.2 deletion syndrome and psychosis spectrum disorders [texte imprimé] / David R. ROALF, Auteur ; Donna M. MCDONALD-MCGINN, Auteur ; Joelle JEE, Auteur ; Mckenna KRALL, Auteur ; T Blaine CROWLEY, Auteur ; Paul J. MOBERG, Auteur ; Christian KOHLER, Auteur ; Monica E. CALKINS, Auteur ; Andrew J.D. CROW, Auteur ; Nicole FLEISCHER, Auteur ; R. Sean GALLAGHER, Auteur ; Virgilio GONZENBACH, Auteur ; Kelly CLARK, Auteur ; Ruben C. GUR, Auteur ; Emily MCCLELLAN, Auteur ; Daniel E. MCGINN, Auteur ; Arianna MORDY, Auteur ; Kosha RUPAREL, Auteur ; Bruce I. TURETSKY, Auteur ; Russell T. SHINOHARA, Auteur ; Lauren WHITE, Auteur ; Elaine ZACKAI, Auteur ; Raquel E. GUR, Auteur. Langues : Anglais (eng) in Journal of Neurodevelopmental Disorders > 16 (2024) Mots-clés : Humans  DiGeorge Syndrome/genetics/physiopathology  Psychotic Disorders/genetics  Female  Male  Adolescent  Child  Craniofacial Abnormalities/genetics  Young Adult  Adult  Machine Learning  Image Processing, Computer-Assisted  22q11.2 deletion syndrome  Clinical high-risk psychosis  Computer-vision  Face  Minor physical anomalies  Psychosis  Schizophrenia  to provide F2G Gestalt data for facial photographs. She was not involved in  project design, implementation, or data analysis. She reviewed and edited the  final manuscript. No other authors have any competing interest to report. Index. décimale : PER Périodiques Résumé : BACKGROUND: Minor physical anomalies (MPAs) are congenital morphological abnormalities linked to disruptions of fetal development. MPAs are common in 22q11.2 deletion syndrome (22q11DS) and psychosis spectrum disorders (PS) and likely represent a disruption of early embryologic development that may help identify overlapping mechanisms linked to psychosis in these disorders. METHODS: Here, 2D digital photographs were collected from 22q11DS (n = 150), PS (n = 55), and typically developing (TD; n = 93) individuals. Photographs were analyzed using two computer-vision techniques: (1) DeepGestalt algorithm (Face2Gene (F2G)) technology to identify the presence of genetically mediated facial disorders, and (2) Emotrics-a semi-automated machine learning technique that localizes and measures facial features. RESULTS: F2G reliably identified patients with 22q11DS; faces of PS patients were matched to several genetic conditions including FragileX and 22q11DS. PCA-derived factor loadings of all F2G scores indicated unique and overlapping facial patterns that were related to both 22q11DS and PS. Regional facial measurements of the eyes and nose were smaller in 22q11DS as compared to TD, while PS showed intermediate measurements. CONCLUSIONS: The extent to which craniofacial dysmorphology 22q11DS and PS overlapping and evident before the impairment or distress of sub-psychotic symptoms may allow us to identify at-risk youths more reliably and at an earlier stage of development. En ligne : https://dx.doi.org/10.1186/s11689-024-09547-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=575

Olfactory Dysfunction in Neurodevelopmental Disorders: A Meta-analytic Review of Autism Spectrum Disorders, Attention Deficit/Hyperactivity Disorder and Obsessive-Compulsive Disorder / Andrew J.D. CROW in Journal of Autism and Developmental Disorders, 50-8 (August 2020)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 50-8 (August 2020) . - p.2685-2697 Titre : Olfactory Dysfunction in Neurodevelopmental Disorders: A Meta-analytic Review of Autism Spectrum Disorders, Attention Deficit/Hyperactivity Disorder and Obsessive-Compulsive Disorder Type de document : texte imprimé Auteurs : Andrew J.D. CROW, Auteur ; Jennica M. JANSSEN, Auteur ; Kayci L. VICKERS, Auteur ; Julia PARISH-MORRIS, Auteur ; Paul J. MOBERG, Auteur ; David R. ROALF, Auteur Article en page(s) : p.2685-2697 Langues : Anglais (eng) Mots-clés : Attention-deficit/hyperactivity disorder  Autism spectrum disorders  Meta-analysis  Obsessive–compulsive disorder  Olfaction Index. décimale : PER Périodiques Résumé : Olfactory dysfunction is recognized in neurodevelopmental disorders and may serve as an early indicator of global dysfunction. The present meta-analysis measures olfaction effect sizes in attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASDs), and obsessive-compulsive disorder (OCD). Meta-analysis included 320 ADHD, 346 ASD, and 208 OCD individuals as compared to 910 controls. Olfactory performance deficits were small-to-moderate and heterogeneous (d =  - 0.42, 95% CI =  - 0.59 < δ <  - 0.25). Meta-analytic results indicate that olfactory dysfunction is evident in individuals with ASD and OCD, with small-to-negligible effects in ADHD. These findings imply olfactory dysfunction is related to clinical phenotype in ASD and OCD, but not ADHD, and warrant inclusion in clinical assessment and evaluation of certain neurodevelopmental disorders. En ligne : http://dx.doi.org/10.1007/s10803-020-04376-9 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=428 [article] Olfactory Dysfunction in Neurodevelopmental Disorders: A Meta-analytic Review of Autism Spectrum Disorders, Attention Deficit/Hyperactivity Disorder and Obsessive-Compulsive Disorder [texte imprimé] / Andrew J.D. CROW, Auteur ; Jennica M. JANSSEN, Auteur ; Kayci L. VICKERS, Auteur ; Julia PARISH-MORRIS, Auteur ; Paul J. MOBERG, Auteur ; David R. ROALF, Auteur . - p.2685-2697. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 50-8 (August 2020) . - p.2685-2697 Mots-clés : Attention-deficit/hyperactivity disorder  Autism spectrum disorders  Meta-analysis  Obsessive–compulsive disorder  Olfaction Index. décimale : PER Périodiques Résumé : Olfactory dysfunction is recognized in neurodevelopmental disorders and may serve as an early indicator of global dysfunction. The present meta-analysis measures olfaction effect sizes in attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASDs), and obsessive-compulsive disorder (OCD). Meta-analysis included 320 ADHD, 346 ASD, and 208 OCD individuals as compared to 910 controls. Olfactory performance deficits were small-to-moderate and heterogeneous (d =  - 0.42, 95% CI =  - 0.59 < δ <  - 0.25). Meta-analytic results indicate that olfactory dysfunction is evident in individuals with ASD and OCD, with small-to-negligible effects in ADHD. These findings imply olfactory dysfunction is related to clinical phenotype in ASD and OCD, but not ADHD, and warrant inclusion in clinical assessment and evaluation of certain neurodevelopmental disorders. En ligne : http://dx.doi.org/10.1007/s10803-020-04376-9 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=428

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