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Next generation phenotyping for diagnosis and phenotype-genotype correlations in Kabuki syndrome.
Hennocq, Quentin; Willems, Marjolaine; Amiel, Jeanne; Arpin, Stéphanie; Attie-Bitach, Tania; Bongibault, Thomas; Bouygues, Thomas; Cormier-Daire, Valérie; Corre, Pierre; Dieterich, Klaus; Douillet, Maxime; Feydy, Jean; Galliani, Eva; Giuliano, Fabienne; Lyonnet, Stanislas; Picard, Arnaud; Porntaveetus, Thantrira; Rio, Marlène; Rouxel, Flavien; Shotelersuk, Vorasuk; Toutain, Annick; Yauy, Kevin; Geneviève, David; Khonsari, Roman H; Garcelon, Nicolas.
Afiliación
  • Hennocq Q; Imagine Institute, INSERM UMR1163, 75015, Paris, France. quentin.hennocq@aphp.fr.
  • Willems M; Service de chirurgie maxillo-faciale et chirurgie plastique, Hôpital Necker-Enfants Malades, Assistance Publique-Hôpitaux de Paris, Paris, France. quentin.hennocq@aphp.fr.
  • Amiel J; Centre de Référence des Malformations Rares de la Face et de la Cavité Buccale MAFACE, Filière Maladies Rares TeteCou, Paris, France. quentin.hennocq@aphp.fr.
  • Arpin S; Faculté de Médecine, Université de Paris Cité, 75015, Paris, France. quentin.hennocq@aphp.fr.
  • Attie-Bitach T; Laboratoire 'Forme et Croissance du Crâne', Faculté de Médecine, Hôpital Necker-Enfants Malades, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France. quentin.hennocq@aphp.fr.
  • Bongibault T; Hôpital Necker-Enfants Malades, 149 rue de Sèvres, 75015, Paris, France. quentin.hennocq@aphp.fr.
  • Bouygues T; Département de Génétique Médicale, Maladies Rares et Médecine Personnalisée, Génétique clinique, CHU Montpellier, Centre de référence anomalies du développement SOOR, INSERM U1183, Montpellier University, Montpellier, France.
  • Cormier-Daire V; Imagine Institute, INSERM UMR1163, 75015, Paris, France.
  • Corre P; Faculté de Médecine, Université de Paris Cité, 75015, Paris, France.
  • Dieterich K; Service de médecine génomique des maladies rares, Hôpital Necker-Enfants Malades, Assistance Publique-Hôpitaux de Paris, Paris, France.
  • Douillet M; Service de Génétique, CHU Tours, UMR 1253, iBrain, Université de Tours, Inserm, Tours, France.
  • Feydy J; Imagine Institute, INSERM UMR1163, 75015, Paris, France.
  • Galliani E; Faculté de Médecine, Université de Paris Cité, 75015, Paris, France.
  • Giuliano F; Service de médecine génomique des maladies rares, Hôpital Necker-Enfants Malades, Assistance Publique-Hôpitaux de Paris, Paris, France.
  • Lyonnet S; Imagine Institute, INSERM UMR1163, 75015, Paris, France.
  • Picard A; Laboratoire 'Forme et Croissance du Crâne', Faculté de Médecine, Hôpital Necker-Enfants Malades, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France.
  • Porntaveetus T; Imagine Institute, INSERM UMR1163, 75015, Paris, France.
  • Rio M; Laboratoire 'Forme et Croissance du Crâne', Faculté de Médecine, Hôpital Necker-Enfants Malades, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France.
  • Rouxel F; Imagine Institute, INSERM UMR1163, 75015, Paris, France.
  • Shotelersuk V; Faculté de Médecine, Université de Paris Cité, 75015, Paris, France.
  • Toutain A; Service de médecine génomique des maladies rares, Hôpital Necker-Enfants Malades, Assistance Publique-Hôpitaux de Paris, Paris, France.
  • Yauy K; Nantes Université, CHU Nantes, Service de chirurgie maxillo-faciale et stomatologie, 44000, Nantes, France.
  • Geneviève D; Nantes Université, Oniris, UnivAngers, CHU Nantes, INSERM, Regenerative Medicine and Skeleton, RMeS, UMR 1229, 44000, Nantes, France.
  • Khonsari RH; Univ. Grenoble Alpes, Inserm, U1209, IAB, CHU Grenoble Alpes, 38000, Grenoble, France.
  • Garcelon N; Imagine Institute, INSERM UMR1163, 75015, Paris, France.
Sci Rep ; 14(1): 2330, 2024 01 28.
Article en En | MEDLINE | ID: mdl-38282012
ABSTRACT
The field of dysmorphology has been changed by the use Artificial Intelligence (AI) and the development of Next Generation Phenotyping (NGP). The aim of this study was to propose a new NGP model for predicting KS (Kabuki Syndrome) on 2D facial photographs and distinguish KS1 (KS type 1, KMT2D-related) from KS2 (KS type 2, KDM6A-related). We included retrospectively and prospectively, from 1998 to 2023, all frontal and lateral pictures of patients with a molecular confirmation of KS. After automatic preprocessing, we extracted geometric and textural features. After incorporation of age, gender, and ethnicity, we used XGboost (eXtreme Gradient Boosting), a supervised machine learning classifier. The model was tested on an independent validation set. Finally, we compared the performances of our model with DeepGestalt (Face2Gene). The study included 1448 frontal and lateral facial photographs from 6 centers, corresponding to 634 patients (527 controls, 107 KS); 82 (78%) of KS patients had a variation in the KMT2D gene (KS1) and 23 (22%) in the KDM6A gene (KS2). We were able to distinguish KS from controls in the independent validation group with an accuracy of 95.8% (78.9-99.9%, p < 0.001) and distinguish KS1 from KS2 with an empirical Area Under the Curve (AUC) of 0.805 (0.729-0.880, p < 0.001). We report an automatic detection model for KS with high performances (AUC 0.993 and accuracy 95.8%). We were able to distinguish patients with KS1 from KS2, with an AUC of 0.805. These results outperform the current commercial AI-based solutions and expert clinicians.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Anomalías Múltiples / Inteligencia Artificial / Enfermedades Vestibulares / Cara / Enfermedades Hematológicas Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Anomalías Múltiples / Inteligencia Artificial / Enfermedades Vestibulares / Cara / Enfermedades Hematológicas Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Reino Unido