title: Syndrome identification based on 2D analysis software.
abstract: Clinical evaluation of children with developmental delay continues to present a challenge to the clinicians. In many cases, the face provides important information to diagnose a condition. However, database support with respect to facial traits is limited at present. Computer-based analyses of 2D and 3D representations of faces have been developed, but it is unclear how well a larger number of conditions can be handled by such systems. We have therefore analysed 2D pictures of patients each being affected with one of 10 syndromes (fragile X syndrome; Cornelia de Lange syndrome; Williams-Beuren syndrome; Prader-Willi syndrome; Mucopolysaccharidosis type III; Cri-du-chat syndrome; Smith-Lemli-Opitz syndrome; Sotos syndrome; Microdeletion 22q11.2; Noonan syndrome). We can show that a classification accuracy of >75% can be achieved for a computer-based diagnosis among the 10 syndromes, which is about the same accuracy achieved for five syndromes in a previous study. Pairwise discrimination of syndromes ranges from 80 to 99%. Furthermore, we can demonstrate that the criteria used by the computer decisions match clinical observations in many cases. These findings indicate that computer-based picture analysis might be a helpful addition to existing database systems, which are meant to assist in syndrome diagnosis, especially as data acquisition is straightforward and involves off-the-shelf digital camera equipment.
authors.affiliation: Institut für Humangenetik, Universitätsklinikum Essen, Essen, Germany. correspondence@s-boehringer.org
authors.forename: Stefan
authors.initials: S
authors.lastname: Boehringer
authors.forename: Tobias
authors.initials: T
authors.lastname: Vollmar
authors.forename: Christiane
authors.initials: C
authors.lastname: Tasse
authors.forename: Rolf P
authors.initials: RP
authors.lastname: Wurtz
authors.forename: Gabriele
authors.initials: G
authors.lastname: Gillessen-Kaesbach
authors.forename: Bernhard
authors.initials: B
authors.lastname: Horsthemke
authors.forename: Dagmar
authors.initials: D
authors.lastname: Wieczorek
mesh_terms: D000293:Adolescent; D000328:Adult; D002648:Child; D002675:Child, Preschool; D019465:Craniofacial Abnormalities / Q000175:diagnosis; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D019066:Facies; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012984:Software; D013577:Syndrome