Optimizing Detection Rate and Characterization of Subtle Paroxysmal Neonatal Abnormal Facial Movements with Multi-Camera Video-Electroencephalogram Recordings.
Objectives We retrospectively analyze the diagnostic accuracy for paroxysmal abnormal facial movements, comparing one camera versus multi-camera approach. Background Polygraphic video-electroencephalogram (vEEG) recording is the current gold standard for brain monitoring in high-risk newborns, especially when neonatal seizures are suspected. One camera synchronized with the EEG is commonly used. Methods Since mid-June 2012, we have started using multiple cameras, one of which point toward newborns' faces. We evaluated vEEGs recorded in newborns in the study period between mid-June 2012 and the end of September 2014 and compared, for each recording, the diagnostic accuracies obtained with one-camera and multi-camera approaches. Results We recorded 147 vEEGs from 87 newborns and found 73 episodes of paroxysmal facial abnormal movements in 18 vEEGs of 11 newborns with the multi-camera approach. By using the single-camera approach, only 28.8% of these events were identified (21/73). Ten positive vEEGs with multicamera with 52 paroxysmal facial abnormal movements (52/73, 71.2%) would have been considered as negative with the single-camera approach. Conclusions The use of one additional facial camera can significantly increase the diagnostic accuracy of vEEGs in the detection of paroxysmal abnormal facial movements in the newborns.
Child Neuropsychiatry Unit, Department of Neuroscience, University of Parma, Parma, Italy.
Francesco
F
Pisani
Child Neuropsychiatry Unit, Department of Neuroscience, University of Parma, Parma, Italy.
Elena
E
Pavlidis
Department of Information Engineering, University of Parma, Parma, Italy.
Luca
L
Cattani
Department of Information Engineering, University of Parma, Parma, Italy.
Gianluigi
G
Ferrari
Department of Information Engineering, University of Parma, Parma, Italy.
Riccardo
R
Raheli
Child Neuropsychiatry Unit, Department of Neuroscience, University of Parma, Parma, Italy.
Carlotta
C
Spagnoli
D003937:Diagnosis, Differential; D020821:Dystonic Disorders / Q000175:diagnosis*; D004569:Electroencephalography / Q000379:methods; D005145:Face; D005260:Female; D006801:Humans; D007231:Infant, Newborn; D008297:Male; D009068:Movement; D009207:Myoclonus / Q000175:diagnosis*; D020447:Parasomnias / Q000175:diagnosis*; D013216:Reflex, Startle; D012189:Retrospective Studies; D012640:Seizures / Q000175:diagnosis*; D014202:Tremor / Q000175:diagnosis*; D014741:Video Recording / Q000379:methods*