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Automated diagnosis of encephalitis in pediatric patients using EEG rhythms and slow biphasic complexes

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Abstract

Slow biphasic complexes (SBC) have been identified in the EEG of patients suffering for inflammatory brain diseases. Their amplitude, location and frequency of appearance were found to correlate with the severity of encephalitis. Other characteristics of SBCs and of EEG traces of patients could reflect the grade of pathology. Here, EEG rhythms are investigated together with SBCs for a better characterization of encephalitis. EEGs have been acquired from pediatric patients: ten controls and ten encephalitic patients. They were split by neurologists into five classes of different severity of the pathology. The relative power of EEG rhythms was found to change significantly in EEGs labeled with different severity scores. Moreover, a significant variation was found in the last seconds before the appearance of an SBC. This information and quantitative indexes characterizing the SBCs were used to build a binary classification decision tree able to identify the classes of severity. True classification rate of the best model was 76.1% (73.5% with leave-one-out test). Moreover, the classification errors were among classes with similar severity scores (precision higher than 80% was achieved considering three instead of five classes). Our classification method may be a promising supporting tool for clinicians to diagnose, assess and make the follow-up of patients with encephalitis.

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Authors and Affiliations

  1. Mathematical Biology and Physiology, Department of Electronics and Telecommunications, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Turin, Italy

    Luca Mesin & Massimo Valerio

  2. Ospedale Infantile Regina Margherita, Department of Child Neuropsychiatry, Universitá di Torino, Turin, Italy

    Giorgio Capizzi

Authors
  1. Luca Mesin
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  2. Massimo Valerio
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  3. Giorgio Capizzi
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Correspondence to Luca Mesin.

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The authors declare that they have no conflict of interest.

Ethical approval

This is a retrospective study conducted on already available data from pediatric patients for which formal consent was obtain from the parents.

Informed consent

As the patients were children, the consent for the examination and data processing was obtained from their parents.

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Mesin, L., Valerio, M. & Capizzi, G. Automated diagnosis of encephalitis in pediatric patients using EEG rhythms and slow biphasic complexes. Phys Eng Sci Med 43, 997–1006 (2020). https://doi.org/10.1007/s13246-020-00893-0

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  • DOI: https://doi.org/10.1007/s13246-020-00893-0

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