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

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.

The relation between lesions and localization of sources of slow biphasic complexes in encephalitis

“…SBCs have been observed in patients with brain inflammations [13,15,28,29] . We have developed an automated processing method to identify SBCs and we have shown in previous studies a good correlation between their onset and the severity of encephalitis [14,18] . Here we have focused on the distribution of the sources of SBCs and their relation with the lesions identified in MRIs.…”

“…In brief, each EEG trace was processed with a set of match filters, each comparing the signal with a scaled version of a prototype biphasic waveform. The identified complexes were then automatically reviewed, excluding outliers and waveforms showing repetitive firings, as some waveforms could have a shape similar to that of an SBC, but they could not satisfy some properties indicated in previous publications [14,17,18] .…”

“…In particular, we have demonstrated that the number and amplitude of complexes reflect the severity of the inflammation in pediatric encephalitic patients [14] . Moreover, we have proposed to integrate information from different features of SBC to improve the diagnosis [18] .…”

Functional Connectivity of EEG in Encephalitis during Slow Biphasic Complexes

“…The slow biphasic complex (SBC) has been observed for decades in the EEG of patients with different brain inflammations [16][17][18]: Rasmussen's syndrome [19][20][21][22][23][24], human immunodeficiency virus (HIV) [25][26][27], West syndrome [17,18] and encephalitis [25]. Interesting properties of SBCs have been recently discovered, based on an automated method to identify them [28], which has allowed the quantifying of their appearance, amplitude, distribution and their relation with the severity of encephalitis [28,29], localization of lesions [30] and EEG rhythms [31]. Specifically, it was found that their number and cumulative amplitude increase with severity [28,29] and that the distribution of their sources is related to the regions in which lesions are detected in magnetic resonance images [30].…”

“…Specifically, it was found that their number and cumulative amplitude increase with severity [28,29] and that the distribution of their sources is related to the regions in which lesions are detected in magnetic resonance images [30]. Moreover, it was recently observed that the EEG is slower in short epochs before the onset of an SBC than in the rest of the trace [31]. This indicates that the brain is preparing for the coordinated discharge of neurons resulting in an SBC by increasing the relative power of low-frequency rhythms.…”