Abstract
Diagnosis and prognosis of patients with disorders of consciousness (DOC) is a challenge for neuroscience and clinical practice. Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) is an effective tool to measure the level of consciousness. However, a scientific and accurate method to quantify TMS-evoked activity is still lacking. This study applied fast perturbational complexity index (PCIst) to the diagnosis and prognosis of DOC patients. TMS-EEG data of 30 normal healthy participants (NOR) and 181 DOC patients were collected. The PCIst was used to assess the time-space complexity of TMS-evoked potentials (TEP). We selected parameters of PCIst in terms of data length, data delay, sampling rate and frequency band. In addition, we collected Coma Recovery Scale-Revised (CRS-R) values for 114 DOC patients after one year. Finally, we trained the classification and regression model. 1) PCIst shows the differences among NOR, minimally consciousness state (MCS) and unresponsive wakefulness syndrome (UWS) and has low computational cost. 2) Optimal parameters of data length and delay after TMS are 300 ms and 101-300 ms. Significant differences of PCIst at 5-8 Hz and 9-12 Hz bands are found among NOR, MCS and UWS groups. PCIst still works when TEP is down-sampled to 250 Hz. 3) PCIst at 9-12 Hz shows the highest performance in diagnosis and prognosis of DOC. This study confirms that PCIst can quantify the level of consciousness. PCIst is a potential measure for the diagnosis and prognosis of DOC patients.
Highlights
Severe brain injury leads to disorders of consciousness (DOC), and DOC patients show none or only some behavioral signs of consciousness [1]
PCIst still works when TMS-evoked potential (TEP) is down-sampled to 250 Hz. 3) PCIst at 9-12Hz shows the highest performance in diagnosis and prognosis of DOC
PCIst is a potential measure for the diagnosis and prognosis of DOC patients
Summary
Severe brain injury leads to disorders of consciousness (DOC), and DOC patients show none or only some behavioral signs of consciousness [1]. The Coma Recovery Scale–Revised (CRS-R) is the gold standard for clinical assessment of consciousness level [5]. It measures patients' consciousness level by behavioral responses to external stimulation. Limited by the operator's proficiency and patient's cooperation, a study found that CRS-R had a 40% misdiagnosis rate in the clinical diagnosis of DOC [6]. Sitt et al reported differences of different consciousness states in terms of EEG power spectra, complexity and functional connectivity. They trained machine learning models for diagnosing patients from different institutions [14]. The above EEG studies cannot quantify the level of consciousness of patients at the individual level, nor did they study the predictive ability of EEG on patients' recovery outcome
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