Evaluation of Heart Rate Variation Analysis during Rest and Tilting in Patients with Temporal Lobe Epilepsy

Spectral entropy indicates electrophysiological and hemodynamic changes in drug-resistant epilepsy - A multimodal MREG study

Objective

Epilepsy causes measurable irregularity over a range of brain signal frequencies, as well as autonomic nervous system functions that modulate heart and respiratory rate variability. Imaging dynamic neuronal signals utilizing simultaneously acquired ultra-fast 10 Hz magnetic resonance encephalography (MREG), direct current electroencephalography (DC-EEG), and near-infrared spectroscopy (NIRS) can provide a more comprehensive picture of human brain function. Spectral entropy (SE) is a nonlinear method to summarize signal power irregularity over measured frequencies. SE was used as a joint measure to study whether spectral signal irregularity over a range of brain signal frequencies based on synchronous multimodal brain signals could provide new insights in the neural underpinnings of epileptiform activity.

Methods

Ten patients with focal drug-resistant epilepsy (DRE) and ten healthy controls (HC) were scanned with 10 Hz MREG sequence in combination with EEG, NIRS (measuring oxygenated, deoxygenated, and total hemoglobin: HbO, Hb, and HbT, respectively), and cardiorespiratory signals. After pre-processing, voxelwise SE_MREG was estimated from MREG data. Different neurophysiological and physiological subfrequency band signals were further estimated from MREG, DC-EEG, and NIRS: fullband (0–5 Hz, FB), near FB (0.08–5 Hz, NFB), brain pulsations in very-low (0.009–0.08 Hz, VLFP), respiratory (0.12–0.4 Hz, RFP), and cardiac (0.7–1.6 Hz, CFP) frequency bands. Global dynamic fluctuations in MREG and NIRS were analyzed in windows of 2 min with 50% overlap.

Results

Right thalamus, cingulate gyrus, inferior frontal gyrus, and frontal pole showed significantly higher SE_MREG in DRE patients compared to HC. In DRE patients, SE of cortical Hb was significantly reduced in FB (p = .045), NFB (p = .017), and CFP (p = .038), while both HbO and HbT were significantly reduced in RFP (p = .038, p = .045, respectively). Dynamic SE of HbT was reduced in DRE patients in RFP during minutes 2 to 6. Fitting to the frontal MREG and NIRS results, DRE patients showed a significant increase in SE_EEG in FB in fronto-central and parieto-occipital regions, in VLFP in parieto-central region, accompanied with a significant decrease in RFP in frontal pole and parietal and occipital (O2, Oz) regions.

Conclusion

This is the first study to show altered spectral entropy from synchronous MREG, EEG, and NIRS in DRE patients. Higher SE_MREG in DRE patients in anterior cingulate gyrus together with SE_EEG and SE_NIRS results in 0.12–0.4 Hz can be linked to altered parasympathetic function and respiratory pulsations in the brain. Higher SE_MREG in thalamus in DRE patients is connected to disturbances in anatomical and functional connections in epilepsy. Findings suggest that spectral irregularity of both electrophysiological and hemodynamic signals are altered in specific way depending on the physiological frequency range.

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Simultaneous imaging methods indicate spectral irregularity in neurovascular and electrophysiological brain pulsations in DRE.

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Altered spectral entropy in EEG, NIRS and BOLD indicate dysfunctional brain pulsations in respiratory frequency in epilepsy.

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Spectral irregularity (0-5 Hz) of BOLD in right thalamus supports previous structural and functional findings in epilepsy.

Altered physiological brain variation in drug-resistant epilepsy

INTRODUCTION

Functional magnetic resonance imaging (fMRI) combined with simultaneous electroencephalography (EEG-fMRI) has become a major tool in mapping epilepsy sources. In the absence of detectable epileptiform activity, the resting state fMRI may still detect changes in the blood oxygen level-dependent signal, suggesting intrinsic alterations in the underlying brain physiology.

METHODS

In this study, we used coefficient of variation (CV) of critically sampled 10 Hz ultra-fast fMRI (magnetoencephalography, MREG) signal to compare physiological variance between healthy controls (n = 10) and patients (n = 10) with drug-resistant epilepsy (DRE).

RESULTS

We showed highly significant voxel-level (p < 0.01, TFCE-corrected) increase in the physiological variance in DRE patients. At individual level, the elevations range over three standard deviations (σ) above the control mean (μ) CV_MREG values solely in DRE patients, enabling patient-specific mapping of elevated physiological variance. The most apparent differences in group-level analysis are found on white matter, brainstem, and cerebellum. Respiratory (0.12-0.4 Hz) and very-low-frequency (VLF = 0.009-0.1 Hz) signal variances were most affected.

CONCLUSIONS

The CV_MREG increase was not explained by head motion or physiological cardiorespiratory activity, that is, it seems to be linked to intrinsic physiological pulsations. We suggest that intrinsic brain pulsations play a role in DRE and that critically sampled fMRI may provide a powerful tool for their identification.

Monitoring peri-ictal changes in heart rate variability, oxygen saturation and blood pressure in epilepsy monitoring unit

PURPOSE

The peri-ictal autonomic disturbances have been studied as predictors of seizure outcome and as markers of seizure onset. We studied the changes in heart rate (HR), HRV, oxygen saturation and blood pressure (BP) in the peri-ictal period in patients with drug-resistant localization-related epilepsy.

METHODOLOGY

Ninety one subjects undergoing video-EEG monitoring, underwent continuous HR, SpO2, BP and Lead II ECG monitoring. The changes during the preictal, ictal and postictal periods were analyzed for 57 seizures in 42 patients with artifact-free recordings and correlated with VEEG ictal onset and MRI characteristics.

RESULTS

Ictal tachycardia was noted in 15 (26.3%) seizures, of which, 60% had temporal lobe onset. HR increased by an average of 20.1% from pre-ictal to ictal phases (p=0.04). Ictal bradycardia was noted in one event with right temporal seizure onset. Heart rate variability (HRV) analysis of the preictal, ictal and postictal phases showed an increase in the sympathetic and decrease in parasympathetic activity during the ictus with relatively preserved total power. Ictal oxygen desaturation (84.1%±3.5%) was noticed in 10 (17.5%) seizures. Ictal hypertension was observed in 15 (26.3%); ictal hypotension was noted in 5 (8.7%) seizures. Both the systolic BP and diastolic BPs increased from the pre-ictal to ictal phase (p=0.01).

CONCLUSIONS

Peri-ictal dysautonomia can present in variable patterns and can be measured and compared over different modalities such as BP, HR and HRV. Though degree of tachycardia and increase in BP were higher during extratemporal onset of seizures, a fall in variability was noted in seizures of temporal lobe origin. Oxygen desaturation is not an uncommon event during the peri-ictal period in localization related epilepsy.

Telemetry-derived heart rate variability responses to a physical stressor

Analysis of heart rate variability (HRV) responses to an orthostatic challenge can be used to investigate autonomic control of heart rate, an index of cardiovascular function. HRV is typically assessed using the electrocardiogram (ECG), which can be impractical for use with large population-based studies.

PURPOSE

To assess the validity and reliability of telemetry-derived HRV responses to an orthostatic challenge.

METHODS

Twenty healthy adults (26 + 5 years, 45% male) were tested on three separate mornings. Following 20-min supine rest, R-R intervals were recorded using a telemetric device during three conditions: BASE, TILT and RECOVERY. ECG was simultaneously used on 1 day for validity comparison. Measures of HRV included the following: standard deviation of normal-to-normal intervals (SDNN), the root-mean-square of successive differences (RMSSD) and the low-frequency (LF) and high-frequency (HF) spectral power.

RESULTS

For all parameters, there was excellent agreement between devices for BASE (r = 0·96-0·99), TILT (r = 0·89-1·00) and RECOVERY (r = 0·96-1·00). For the telemetric device, between-day intraclass coefficient values for RMSDD, SDNN and HF were all above the 0·75 criterion for each condition, indicating excellent between-day reliability. For each condition, the reliability coefficient, expressed as a percentage of the mean (RC%), was marginally lower (greater reliability) for RMSDD (RC% 11-13) and SDNN (RC% 10-12) compared to HF (RC% 12-17). However, SDNN did not significantly respond to the orthostatic challenge.

CONCLUSION

Telemetric HRV, particularly RMSDD and HF, can be used to provide a sensitive, valid and reliable assessment of autonomic control of heart rate.

Neuroanatomical correlates of atrial fibrillation: a longitudinal MRI study

BACKGROUND AND PURPOSE

To determine baseline volume and rate of volume change of whole brain, hippocampus, and entorhinal cortex in patients with atrial fibrillation.

METHODS

We analyzed clinical and neuroimaging data collected as part of Alzheimer's Disease Neuroimaging Initiative in the United States and Canada. Patients with atrial fibrillation were identified based on baseline clinical/cognitive assessments, and age and gender-matched controls without atrial fibrillations were selected (1:1 ratio). All participants underwent 1.5 T structural magnetic resonance imaging (MRI) at specified intervals (6 or 12 months) for 2-3 years.

RESULTS

A total of 33 persons with atrial fibrillation were included. There was no difference in whole brain and ventricular volumes at baseline MRI between cases and controls. There was significantly lower entorhinal cortex volume on right (p = 0.01) and left (p = 0.01) sides in patients with atrial fibrillation. There was significantly lower volume for middle temporal lobes on right (p = 0.04) and left (p = 0.001) sides. The rate of progression of atrophy in entorhinal cortex and middle temporal lobes was not different between patients with atrial fibrillation and controls.

CONCLUSIONS

The association of atrial fibrillation with volume loss in entorhinal cortex and middle temporal lobes may provide new insights into pathophysiology of atrial fibrillation.