Electroencephalogram (EEG) Spike Metrics Discriminate Impending Epileptic Spasms From Other Seizures in Children With Tuberous Sclerosis Complex: A Pilot Study

Abstract

In data from a multicenter prospective observational study, we assessed whether interictal epileptiform discharge metrics in the pre-seizure onset surveillance scalp electroencephalograms (EEGs) in children with tuberous sclerosis complex could predict seizure outcomes, specifically epileptic spasms. In 16 children with eligible EEG data (7 with epileptic spasms and 9 with other seizure types) and 16 controls, 2 spike metrics were calculated through automated detection followed by expert review: (1) spike rate (spikes per minute) and (2) number of unique spike foci. In patients who developed seizures, a combination of spike rate threshold of ≥2 per minute and ≥2 unique spike foci during sleep was highly predictive of impending epileptic spasms (100% positive predictive value, 2 false negatives). One control patient was falsely predicted to develop epileptic spasms, decreasing the overall positive predictive value to 83.3%. These findings suggest that EEG spike metrics could predict impending epileptic spasms in children with tuberous sclerosis complex, pending larger-scale validation.

Keywords

epilepsy epileptic spasms epileptiform discharges infantile epileptic spasms syndrome tuberous sclerosis complex

Tuberous sclerosis complex (TSC) is a rare autosomal dominant neurocutaneous disorder that affects several organ systems, with an incidence of ∼1 in 6000 to 10 000 live births.¹ It is caused by pathogenic variants in the TSC1 or TSC2 gene, which causes malfunction of the hamartin or tuberin proteins, respectively.^2,3 This protein complex aids in the regulation of cellular growth, differentiation, migration, and proliferation.² Various lesions can appear in the brain and other organs such as the kidneys, heart, skin, retina, and lungs.⁴

The neurologic symptoms associated with tuberous sclerosis complex are particularly devastating as they appear early in life and affect neurodevelopment. Epilepsy is one of the most common neurologic manifestations of tuberous sclerosis complex, occurring in up to 80% to 90% of patients.⁵ Among these, approximately 50% develop infantile epileptic spasms syndrome, a syndrome with developmental and epileptic encephalopathy that arises during a period of steep neurodevelopment.^6,7 Infantile epileptic spasms syndrome classically manifests in infancy and is characterized by clusters of flexor, extensor, or mixed spasms, known as epileptic spasms.^7,8 Epileptic spasms are strongly associated with poor neurologic outcomes, including intellectual disability, autism spectrum disorder, and refractory epilepsy.⁹

The early diagnosis of tuberous sclerosis complex allows for close monitoring of the emergence of symptoms, including epilepsy. An increasing body of literature suggests that early or preventative treatment of epileptic spasms may be associated with improved epilepsy outcomes although impact on neurodevelopment has not yet been demonstrated.^10,11 Vigabatrin, the first-line treatment for epileptic spasms in tuberous sclerosis complex and used in both preventative trials in Europe and the USA, however, is associated with side effects including potential for retinal toxicity.¹² With serial electroencephalograms (EEGs), the majority of children with impending epilepsy can be identified weeks to months prior to the clinical onset of their seizures, allowing for a clinical decision to preemptively treat children at high risk for epilepsy.¹³

The current study goals differ and focus on the identification of quantitative EEG features. Here, we aimed to identify a biomarker of impending epileptic spasms using quantification of interictal epileptiform discharge (referred to as “spikes” in this manuscript, and includes sharp waves) metrics in the pre-seizure onset surveillance scalp EEGs in children with tuberous sclerosis complex. We investigated whether (1) spike rate and (2) number of spike foci could discriminate between impending epileptic spasms versus impending any other seizure types (AS), to potentially allow for tailoring preventative medication in tuberous sclerosis complex to a specific seizure type. We hypothesized that higher spike rates and a higher number of independently active spike foci would be associated with an elevated risk for epileptic spasms, as compared to AS.

Patients and Methods

Data Collection

For the TSC Autism Center of Excellence Research Network (TACERN) prospective multicenter observational study of early predictors of epilepsy and autism spectrum disorder, 156 children between the ages of zero and 36 months with tuberous sclerosis complex were enrolled at 5 centers: the University of Alabama at Birmingham, Boston Children's Hospital, University of California Los Angeles, Cincinnati Children's Hospital Medical Center, and University of Texas Health Science Center at Houston. Enrollment occurred from September 2012 to December 2018. Participants of the TSC Epilepsy Biomarker Study (TSC-EBS), conducted concurrently at the same 5 centers, were also eligible for inclusion in the current analysis. TSC-EBS was a prospective multicenter observational study (some dual-enrolled in both TACERN and TSC-EBS) for evaluation of conventional EEG as a predictive biomarker of impending seizure onset in tuberous sclerosis complex infants.

Demographic and clinical data were retrieved from case record forms. Data collected included race, gender, genetic testing, age at the time of EEG recording, age at onset for each seizure type, seizure classification, and antiseizure medication use.

EEG Recording and Interpretation

A 1-hour awake and asleep EEG acquisition protocol was standardized across all 5 sites, with a sampling rate of 2000 Hz, a 500-Hz high-frequency filter, no low-frequency filter, and 24 electrodes placed according to the internal 10-20 system of electrode placement, including ground and reference. In the TACERN study, EEG acquisitions occurred at the baseline enrollment study visit and at ages 3, 6, 9, 12, 18, 24, and 36 months. In patients also enrolled in TSC-EBS, more surveillance EEGs were obtained within the same time span: before 3 weeks of age, at 6 weeks, and at 3, 4.5, 6, 9, 12, 18, and 24 months. Pre-seizure onset EEGs were retrieved from a centralized online repository and, when needed, supplemented with local backup data.

We excluded children with poor-quality EEG data, those treated with antiseizure medications at the time of EEG acquisition, and those who developed epileptic spasms after first developing AS. If more than 1 EEG prior to seizure onset was available, files were selected that were closest to the onset and had stage II sleep captured. The EEG files were visually reviewed for artifact and data quality, which rendered only 16 eligible patients with an EEG prior to the onset of seizures (Figure 1). As our study focused on the EEGs before the first seizure type to emerge, patients with AS who then also developed epileptic spasms during the study were excluded. Sixteen age-matched controls, enrolled in the same TACERN and TSC-EBS studies, but who did not develop epilepsy for the duration of the study, were included as controls to assess false positive spike metrics. We quantified spikes during stage II sleep to reduce artifacts related to the awake state, for consistency of state across subjects, and to capitalize on sleep-associated spike augmentation.¹⁴ Stage II sleep was defined as starting at the first evident sleep spindle until the last occurrence before the emergence of an EEG arousal pattern. For neonatal and early infantile EEGs, age-specific patterns including trace alternant were used. The EEG data were de-identified, stripped from technician comments, and rearranged into random order to maintain blinding.

EEG Analysis and Spike Detection

For conventional metrics, preprocessing and automated spike detection were performed using Persyst 14 (Persyst, Solana Beach, CA). This commercially available software contains a spike review feature based on machine learning, which detects individual spikes and groups them by electrode. We opted for the “high sensitivity” setting during detection to limit the number of potentially missed spikes (false negatives). For the purposes of this manuscript, spikes and sharp waves were considered equivalent.

To achieve optimal specificity and sensitivity in spike quantification, we applied a recently proposed hybrid approach of human expert review of automatically detected spikes.¹⁵ Two independent board-certified pediatric electroencephalographers (JP and AH) independently verified accurate delineation of stage II sleep and reviewed all detected spikes to select spikes meeting the International Federation of Clinical Neurophysiology criteria¹⁶ and discarded excessively detected spikes. An independent spike focus was defined as a recurrent discharge with similar morphology and voltage field, allowing for variations in the distribution of the local maximum in the involved leads. In addition, both readers independently reviewed the original tracing to ensure no spike populations were missed. Next, a joint review rendered only consensus spikes and foci. Finally, the data were cross-validated with the formal TACERN and P20 scoring sheets¹³ for the presence or absence of interictal epileptiform discharges. Except for the patient's age, the readers were blinded to all clinical variables. Our workflow is depicted in Figure 2.

We calculated the following EEG metrics prior to seizure onset: (1) spike rate (spikes per minute) for the total EEG and during stage II sleep only; (2) number of individual spike foci for the total EEG and during stage II sleep only, based on 2 (and more conservatively, 5) or more recurrent spikes per focus.

Data Availability Statement and IRB Approval

All data from the TACERN prospective multicenter observational study of early predictors of epilepsy and autism spectrum disorder are deposited at the National Database for Autism Research (NDAR) and are available to the public and researchers. Beyond NDAR, researchers can be granted access to additional clinical and surgical data collected for this manuscript by submitting a data access request to the TACERN collaborative. The study protocols were approved by the internal review boards at each site with direction from the leading regulatory core at Cincinnati Children's Hospital Medical Center. Informed consent was obtained from the parents or legal guardians of all participants. The study was conducted in accordance with Good Clinical Practice guidelines. Data from each study site were entered into a Web-based, distributed data management system meeting Health Insurance Portability and Accountability Act privacy regulations.

Results

Demographic and Clinical Data

Thirty-two children with tuberous sclerosis complex in the TACERN and TSC-EBS studies were included in the current study: 7 children with EEGs prior to epileptic spasms, 9 with EEG data prior to AS, and 16 age-matched controls who did not develop epilepsy for the duration of the study (Figure 1). Demographics, clinical data, and spike metrics are represented in Table 1. Of the children, 20 (62.5%) were male and 18 (56.3%) had TSC2 pathogenic variants. The median age at time of EEG was 138.5 days (range 47-416): 140 days (range 47-400) for the AS group, 126 days (range 47-403) for the epileptic spasms group, and 139.5 days (range 50-416) for the control group. Median duration from EEG to seizure onset was 67 days (24-259) for AS group and 51.5 days (12-106) for epileptic spasms group. Mean duration of total EEG recording was 57 minutes (range 40-90) and 24 minutes during stage II sleep (range 6-59).

Table 1.

Demographics, Clinical Data and Spike Metrics for the ES, AS, and Control Patients.

						Total			Sleep
Patient	Gender	Genetic testing	Age at EEG (days)	Duration until seizure (days)	Clinical seizure type	Spikes per minute^a	Spike foci (>1)^b	Spike foci (≥5)^c	Spikes per minute^d	Spike foci (>1)^e	Spike foci (≥5)^f
ES
1	Female	TSC2	47	58	ES	0	0	0	0	0	0
2	Male	TSC2	403	45	ES	9	8	8	12.9	7	7
3	Male	Unknown	113	74	ES	0.7	5	3	1.3	4	2
4	Female	TSC2	102	26	ES	4.6	10	6	8.3	8	4
5	Female	TSC2	126	45	ES	0.9	5	4	3.3	4	3
6	Male	TSC2	274	106	ES	1.1	3	3	3.2	3	3
7	Female	Unknown	165	12^g	ES	10.1	8	8	12.5	8	4
AS
8	Male	TSC1	196	59	F	0	0	0	0	0	0
9	Male	TSC2	180	67	F	1.2	5	3	1	5	3
10	Female	TSC2	73	259	F	0	0	0	0	0	0
11	Male	NMI	400	93	F	0	0	0	0	0	0
12	Female	TSC2	98	104	F	0.2	3	1	0.7	3	1
13	Female	TSC2 VUS	367	37	F	0	0	0	0	0	0
14	Female	TSC2	136	171	G + F	0.1	1	0	0.1	1	0
15	Female	TSC1	140	24	F	0	0	0	0	0	0
16	Male	TSC2	47	55	F	0.2	4	1	0.2	2	0
Control
17	Male	unknown	77	N/A	N/A	0	0	0	0	0	0
18	Male	TSC2	178	N/A	N/A	1.6	5	3	2.7	3	3
19	Male	NMI	142	N/A	N/A	0	0	0	0	0	0
20	Male	TSC2	136	N/A	N/A	0	0	0	0	0	0
21	Male	TSC1	171	N/A	N/A	0	0	0	0	0	0
22	Male	TSC2 VUS	134	N/A	N/A	0	0	0	0	0	0
23	Male	TSC1	137	N/A	N/A	0	0	0	0	0	0
24	Female	TSC1	219	N/A	N/A	0	0	0	0	0	0
25	Male	TSC1	137	N/A	N/A	0	0	0	0	0	0
26	Male	TSC1	86	N/A	N/A	0	0	0	0	0	0
27	Male	TSC2	416	N/A	N/A	0	0	0	0	0	0
28	Male	TSC2	62	N/A	N/A	0	0	0	0	0	0
29	Male	TSC1	369	N/A	N/A	0	0	0	0	0	0
30	Male	TSC1	275	N/A	N/A	0	0	0	0	0	0
31	Female	TSC2	50	N/A	N/A	0	0	0	0	0	0
32	Female	TSC2 VUS	384	N/A	N/A	0	0	0	0	0	0

Abbreviations: AS, any other seizure types; EEG, electroencephalography; ES, epileptic spasms; F, focal; G, generalized; N/A, not applicable; NMI, no mutation identified; VUS, variant of unknown significance.

^aTotal number of spikes divided by the duration of the total EEG in minutes.

^bTotal spike foci with more than one spike detected during total EEG.

^cTotal spike foci with five or more spikes detected during total EEG.

^dSpikes found during stage II sleep divided by the duration of stage II sleep in minutes.

^eSpike foci with more than one spike detected during the duration of stage II sleep.

^fSpike foci with five or more spikes detected during duration of stage II sleep.

^gDuration until onset seizure of this patient is until the start of vigabatrin.

Spike Rate

During stage II sleep, the mean spike rate was 0.22 per minute (range 0-1.0) and 5.93 (range 0-12.9) for the AS and epileptic spasms groups, respectively (Table 1). Analysis of the total EEG noted a mean spike rate of 0.19 per minute (range 0-1.2) and 3.78 per minute (range 0-10.1) for the AS and epileptic spasms groups, respectively. In the AS group, spike rate for the total EEG and during stage II sleep was not correlated with time to seizure onset. In the epileptic spasms group, spike rate appeared to increase with proximity to seizure onset, but correlation analysis could not be performed because of small numbers.

AS and epileptic spasms groups were separated by a spike rate threshold of ≥2 per minute during sleep (Fisher exact test, P = .0048, positive predictive value for predicting epileptic spasms 100%), but not when awake EEG data were included (P = .0625) (Table 2). A single control patient (No. 18) exhibited spikes in the EEG without developing seizures. When control patients were included in the analysis, the positive predictive value for predicting epileptic spasms using a spike threshold of ≥2 per minute during sleep was 83.3% (P = .0006).

Table 2.

Sensitivity and Specificity of the Spike Rate (Left Side) and Spike Foci (With ≥5 Spikes per Focus) (Right Side), Both Expressed as Percentages, During Stage II Sleep.^a

Spike rate during stage II sleep	Sensitivity, %	Specificity, %	Spike foci during stage II sleep	Sensitivity, %	Specificity, %
≥1	85.7	88.9	≥1	85.7	77.8
≥2	71.4	100	≥2	85.7	88.9
≥3	71.4	100	≥3	71.4	88.9
≥4	42.9	100	≥4	42.9	100
≥5	42.9	100	≥5	14.3	100
≥6	42.9	100	≥6	14.3	100

Abbreviation: ES, epileptic spasms.

The table compares their ability to discriminate impending ES from any other seizure types in children with tuberous sclerosis complex.

Spike Foci

During stage II sleep, the mean number of spike foci was 1.22 (range 0-5) and 4.86 (range 0-8) for the AS and epileptic spasms groups, respectively (Table 1). Analysis of the total EEG noted a mean number of spike foci of 1.44 (range 0-5) and 5.57 (range 0-10) for the AS and epileptic spasms groups, respectively.

For the total EEG, an increase in the number of spike foci (defined as >1 spike at a single location) was associated with an increased risk for epileptic spasms (OR 1.728, 95% CI 1.032-2.896, P = .038). When a spike focus was defined as ≥5 spikes at a single location, this association was stronger (OR 2.835, 95% CI 1.072-7.499, P = .036).

During sleep, the association between number of spike foci and risk for epileptic spasms was also present, both with spike foci defined as >1 recurrent spike (OR 1.857, 95% CI 1.032-3.341, P = .039) and as ≥5 spikes at a single location (OR 3.155, 95% CI 1.172-8.495, P = .023).

Using the latter metric of ≥5 spikes per focus during sleep, a threshold of ≥2 foci effectively separated the AS and epileptic spasms groups (Fisher exact, P = .0087, positive predictive value for predicting epileptic spasms 85.7%). However, when the control group was included in the analysis, the positive predictive value for predicting epileptic spasms was 75% (P = .0002). There was no correlation between number of foci and duration of sleep recording (Table 2).

Predictive Value for Epileptic Spasms Versus Other Seizures

The best-performing metrics of a (1) spike rate threshold of ≥2 spikes per minute combined with (2) spike focus threshold of ≥2 (with ≥5 spikes per focus) in the sleep-only portion of an EEG prior to seizure onset, separated the AS and epileptic spasms groups without false positives in these 2 groups, and only 2 false negatives (Fisher exact P = .0048, positive predictive value for predicting epileptic spasms 100%). Prediction did not improve when both criteria were combined, as 2 patients who developed epileptic spasms had neither a high spike rate nor a high number of spike foci. However, in the control group, there was 1 false positive (case 18) with a sleep spike rate of 2.3 and 3 spike foci, who did not develop either epileptic spasms or AS. When controls were included in the analysis, the positive predictive value for predicting epileptic spasms by a spike rate threshold of ≥2 per minute during sleep and spike focus threshold of ≥2 was 83.3% (P = .0006).

Discussion

This pilot study provides first steps toward the prediction of impending epileptic spasms using EEG data available from routine clinical care in children with tuberous sclerosis complex. In patients who developed seizures, the 2 metrics combined (1) the spike rate of ≥2 spikes per minute AND (2) ≥2 spike foci (with ≥5 spikes per focus) in the sleep-only portion of an EEG prior to seizure onset, discriminated impending epileptic spasms from AS without false positives. When all patients were included in the analysis, these same metrics predicted epileptic spasms with one false positive in the control group. Although the 2 metrics each individually had a good predictive value, the combination did not improve their performance. Should this marker be validated in a much larger cohort, one could then also determine thresholds for minimizing false negatives (cases of epileptic spasms not identified) or for minimizing false positives (cases of epileptic spasms falsely predicted). Our findings represent a “proof of principle” only and the data set is too small, with too many patients lost, to infer any clinical implications.

Mytinger et al¹⁷ used a threshold of ≥3 foci in the grading of the interictal EEG in children with active epileptic spasms. In case 7 from our study, the patient developed a marked epileptic encephalopathy with a BASED score of 5 and was started on vigabatrin 12 days later for presumed spasms. Despite the similarity between the 2 scoring methods, we did not examine the utility of the BASED score in this population, as it primarily indicates the likelihood of epileptic encephalopathy at the time of the EEG and includes background pattern assessment. Similarly, Muzykewicz et al¹⁸ analyzed the prognostic utility of various EEG features in patients with tuberous sclerosis complex and active infantile spasms after onset had occurred. In our study, clinically reported seizures were not present at the time of the EEG, and we aimed to differentiate future epileptic spasms from other impending seizures.

We have previously reported the predictive value of the first abnormal EEG for the onset of seizures in tuberous sclerosis complex,¹³ with a mean lag time of 3.6 months. That study, however, included only the first abnormal EEG. Here, we included all patients with any pre-seizure EEG, even when recorded close to seizure onset. Theoretically, this would allow for using our spike quantification in any scenario prior to seizure onset to assess the risk for impending epileptic spasms, but future validation studies would benefit from the application of our metrics in a longitudinal design—and analyze both the first and later EEGs. Unfortunately, a direct comparison to this article is not feasible, as the goal of the Wu et al¹³ study was different—the current study required detailed computer analysis of raw EEG data, which required a substantial dedicated effort of recovery and harmonization of multicenter data collected over several years.

The EPISTOP study (long-term, prospective study evaluating clinical and molecular biomarkers of epileptogenesis in a genetic model of epilepsy—tuberous sclerosis complex, NCT02098759) used pre-seizure onset EEGs to randomize children (randomized arm) or use local prevailing practice (nonrandomized arm) to decide on the preemptive use of vigabatrin in children with tuberous sclerosis complex in the first 2 years of life.¹¹ EEGs were defined as containing epileptiform activity when spikes were present in >10% of total recording, or presence of 2 or more spike foci, or widespread/generalized activity (including hypsarrhythmia). The applied spike rate criterion would suggest an average spike rate of >6 spikes per minute, yet only 40% of the 25 patients in the non-treatment arms developed epileptic spasms. However, EEGs were scored by clinical readers rather than computationally quantified, and sleep was not separately analyzed. This discrepancy does suggest, again, that further validation of our metrics (and thresholds) is needed. In the PREVeNT study (Preventing Epilepsy Using Vigabatrin in Infants with Tuberous Sclerosis Complex Trial, NCT02849457), a prospective multicenter, randomized, placebo-controlled, double-blind clinical trial of early preemptive vigabatrin versus use of vigabatrin after seizure onset, any epileptiform discharge in the EEG that was agreed on by the 2 centralized readers, would prompt randomization to active drug or placebo.¹⁹ We intend to use the children in the placebo-arm delayed treatment arm from the PREVeNT trial to further explore spike metrics in the prediction of seizure types in tuberous sclerosis complex.

In summary, our findings suggest discrimination between impending epileptic spasms and impending any other seizure types is possible. However, because of the small number of included patients, a larger-scale replication is warranted before any clinical implementation. Currently, vigabatrin remains the drug of first choice in epilepsy associated with tuberous sclerosis complex in children under 1 year of age, given the risk of epileptic spasms following AS (focal seizures); there are no current data to support conventional or preemptive treatment with other medications in infants with tuberous sclerosis complex.

A major limitation of the study is the high number of missing recordings, and many EEG files were corrupted during the retrieval and unarchiving of TACERN study data. Ongoing efforts are being made to recuperate EEGs from local repositories at participating sites. Furthermore, prominent artifacts in the EEGs prevented analysis through our semi-automated pipeline and were therefore excluded. Another potential limitation is the modest interrater agreement with regard to individual interictal epileptiform discharges.²⁰ In line with Kural et al,¹⁵ we, therefore, opted for a hybrid approach that capitalized on the high sensitivity of spike detection, followed by human expert review to determine consensus spikes.

Conclusion

Our pilot study suggests higher spike rates and a higher number of independently active spike foci are each associated with an elevated risk for impending epileptic spasms, as compared to other seizure types. The current study is too small to inform any clinical decisions regarding the preventative treatment of epilepsy in tuberous sclerosis complex and needs larger-scale validation.

Footnotes

Acknowledgements

The authors are deeply grateful to the patients and their families for their unwavering support and dedication to advancing research in tuberous sclerosis complex.

Author Contributions

J.P. conceptualized the study and supervised the project. P.B. developed the methodology, collected and analyzed the data, and wrote the manuscript. J.P. and A.H. independently verified accurate delineation of stage II sleep and reviewed all detected spikes. All authors provided critical feedback on the manuscript and approved the final manuscript.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding Information (TACERN/P20)

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research reported in this publication was supported by the National Institute of Neurological Disorders and Stroke of the National Institutes of Health (NINDS) and Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD) under Award Numbers U01NS082320 and P20NS0801999. Research was also supported by the Department of Defense (DoD) under Award Number HT9425-24-1-0485 (PI: R. R. Rajaraman). Additional funding came from the MacPherson Fund, Inc, and the Greenberg, Furman, Tamburo, Strem, and Hayes families. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Clinical Trial Registration

Clinicaltrials.gov: NCT01780441 (TACERN) and NCT01767779 (TSC-EBS).

ORCID iDs

Pauline J. Brandon Bravo Bruinsma

Aristides Hadjinicolaou

Mustafa Sahin

Brenda E. Porter

Jurriaan M. Peters

Rajsekar R. Rajaraman

Darcy A. Krueger

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