Structural brain abnormalities in patients with psychogenic nonepileptic seizures

From Software to Hardware: A Case Series of Functional Neurological Symptoms and Cerebrovascular Disease

OBJECTIVE

Neuroimaging studies have identified alterations in both brain structure and functional connectivity in patients with functional neurological disorder (FND). For many patients, FND emerges from physical precipitating events. Nevertheless, there are a limited number of case series in the literature that describe the clinical presentation and neuroimaging correlates of FND following cerebrovascular disease.

METHODS

The authors collected data from two clinics in the United Kingdom on 14 cases of acute, improving, or delayed functional neurological symptoms following cerebrovascular events.

RESULTS

Most patients had functional neurological symptoms that were localized to cerebrovascular lesions, and the lesions mapped onto regions known to be part of functional networks disrupted in FND, including the thalamus, anterior cingulate gyrus, insula, and temporoparietal junction.

CONCLUSIONS

The findings demonstrate that structural lesions can lead to FND symptoms, possibly explained through changes in relevant mechanistic functional networks.

Are brain MRI abnormalities associated with the semiology of functional seizures?

PURPOSE

To investigate whether radiologically apparent brain magnetic resonance imaging (MRI) abnormalities are associated with the functional seizure (FS) semiology.

METHODS

All patients with a diagnosis of FS at the epilepsy centers at Shiraz University of Medical Sciences, Iran; Aichi Medical University Hospital, Japan; University of Michigan, USA; University of California, Los Angeles, USA; Emory University School of Medicine, USA; and Hospital el Cruce, Argentina, were studied.

RESULTS

One hundred patients were included; 77 (77%) had motor functional seizures. Lobar location of brain abnormality did not have an association with the semiology (p = .83). There was no significant difference between ictal behaviors in patients with frontal or parietal lesions compared to those with temporal or occipital lesions.

CONCLUSION

There were no associations between functional seizure ictal behaviors and locations of the radiologically apparent brain MRI abnormalities. Further studies are needed to evaluate the underpinnings of varying behaviors in FS.

Clinical MRI morphological analysis of functional seizures compared to seizure-naïve and psychiatric controls

PURPOSE

Functional seizures (FS), also known as psychogenic nonepileptic seizures (PNES), are physical manifestations of acute or chronic psychological distress. Functional and structural neuroimaging have identified objective signs of this disorder. We evaluated whether magnetic resonance imaging (MRI) morphometry differed between patients with FS and clinically relevant comparison populations.

METHODS

Quality-screened clinical-grade MRIs were acquired from 666 patients from 2006 to 2020. Morphometric features were quantified with FreeSurfer v6. Mixed-effects linear regression compared the volume, thickness, and surface area within 201 regions-of-interest for 90 patients with FS, compared to seizure-naïve patients with depression (n = 243), anxiety (n = 68), and obsessive-compulsive disorder (OCD, n = 41), respectively, and to other seizure-naïve controls with similar quality MRIs, accounting for the influence of multiple confounds including depression and anxiety based on chart review. These comparison populations were obtained through review of clinical records plus research studies obtained on similar scanners.

RESULTS

After Bonferroni-Holm correction, patients with FS compared with seizure-naïve controls exhibited thinner bilateral superior temporal cortex (left 0.053 mm, p = 0.014; right 0.071 mm, p = 0.00006), thicker left lateral occipital cortex (0.052 mm, p = 0.0035), and greater left cerebellar white-matter volume (1085 mm³, p = 0.0065). These findings were not accounted for by lower MRI quality in patients with FS.

CONCLUSIONS

These results reinforce prior indications of structural neuroimaging correlates of FS and, in particular, distinguish brain morphology in FS from that in depression, anxiety, and OCD. Future work may entail comparisons with other psychiatric disorders including bipolar and schizophrenia, as well as exploration of brain structural heterogeneity within FS.

Factors associated with comorbid epilepsy in patients with psychogenic nonepileptic seizures: A large cohort study

OBJECTIVE

Comorbid epilepsy and psychogenic nonepileptic seizures (PNES) occur in 12-22% of cases and the diagnosis of both simultaneous disorders is challenging. We aimed to identify baseline characteristics that may help distinguish patients with PNES-only from those with comorbid epilepsy.

METHODS

We performed a longitudinal cohort study on those patients diagnosed with PNES in our epilepsy monitoring unit (EMU) between May 2001 and February 2011, prospectively followed up until September 2016. Patients were classified into PNES-only, PNES + possible or probable epilepsy, and PNES + definite epilepsy based on the clinical, vEEG, and neuroimaging data. Demographic and basal clinical data were obtained from chart review. Multiple regression models were performed to identify significant predictors of PNES + definite epilepsy, excluding patients with only possible or probable epilepsy for this specific analysis.

RESULTS

One-hundred and ninety four patients with PNES-only, 30 with PNES + possible or probable epilepsy and 47 with PNES + definite epilepsy were included. 73.8% were female and the mean age at EMU admission was 37.4 ± standard deviation 13.5 years. Patients with PNES + definite epilepsy most likely had never worked, had history of febrile seizures, structural brain lesions, developmental disabilities, and maximum reported seizure duration between 0.5 and 2 min. Patients with PNES-only were on fewer anti-seizure medications (ASM), reported more frequently an initial minor head trauma, seizures longer than 10 min, and a higher number of neurological and medical illnesses - being migraine (18.1%), other types of headaches (18.5%), and asthma (15.5%) the most prevalent ones. All p < 0.05. On the hierarchical regression analysis, history of febrile seizures, developmental disabilities, brain lesions, longest reported seizure duration between 0.5 and 2 min, and lack of neurological comorbidity, remained as significant predictors of PNES + epilepsy. The model's performance of a 5-fold cross-validation analysis showed an overall accuracy of 84.7% to classify patients correctly.

CONCLUSIONS

Some demographic and clinical characteristics may support the presence of comorbid epilepsy in patients with PNES, being unemployment, the presence of brain lesions, developmental disabilities, history of febrile seizures, seizure duration and lack of comorbid headaches the most relevant ones.

Quality of Life in Psychogenic Nonepileptic Seizures: An Evolutionary Concept Analysis

Psychogenic nonepileptic seizures (PNES) pose a serious threat to quality of life (QOL) in patients who battle the disorder. As psychological treatment options have progressed, improvement in QOL has become a more common desired outcome. Despite its relevance in PNES research and treatment, QOL has not been defined in the PNES population. Rodgers' Evolutionary Method of concept analysis was used to analyze 47 articles and clarify the concept of QOL in PNES. QOL in PNES is subjective, multidimensional, associated with symptoms, and dynamic in nature. This conceptualization of QOL in PNES may be useful in future PNES research and treatment.

A minority of patients with functional seizures have abnormalities on neuroimaging

OBJECTIVE

Functional seizures often are managed incorrectly as a diagnosis of exclusion. However, a significant minority of patients with functional seizures may have abnormalities on neuroimaging that typically are associated with epilepsy, leading to diagnostic confusion. We evaluated the rate of epilepsy-associated findings on MRI, FDG-PET, and CT in patients with functional seizures.

METHODS

We studied radiologists' reports from neuroimages at our comprehensive epilepsy center from a consecutive series of patients diagnosed with functional seizures without comorbid epilepsy from 2006 to 2019. We summarized the MRI, FDG-PET, and CT results as follows: within normal limits, incidental findings, unrelated findings, non-specific abnormalities, post-operative study, epilepsy risk factors (ERF), borderline epilepsy-associated findings (EAF), and definitive EAF.

RESULTS

Of the 256 MRIs, 23% demonstrated ERF (5%), borderline EAF (8%), or definitive EAF (10%). The most common EAF was hippocampal sclerosis, with the majority of borderline EAF comprising hippocampal atrophy without T2 hyperintensity or vice versa. Of the 87 FDG-PETs, 26% demonstrated borderline EAF (17%) or definitive EAF (8%). Epilepsy-associated findings primarily included focal hypometabolism, especially of the temporal lobes, with borderline findings including subtle or questionable hypometabolism. Of the 51 CTs, only 2% had definitive EAF.

SIGNIFICANCE

This large case series provides further evidence that, while uncommon, EAF are seen in patients with functional seizures. A significant portion of these abnormal findings are borderline. The moderately high rate of these abnormalities may represent framing bias from the indication of the study being "seizures," the relative subtlety of EAF, or effects of antiseizure medications.

DDESVSFS: A simple, rapid and comprehensive screening tool for the Differential Diagnosis of Epileptic Seizures VS Functional Seizures

OBJECTIVE

Functional seizures (FS) are often misclassified as epileptic seizures (ES). This study aimed to create an easy to use but comprehensive screening tool to guide further evaluation of patients presenting with this diagnostic dilemma.

MATERIALS AND METHODS

Demographic, clinical and diagnostic data were collected on patients admitted for video-EEG monitoring for clarification of their diagnosis. Upon discharge, patients were classified as having ES vs FS. Using the collected characteristics and video-EEG diagnosis, we created a multivariable logistic regression model to identify predictors of ES. Then, we trained an integer-coefficient model with the most frequently selected predictors, creating a pointing system coined DDESVSFS, with scores ranging from -17 to +8 points.

RESULTS

43 patients with FS and 165 patients with ES were recruited. In the final integer-coefficient model, 8 predictors were identified as significant in differentiating ES from FS: normal electroencephalogram (-3 points), predisposing factors for FS (-3 points), increased number of comorbidities (-3 points), semiology suggestive of FS (-4 points), increased seizure frequency (-4 points), longer disease duration (+3 points), antiepileptic polypharmacy (+2 points) and compliance with antiepileptic drugs (+3 points). Cumulative scores of ≤ -9 points carried <5% predictive value for ES, while cumulative scores of ≥ -1 points carried >95% predictive value. The model performed well (AUC: 0.923, sensitivity: 0.945, specificity: 0.698).

CONCLUSIONS

We propose DDESVSFS as a simple, rapid and comprehensive prediction score for the Differential Diagnosis of Epileptic Seizures VS Functional Seizures. Large prospective studies are needed to evaluate its utility in clinical practice.

Unexpected brain imaging findings in patients with seizures

New imaging technologies have advanced our ability to localize the epileptogenic zone in patients with epilepsy. As a result of the constant improvement of the image quality, magnetic resonance imaging (MRI) has become the most important ancillary tool in the management of patients with epilepsy. Magnetic resonance imaging for the evaluation of patients with epilepsy should be done using a special temporal lobe protocol and read by physicians experienced with the findings in patients with epilepsy. On the other hand, in the healthy populations, incidental structural brain abnormalities have been reported in 18% of people. Incidental, subtle, or unexpected structural brain abnormalities have also been reported in many patients who were investigated because of having seizures. In the current narrative review, we will discuss some of these instances, where structural brain abnormalities are discovered unexpectedly, are subtle (but important) and/or may be considered as incidental.

Stigma in psychogenic nonepileptic seizures

OBJECTIVE

There is scarce literature on stigma in families living with psychogenic nonepileptic seizures (PNES). Using a cohort of patients with epileptic seizures (ES) and their caregivers as controls, we aimed to quantify the level of patient and caregiver stigma in PNES and identify associations of patient and caregiver characteristics with it.

METHODS

Patients with PNES and ES and their caregivers completed surveys about demographic, clinical, and psychosocial characteristics. Multivariate regression analysis was used to identify correlates of patient and caregiver stigma.

RESULTS

Forty-three patients with PNES and 165 patients with ES were recruited. Compared with patients with ES, patients with PNES had shorter disease duration, higher seizure frequency, normal diagnostic data, poorer psychosocial health, and fewer antiseizure medications (ASMs). A total of 76.5% of patients with PNES and 59.5% of patients with ES felt stigmatized. Patient stigma level was higher in patients with PNES compared with those with ES, and it was negatively associated with patient quality of life (QOL). Additionally, 28 caregivers of patients with PNES and 99 caregivers of patients with ES were recruited. There were no significant demographic, caregiving, or psychosocial differences between the two caregiver cohorts. Seventy-two percent of caregivers of patients with PNES and 47% of caregivers of patients with ES felt stigmatized. Caregiver stigma level was also higher in caregivers of patients with PNES compared with caregivers of patients with ES, and it was negatively associated with patient QOL and positively associated with patient and caregiver anxiety.

CONCLUSION

Compared with those with ES, patients and caregivers living with PNES experience stigma more frequently and to a higher extent. Patient QOL emerges as a consistent correlate of that stigma.