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Available online at www.sciencedirect.com
www.elsevier.com/locate/brainres
Research Report
White matter diffusion abnormalities in patients with psychogenic non-epileptic seizures Seongtaek Leea, Jane B. Allendorferb, Tyler E. Gastonb, Joseph C. Griffisc, Kathleen A. Hernandod, Robert C. Knowltone, Jerzy P. Szaflarskib, Lawrence W. Ver Hoefa,b,f,n a
Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL 35294, USA Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35294, USA c Department of Psychology, University of Alabama at Birmingham, Birmingham, AL 35294, USA d School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA e Department of Neurology, University of California, San Francisco, San Francisco, CA 94143, USA f Neurology service, Birmingham VA Medical Center, Birmingham, AL 35294, USA b
art i cle i nfo
ab st rac t
Article history:
The purpose of this study was to conduct a preliminary investigation of the white matter
Accepted 26 April 2015
characteristics in patients with psychogenic non-epileptic seizures (PNES). Diffusion Tensor Imaging (DTI) data were collected at 3 T in 16 patients with PNES and 16 age-
Keywords:
and sex-matched healthy controls (HC). All patients with PNES had their diagnosis
Psychogenic non-epileptic seizures
confirmed via video/EEG monitoring; HCs had no comorbid neurological or psychiatric
(PNES)
conditions. DTI indices including fractional anisotropy (FA), and mean diffusivity (MD)
Diffusion tensor imaging (DTI)
were calculated and compared between patients with PNES and HCs using Tract-Based
Tract-based spatial statistics (TBSS)
Spatial Statistics (TBSS). Significantly higher FA values were observed in patients with
Uncinate fasciculus (UF)
PNES in the left corona radiata, left internal and external capsules, left superior temporal
Superior temporal gyrus (STG)
gyrus, as well as left uncinate fasciculus (UF) (Po0.05; corrected for multiple comparisons). There was no significant change in other indices between patients with PNES and HCs. These findings suggest that patients with PNES have significantly altered white matter structural connectivity when compared to age- and sex-matched HCs. These abnormalities are present in left hemispheric regions associated with emotion regulation and motor pathways. While the relationship between the pathophysiology of PNES and these abnormalities is not entirely clear, this work provides an initial basis to guide future prospective studies. & 2015 Published by Elsevier B.V.
n Corresponding author at: Department of Biomedical Engineering, University of Alabama at Birmingham, Suite 312, 1719 6th Ave South, Birmingham, AL 35294, USA. Fax: þ1 205 996 4802. E-mail address: [email protected] (L.W. Ver Hoef).
http://dx.doi.org/10.1016/j.brainres.2015.04.050 0006-8993/& 2015 Published by Elsevier B.V.
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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1.
Introduction
Psychogenic non-epileptic seizures (PNES) have been described as paroxysmal behaviors that clinically resemble epileptic seizures but show no epileptiform brain activity on EEG (Devinsky et al., 2011). Due to the clinical similarities between PNES and epileptic seizures, patients with PNES are often misdiagnosed with epilepsy and frequently receive inappropriate treatments including antiepileptic drugs (AEDs). The costs of these unnecessary interventions are staggering with one study estimating the expenses for AEDs, laboratory testing, diagnostic evaluations including EEGs and MRIs, and emergency room visits at $900 million per year in the US alone (Martin et al., 1998). Therefore, it is imperative for neurologists, psychiatrists, and neuropsychologists to better understand the pathophysiology of PNES in order to develop better and more effective treatments and to avoid the unnecessary economic burden related to PNES. Recently, efforts to understand the nature and pathogenesis of PNES have intensified, but much remains unknown. The majority of research has revolved around video/EEG monitoring, which is considered the gold standard for the diagnosis of PNES. Such investigations have revealed not only various clinical characteristics of PNES but also associations between various types of events and specific neuropsychological profiles (Griffith et al., 2008; Selwa et al., 2000). Further, an electrophysiologic study in patients with PNES revealed decreased prefrontal and parietal EEG synchronization possibly explaining the dysfunction in the fronto-parietal networks observed in these patients (Knyazeva et al., 2011). Studies have also found a relationship between PNES and structural MRI findings. Structural abnormalities are more commonly detected in patients with PNES compared to the general population (Reuber et al., 2002), and may be seen in up to 65% of PNES patients (Devinsky et al., 2001). Another study based on voxel based morphometry and cortical thickness analysis suggested that motor and premotor areas in the right hemisphere and the bilateral cerebellum are involved in the pathogenesis of PNES (Labate et al., 2012). Conventional MRI, however, is limited by the fact that structural information alone does not provide insight into the brain networks that can underlie the pathophysiology of PNES and that can be examined in depth with e.g., fMRI and connectivity analyses (Allendorfer and Szaflarski, 2014). One study already found abnormally strong functional connectivity between regions involved in movement (precentral sulcus), executive control (inferior frontal gyrus) and emotion (insula) suggesting that abnormal emotion processing can affect executive control and can be linked to abnormal expression of motor function such as seizure-like episodes (van der Kruijs et al., 2012). These authors also reported abnormalities in resting-state networks that provide neural correlates for an underlying process of dissociation (van der Kruijs et al., 2014). DTI is a technique that allows for noninvasive probing of cerebral white matter micro-structure in vivo. Diffusion of water molecules is often described using a tensor model from which numerous diffusion-based metrics such as fractional anisotropy (FA) and mean diffusivity (MD) can be derived (Hagmann et al., 2006). FA is one of the most widely used of
these indices and reflects the degree of uniformity of the underlying fiber structure while MD represents the averaged magnitude of the displacement of water molecules (Basser and Pierpaoli, 1996). To our knowledge, only two previous studies have analyzed diffusion tensor imaging (DTI) data in patients with PNES. In the study by Ding et al. (2013), analysis of resting state fMRI and DTI data using a graph theory approach demonstrated differences in the topological organization of the brain between patients with PNES and healthy controls indicating the possibility that abnormal structural connectivity may underlie PNES (Ding et al., 2013). A recent study by Hernando et al. (2015) used diffusion tensor tractography to examine connectivity of the uncinate fasciculus (UF), a white matter tract connecting the limbic regions of the amygdala and hippocampus with the prefrontal cortex, and found that increasing age of PNES onset was associated with more leftward asymmetry of FA for the UF. In this preliminary study, we compare diffusion indices along white matter tracts in patients with PNES to healthy controls (HCs) using tract-based spatial statistics (TBSS) to determine whether structural abnormalities, reflected in abnormalities of FA and MD, are associated with PNES. Unlike Hernando et al. (2015) which focused on one specific white matter tract, we utilized a whole-brain approach to examine differences in overall white matter integrity between patients with PNES and HCs. Our approach also differs from the study by Ding et al. (2013), which used structural and functional connectivity methods; instead, we use direct measurements of tract integrity that require less assumptions to characterize white matter abnormalities. We hypothesized that abnormalities in the structures supporting emotional processing, e.g., the UF may be observed in PNES (Hernando et al., 2015).
2.
Results
Compared to healthy controls, patients with PNES showed regions of significantly increased FA values (Po0.05; corrected) in the left hemisphere including the internal and external capsules, corona radiata, UF, and superior temporal gyrus (Table 3; Fig. 1). Of note, the FA skeleton cannot reliably differentiate contributions from the external capsule, extreme capsule, or insular juxtacortical white matter due to their close proximity; however, all of the white matter contributions in this area will be collectively referred to as the “external capsule”. Significantly decreased FA values were not observed in patients with PNES relative to HCs. Also, there was no significant difference in MD between patients with PNES and HCs. When the cutoff value for significance was raised to Po0.1 corrected, the right corona radiata and internal capsule also showed increased FA values; the general regions of increased FA values seen using Po0.05 showed more extensive involvement at Po0.1, but no other new areas showed significant differences. To determine whether the observed differences were related to true differences between subjects and not an artifact caused by use of different scanners or slight differences in sequences, we performed F-tests for inter-group differences across scanners. These secondary analyses did not reveal any significant differences in FA measurements across scanners at Po0.05 corrected, suggesting that variability in FA measurements among subjects
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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Fig. 1 – Overview of differences in fractional anisotropy (FA) between patients with PNES patients and age- and gendermatched controls. TBSS results showing representative slices of increased FA values (in red) of the left corona radiata (A), the left internal and external capsule (B), left STG (C), and left UF (D) in axial view (Po0.05, FWE-corrected). The mean FA skeleton image (green) is overlaid on the MNI 152 brain. The images are displayed in radiological convention.
was not due to differences in the scanner used to collect the data. We further analyzed the effects of event frequency and duration of illness on the average FA value in the regions of increased FA, which showed that neither one was significantly correlated (R¼ 0.17, P¼ 0.54 and R¼ 0.16, P¼ 0.56, respectively) with the FA values in the areas of interest.
3.
Discussion
In this study, we examined whether there are differences in whole brain white matter integrity between patients with PNES and HCs using DTI and TBSS. As hypothesized, we found significant differences between patients with PNES and HCs in regional FA values. Overall, we found increased FA values in several left hemispheric regions and no areas of decreased FA. The finding of increased structural connectivity in PNES is in contrast with studies examining many other pathologic processes that are typically associated with decreased rather than increased structural connectivity (Riley et al., 2010). The areas of increased connectivity identified in our study are discussed below.
3.1.
Increased FA in uncinate fasciculus (UF)
The UF is a major white matter tract that connects the anterior temporal lobe to the inferior frontal lobe (orbitofrontal area) (Von Der Heide et al., 2013). It is has been proposed that UF is involved in emotion processing and memory
(Gaffan and Wilson, 2008; Ross, 2008), and it is thought to play a major role in emotion regulation (Yasmin et al., 2008). Since abnormal processing and regulation of emotional responses is believed to play a role in the pathology of PNES (Urbanek et al., 2014), it is not surprising to find differences between healthy controls and patients with PNES in the integrity of the UF (Fig. 1D). In one study, increased values of FA in the left UF correlated with the degree to which healthy women employed an emotional regulation mechanism known as “reappraisal” in which negative emotions or experiences are coped with by reframing the experience in a more positive light, as compared to those who typically cope with negative emotions by suppressing them (Zuurbier et al., 2013). However, in men such an effect was not seen. Since all but one of the PNES patients in our study were women, which is typical of the PNES population (Szaflarski et al., 2000), our finding of increased FA in the left UF may reflect increased use of – and thus reinforcement of – networks associated with reappraisal to cope with the greater degree of stressful or traumatic experiences common in the lives of patients with PNES (Bodde et al., 2009). Interestingly, a small study of 8 patients with PNES found that increased leftward asymmetry of FA in the UF was associated with increased age of illness onset, and that 6 of the 8 patients with age of PNES onset greater than 30 years old exhibited leftward asymmetric FA (Hernando et al., 2015). Although we found no significant associations between average FA and clinical measures, given that age of PNES onset for the majority of our patients (11/16) was greater than 30 years old, this factor may be contributing
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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to the increased average FA observed in the left UF of PNES patients compared to HCs. Another study reported that decreased FA in the left UF correlated with poor performance on negative emotional recognition and episodic memory tasks in patients with amnestic mild cognitive impairment (Fujie et al., 2008). In contrast to these results, PNES patients showed increased FA in the left UF, which may reflect heightened sensitivity of PNES patients to recognize negative emotions due to reinforcement of this white matter pathway (Hixson et al., 2006; Testa et al., 2012).
3.2.
Increased FA in corona radiata and internal capsule
The corticospinal tracts, which pass through the corona radiata and the posterior internal capsule, mediate control of motor functions. We have found increased FA values in the posterior limb of the left internal capsule (Fig. 1B) and corona radiata (Fig. 1A) in patients with PNES when compared to healthy controls. We also found higher FA values in the anterior limb of the left internal capsule (Fig. 1B), which connects the striatum to the motor cortex. This may reflect involvement of the motor system in producing coordinated major motor activity seen in 11 of our 16 patients. While using a significance cutoff of P ¼0.05, only areas associated with the left hemispheric motor system were significantly different in patients with PNES compared to healthy controls. The right coronal radiata and internal capsule also showed significantly increased FA in patients with PNES when the cutoff P-value was changed to 0.1; this was the only additional brain region to show significance with this change. While the reasons for this asymmetry are not clear, we assume they are related to hemispheric dominance and the typically increased expression of structural connectivity in the dominant hemisphere.
3.3.
Increased FA in external capsule
Interpreting the finding of increased FA in the area of the external capsule is complicated by the fact that the external capsule, extreme capsule, and insular juxtacortical fibers are closely apposed in this area and are not clearly distinguished with TBSS. One study reported increased FA values of the right external capsule, as well as in the anterior and posterior limbs of the internal capsule and corona radiata in patients with functional dyspepsia (Zhou et al., 2013) which, like PNES, falls under the broad category of somatoform disorders. These findings, to a large degree, mirror in the right hemisphere our findings in the left hemisphere (Fig. 1B), raising the possibility that somatoform disorders associated with depression and/or anxiety may involve homologous structures on either side of the brain. While the reasons for the differences in laterality between the studies are not clear, they may be related to the clinical presentation of the conversion disorder or other factors that remain to be explored in the future.
3.4.
Increased FA in superior temporal gyrus (STG)
The superior temporal gyrus is well known to be involved in receptive language processing in the dominant hemisphere and primary auditory processing bilaterally (Kim et al., 2011).
There is a growing body of evidence that the STG is also involved in perception of emotions (de Greck et al., 2012; Husain et al., 2014; Pehrs et al., 2013; Robins et al., 2009). In one fMRI study increased activation in the bilateral STG was observed in response to pleasant or unpleasant sounds when compared to neutral sounds (Husain et al., 2014); HCs showed increased activation in the left STG specifically while listening to pleasant or unpleasant sounds, compared to neutral sounds. These findings suggest that STG, especially on the left, is involved not just in language and primary auditory processing but also in affective/emotional processing. While not tested in the current study, we speculate that increased FA values in the left STG of patients with PNES may be related to abnormal affective perception or emotional regulation of auditory stimuli. Similarly, one study investigated patterns of fMRI activation to dynamic audiovisual emotional stimuli while watching a short movie (Robins et al., 2009). These authors compared an average response to multiple types of emotional stimuli (angry, fearful, and happy) to neutral stimuli and found greater activation to emotional stimuli in the bilateral anterior STG. These and other studies (de Greck et al., 2012; Pehrs et al., 2013) suggest that STG responds differently to auditory, audiovisual, and visual-only stimuli based on the emotional content of the stimulus. Finally, our results are in agreement with the study by Ding et al. (2013), who observed decreased regional structural nodal connectivity strength in STG bilaterally along with several other brain regions as well as globally decreased structural connectivity strength in PNES patients compared to controls. While each of these studies cannot be directly compared to ours due to differences in imaging method (fMRI vs. DTI) or analysis approach, our finding of increased FA in the STG suggests that patients with PNES have particularly robust white matter pathways in this area commonly involved in mediating cortical responses to emotional stimuli. Future studies combining structural DTI connections of limbic brain regions and fMRI of emotional processing would help to clarify these structure– function relationships in patients with PNES. Other imaging modalities that are commonly used to evaluate epilepsy patients have also been applied to study PNES in a limited number of reports. A number of studies have described cases in which ictal/interictal-SPECT was performed on patients with PNES. In the majority of cases SPECT results were negative, and in some cases a positive result was found, though the locations were not consistent across studies (Biraben et al., 1999; Ettinger et al., 1998; Neiman et al., 2009; Spanaki et al., 1999; Varma et al., 1996). Another study reported that group analysis of patients with PNES revealed significant PET hypometabolism within the right inferior parietal and central area, and within the bilateral anterior cingulate cortex (Arthuis et al., 2014). While making a direct correlation between these findings and the results of the present study is challenging, these reports are nonetheless supportive of the notion that differences between patients with PNES and HCs exist and may be observable with imaging. The pathological mechanisms underlying the higher FA in PNES patients remain unknown due to the difficulty in designing and conducting a study that could definitely answer this question. Arguing from basic principles, the plausible explanations for increased FA include increased fiber number density, reflecting a greater number of axonal
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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connections between brain regions, or reduced fiber branching or crossing fibers (Beaulieu, 2002; Hoeft et al., 2007). However, the contributions of these and other factors that increase anisotropy need further investigation. To our knowledge, reports on pathological findings associated with increased FA are still scarce, and the pathophysiology of PNES is still not clear. This study is intended to be exploratory and is limited in several ways. First, our subjects displayed a variety of comorbid psychiatric conditions including depression, anxiety, bipolar disorder, and obsessive-compulsive disorder. Due to the retrospective nature of this work, a thorough characterization of the presence and severity of these conditions was not possible, and therefore, the relative contribution of each to the observed changes in FA cannot be established. Nonetheless, these conditions are quite common in patients with PNES, therefore the study sample is felt by us to be representative of the PNES population. Much larger prospective studies will be needed to have sufficient power to tease out the relative contribution of each of these variables. Second, in the discussion above we describe possible rationales as to how the observed findings may reflect our conceptual understanding of PNES, particularly regarding affective perception and emotional regulation, but it should be noted that none of these putative psychodynamics were tested directly and further work is needed to confirm or deny these postulates. The small sample size of the study and retrospective nature of its design preclude an in-depth evaluation of the correlation between DTI changes and a variety of psychometric measures, psychiatric diagnoses, specific features of semiology, or response to treatment. All of these are worthy of future exploration under prospective examination.
5
5.
Experimental procedures
identified through databases containing demographic and clinical information from all patients admitted for video/ EEG evaluation to the Epilepsy Monitoring Unit (EMU) at the University of Alabama at Birmingham (UAB). Diagnosis of PNES was made based on inpatient video-EEG monitoring by attending epileptologists in the EMU during admission in accord with published guidelines for “Documented PNES” (LaFrance et al., 2013). Patients were excluded from analyses if they had definite or suspected comorbid epilepsy, inconclusive video-EEG evaluation (no events captured), abnormal EEG with epileptiform discharges, or recording of only some but not all types of a patient’s habitual events. Based on a previously published classification, the included PNES patients were categorized as having major motor (n¼ 10), minor motor (n¼ 1), waxy flexibility (n¼ 3), or subjective (n¼ 2) events (Griffith et al., 2007). Patients with significant neurological comorbidity (e.g., traumatic brain injury, brain tumors or mental retardation) were excluded. One patient had a non-specific area of white matter hyperintensity on T2 FLAIR images high in the dorsal convexity of the right frontal lobe above the major hemispheric white matter tracts, but the scans of the remaining patients were all normal in appearance. The aforementioned hyperintensity did not overlap any of the areas found to be different between groups at either Po0.05 or Po0.10, therefore the patient was retained in the analysis to maximize the statistical power in light of the limited sample size of this study. Of note, the presence of this lesion is consistent with the findings of Devinsky et al. (2001) who found that structural imaging abnormalities in patients with PNES were more commonly seen in the right hemisphere than the left. Among the 16 patients in this study, seven patients reported a history of depression, one of whom also reported a history of obsessive-compulsive disorder; five patients reported a history of anxiety, three of whom also reported a history of depression; and the one patient who reported both history of depression and anxiety also reported a history of bipolar disorder. These classifications are based on selfreported conditions in their medical history at admission to the EMU. Upon diagnosis of PNES, all patients were referred to community-based psychologists, hence thorough psychiatric assessment was not available to us on these patients. Healthy controls had no known history of neurologic disorders. The retrospective study of patients with PNES was approved by the Institutional Review Board (IRB) at UAB with consent waived (n¼ 9; DTI data collected for clinical purposes); subjects who were enrolled in a prospective research study signed an IRB-approved consent form. Healthy controls were identified from a large database of normative data collected via NIH R01 HD068488; all participants signed an IRB-approved informed consent form. The details of the demographic and clinical characteristics of PNES patients are presented in Table 1.
5.1.
Participants
5.2.
4.
Conclusion
This study investigated white matter DTI characteristics in patients with PNES. Compared to healthy controls, patients with PNES showed significantly increased FA values in left hemispheric areas involved in the regulation and perception of emotions (UF and STG) and motor system control (corona radiata and internal and external capsule). While not specifically tested in this study, we believe that the increased strength in white matter connectivity of these regions is either the result of or contributes to the underlying etiology of PNES. Further studies of changes in structural and functional connectivity in response to treatment (e.g., cognitive behavioral therapy) (LaFrance et al., 2014) are needed in order for us to better understand the neuropathological substrates of this complex and highly prevalent disorder.
Sixteen patients with a definite diagnosis of PNES (15 females, mean age: 39.81714.12 years) and 16 age- and gendermatched healthy controls (HCs; 15 females, mean age: 40.44713.83) were enrolled. The PNES patients were
Image acquisition
All neuroimaging data were collected at 3 T using a 32direction DTI sequence obtained as part of either a routine clinical evaluation (n¼ 9) on Philips Achieva scanner (Philips Medical Systems, Eindhoven, Netherlands) or a research
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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Table 1 – Demographics and clinical characteristics of patients with PNES. Patient ID
Age
Gender
Age of onset
PNES duration (years)
Mean frequency of events (per month)
PNES semiology classification
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 P16
46 33 45 33 43 57 19 56 52 49 21 22 62 51 35 21
F F F F F F F F F F M F F F F F
44 33 32 32 40 57 15 55 41 47 21 13 51 45 33 18
2 0.9 13 1 2.6 0.3 4 1.2 11 2.1 0.2 9 10 6 2 3.8
60 8 0.7 6 2 45 2 255 20 60 16.7 8 60 2.3 0.3 2
Major motor Major motor Major motor Major motor Major motor Waxy flexibility Major motor Minor motor Subjective Subjective Major motor Major motor Major motor Major motor Waxy flexibility Waxy flexibility
Table 2 – DTI scan parameters for each scanner.
Acquired voxel size (mm) Reconstructed voxel size (mm) FOV (mm) TR (ms) TE (ms) Slices b-Value (s/mm2)
UAB Philips Achieva (9 patients)
UC Philips Achieva (9 controls)
UAB Siemens Allegra (7 patients; 7 controls)
2.0 2.0 2.0 1.7 1.7 2.0
2.4 2.4 2.4 1.9 1.9 2.4
2.5 2.5 2.5 2.5 2.5 2.5
244 244 9722 84 70 800
180 180 9403 69 55 800
240 240 9400 89 55 1000
Table 3 – The areas of increased/decreased FA and MD values in PNES. Regions of increased FA in PNES
Left Left Left Left Left
corona radiata uncinate fasciculus internal capsule external capsule superior temporal gyrus
MNI coordinates x
y
z
27 34 24 31 55
3 4 13 8 21
22 11 14 11 2
study (n¼ 7) on a Siemens Allegra scanner (Siemens Medical Solutions, Erlangen, Germany), both at UAB. For control data, nine scans were collected on a Philips Achieva scanner at the University of Cincinnati and seven scans were collected on a Siemens Allegra scanner at UAB. The DTI scan parameters were similar for each scanner and are listed in Table 2.
5.3.
P-value
Preprocessing of neuroimaging data
The neuroimaging data were converted from DICOM (Digital Imaging and Communications in Medicine) format to NIfTI (Neuroimaging Informatics Technology Initiative) format. The AFNI (Analysis of Functional NeuroImages) software package was used (http://afni.nimh.nih.gov/) (Cox, 1996) to
0.0392 0.0456 0.0406 0.0414 0.0478
preprocess the anatomical and DTI scans. The motion and eddy current corrections were performed and skull-stripping was carried out to allow the anatomical data to be subsequently matched to the DTI data. The skull-stripped brain images were resampled to the same matrix size and orientation as the DTI dataset in order to mask out non-brain voxels. Finally, fractional anisotropy (FA) and mean diffusivity (MD) were calculated.
5.4.
TBSS analysis
The voxel-wise analysis of multi-subject diffusion data was carried out in FSL using TBSS (Allendorfer et al., 2012; Smith et al., 2006). Whole-brain white matter was analyzed as
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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follows. First, all FA maps are aligned to a white matter template in standard space using nonlinear registration, and all aligned FA images were averaged to create a group mean FA image. The mean FA image was thresholded at a mean FA value of 0.2 to include the major white matter tracts and to suppress regions of partial grey matter and/or high intersubject variability. Next, the mean FA image was eroded to produce a skeletonized mean FA image, which is thought to reflect the center of fiber bundles in both groups. Nonparametric, unpaired t-tests between PNES and age- and gender-matched HCs were performed for voxel-wise group comparisons using the ‘randomise’ permutation test in FSL (Winkler et al., 2014). The number of permutations was 5000 and the differences between two groups were considered significant at Po0.05 corrected (familywise error rate [FWE]) using threshold-free cluster enhancement (TFCE) (Smith and Nichols, 2009). Additionally, we computed a group-level analysis while controlling for scanner type by including each scanner as a grouping variable in the group-level model. We then evaluated the effect of the scanner on FA values by computing an orthogonal F contrast comparing mean FA measurements among scanners. Results were considered significant for Po0.05, corrected for the voxel-level family-wise error rate. We also tested for correlations for the clinical parameters of duration of illness and for mean frequency of events with averaged FA values from the regions of increased FA. Spearman’s rho was used to estimate the correlation; Spearman’s rho was chosen because of non-normality of the distribution of PNES patients’ clinical parameters.
Disclosure of conflicts of interest None of the authors has any conflict of interest to disclose.
r e f e r e n c e s
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Available online at www.sciencedirect.com
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Research Report
White matter diffusion abnormalities in patients with psychogenic non-epileptic seizures Seongtaek Leea, Jane B. Allendorferb, Tyler E. Gastonb, Joseph C. Griffisc, Kathleen A. Hernandod, Robert C. Knowltone, Jerzy P. Szaflarskib, Lawrence W. Ver Hoefa,b,f,n a
Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL 35294, USA Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35294, USA c Department of Psychology, University of Alabama at Birmingham, Birmingham, AL 35294, USA d School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA e Department of Neurology, University of California, San Francisco, San Francisco, CA 94143, USA f Neurology service, Birmingham VA Medical Center, Birmingham, AL 35294, USA b
art i cle i nfo
ab st rac t
Article history:
The purpose of this study was to conduct a preliminary investigation of the white matter
Accepted 26 April 2015
characteristics in patients with psychogenic non-epileptic seizures (PNES). Diffusion Tensor Imaging (DTI) data were collected at 3 T in 16 patients with PNES and 16 age-
Keywords:
and sex-matched healthy controls (HC). All patients with PNES had their diagnosis
Psychogenic non-epileptic seizures
confirmed via video/EEG monitoring; HCs had no comorbid neurological or psychiatric
(PNES)
conditions. DTI indices including fractional anisotropy (FA), and mean diffusivity (MD)
Diffusion tensor imaging (DTI)
were calculated and compared between patients with PNES and HCs using Tract-Based
Tract-based spatial statistics (TBSS)
Spatial Statistics (TBSS). Significantly higher FA values were observed in patients with
Uncinate fasciculus (UF)
PNES in the left corona radiata, left internal and external capsules, left superior temporal
Superior temporal gyrus (STG)
gyrus, as well as left uncinate fasciculus (UF) (Po0.05; corrected for multiple comparisons). There was no significant change in other indices between patients with PNES and HCs. These findings suggest that patients with PNES have significantly altered white matter structural connectivity when compared to age- and sex-matched HCs. These abnormalities are present in left hemispheric regions associated with emotion regulation and motor pathways. While the relationship between the pathophysiology of PNES and these abnormalities is not entirely clear, this work provides an initial basis to guide future prospective studies. & 2015 Published by Elsevier B.V.
n Corresponding author at: Department of Biomedical Engineering, University of Alabama at Birmingham, Suite 312, 1719 6th Ave South, Birmingham, AL 35294, USA. Fax: þ1 205 996 4802. E-mail address: [email protected] (L.W. Ver Hoef).
http://dx.doi.org/10.1016/j.brainres.2015.04.050 0006-8993/& 2015 Published by Elsevier B.V.
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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1.
Introduction
Psychogenic non-epileptic seizures (PNES) have been described as paroxysmal behaviors that clinically resemble epileptic seizures but show no epileptiform brain activity on EEG (Devinsky et al., 2011). Due to the clinical similarities between PNES and epileptic seizures, patients with PNES are often misdiagnosed with epilepsy and frequently receive inappropriate treatments including antiepileptic drugs (AEDs). The costs of these unnecessary interventions are staggering with one study estimating the expenses for AEDs, laboratory testing, diagnostic evaluations including EEGs and MRIs, and emergency room visits at $900 million per year in the US alone (Martin et al., 1998). Therefore, it is imperative for neurologists, psychiatrists, and neuropsychologists to better understand the pathophysiology of PNES in order to develop better and more effective treatments and to avoid the unnecessary economic burden related to PNES. Recently, efforts to understand the nature and pathogenesis of PNES have intensified, but much remains unknown. The majority of research has revolved around video/EEG monitoring, which is considered the gold standard for the diagnosis of PNES. Such investigations have revealed not only various clinical characteristics of PNES but also associations between various types of events and specific neuropsychological profiles (Griffith et al., 2008; Selwa et al., 2000). Further, an electrophysiologic study in patients with PNES revealed decreased prefrontal and parietal EEG synchronization possibly explaining the dysfunction in the fronto-parietal networks observed in these patients (Knyazeva et al., 2011). Studies have also found a relationship between PNES and structural MRI findings. Structural abnormalities are more commonly detected in patients with PNES compared to the general population (Reuber et al., 2002), and may be seen in up to 65% of PNES patients (Devinsky et al., 2001). Another study based on voxel based morphometry and cortical thickness analysis suggested that motor and premotor areas in the right hemisphere and the bilateral cerebellum are involved in the pathogenesis of PNES (Labate et al., 2012). Conventional MRI, however, is limited by the fact that structural information alone does not provide insight into the brain networks that can underlie the pathophysiology of PNES and that can be examined in depth with e.g., fMRI and connectivity analyses (Allendorfer and Szaflarski, 2014). One study already found abnormally strong functional connectivity between regions involved in movement (precentral sulcus), executive control (inferior frontal gyrus) and emotion (insula) suggesting that abnormal emotion processing can affect executive control and can be linked to abnormal expression of motor function such as seizure-like episodes (van der Kruijs et al., 2012). These authors also reported abnormalities in resting-state networks that provide neural correlates for an underlying process of dissociation (van der Kruijs et al., 2014). DTI is a technique that allows for noninvasive probing of cerebral white matter micro-structure in vivo. Diffusion of water molecules is often described using a tensor model from which numerous diffusion-based metrics such as fractional anisotropy (FA) and mean diffusivity (MD) can be derived (Hagmann et al., 2006). FA is one of the most widely used of
these indices and reflects the degree of uniformity of the underlying fiber structure while MD represents the averaged magnitude of the displacement of water molecules (Basser and Pierpaoli, 1996). To our knowledge, only two previous studies have analyzed diffusion tensor imaging (DTI) data in patients with PNES. In the study by Ding et al. (2013), analysis of resting state fMRI and DTI data using a graph theory approach demonstrated differences in the topological organization of the brain between patients with PNES and healthy controls indicating the possibility that abnormal structural connectivity may underlie PNES (Ding et al., 2013). A recent study by Hernando et al. (2015) used diffusion tensor tractography to examine connectivity of the uncinate fasciculus (UF), a white matter tract connecting the limbic regions of the amygdala and hippocampus with the prefrontal cortex, and found that increasing age of PNES onset was associated with more leftward asymmetry of FA for the UF. In this preliminary study, we compare diffusion indices along white matter tracts in patients with PNES to healthy controls (HCs) using tract-based spatial statistics (TBSS) to determine whether structural abnormalities, reflected in abnormalities of FA and MD, are associated with PNES. Unlike Hernando et al. (2015) which focused on one specific white matter tract, we utilized a whole-brain approach to examine differences in overall white matter integrity between patients with PNES and HCs. Our approach also differs from the study by Ding et al. (2013), which used structural and functional connectivity methods; instead, we use direct measurements of tract integrity that require less assumptions to characterize white matter abnormalities. We hypothesized that abnormalities in the structures supporting emotional processing, e.g., the UF may be observed in PNES (Hernando et al., 2015).
2.
Results
Compared to healthy controls, patients with PNES showed regions of significantly increased FA values (Po0.05; corrected) in the left hemisphere including the internal and external capsules, corona radiata, UF, and superior temporal gyrus (Table 3; Fig. 1). Of note, the FA skeleton cannot reliably differentiate contributions from the external capsule, extreme capsule, or insular juxtacortical white matter due to their close proximity; however, all of the white matter contributions in this area will be collectively referred to as the “external capsule”. Significantly decreased FA values were not observed in patients with PNES relative to HCs. Also, there was no significant difference in MD between patients with PNES and HCs. When the cutoff value for significance was raised to Po0.1 corrected, the right corona radiata and internal capsule also showed increased FA values; the general regions of increased FA values seen using Po0.05 showed more extensive involvement at Po0.1, but no other new areas showed significant differences. To determine whether the observed differences were related to true differences between subjects and not an artifact caused by use of different scanners or slight differences in sequences, we performed F-tests for inter-group differences across scanners. These secondary analyses did not reveal any significant differences in FA measurements across scanners at Po0.05 corrected, suggesting that variability in FA measurements among subjects
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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Fig. 1 – Overview of differences in fractional anisotropy (FA) between patients with PNES patients and age- and gendermatched controls. TBSS results showing representative slices of increased FA values (in red) of the left corona radiata (A), the left internal and external capsule (B), left STG (C), and left UF (D) in axial view (Po0.05, FWE-corrected). The mean FA skeleton image (green) is overlaid on the MNI 152 brain. The images are displayed in radiological convention.
was not due to differences in the scanner used to collect the data. We further analyzed the effects of event frequency and duration of illness on the average FA value in the regions of increased FA, which showed that neither one was significantly correlated (R¼ 0.17, P¼ 0.54 and R¼ 0.16, P¼ 0.56, respectively) with the FA values in the areas of interest.
3.
Discussion
In this study, we examined whether there are differences in whole brain white matter integrity between patients with PNES and HCs using DTI and TBSS. As hypothesized, we found significant differences between patients with PNES and HCs in regional FA values. Overall, we found increased FA values in several left hemispheric regions and no areas of decreased FA. The finding of increased structural connectivity in PNES is in contrast with studies examining many other pathologic processes that are typically associated with decreased rather than increased structural connectivity (Riley et al., 2010). The areas of increased connectivity identified in our study are discussed below.
3.1.
Increased FA in uncinate fasciculus (UF)
The UF is a major white matter tract that connects the anterior temporal lobe to the inferior frontal lobe (orbitofrontal area) (Von Der Heide et al., 2013). It is has been proposed that UF is involved in emotion processing and memory
(Gaffan and Wilson, 2008; Ross, 2008), and it is thought to play a major role in emotion regulation (Yasmin et al., 2008). Since abnormal processing and regulation of emotional responses is believed to play a role in the pathology of PNES (Urbanek et al., 2014), it is not surprising to find differences between healthy controls and patients with PNES in the integrity of the UF (Fig. 1D). In one study, increased values of FA in the left UF correlated with the degree to which healthy women employed an emotional regulation mechanism known as “reappraisal” in which negative emotions or experiences are coped with by reframing the experience in a more positive light, as compared to those who typically cope with negative emotions by suppressing them (Zuurbier et al., 2013). However, in men such an effect was not seen. Since all but one of the PNES patients in our study were women, which is typical of the PNES population (Szaflarski et al., 2000), our finding of increased FA in the left UF may reflect increased use of – and thus reinforcement of – networks associated with reappraisal to cope with the greater degree of stressful or traumatic experiences common in the lives of patients with PNES (Bodde et al., 2009). Interestingly, a small study of 8 patients with PNES found that increased leftward asymmetry of FA in the UF was associated with increased age of illness onset, and that 6 of the 8 patients with age of PNES onset greater than 30 years old exhibited leftward asymmetric FA (Hernando et al., 2015). Although we found no significant associations between average FA and clinical measures, given that age of PNES onset for the majority of our patients (11/16) was greater than 30 years old, this factor may be contributing
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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to the increased average FA observed in the left UF of PNES patients compared to HCs. Another study reported that decreased FA in the left UF correlated with poor performance on negative emotional recognition and episodic memory tasks in patients with amnestic mild cognitive impairment (Fujie et al., 2008). In contrast to these results, PNES patients showed increased FA in the left UF, which may reflect heightened sensitivity of PNES patients to recognize negative emotions due to reinforcement of this white matter pathway (Hixson et al., 2006; Testa et al., 2012).
3.2.
Increased FA in corona radiata and internal capsule
The corticospinal tracts, which pass through the corona radiata and the posterior internal capsule, mediate control of motor functions. We have found increased FA values in the posterior limb of the left internal capsule (Fig. 1B) and corona radiata (Fig. 1A) in patients with PNES when compared to healthy controls. We also found higher FA values in the anterior limb of the left internal capsule (Fig. 1B), which connects the striatum to the motor cortex. This may reflect involvement of the motor system in producing coordinated major motor activity seen in 11 of our 16 patients. While using a significance cutoff of P ¼0.05, only areas associated with the left hemispheric motor system were significantly different in patients with PNES compared to healthy controls. The right coronal radiata and internal capsule also showed significantly increased FA in patients with PNES when the cutoff P-value was changed to 0.1; this was the only additional brain region to show significance with this change. While the reasons for this asymmetry are not clear, we assume they are related to hemispheric dominance and the typically increased expression of structural connectivity in the dominant hemisphere.
3.3.
Increased FA in external capsule
Interpreting the finding of increased FA in the area of the external capsule is complicated by the fact that the external capsule, extreme capsule, and insular juxtacortical fibers are closely apposed in this area and are not clearly distinguished with TBSS. One study reported increased FA values of the right external capsule, as well as in the anterior and posterior limbs of the internal capsule and corona radiata in patients with functional dyspepsia (Zhou et al., 2013) which, like PNES, falls under the broad category of somatoform disorders. These findings, to a large degree, mirror in the right hemisphere our findings in the left hemisphere (Fig. 1B), raising the possibility that somatoform disorders associated with depression and/or anxiety may involve homologous structures on either side of the brain. While the reasons for the differences in laterality between the studies are not clear, they may be related to the clinical presentation of the conversion disorder or other factors that remain to be explored in the future.
3.4.
Increased FA in superior temporal gyrus (STG)
The superior temporal gyrus is well known to be involved in receptive language processing in the dominant hemisphere and primary auditory processing bilaterally (Kim et al., 2011).
There is a growing body of evidence that the STG is also involved in perception of emotions (de Greck et al., 2012; Husain et al., 2014; Pehrs et al., 2013; Robins et al., 2009). In one fMRI study increased activation in the bilateral STG was observed in response to pleasant or unpleasant sounds when compared to neutral sounds (Husain et al., 2014); HCs showed increased activation in the left STG specifically while listening to pleasant or unpleasant sounds, compared to neutral sounds. These findings suggest that STG, especially on the left, is involved not just in language and primary auditory processing but also in affective/emotional processing. While not tested in the current study, we speculate that increased FA values in the left STG of patients with PNES may be related to abnormal affective perception or emotional regulation of auditory stimuli. Similarly, one study investigated patterns of fMRI activation to dynamic audiovisual emotional stimuli while watching a short movie (Robins et al., 2009). These authors compared an average response to multiple types of emotional stimuli (angry, fearful, and happy) to neutral stimuli and found greater activation to emotional stimuli in the bilateral anterior STG. These and other studies (de Greck et al., 2012; Pehrs et al., 2013) suggest that STG responds differently to auditory, audiovisual, and visual-only stimuli based on the emotional content of the stimulus. Finally, our results are in agreement with the study by Ding et al. (2013), who observed decreased regional structural nodal connectivity strength in STG bilaterally along with several other brain regions as well as globally decreased structural connectivity strength in PNES patients compared to controls. While each of these studies cannot be directly compared to ours due to differences in imaging method (fMRI vs. DTI) or analysis approach, our finding of increased FA in the STG suggests that patients with PNES have particularly robust white matter pathways in this area commonly involved in mediating cortical responses to emotional stimuli. Future studies combining structural DTI connections of limbic brain regions and fMRI of emotional processing would help to clarify these structure– function relationships in patients with PNES. Other imaging modalities that are commonly used to evaluate epilepsy patients have also been applied to study PNES in a limited number of reports. A number of studies have described cases in which ictal/interictal-SPECT was performed on patients with PNES. In the majority of cases SPECT results were negative, and in some cases a positive result was found, though the locations were not consistent across studies (Biraben et al., 1999; Ettinger et al., 1998; Neiman et al., 2009; Spanaki et al., 1999; Varma et al., 1996). Another study reported that group analysis of patients with PNES revealed significant PET hypometabolism within the right inferior parietal and central area, and within the bilateral anterior cingulate cortex (Arthuis et al., 2014). While making a direct correlation between these findings and the results of the present study is challenging, these reports are nonetheless supportive of the notion that differences between patients with PNES and HCs exist and may be observable with imaging. The pathological mechanisms underlying the higher FA in PNES patients remain unknown due to the difficulty in designing and conducting a study that could definitely answer this question. Arguing from basic principles, the plausible explanations for increased FA include increased fiber number density, reflecting a greater number of axonal
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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connections between brain regions, or reduced fiber branching or crossing fibers (Beaulieu, 2002; Hoeft et al., 2007). However, the contributions of these and other factors that increase anisotropy need further investigation. To our knowledge, reports on pathological findings associated with increased FA are still scarce, and the pathophysiology of PNES is still not clear. This study is intended to be exploratory and is limited in several ways. First, our subjects displayed a variety of comorbid psychiatric conditions including depression, anxiety, bipolar disorder, and obsessive-compulsive disorder. Due to the retrospective nature of this work, a thorough characterization of the presence and severity of these conditions was not possible, and therefore, the relative contribution of each to the observed changes in FA cannot be established. Nonetheless, these conditions are quite common in patients with PNES, therefore the study sample is felt by us to be representative of the PNES population. Much larger prospective studies will be needed to have sufficient power to tease out the relative contribution of each of these variables. Second, in the discussion above we describe possible rationales as to how the observed findings may reflect our conceptual understanding of PNES, particularly regarding affective perception and emotional regulation, but it should be noted that none of these putative psychodynamics were tested directly and further work is needed to confirm or deny these postulates. The small sample size of the study and retrospective nature of its design preclude an in-depth evaluation of the correlation between DTI changes and a variety of psychometric measures, psychiatric diagnoses, specific features of semiology, or response to treatment. All of these are worthy of future exploration under prospective examination.
5
5.
Experimental procedures
identified through databases containing demographic and clinical information from all patients admitted for video/ EEG evaluation to the Epilepsy Monitoring Unit (EMU) at the University of Alabama at Birmingham (UAB). Diagnosis of PNES was made based on inpatient video-EEG monitoring by attending epileptologists in the EMU during admission in accord with published guidelines for “Documented PNES” (LaFrance et al., 2013). Patients were excluded from analyses if they had definite or suspected comorbid epilepsy, inconclusive video-EEG evaluation (no events captured), abnormal EEG with epileptiform discharges, or recording of only some but not all types of a patient’s habitual events. Based on a previously published classification, the included PNES patients were categorized as having major motor (n¼ 10), minor motor (n¼ 1), waxy flexibility (n¼ 3), or subjective (n¼ 2) events (Griffith et al., 2007). Patients with significant neurological comorbidity (e.g., traumatic brain injury, brain tumors or mental retardation) were excluded. One patient had a non-specific area of white matter hyperintensity on T2 FLAIR images high in the dorsal convexity of the right frontal lobe above the major hemispheric white matter tracts, but the scans of the remaining patients were all normal in appearance. The aforementioned hyperintensity did not overlap any of the areas found to be different between groups at either Po0.05 or Po0.10, therefore the patient was retained in the analysis to maximize the statistical power in light of the limited sample size of this study. Of note, the presence of this lesion is consistent with the findings of Devinsky et al. (2001) who found that structural imaging abnormalities in patients with PNES were more commonly seen in the right hemisphere than the left. Among the 16 patients in this study, seven patients reported a history of depression, one of whom also reported a history of obsessive-compulsive disorder; five patients reported a history of anxiety, three of whom also reported a history of depression; and the one patient who reported both history of depression and anxiety also reported a history of bipolar disorder. These classifications are based on selfreported conditions in their medical history at admission to the EMU. Upon diagnosis of PNES, all patients were referred to community-based psychologists, hence thorough psychiatric assessment was not available to us on these patients. Healthy controls had no known history of neurologic disorders. The retrospective study of patients with PNES was approved by the Institutional Review Board (IRB) at UAB with consent waived (n¼ 9; DTI data collected for clinical purposes); subjects who were enrolled in a prospective research study signed an IRB-approved consent form. Healthy controls were identified from a large database of normative data collected via NIH R01 HD068488; all participants signed an IRB-approved informed consent form. The details of the demographic and clinical characteristics of PNES patients are presented in Table 1.
5.1.
Participants
5.2.
4.
Conclusion
This study investigated white matter DTI characteristics in patients with PNES. Compared to healthy controls, patients with PNES showed significantly increased FA values in left hemispheric areas involved in the regulation and perception of emotions (UF and STG) and motor system control (corona radiata and internal and external capsule). While not specifically tested in this study, we believe that the increased strength in white matter connectivity of these regions is either the result of or contributes to the underlying etiology of PNES. Further studies of changes in structural and functional connectivity in response to treatment (e.g., cognitive behavioral therapy) (LaFrance et al., 2014) are needed in order for us to better understand the neuropathological substrates of this complex and highly prevalent disorder.
Sixteen patients with a definite diagnosis of PNES (15 females, mean age: 39.81714.12 years) and 16 age- and gendermatched healthy controls (HCs; 15 females, mean age: 40.44713.83) were enrolled. The PNES patients were
Image acquisition
All neuroimaging data were collected at 3 T using a 32direction DTI sequence obtained as part of either a routine clinical evaluation (n¼ 9) on Philips Achieva scanner (Philips Medical Systems, Eindhoven, Netherlands) or a research
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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brain research ] (]]]]) ]]]–]]]
Table 1 – Demographics and clinical characteristics of patients with PNES. Patient ID
Age
Gender
Age of onset
PNES duration (years)
Mean frequency of events (per month)
PNES semiology classification
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 P16
46 33 45 33 43 57 19 56 52 49 21 22 62 51 35 21
F F F F F F F F F F M F F F F F
44 33 32 32 40 57 15 55 41 47 21 13 51 45 33 18
2 0.9 13 1 2.6 0.3 4 1.2 11 2.1 0.2 9 10 6 2 3.8
60 8 0.7 6 2 45 2 255 20 60 16.7 8 60 2.3 0.3 2
Major motor Major motor Major motor Major motor Major motor Waxy flexibility Major motor Minor motor Subjective Subjective Major motor Major motor Major motor Major motor Waxy flexibility Waxy flexibility
Table 2 – DTI scan parameters for each scanner.
Acquired voxel size (mm) Reconstructed voxel size (mm) FOV (mm) TR (ms) TE (ms) Slices b-Value (s/mm2)
UAB Philips Achieva (9 patients)
UC Philips Achieva (9 controls)
UAB Siemens Allegra (7 patients; 7 controls)
2.0 2.0 2.0 1.7 1.7 2.0
2.4 2.4 2.4 1.9 1.9 2.4
2.5 2.5 2.5 2.5 2.5 2.5
244 244 9722 84 70 800
180 180 9403 69 55 800
240 240 9400 89 55 1000
Table 3 – The areas of increased/decreased FA and MD values in PNES. Regions of increased FA in PNES
Left Left Left Left Left
corona radiata uncinate fasciculus internal capsule external capsule superior temporal gyrus
MNI coordinates x
y
z
27 34 24 31 55
3 4 13 8 21
22 11 14 11 2
study (n¼ 7) on a Siemens Allegra scanner (Siemens Medical Solutions, Erlangen, Germany), both at UAB. For control data, nine scans were collected on a Philips Achieva scanner at the University of Cincinnati and seven scans were collected on a Siemens Allegra scanner at UAB. The DTI scan parameters were similar for each scanner and are listed in Table 2.
5.3.
P-value
Preprocessing of neuroimaging data
The neuroimaging data were converted from DICOM (Digital Imaging and Communications in Medicine) format to NIfTI (Neuroimaging Informatics Technology Initiative) format. The AFNI (Analysis of Functional NeuroImages) software package was used (http://afni.nimh.nih.gov/) (Cox, 1996) to
0.0392 0.0456 0.0406 0.0414 0.0478
preprocess the anatomical and DTI scans. The motion and eddy current corrections were performed and skull-stripping was carried out to allow the anatomical data to be subsequently matched to the DTI data. The skull-stripped brain images were resampled to the same matrix size and orientation as the DTI dataset in order to mask out non-brain voxels. Finally, fractional anisotropy (FA) and mean diffusivity (MD) were calculated.
5.4.
TBSS analysis
The voxel-wise analysis of multi-subject diffusion data was carried out in FSL using TBSS (Allendorfer et al., 2012; Smith et al., 2006). Whole-brain white matter was analyzed as
Please cite this article as: Lee, S., et al., White matter diffusion abnormalities in patients with psychogenic nonepileptic seizures. Brain Research (2015), http://dx.doi.org/10.1016/j.brainres.2015.04.050
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follows. First, all FA maps are aligned to a white matter template in standard space using nonlinear registration, and all aligned FA images were averaged to create a group mean FA image. The mean FA image was thresholded at a mean FA value of 0.2 to include the major white matter tracts and to suppress regions of partial grey matter and/or high intersubject variability. Next, the mean FA image was eroded to produce a skeletonized mean FA image, which is thought to reflect the center of fiber bundles in both groups. Nonparametric, unpaired t-tests between PNES and age- and gender-matched HCs were performed for voxel-wise group comparisons using the ‘randomise’ permutation test in FSL (Winkler et al., 2014). The number of permutations was 5000 and the differences between two groups were considered significant at Po0.05 corrected (familywise error rate [FWE]) using threshold-free cluster enhancement (TFCE) (Smith and Nichols, 2009). Additionally, we computed a group-level analysis while controlling for scanner type by including each scanner as a grouping variable in the group-level model. We then evaluated the effect of the scanner on FA values by computing an orthogonal F contrast comparing mean FA measurements among scanners. Results were considered significant for Po0.05, corrected for the voxel-level family-wise error rate. We also tested for correlations for the clinical parameters of duration of illness and for mean frequency of events with averaged FA values from the regions of increased FA. Spearman’s rho was used to estimate the correlation; Spearman’s rho was chosen because of non-normality of the distribution of PNES patients’ clinical parameters.
Disclosure of conflicts of interest None of the authors has any conflict of interest to disclose.
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