Quantitative magnetic resonance techniques in epilepsy

Epilepsy is a chronic brain disorder characterized by unprovoked recurrent seizures that give rise to episodes of abnormal neuronal activity in the central nervous system. The most common application of magnetic resonance imaging (MRI) techniques in the epileptic brain is the identification of the underlying cause for a person’s epilepsy, and possibly the localization of the epileptic focus. In addition, quantitative magnetic resonance (MR) techniques enable examining certain relatively subtle aspects of epilepsy within the brain that go beyond the identification of seizure focus within the brain. In this thesis a number of studies are presented that investigate the application of quantitative MR techniques to epilepsy-related abnormalities of metabolism, microstructures and brain function. The research project was aimed at developing and validating quantitative MR techniques (spectroscopy, diffusion, T2 relaxometry, and functional magnetic resonance imaging) with clinical diagnostic potential. The main focus was on data acquisition and processing, and the application of this multi-modal MR approach in both patients with epilepsy and an animal model of epileptogenesis. We explored in a clinical setting how the cognitive consequences of epilepsy (either due to medication or due to seizures) may be reflected in altered MR tissue characteristics. Furthermore, using an experimental model of febrile convulsions, it was investigated whether neurological abnormalities, possibly linked with epileptogenesis and thus with epilepsy, could be detected by quantitative MR. A general introduction into quantitative MR techniques and epilepsy is given in Chapter 1. Chapter 2 describes a thorough review on absolute quantification of metabolites using spectroscopy, which can substantially improve the diagnostic utility of spectroscopy. Absolute quantification requires more time and expertise than relative quantification, as additional calibrations for concentration determination and spectrum analyses have to be performed. One can only benefit from absolute quantification if all additional reference steps are executed properly; otherwise unwanted additional errors may be introduced. Chapter 3 concerns a clinically relevant reproducibility study of several quantitative MR techniques which was performed on a 3.0 Tesla MR system. Repeated measurements in 10 healthy volunteers were used to establish the reproducibility of quantitative measures derived from different quantitative MR techniques, namely the T2 relaxation time, the apparent diffusion coefficient (ADC), the fractional anisotropy (FA), and metabolite concentrations of N-acetyl-aspartate (NAA), total creatine (tCr), choline (Cho) and myo-inositol (mI). The reproducibility of quantitative brain MR at 3.0 T appeared to be better than, or at least comparable to the reproducibility at 1.5 T. A newly developed statistical image analysis method, which offers considerably increased sensitivity for the detection of subtle signal changes in images of several neurological MR applications, is described in Chapter 4. This method, the regional false discovery rate (FDR) control, increases sensitivity by exploiting the spatially clustered nature of neuroimaging effects. The method was validated, characterized, and compared to some other commonly used methods (uncorrected thresholding, Bonferroni correction, and conventional FDR-control). It was found that the new method showed considerably higher sensitivity as compared to conventional FDR-control. Application of the method to two different neuroimaging applications, revealed substantial improvements compared to the other methods. Quantitative MR (T2 relaxation, diffusion, spectroscopy, and functional MRI) at 1.5 T and neuropsychological assessment was performed in a group of patients with localization related epilepsy and secondarily generalized tonicoclonic seizures (SGTCS) to study cognitive deterioration. Chapter 5 relates to the investigation of the effect of these seizures on microstructural and metabolic changes in brain tissue characteristics. Frontal, but not temporal, MR abnormalities were found to be related to SGTCS. These findings confirm that SGTCS do have a substantial effect on frontal brain function and on the microstructural brain tissue characteristics. This knowledge may help to obtain a better understanding and anticipatory treatment of SGTCS-related cognitive deterioration. In Chapter 6 it was investigated using functional MRI whether a higher number of SGCTS were associated with a functional reorganization of working memory. It was found that high numbers of SGTCS resulted in a decrease in intelligence scores and altered prefrontal brain activation. A shift from frontotemporal to prefrontal activation seemed to have occurred, suggesting that a functional reorganization of working memory is induced by a high number of SGTCS. It remains uncertain if this reorganization reflected compensatory mechanisms, or the underlying pathological processes of cognitive deterioration. In the same patient group it was found in Chapter 7 that the presence of a certain marker for neuronal damage in blood serum (telencephalin) correlates with a decreased frontotemporal activity during an functional MRI memory task

Assessing and minimizing the effects of noise and motion in clinical DTI at 3 T

\u3cp\u3eCompared with conventional MRI, diffusion tensor imaging (DTI) is more prone to thermal noise and motion. Optimized sampling schemes have been proposed that reduce the propagation of noise. At 3 T, however, motion may play a more dominant role than noise. Although the effects of noise at 3 T are less compared with 1.5 T because of the higher signal-to-noise ratio, motion is independent of field strength and will persist. To improve the reliability of clinical DTI at 3 T, it is important to know to what extent noise and motion contribute to the uncertainties of the DTI indices. In this study, the effects of noise- and motion-related signal uncertainties are disentangled using in vivo measurements and computer simulations. For six clinically standard available sampling schemes, the reproducibility was assessed in vivo, with and without motion correction applied. Additionally, motion and noise simulations were performed to determine the relative contributions of motion and noise to the uncertainties of the mean diffusivity (MD) and fractional anisotropy (FA). It is shown that the contributions of noise and motion are of the same order of magnitude at 3 T. Similar to the propagation of noise, the propagation of motion-related signal perturbations is also influenced by the choice of sampling scheme. Sampling schemes with only six diffusion directions demonstrated a lower reproducibility compared with schemes with 15 and 32 directions and feature a positive bias for the FA in relatively isotropic tissue. Motion correction helps improving the precision and accuracy of DTI indices.\u3c/p\u3

Interaction between blood-brain barrier and glymphatic system in solute clearance

\u3cp\u3eNeurovascular pathology concurs with protein accumulation, as the brain vasculature is important for waste clearance. Interstitial solutes, such as amyloid-β were previously thought to be primarily cleared from the brain by blood-brain barrier transport. Recently, the glymphatic system was discovered, in which cerebrospinal fluid is exchanged with interstitial fluid, facilitated by the aquaporin-4 water channels on the astroglial endfeet. Glymphatic flow can clear solutes from the interstitial space. Blood-brain barrier transport and glymphatic clearance likely serve complementary roles with partially overlapping mechanisms providing a well-conditioned neuronal environment. Disruption of these mechanisms can lead to protein accumulation and may initiate neurodegenerative disorders, for instance amyloid-β accumulation and Alzheimer's disease. Although both mechanisms seem to have a similar purpose, their interaction has not been clearly discussed previously. This review focusses on this interaction in healthy and pathological conditions. Future health initiatives improving waste clearance might delay or even prevent onset of neurodegenerative disorders. Defining glymphatic flow kinetics using imaging may become an alternative way to identify those at risk of Alzheimer's disease.\u3c/p\u3

A new analysis approach for T\u3csub\u3e2\u3c/sub\u3e relaxometry myelin water quantification: Orthogonal Matching Pursuit

\u3cp\u3ePurpose: In vivo myelin quantification can provide valuable noninvasive information on neuronal maturation and development, as well as insights into neurological disorders. Multiexponential analysis of multiecho T\u3csub\u3e2\u3c/sub\u3e relaxation is a powerful and widely applied method for the quantification of the myelin water fraction (MWF). In recent literature, the MWF is most commonly estimated using a regularized nonnegative least squares algorithm. Methods: The orthogonal matching pursuit algorithm is proposed as an alternative method for the estimation of the MWF. The orthogonal matching pursuit is a greedy sparse reconstruction algorithm with a low computation complexity. For validation, both methods are compared to a ground truth using numerical simulations and a phantom model using comparable computation times. The numerical simulations were used to measure the theoretical errors, as well as the effects of varying the SNR, strength of the regularization, and resolution of the basis set. Additionally, a phantom model was used to estimate the performance of the 2 methods while including errors occurring due to the MR measurement. Lastly, 4 healthy subjects were scanned to evaluate the in vivo performance. Results: The results in simulations and phantoms demonstrate that the MWFs determined with the orthogonal matching pursuit are 1.7 times more accurate as compared to the nonnegative least squares, with a comparable precision. The remaining bias of the MWF is shown to be related to the regularization of the nonnegative least squares algorithm and the Rician noise present in magnitude MR images. Conclusion: The orthogonal matching pursuit algorithm provides a more accurate alternative for T\u3csub\u3e2\u3c/sub\u3e relaxometry myelin water quantification.\u3c/p\u3

Wavelet entropy of BOLD time series:an application to Rolandic epilepsy

\u3cp\u3ePurpose: To assess the wavelet entropy for the characterization of intrinsic aberrant temporal irregularities in the time series of resting-state blood-oxygen-level-dependent (BOLD) signal fluctuations. Further, to evaluate the temporal irregularities (disorder/order) on a voxel-by-voxel basis in the brains of children with Rolandic epilepsy. Materials and Methods: The BOLD time series was decomposed using the discrete wavelet transform and the wavelet entropy was calculated. Using a model time series consisting of multiple harmonics and nonstationary components, the wavelet entropy was compared with Shannon and spectral (Fourier-based) entropy. As an application, the wavelet entropy in 22 children with Rolandic epilepsy was compared to 22 age-matched healthy controls. The images were obtained by performing resting-state functional magnetic resonance imaging (fMRI) using a 3T system, an 8-element receive-only head coil, and an echo planar imaging pulse sequence (T\u3csub\u3e2\u3c/sub\u3e \u3csup\u3e*\u3c/sup\u3e -weighted). The wavelet entropy was also compared to spectral entropy, regional homogeneity, and Shannon entropy. Results: Wavelet entropy was found to identify the nonstationary components of the model time series. In Rolandic epilepsy patients, a significantly elevated wavelet entropy was observed relative to controls for the whole cerebrum (P = 0.03). Spectral entropy (P = 0.41), regional homogeneity (P = 0.52), and Shannon entropy (P = 0.32) did not reveal significant differences. Conclusion: The wavelet entropy measure appeared more sensitive to detect abnormalities in cerebral fluctuations represented by nonstationary effects in the BOLD time series than more conventional measures. This effect was observed in the model time series as well as in Rolandic epilepsy. These observations suggest that the brains of children with Rolandic epilepsy exhibit stronger nonstationary temporal signal fluctuations than controls. Level of Evidence: 2. Technical Efficacy: Stage 3. J. Magn. Reson. Imaging 2017;46:1728–1737.\u3c/p\u3

Spectral diffusion analysis of intravoxel incoherent motion MRI in cerebral small vessel disease

\u3cp\u3eBackground: Cerebral intravoxel incoherent motion (IVIM) imaging assumes two components. However, more compartments are likely present in pathologic tissue. We hypothesized that spectral analysis using a nonnegative least-squares (NNLS) approach can detect an additional, intermediate diffusion component, distinct from the parenchymal and microvascular components, in lesion-prone regions. Purpose: To investigate the presence of this intermediate diffusion component and its relation with cerebral small vessel disease (cSVD)-related lesions. Study Type: Prospective cross-sectional study. Population: Patients with cSVD (n = 69, median age 69.8) and controls (n = 39, median age 68.9). Field Strength/Sequence: Whole-brain inversion recovery IVIM acquisition at 3.0T. Assessment: Enlarged perivascular spaces (PVS) were rated by three raters. White matter hyperintensities (WMH) were identified on a fluid attenuated inversion recovery (FLAIR) image using a semiautomated algorithm. Statistical Tests: Relations between IVIM measures and cSVD-related lesions were studied using the Spearman's rank order correlation. Results: NNLS yielded diffusion spectra from which the intermediate volume fraction f \u3csub\u3eint\u3c/sub\u3e was apparent between parenchymal diffusion and microvasular pseudodiffusion. WMH volume and the extent of MRI-visible enlarged PVS in the basal ganglia (BG) and centrum semiovale (CSO) were correlated with f \u3csub\u3eint\u3c/sub\u3e in the WMHs, BG, and CSO, respectively. f \u3csub\u3eint\u3c/sub\u3e was 4.2 ± 1.7%, 7.0 ± 4.1% and 13.6 ± 7.7% in BG and 3.9 ± 1.3%, 4.4 ± 1.4% and 4.5 ± 1.2% in CSO for the groups with low, moderate, and high number of enlarged PVS, respectively, and increased with the extent of enlarged PVS (BG: r = 0.49, P < 0.01; CSO: r = 0.23, P = 0.02). f \u3csub\u3eint\u3c/sub\u3e in the WMHs was 27.1 ± 13.1%, and increased with the WMH volume (r = 0.57, P < 0.01). Data Conclusion: We revealed the presence of an intermediate diffusion component in lesion-prone regions of cSVD and demonstrated its relation with enlarged PVS and WMHs. In tissue with these lesions, tissue degeneration or perivascular edema can lead to more freely diffusing interstitial fluid contributing to f \u3csub\u3eint\u3c/sub\u3e. Level of Evidence: 2. Technical Efficacy: Stage 2. J. Magn. Reson. Imaging 2020;51:1170–1180. \u3c/p\u3

The cognitive profile of ethosuximide in children

\u3cp\u3eIntroduction: Although ethosuximide is one of the oldest antiepileptic drugs (AEDs), little information is available about the cognitive side effects of ethosuximide. Objective: The aim of this study was to investigate the cognitive profile of ethosuximide. Methods: In this cross-sectional study, we used an extensive neuropsychological test battery in patients with epilepsy aged 6–16 years who were treated with monotherapy ethosuximide. We evaluated the efficacy of the drug by seizure frequency (seizure free or not). Results: We included 61 patients with a mean age of 9.4 years [standard deviation (SD) 2.7] who used on average 686 mg/day (SD 245) ESM as monotherapy. ESM was effective in the majority of the patients (70 % were seizure free for at least 6 months at moment of inclusion). The total study population showed impairments of intelligence, visuomotor, and attentional function including activation/alertness. Comparisons between the well-controlled patients and patients who were not in remission showed significantly lower intelligence values and lower performance on the visual-perceptual and attentional tasks for the group with ongoing seizures. Our results suggested that the higher order cognitive dysfunctions (such as intelligence and visual-perceptual functions) may be regarded as seizure or aetiology effects and that the impaired fluid cognitive functions, such as activation/alertness, sustained auditory attention and attentional control or switching, were due to ESM. Conclusion: This study suggests the attentional dysfunction resulting in psychomotor slowing and alertness deficits may be regarded as effects of ethosuximide. Although no untreated baseline assessment was available, these effects are comparable to those of other AEDs, and ethosuximide may therefore be considered an AED with only mild effects on cognition. As ethosuximide is a first-line therapy for absence seizures in childhood, and drug-induced cognitive impairment may interfere with development, learning, and academic achievement, these findings are of interest to clinicians who prescribe this drug, especially when informing parents.\u3c/p\u3

Working memory network alterations in high-functioning adolescents with an autism spectrum disorder

\u3cp\u3eAim: People with autism spectrum disorder (ASD) typically have deficits in the working memory (WM) system. WM is found to be an essential chain in successfully navigating in the social world. We hypothesize that brain networks for WM have an altered network integrity in ASD compared to controls. Methods: Thirteen adolescents (one female) with autistic disorder (n = 1), Asperger's disorder (n = 7), or pervasive developmental disorder not otherwise specified (n = 5), and 13 typically developing healthy control adolescents (one female) participated in this study. Functional magnetic resonance imaging (MRI) was performed using an n-back task and in resting state. Results: The analysis of the behavioral data revealed deficits in WM performance in ASD, but only when tested to the limit. Adolescents with ASD showed lower binary global efficiency in the WM network than the healthy control group with n-back and resting-state data. This correlated with diagnostic scores for total problems, reciprocity, and language. Conclusion: Adolescents with higher-functioning autism have difficulty with the WM system, which is typically compensated. Functional MRI markers of brain network organization in ASD are related to characteristics of autism as represented in diagnostic scores. Therefore, functional MRI provides neuronal correlates for memory difficulties in adolescents with ASD.\u3c/p\u3

Structural covariance networks relate to the severity of epilepsy with focal-onset seizures

\u3cp\u3ePurpose: The brains of patients with epilepsy may exhibit various morphological abnormalities, which are often not directly visible on structural MR images, as they may be focally subtle or related to a more large-scale inconspicuous disorganization of brain structures. To explore the relation between structural brain organization and epilepsy characteristics, including severity and cognitive co-morbidity, we determined structural covariance networks (SCNs). SCNs represent interregional correlations of morphologic measures, for instance in terms of cortical thickness, between various large-scale distributed brain regions. Methods: Thirty-eight patients with focal seizures of all subtypes and 21 healthy controls underwent structural MRI, neurological, and IQ assessment. Cortical thickness was derived from the structural MRIs using FreeSurfer. Subsequently, SCNs were constructed on a group-level based on correlations of the cortical thicknesses between various brain regions. Individual SCNs for the epilepsy patients were extracted by adding the respective patient to the control group prior to the SCN construction (i.e. add-one-patient approach). Calculated network measures, i.e. path length, clustering coefficient and betweenness centrality were correlated with characteristics related to the severity of epilepsy, including seizure history and age at onset of epilepsy, and cognitive performance. Results: Stronger clustering in the individual SCN was associated with a higher number of focal to bilateral tonic-clonic seizures during life time, a younger age at onset, and lower cognitive performance. The path length of the individual SCN was not related to the severity of epilepsy or cognitive performance. Higher betweenness centrality of the left cuneus and lower betweenness centrality of the right rostral middle frontal gyrus were associated with increased drug load and younger age at onset, respectively. Conclusions: These results indicate that the correlations between interregional variations of cortical thickness reflect disease characteristics or responses to the disease and deficits in patients with epilepsy with focal seizures.\u3c/p\u3

Chronic antiepileptic drug use and functional network efficiency:a functional magnetic resonance imaging study

\u3cp\u3eAIM: To increase our insight in the neuronal mechanisms underlying cognitive side-effects of antiepileptic drug (AED) treatment.\u3c/p\u3e\u3cp\u3eMETHODS: The relation between functional magnetic resonance-acquired brain network measures, AED use, and cognitive function was investigated. Three groups of patients with epilepsy with a different risk profile for developing cognitive side effects were included: A low risk category (lamotrigine or levetiracetam, n = 16), an intermediate risk category (carbamazepine, oxcarbazepine, phenytoin, or valproate, n = 34) and a high risk category (topiramate, n = 5). Brain connectivity was assessed using resting state functional magnetic resonance imaging and graph theoretical network analysis. The Computerized Visual Searching Task was used to measure central information processing speed, a common cognitive side effect of AED treatment.\u3c/p\u3e\u3cp\u3eRESULTS: Central information processing speed was lower in patients taking AEDs from the intermediate and high risk categories, compared with patients from the low risk category. The effect of risk category on global efficiency was significant (P < 0.05, ANCOVA), with a significantly higher global efficiency for patient from the low category compared with the high risk category (P < 0.05, post-hoc test). Risk category had no significant effect on the clustering coefficient (ANCOVA, P > 0.2). Also no significant associations between information processing speed and global efficiency or the clustering coefficient (linear regression analysis, P > 0.15) were observed.\u3c/p\u3e\u3cp\u3eCONCLUSION: Only the four patients taking topiramate show aberrant network measures, suggesting that alterations in functional brain network organization may be only subtle and measureable in patients with more severe cognitive side effects.\u3c/p\u3