Niels K. Focke

Voxel-based diffusion tensor imaging in patients with mesial temporal lobe epilepsy and hippocampal sclerosis

BACKGROUNDnMesial temporal lobe epilepsy (mTLE) with hippocampus sclerosis (HS) is an important cause for focal epilepsy. In this study, we explored the integrity of connecting networks using diffusion tensor imaging (DTI) and two whole-brain voxel-based methods: statistical parametric mapping (SPM) and tract-based spatial statistics (TBSS).nnnMETHODSnThirty-three consecutive patients with mTLE and HS undergoing presurgical evaluation were scanned at 3 T, a DTI data set was acquired and parametric maps of fractional anisotropy (FA) and mean diffusivity (MD) were calculated. Twenty-one patients had left hippocampal sclerosis (LHS) and 12 patients had right HS (RHS). These groups were compared to 37 normal control subjects using both SPM5 and TBSS.nnnRESULTSnThe ipsilateral temporal lobe showed widespread FA reduction in both groups. The limbic system was clearly abnormal in the LHS group, also involving the arcuate fasciculus. In RHS, changes were more restricted but also showed involvement of the contralateral temporal and inferior frontal lobe. Increased MD was found in the ipsilateral hippocampus by SPM that was only marginally detected by TBSS. In white matter regions, however, TBSS was more sensitive to changes than SPM.nnnCONCLUSIONnDTI detects extensive changes in mTLE with HS. The affected networks were principally in the ipsilateral temporal lobe and the limbic system but also the arcuate fasciculus. SPM and TBSS gave complementary information with higher sensitivity to FA changes using TBSS.

Defining Meyer's loop–temporal lobe resections, visual field deficits and diffusion tensor tractography

Anterior temporal lobe resection is often complicated by superior quadrantic visual field deficits (VFDs). In some cases this can be severe enough to prohibit driving, even if a patient is free of seizures. These deficits are caused by damage to Meyers loop of the optic radiation, which shows considerable heterogeneity in its anterior extent. This structure cannot be distinguished using clinical magnetic resonance imaging sequences. Diffusion tensor tractography is an advanced magnetic resonance imaging technique that enables the parcellation of white matter. Using seed voxels antero-lateral to the lateral geniculate nucleus, we applied this technique to 20 control subjects, and 21 postoperative patients. All patients had visual fields assessed with Goldmann perimetry at least three months after surgery. We measured the distance from the tip of Meyers loop to the temporal pole and horn in all subjects. In addition, we measured the size of temporal lobe resection using postoperative T1-weighted images, and quantified VFDs. Nine patients suffered VFDs ranging from 22% to 87% of the contralateral superior quadrant. In patients, the range of distance from the tip of Meyers loop to the temporal pole was 24–43 mm (mean 34 mm), and the range of distance from the tip of Meyers loop to the temporal horn was −15 to +9 mm (mean 0 mm). In controls the range of distance from the tip of Meyers loop to the temporal pole was 24–47 mm (mean 35 mm), and the range of distance from the tip of Meyers loop to the temporal horn was −11 to +9 mm (mean 0 mm). Both quantitative and qualitative results were in accord with recent dissections of cadaveric brains, and analysis of postoperative VFDs and resection volumes. By applying a linear regression analysis we showed that both distance from the tip of Meyers loop to the temporal pole and the size of resection were significant predictors of the postoperative VFDs. We conclude that there is considerable variation in the anterior extent of Meyers loop. In view of this, diffusion tensor tractography of the optic radiation is a potentially useful method to assess an individual patients risk of postoperative VFDs following anterior temporal lobe resection.

Nonmotor and diagnostic findings in subjects with de novo Parkinson disease of the DeNoPa cohort

Objective: To determine nonmotor signs (NMS) and evaluate the utility of several diagnostic tools in patients with de novo Parkinson disease (PD). Methods: This is a large single-center study of the DeNoPa cohort, including frequency-matched healthy controls. This study covers motor signs, NMS, and a combination of diagnostic tests including olfactory testing, transcranial sonography of substantia nigra (TCS), and polysomnography (PSG). We report the frequency and characteristics of NMS and the outcomes of nonmotor tests at the time of diagnosis. Results: Cross-sectional analyses of baseline investigations identified significant differences in the NMS Questionnaire (NMSQuest) and the Scopa-AUT Gastrointestinal score in 159 drug-naïve PD patients vs 110 controls. In addition, patients with PD showed reduced olfactory function, hyperechogenicity on TCS, and higher frequency of REM sleep behavior disorder (RBD). In exploring predictive markers, we found that the combination of several investigations, i.e., the NMSQuest, Scopa-AUT Gastrointestinal score, and Smell Identification Test reached an area under the receiver operating characteristic curve (AUC) of 0.913 (95% confidence interval [CI] 0.878–0.948). With the addition of serum cholesterol and mean heart rate values, the AUC value reached 0.919 (95% CI 886–0.953); when TCS and PSG were added, the AUC increased to 0.963 (95% CI 0.943–0.982). Conclusions: We show feasibility and utility of standardized data acquisition in a large, single-center cohort of patients with de novo PD and matched healthy controls. The baseline results from our prospective investigations reached a value of >0.9 sensitivity and specificity for biological markers when we added routine laboratory investigations and quantified nonmotor features including sleep.

Individual voxel-based subtype prediction can differentiate progressive supranuclear palsy from idiopathic parkinson syndrome and healthy controls

Voxel‐based morphometry (VBM) shows a differentiated pattern in patients with atypical Parkinson syndrome but so far has had little impact in individual cases. It is desirable to translate VBM findings into clinical practice and individual classification. To this end, we examined whether a support vector machine (SVM) can provide useful accuracies for the differential diagnosis. We acquired a volumetric 3D T1‐weighted MRI of 21 patients with idiopathic Parkinson syndrome (IPS), 11 multiple systems atrophy (MSA‐P) and 10 progressive supranuclear palsy (PSP), and 22 healthy controls. Images were segmented, normalized, and compared at group level with SPM8 in a classical VBM design. Next, a SVM analysis was performed on an individual basis with leave‐one‐out cross‐validation. VBM showed a strong white matter loss in the mesencephalon of patients with PSP, a putaminal grey matter loss in MSA, and a cerebellar grey matter loss in patients with PSP compared with IPS. The SVM allowed for an individual classification in PSP versus IPS with up to 96.8% accuracy with 90% sensitivity and 100% specificity. In MSA versus IPS, an accuracy of 71.9% was achieved; sensitivity, however, was low with 36.4%. Patients with IPS could not be differentiated from controls. In summary, a voxel‐based SVM analysis allows for a reliable classification of individual cases in PSP that can be directly clinically useful. For patients with MSA and IPS, further developments like quantitative MRI are needed. Hum Brain Mapp, 2011.

The structural plasticity of white matter networks following anterior temporal lobe resection

Anterior temporal lobe resection is an effective treatment for refractory temporal lobe epilepsy. The structural consequences of such surgery in the white matter, and how these relate to language function after surgery remain unknown. We carried out a longitudinal study with diffusion tensor imaging in 26 left and 20 right temporal lobe epilepsy patients before and a mean of 4.5 months after anterior temporal lobe resection. The whole-brain analysis technique tract-based spatial statistics was used to compare pre- and postoperative data in the left and right temporal lobe epilepsy groups separately. We observed widespread, significant, mean 7%, decreases in fractional anisotropy in white matter networks connected to the area of resection, following both left and right temporal lobe resections. However, we also observed a widespread, mean 8%, increase in fractional anisotropy after left anterior temporal lobe resection in the ipsilateral external capsule and posterior limb of the internal capsule, and corona radiata. These findings were confirmed on analysis of the native clusters and hand drawn regions of interest. Postoperative tractography seeded from this area suggests that this cluster is part of the ventro-medial language network. The mean pre- and postoperative fractional anisotropy and parallel diffusivity in this cluster were significantly correlated with postoperative verbal fluency and naming test scores. In addition, the percentage change in parallel diffusivity in this cluster was correlated with the percentage change in verbal fluency after anterior temporal lobe resection, such that the bigger the increase in parallel diffusivity, the smaller the fall in language proficiency after surgery. We suggest that the findings of increased fractional anisotropy in this ventro-medial language network represent structural reorganization in response to the anterior temporal lobe resection, which may damage the more susceptible dorso-lateral language pathway. These findings have important implications for our understanding of brain injury and rehabilitation, and may also prove useful in the prediction and minimization of postoperative language deficits.

Voxel‐based analysis of whole brain FLAIR at 3T detects focal cortical dysplasia

Background: Focal Cortical Dysplasia (FCD) is an important cause for pharmacoresistant epilepsy that can be treated surgically. The identification of the abnormal cortex on standard MRI can be difficult and computational techniques have been developed to increase sensitivity. In this study we evaluate the potential of a novel whole‐brain voxel‐based technique using normalized FLAIR signal intensity (nFSI) at 3 Tesla.

Automated MR image classification in temporal lobe epilepsy.

In those with drug refractory focal epilepsy, MR imaging is important for identifying structural causes of seizures that may be amenable to surgical treatment. In up to 25% of potential surgical candidates, however, MRI is reported as unremarkable even when employing epilepsy specific sequences. Automated MRI classification is a desirable tool to augment the interpretation of images, especially when changes are subtle or distributed and may be missed on visual inspection. Support vector machines (SVM) have recently been described to be useful for voxel-based MR image classification. In the present study we sought to evaluate whether this method is feasible in temporal lobe epilepsy, with adequate accuracy. We studied 38 patients with hippocampal sclerosis and unilateral (mesial) temporal lobe epilepsy (mTLE) (20 left) undergoing presurgical evaluation and 22 neurologically normal control subjects. 3D T1-weighted images were acquired at 3T (GE Excite), segmented into tissue classes, normalized and smoothed with SPM8. Diffusion tensor imaging (DTI) and double echo images for T2 relaxometry were also acquired and processed. The SVM analysis was done with the libsvm software package in a leave-one-out cross-validation design and predictive accuracy was measured. Local weighting was applied by SPM F-contrast maps. Best accuracies were achieved using the gray matter based segmentation (90-100%) and mean diffusivity (95-97%). For the three-way classification, accuracies were 88 and 93% respectively. Local weighting generally improved the accuracies except in the FA-based processing for which no effect was noted. Removing the hippocampus from the analysis, on the other hand, reduced the obtainable diagnostic indices but these were still >90% for DTI-based methods and lateralization based on gray matter maps. These findings show that automated SVM image classification can achieve high diagnostic accuracy in mTLE and that voxel-based MRI can be used at the individual subject level. This could be helpful for screening assessments of MRI scans in patients with epilepsy and when no lesion is detected on visual evaluation.

Automated normalized FLAIR imaging in MRI-negative patients with refractory focal epilepsy.

Background:u2002 Patients with focal epilepsy that is refractory to medical treatment are often considered candidates for resective surgery. Magnetic resonance imaging (MRI) has a very important role in the presurgical work‐up of these patients, but is unremarkable in about one‐third of cases. These patients are often deferred from surgery or have a less positive outcome if surgery is eventually undertaken. The aim of this study was to evaluate our recently described voxel‐based technique using routine T2‐FLAIR (fluid‐attenuated inversion‐recovery) scans in MRI‐negative patients and to compare the results with video‐EEG (electroencephalography) telemetry (VT) findings.

Multi-site voxel-based morphometry--not quite there yet.

Voxel-based morphometry (VBM) is a widely applied method in computational neurosciences but it is currently recommended to compare only data collected at a single MRI scanner. Multi-site VBM would be a desirable approach to increase group size and, thus, statistical power. We aimed to assess if multi-site VBM is feasible on similar hardware and compare the magnitude of inter- and intra-scanner differences. 18 healthy subjects were scanned in two identical 3T MRI scanners using different head coil designs, twice in scanner A and once in scanner B. 3D T1-weighted images were processed with SPM8 and FSL4.1 and compared as paired t-test (scan versus re-scan) on a voxel basis by means of a general linear model (GLM). Additionally, coefficient-of-difference (coeffD) maps were calculated for respective pairs of gray matter segmentations. We found considerable inter-scanner differences clearly exceeding a commonly used GLM significance threshold of p<0.05 (FWE corrected). The spatial pattern of detected differences was dependent on whether SPM8 or FSL4.1 was used. The inclusion of global correcting factors either aggravated (SPM8) or reduced the GLM detected differences (FSL4.1). The coeffD analysis revealed markedly higher variability within the FSL4.1 stream both for the inter- and the intra-scanner comparison. A lowered bias cutoff (30 mm FWHM) in SPM8 improved the comparability for cortical areas. Intra-scanner scan/re-scan differences were generally weaker and did not exceed a p<0.05 (FWE corrected) threshold in the GLM analysis. At 3T profound inter-scanner differences are to be expected that could severely confound an unbalanced VBM analysis. These are like related to the receive bias of the radio-frequency hardware.

Hippocampal activation correlates with visual confrontation naming: fMRI findings in controls and patients with temporal lobe epilepsy

Summary Purpose In patients with left temporal lobe epilepsy (TLE) due to hippocampal sclerosis (HS) decreased naming ability is common, suggesting a critical role for the medial left temporal lobe in this task. We investigated the integrity of language networks with functional MRI (fMRI) in controls and TLE patients. Experimental design We performed an fMRI verbal fluency paradigm in 22 controls and 66 patients with unilateral mesial TLE (37 left HS, 29 right HS). Verbal fluency and naming ability were investigated as part of the standard presurgical neuropsychological assessment. Naming ability was assessed using a visual confrontation naming test. Results Left TLE patients had significantly lower naming scores than controls and those with right TLE. Right TLE patients performed less well than controls, but better than those with left TLE. Left TLE had significantly lower scores for verbal fluency than controls. In controls and right TLE, left hippocampal activation during the verbal fluency task was significantly correlated with naming, characterised by higher scores in subjects with greater hippocampal fMRI activation. In left TLE no correlation with naming scores was seen in the left hippocampus, but there was a significant correlation in the left middle and inferior frontal gyri, not observed in controls and right TLE. In left and right TLE, out of scanner verbal fluency scores significantly correlated with fMRI activation for verbal fluency in the left middle and inferior frontal gyri. Conclusion Good confrontation naming ability depends on the integrity of the hippocampus and the connecting fronto-temporal networks. Functional MRI activation in the left hippocampus during verbal fluency is associated with naming function in healthy controls and patients with right TLE. In left TLE, there was evidence of involvement of the left frontal lobe when naming was more proficient, most likely reflecting a compensatory response due to the ongoing epileptic activity and/or underlying pathology.