Hans-Peter Müller

The contribution of white and gray matter differences to developmental dyslexia : Insights from DTI and VBM at 3.0 T

Developmental dyslexia is one of the most common neuropsychological disorders in children and adults. Only few data are available on the pathomechanisms of this specific dysfunction, assuming--among others--that dyslexia might be a disconnection syndrome of anterior and posterior brain regions involved in phonological and orthographic aspects of the reading process, as well as in the integration of phonemes and graphemes. Therefore, diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) were used to verify the hypothesis of altered white and gray matter structure in German dyslexic adults. DTI revealed decreased fractional anisotropy (FA) in bilateral fronto-temporal and left temporo-parietal white matter regions (inferior and superior longitudinal fasciculus). Significant correlations between white matter anisotropy and speed of pseudoword reading were found. In dyslexics, gray matter volumes (as measured by VBM) were reduced in the superior temporal gyrus of both hemispheres. So far, our results, based on a combined analysis of white and gray matter abnormalities, provide exceedingly strong evidence for a disconnection syndrome or dysfunction of cortical areas relevant for reading and spelling. Thus, we suggest that this imbalance of neuronal communication between the respective brain areas might be the crucial point for the development of dyslexia.

Diffusion tensor imaging analysis of sequential spreading of disease in amyotrophic lateral sclerosis confirms patterns of TDP-43 pathology.

Diffusion tensor imaging can identify amyotrophic lateral sclerosis-associated patterns of brain alterations at the group level. Recently, a neuropathological staging system for amyotrophic lateral sclerosis has shown that amyotrophic lateral sclerosis may disseminate in a sequential regional pattern during four disease stages. The objective of the present study was to apply a new methodological diffusion tensor imaging-based approach to automatically analyse in vivo the fibre tracts that are prone to be involved at each neuropathological stage of amyotrophic lateral sclerosis. Two data samples, consisting of 130 diffusion tensor imaging data sets acquired at 1.5 T from 78 patients with amyotrophic lateral sclerosis and 52 control subjects; and 55 diffusion-tensor imaging data sets at 3.0 T from 33 patients with amyotrophic lateral sclerosis and 22 control subjects, were analysed by a tract of interest-based fibre tracking approach to analyse five tracts that become involved during the course of amyotrophic lateral sclerosis: the corticospinal tract (stage 1); the corticorubral and the corticopontine tracts (stage 2); the corticostriatal pathway (stage 3); the proximal portion of the perforant path (stage 4); and two reference pathways. The statistical analyses of tracts of interest showed differences between patients with amyotrophic lateral sclerosis and control subjects for all tracts. The significance level of the comparisons at the group level was lower, the higher the disease stage with corresponding involved fibre tracts. Both the clinical phenotype as assessed by the amyotrophic lateral sclerosis functional rating scale-revised and disease duration correlated significantly with the resulting staging scheme. In summary, the tract of interest-based technique allowed for individual analysis of predefined tract structures, thus making it possible to image in vivo the disease stages in amyotrophic lateral sclerosis. This approach can be used not only for individual clinical work-up purposes, but enlarges the spectrum of potential non-invasive surrogate markers as a neuroimaging-based read-out for amyotrophic lateral sclerosis studies within a clinical context.

Cerebral white matter alterations in idiopathic restless legs syndrome, as measured by diffusion tensor imaging

In search for the pathoanatomical correlate of the restless legs syndrome (RLS), various neuroimaging and electrophysiological techniques have demonstrated partly conflicting results of cortical, subcortical, brainstem, and spinal alterations. In a novel approach, the delineation of potential cerebral white matter tract disruption was investigated by application of quantitative whole brain‐based diffusion tensor imaging (DTI) to a well characterized group of 45 patients with idiopathic RLS. The data of patients and 30 healthy controls were statistically compared including computation of regional fractional anisotropy (FA) as a quantitative marker of white matter integrity by use of the tensor imaging and fiber tracking software. In the patient group, multiple subcortical areas of significantly reduced FA were observed bihemispherically in close proximity to the primary and associate motor and somatosensory cortices, in the right‐hemispheric thalamus (posterior ventral lateral nucleus), in motor projectional fibers and adjacent to the left anterior cingulum. Together with the results of a recent study by use of an MRI‐based gray matter analysis, which localized RLS‐associated changes in the sensorimotor cortices, these findings gave support to an altered subcortical network, with the major component of altered cerebral sensorimotor pathways, within a hodological concept of the RLS pathoanatomy.

Quantification of human body fat tissue percentage by MRI

The MRI‐based evaluation of the quantity and regional distribution of adipose tissue is one objective measure in the investigation of obesity. The aim of this article was to report a comprehensive and automatic analytical method for the determination of the volumes of subcutaneous fat tissue (SFT) and visceral fat tissue (VFT) in either the whole human body or selected slices or regions of interest. Using an MRI protocol in an examination position that was convenient for volunteers and patients with severe diseases, 22 healthy subjects were examined. The software platform was able to merge MRI scans of several body regions acquired in separate acquisitions. Through a cascade of image processing steps, SFT and VFT volumes were calculated. Whole‐body SFT and VFT distributions, as well as fat distributions of defined body slices, were analysed in detail. Complete three‐dimensional datasets were analysed in a reproducible manner with as few operator‐dependent interventions as possible. In order to determine the SFT volume, the ARTIS (Adapted Rendering for Tissue Intensity Segmentation) algorithm was introduced. The advantage of the ARTIS algorithm was the delineation of SFT volumes in regions in which standard region grow techniques fail. Using the ARTIS algorithm, an automatic SFT volume detection was feasible. MRI data analysis was able to determine SFT and VFT volume percentages using new analytical strategies. With the techniques described, it was possible to detect changes in SFT and VFT percentages of the whole body and selected regions. The techniques presented in this study are likely to be of use in obesity‐related investigations, as well as in the examination of longitudinal changes in weight during various medical conditions. Copyright

Neuroanatomical patterns of cerebral white matter involvement in different motor neuron diseases as studied by diffusion tensor imaging analysis

Abstract This study was designed to investigate differences of white matter (WM) involvement patterns in various motor neuron disorders (MND) by use of diffusion tensor imaging (DTI).DTI was acquired in ALS (n = 20), primary lateral sclerosis (n = 20), pure hereditary spastic paraparesis (HSP) (n = 20), and complicated HSP (n = 12). The data analysis was performed by voxelwise comparison of fractional anisotropy (FA) maps at group level together with fibre tracking in regions of interest (ROI) accompanied by tractwise fractional anisotropy statistics. DTI analysis revealed widespread patterns of alterations with a predominant deterioration of the motor system. These alterations encompassed, as the key structures, not only the corticospinal tracts (CST) but also distinct areas of the corpus callosum (CC), in particular its motor segment III. In conclusion, whole brain-based and tract-based DTI analysis was able to define a distinct WM pathoanatomy of different MND. These results may serve as an additional guidance in the identification of MRI-based parameters by showing a consistent CST and CC involvement, with differences in the extent of pathology, across a range of clinically different disorders. For potential future developments in MRI diagnostics in MND, a (perhaps multiparametric) ROI-based approach should include CST and the CC motor segment.

Retinal single-layer analysis in Parkinsonian syndromes: an optical coherence tomography study

We report a newly developed analysis algorithm for optical coherence tomography (OCT) that makes a retinal single-layer analysis with calculation of the average thickness of retinal layers possible. The aim of the study was to examine specific patterns of retinal layer pathology as a potential marker of neurodegeneration in Parkinson’s disease (PD), progressive supranuclear palsy (PSP), and multiple system atrophy (MSA). Spectral domain OCT with a semiautomatic algorithm to calculate the average thickness of single retinal layers was applied to foveal scans of 65 PD, 16 PSP, and 12 MSA patients as well as 41 matched controls. Demographic and clinical data were collected for correlation analysis. Only PSP and MSA showed a significant reduction of retinal layers in comparison to controls. In PD, there were no significant findings in single retinal layer measurement. Most remarkably, the thickening of the outer nuclear layer in PSP and the outer plexiform layer in MSA was highly specific for these disease entities and allowed differentiating PSP from MSA with high sensitivity and specificity. With this analysis algorithm of OCT data, disease-specific retinal layer changes could be observed. Despite a general tendency to whole retinal and single retinal layer thinning that may reflect neurodegeneration in all Parkinsonian syndromes, the specific findings in MSA and PSP may serve as a highly sensitive and specific differential diagnostic tool and as a progression marker in these disease entities. Upcoming studies with a longitudinal setting will have to prove this assumption.

Adipose Tissue Distribution Predicts Survival in Amyotrophic Lateral Sclerosis.

Background amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that leads to death within a few years after diagnosis. Malnutrition and weight loss are frequent and are indexes of poor prognosis. Total body fat and fat distribution have not been studied in ALS patients. Objectives Our aim was to describe adipose tissue content and distribution in ALS patients. Design We performed a cross-sectional study in a group of ALS patients (n = 62, mean disease duration 22 months) along with age and gender matched healthy controls (n = 62) using a MRI-based method to study quantitatively the fat distribution. Results Total body fat of ALS patients was not changed as compared with controls. However, ALS patients displayed increased visceral fat and an increased ratio of visceral to subcutaneous fat. Visceral fat was not correlated with clinical severity as judged using the ALS functional rating scale (ALS-FRS-R), while subcutaneous fat in ALS patients correlated positively with ALS-FRS-R and disease progression. Multiple regression analysis showed that gender and ALS-FRS-R, but not site of onset, were significant predictors of total and subcutaneous fat. Increased subcutaneous fat predicted survival in male patients but not in female patients (p<0.05). Conclusions Fat distribution is altered in ALS patients, with increased visceral fat as compared with healthy controls. Subcutaneous fat content is a predictor of survival of ALS patients.

Intersubject variability in the analysis of diffusion tensor images at the group level: fractional anisotropy mapping and fiber tracking techniques

INTRODUCTION Diffusion tensor imaging (DTI) provides comprehensive information about quantitative diffusion and connectivity in the human brain. Transformation into stereotactic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The objective of the present study was to optimize technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. METHODS Different averaging methods for mean diffusion-weighted images containing DTI information were compared, i.e., region of interest-based fractional anisotropy (FA) mapping, fiber tracking (FT) and corresponding tractwise FA statistics (TFAS). The novel technique of intersubject FT that takes into account directional information of single data sets during the FT process was compared to standard FT techniques. Application of the methods was shown in the comparison of normal subjects and subjects with defined white matter pathology (alterations of the corpus callosum). RESULTS Fiber tracking was applied to averaged data sets and showed similar results compared with FT on single subject data. The application of TFAS to averaged data showed averaged FA values around 0.4 for normal controls. The values were in the range of the standard deviation for averaged FA values for TFAS applied to single subject data. These results were independent of the applied averaging technique. A significant reduction of the averaged FA values was found in comparison to TFAS applied to data from subjects with defined white matter pathology (FA around 0.2). CONCLUSION The applicability of FT techniques in the analysis of different subjects at the group level was demonstrated. Group comparisons as well as FT on group averaged data were shown to be feasible. The objective of this work was to identify the most appropriate method for intersubject averaging and group comparison which incorporates intersubject variability of the directional information.

Stability of white matter changes related to Huntington's disease in the presence of imaging noise: a DTI study

Movement artifacts and other sources of noise are a matter of concern particularly in the neuroimaging research of movement disorders such as Huntington’s disease (HD). Using diffusion weighted imaging (DWI) and fractional anisotropy (FA) as a compound marker of white matter integrity, we investigated the effect of movement on HD specific changes in magnetic resonance imaging (MRI) data and how post hoc compensation for it affects the MRI results. To this end, we studied by 3T MRI: 18 early affected, 22 premanifest gene-positive subjects, 23 healthy controls (50 slices of 2.3 mm thickness per volume, 64 diffusion-weighted directions (b = 1000 s/mm2), 8 minimal diffusion-weighting (b = 100 s/mm2)); and by 1.5 T imaging: 29 premanifest HD, 30 controls (40 axial slices of 2.3 mm thickness per volume, 61 diffusion-weighted directions (b = 1000 s/mm2), minimal diffusion-weighting (b = 100 s/mm2)). An outlier based method was developed to identify movement and other sources of noise by comparing the index DWI direction against a weighted average computed from all other directions of the same subject. No significant differences were observed when separately comparing each group of patients with and without removal of DWI volumes that contained artifacts. In line with previous DWI-based studies, decreased FA in the corpus callosum and increased FA around the basal ganglia were observed when premanifest mutation carriers and early affected patients were compared with healthy controls. These findings demonstrate the robustness of the FA value in the presence of movement and thus encourage multi-center imaging studies in HD.

Evaluating multicenter DTI data in Huntington's disease on site specific effects: An ex post facto approach☆

Purpose Assessment of the feasibility to average diffusion tensor imaging (DTI) metrics of MRI data acquired in the course of a multicenter study. Materials and methods Sixty-one early stage Huntingtons disease patients and forty healthy controls were studied using four different MR scanners at four European sites with acquisition protocols as close as possible to a given standard protocol. The potential and feasibility of averaging data acquired at different sites was evaluated quantitatively by region-of-interest (ROI) based statistical comparisons of coefficients of variation (CV) across centers, as well as by testing for significant group-by-center differences on averaged fractional anisotropy (FA) values between patients and controls. In addition, a whole-brain based statistical between-group comparison was performed using FA maps. Results The ex post facto statistical evaluation of CV and FA-values in a priori defined ROIs showed no differences between sites above chance indicating that data were not systematically biased by center specific factors. Conclusion Averaging FA-maps from DTI data acquired at different study sites and different MR scanner types does not appear to be systematically biased. A suitable recipe for testing on the possibility to pool multicenter DTI data is provided to permit averaging of DTI-derived metrics to differentiate patients from healthy controls at a larger scale.