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

Temporal and spatial progression of microstructural cerebral degeneration in ALS: A multicentre longitudinal diffusion tensor imaging study

OBJECTIVE

The corticospinal tract (CST) reveals progressive microstructural alterations in ALS measurable by DTI. The aim of this study was to evaluate fractional anisotropy (FA) along the CST as a longitudinal marker of disease progression in ALS.

METHODS

The study cohort consisted of 114 patients with ALS and 110 healthy controls from the second prospective, longitudinal, multicentre study of the Canadian ALS Neuroimaging Consortium (CALSNIC-2). DTI and clinical data from a harmonized protocol across 7 centres were collected. Thirty-nine ALS patients and 61 controls completed baseline and two follow-up visits and were included for longitudinal analyses. Whole brain-based spatial statistics and hypothesis-guided tract-of-interest analyses were performed for cross-sectional and longitudinal analyses.

RESULTS

FA was reduced at baseline and longitudinally in the CST, mid-corpus callosum (CC), frontal lobe, and other ALS-related tracts, with alterations most evident in the CST and mid-CC. CST and pontine FA correlated with functional impairment (ALSFRS-R), upper motor neuron function, and clinical disease progression rate. Reduction in FA was largely located in the upper CST; however, the longitudinal decline was greatest in the lower CST. Effect sizes were dependent on region, resulting in study group sizes between 17 and 31 per group over a 9-month interval. Cross-sectional effect sizes were maximal in the upper CST; whereas, longitudinal effect sizes were maximal in mid-callosal tracts.

CONCLUSIONS

Progressive microstructural alterations in ALS are most prominent in the CST and CC. DTI can provide a biomarker of cerebral degeneration in ALS, with longitudinal changes in white matter demonstrable over a reasonable observation period, with a feasible number of participants, and within a multicentre framework.

Neurodegeneration or dysfunction in Phelan-McDermid syndrome? A multimodal approach with CSF and computational MRI

BACKGROUND

Phelan-McDermid syndrome (PMS) is a rare multisystem disease with global developmental delay and autistic features. Genetically, the disease is based on a heterozygous deletion of chromosome 22q13.3 with involvement of at least part of the SHANK3 gene or heterozygous pathogenic variants in SHANK3. Pathophysiologically, this syndrome has been regarded as a synaptopathy, but current data suggest an additional concept, since axonal functions of neurons are also impaired, thus, the specific pathophysiological processes in this disease are not yet fully understood. Since symptoms of the autism spectrum, regression, and stagnation in development occur, we investigated whether neuroinflammatory and neurodegenerative processes may also play a role. To this end, we analysed biomarkers in cerebrospinal fluid (CSF) and parameters from magnetic resonance imaging with high-resolution structural T1w volumetry and diffusion tensor imaging analysis in 19 Phelan-McDermid syndrome patients.

RESULTS

CSF showed no inflammation but abnormalities in tau protein and amyloid-ß concentrations, however, with no typical biomarker pattern as in Alzheimer's disease. It could be demonstrated that these CSF changes were correlated with integrity losses of the fibres in the corticospinal tract as well as in the splenium and dorsal part of the cingulum. High CSF levels of tau protein were associated with loss of integrity of fibres in the corticospinal tract; lower levels of amyloid-ß were associated with decreasing integrity of fibre tracts of the splenium and posterior cingulate gyrus. Volumetric investigations showed global atrophy of the white matter, but not the grey matter, and particularly not in temporal or mesiotemporal regions, as is typical in later stages of Alzheimer's disease.

CONCLUSIONS

In summary, alterations of neurodegenerative CSF markers in PMS individuals could be demonstrated which were correlated with structural connectivity losses of the corticospinal tract, the splenium, and the dorsal part of the cingulum, which can also be associated with typical clinical symptoms in these patients. These findings might represent a state of dysfunctional processes with ongoing degenerative and regenerative processes or a kind of accelerated aging. This study should foster further clinical diagnostics like tau- and amyloid-PET imaging as well as novel scientific approaches especially in basic research for further mechanistic proof.

Sequential alterations in diffusion metrics as correlates of disease severity in amyotrophic lateral sclerosis

BACKGROUND AND OBJECTIVE

The neuropathology of amyotrophic lateral sclerosis (ALS) follows a regional distribution pattern in the brain with four stages. Using diffusion tensor imaging (DTI), this pattern can be translated into a tract-based staging scheme to assess cerebral progression in vivo. This study investigates the association between the sequential alteration pattern and disease severity in patients with ALS.

METHODS

DTI data of 325 patients with ALS and 130 healthy controls were analyzed in a tract of interest (TOI)-based approach. Patients were categorized according to their ALS-FRS-R scores into groups with declining functionality. The fractional anisotropy (FA) values in the tracts associated with neuropathological stages were group-wise compared with healthy controls.

RESULTS

The FA in the tracts associated with ALS stages showed a decrease which could be related to the disease severity stratification, i.e., at the group level, the lower the ALS-FRS-R of the categorized patient group, the higher was the effect size of the stage-related tract. In the patient group with the highest ALS-FRS-R, Cohen's d showed a medium effect size in the corticospinal tract and small effect sizes in the other stage-related tracts. Overall, the lower the ALS-FRS-R of the categorized patient group the higher was the effect size of the comparison with healthy controls.

CONCLUSION

The progression of white matter alterations across tracts according to the model of sequential tract involvement is associated with clinical disease severity in patients with ALS, suggesting the use of staging-based DTI as a technical marker for disease progression.

Artificial neural networks for non-linear age correction of diffusion metrics in the brain

Human aging is characterized by progressive loss of physiological functions. To assess changes in the brain that occur with increasing age, the concept of brain aging has gained momentum in neuroimaging with recent advancements in statistical regression and machine learning (ML). A common technique to assess the brain age of a person is, first, fitting a regression model to neuroimaging data from a group of healthy subjects, and then, using the resulting model for age prediction. Although multiparametric MRI-based models generally perform best, models solely based on diffusion tensor imaging have achieved similar results, with the benefits of faster data acquisition and better replicability across scanners and field strengths. In the present study, we developed an artificial neural network (ANN) for brain age prediction based upon tract-based fractional anisotropy (FA). Consequently, we investigated if this age-prediction model could also be used for non-linear age correction of white matter diffusion metrics in healthy adults. The brain age prediction accuracy of the ANN (R 2 = 0.47) was similar to established multimodal models. The comparison of the ANN-based age-corrected FA with the tract-wise linear age-corrected FA resulted in an R 2 value of 0.90 [0.82; 0.93] and a mean difference of 0.00 [-0.04; 0.05] for all tract systems combined. In conclusion, this study demonstrated the applicability of complex ANN models to non-linear age correction of tract-based diffusion metrics as a proof of concept.

Longitudinal monitoring of amyotrophic lateral sclerosis by diffusion tensor imaging: Power calculations for group studies

Introduction

Diffusion tensor imaging (DTI) can be used to map disease progression in amyotrophic lateral sclerosis (ALS) and therefore is a promising candidate for a biomarker in ALS. To this end, longitudinal study protocols need to be optimized and validated regarding group sizes and time intervals between visits. The objective of this study was to assess the influences of sample size, the schedule of follow-up measurements, and measurement uncertainties on the statistical power to optimize longitudinal DTI study protocols in ALS.

Patients and methods

To estimate the measurement uncertainty of a tract-of–interest-based DTI approach, longitudinal test-retest measurements were applied first to a normal data set. Then, DTI data sets of 80 patients with ALS and 50 healthy participants were analyzed in the simulation of longitudinal trajectories, that is, longitudinal fractional anisotropy (FA) values for follow-up sessions were simulated for synthetic patient and control groups with different rates of FA decrease in the corticospinal tract. Monte Carlo simulations of synthetic longitudinal study groups were used to estimate the statistical power and thus the potentially needed sample sizes for a various number of scans at one visit, different time intervals between baseline and follow-up measurements, and measurement uncertainties.

Results

From the simulation for different longitudinal FA decrease rates, it was found that two scans per session increased the statistical power in the investigated settings unless sample sizes were sufficiently large and time intervals were appropriately long. The positive effect of a second scan per session on the statistical power was particularly pronounced for FA values with high measurement uncertainty, for which the third scan per session increased the statistical power even further.

Conclusion

With more than one scan per session, the statistical power of longitudinal DTI studies can be increased in patients with ALS. Consequently, sufficient statistical power can be achieved even with limited sample sizes. An improved longitudinal DTI study protocol contributes to the detection of small changes in diffusion metrics and thereby supports DTI as an applicable and reliable non-invasive biomarker in ALS.

A multivariate Bayesian classification algorithm for cerebral stage prediction by diffusion tensor imaging in amyotrophic lateral sclerosis

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Novel DTI-based classification of ALS disease stages by a Bayesian approach is applied.

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Bayesian classification algorithm improves threshold-based staging method.

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Step forward in MRI-based patient stratification in ALS in vivo.

Background and Objective

Diffusion tensor imaging (DTI) can be used to tract-wise map correlates of the sequential disease progression and, therefore, to assess disease stages of amyotrophic lateral sclerosis (ALS) in vivo. According to a threshold-based sequential scheme, a classification of ALS patients into disease stages is possible, however, several patients cannot be staged for methodological reasons. This study aims to implement a multivariate Bayesian classification algorithm for disease stage prediction at an individual ALS patient level based on DTI metrics of involved tract systems to improve disease stage mapping.

Methods

The analysis of fiber tracts involved in each stage of ALS was performed in 325 ALS patients and 130 age- and gender-matched healthy controls. Based on Bayes’ theorem and in accordance with the sequential disease progression, a multistage classifier was implemented. Patients were categorized into in vivo DTI stages using the threshold-based method and the Bayesian algorithm. By the margin of confidence, the reliability of the Bayesian categorizations was accessible.

Results

Based on the Bayesian multistage classifier, 88% of all ALS patients could be assigned into an ALS stage compared to 77% using the threshold-based staging scheme. Additionally, the confidence of all classifications could be estimated.

Conclusions

By the application of the multi-stage Bayesian classifier, an individualized in vivo cerebral staging of ALS patients was possible based on the sequentially involved tract systems and, furthermore, the reliability of the respective classifications could be determined. The Bayesian classification algorithm is an improvement of the threshold-based staging method and could provide a framework for extending the DTI-based in vivo cerebral staging in ALS.

Multimodal in vivo staging in amyotrophic lateral sclerosis using artificial intelligence

Background

The underlying neuropathological process of amyotrophic lateral sclerosis (ALS) can be classified in a four‐stage sequential pTDP‐43 cerebral propagation scheme. Using diffusion tensor imaging (DTI), in vivo imaging of these stages has already been shown to be feasible for the specific corticoefferent tract systems. Because both cognitive and oculomotor dysfunctions are associated with microstructural changes at the brain level in ALS, a cognitive and an oculomotor staging classification were developed, respectively. The association of these different in vivo staging schemes has not been attempted to date.

Methods

A total of 245 patients with ALS underwent DTI, video‐oculography, and cognitive testing using Edinburgh Cognitive and Behavioral ALS Screen (ECAS). A set of tract‐related diffusion metrics, cognitive, and oculomotor parameters was selected for further analysis. Hierarchical and k‐means clustering algorithms were used to obtain an optimal cluster solution.

Results

According to cluster analysis, differentiation of patients with ALS into four clusters resulted: Cluster A showed the highest fractional anisotropy (FA) values and thereby the best performances in executive oculomotor tasks and cognitive tests, whereas cluster D showed the lowest FA values, the lowest ECAS scores, and the worst executive oculomotor performance across all clusters. Clusters B and C showed intermediate results regarding parameter values.

Discussion

In a multimodal dataset of technical assessments of brain structure and function in ALS, an artificial intelligence‐based cluster analysis showed high congruence of DTI, executive oculomotor function, and neuropsychological performance for mapping in vivo correlates of neuropathological spreading.

Segmental Alterations of the Corpus Callosum in Progressive Supranuclear Palsy: A Multiparametric Magnetic Resonance Imaging Study

Background: The regional distribution of the widespread cerebral morphological alterations in progressive supranuclear palsy (PSP) is considered to include segmental parts of the corpus callosum (CC). Objective: The study was designed to investigate the regional white matter (WM) of the CC by T1 weighted magnetic resonance imaging (T1w MRI) data combined with diffusion tensor imaging (DTI) data in PSP patients, differentiated in the variants Richardson syndrome and PSP-parkinsonism, and to compare them with Parkinson's Disease (PD) patients and healthy controls, in order to identify macro- and micro-structural alterations in vivo. Methods: MRI-based WM mapping was used to perform an operator-independent segmentation for the different CC segments in 66 PSP patients vs. 66 PD patients vs. 44 matched healthy controls. The segmentation was followed by both planimetric and texture analysis of the separated CC areas for the comparison of the three groups. Results were complemented by a DTI-based tract-of-interest analysis of the associated callosal tracts. Results: Significant alterations of the parameters entropy and homogeneity compared to controls were observed for PSP as well as for PD for the CC areas I, II, and III. The inhomogeneity in area II in the PSP cohort was the highest and differed significantly from PD. A combined score was defined as a potential marker for the different types of neurodegenerative parkinsonism; receiver operating characteristics (ROC) curves were calculated with areas under the curve values of 0.86 for PSP vs. controls, 0.72 for PD vs. controls, and 0.69 for PSP vs. PD, respectively. Conclusion: The multiparametric MRI texture and DTI analysis demonstrated extensive alterations of the frontal CC in neurodegenerative parkinsonism, whereas regional CC atrophy cannot be regarded as a constant neuroimaging feature of PSP. Specifically, the comparison PSP vs. PD revealed significant alterations in callosal area II. The combination of the texture and the DTI parameters might contribute as a neuroimaging marker for the assessment of the CC in PSP, including the differentiation vs. PD.

Age-Related Alterations in DTI Metrics in the Human Brain-Consequences for Age Correction

Background: Over the life span, the diffusion metrics in brain MRI show different, partly nonlinear changes. These age-dependent changes also seem to exhibit regional differences with respect to the brain anatomy. The age correction of a study cohort's diffusion metrics might thus require consideration of age-related factors. Methods: Diffusion tensor imaging data sets were acquired from 219 healthy participants at ages between 19 and 81 years. Fractional anisotropy (FA), mean diffusivity (MD), and axial and radial diffusivity (AD and RD, respectively) maps were analyzed by a tract of interest-based fiber tracking approach. To describe diffusion metrics as a function of the participant age, linear splines were used to perform curve fitting in 21 specific tract systems covering different functional areas and diffusion directions. Results: In the majority of tracts, an interpolation with a change of alteration rate during adult life described the diffusion properties more accurately than a linear model. Consequently, the diffusion properties remained relatively stable until a decrease (of FA) or increase (of MD, AD, and RD) started at a region-specific time point, whereas a uniform change of diffusion properties was observed only in a few tracts. Single tracts, e.g., located in the cerebellum, remained nearly unaltered throughout the ages between 19 and 81 years. Conclusions: Age corrections of diffusion properties should not be applied to all white matter regions and all age spans in the same way. Therefore, we propose three different approaches for age correction based on fiber tracking techniques, i.e., no correction for areas that do not experience age-related changes and two variants of an age correction depending on the age range of the cohort and the tracts considered.

Segmental involvement of the corpus callosum in C9orf72-associated ALS: a tract of interest-based DTI study

Background:

C9orf72 hexanucleotide repeat expansions are associated with widespread cerebral alterations, including white matter alterations. However, there is lack of information on changes in commissure fibres. Diffusion tensor imaging (DTI) can identify amyotrophic lateral sclerosis (ALS)-associated patterns of regional brain alterations at the group level. The objective of this study was to investigate the structural connectivity of the corpus callosum (CC) in ALS patients with C9orf72 expansions.

Methods:

DTI-based white matter mapping was performed by a hypothesis-guided tractwise analysis of fractional anisotropy (FA) maps for 25 ALS patients with C9orf72 expansion versus 25 matched healthy controls. Furthermore, a comparison with a patient control group of 25 sporadic ALS patients was performed. DTI-based tracts that originate from callosal sub-areas I to V were identified and correlated with clinical data.

Results:

The analysis of white matter integrity demonstrated regional FA reductions for tracts of the callosal areas II and III for ALS patients with C9orf72 expansions while FA reductions in sporadic ALS patients were observed only for tracts of the callosal area III; these reductions were correlated with clinical parameters.

Conclusion:

The tract-of-interest-based analysis showed a microstructural callosal involvement pattern in C9orf72-associated ALS that included the motor segment III together with frontal callosal connections, as an imaging signature of the C9orf72-associated overlap of motor neuron disease and frontotemporal pathology.

A prospective harmonized multicenter DTI study of cerebral white matter degeneration in ALS

OBJECTIVE

To evaluate progressive white matter (WM) degeneration in amyotrophic lateral sclerosis (ALS).

METHODS

Sixty-six patients with ALS and 43 healthy controls were enrolled in a prospective, longitudinal, multicenter study in the Canadian ALS Neuroimaging Consortium (CALSNIC). Participants underwent a harmonized neuroimaging protocol across 4 centers that included diffusion tensor imaging (DTI) for assessment of WM integrity. Three visits were accompanied by clinical assessments of disability (ALS Functional Rating Scale-Revised [ALSFRS-R]) and upper motor neuron (UMN) function. Voxel-wise whole-brain and quantitative tract-wise DTI assessments were done at baseline and longitudinally. Correction for site variance incorporated data from healthy controls and from healthy volunteers who underwent the DTI protocol at each center.

RESULTS

Patients with ALS had a mean progressive decline in fractional anisotropy (FA) of the corticospinal tract (CST) and frontal lobes. Tract-wise analysis revealed reduced FA in the CST, corticopontine/corticorubral tract, and corticostriatal tract. CST FA correlated with UMN function, and frontal lobe FA correlated with the ALSFRS-R score. A progressive decline in CST FA correlated with a decline in the ALSFRS-R score and worsening UMN signs. Patients with fast vs slow progression had a greater reduction in FA of the CST and upper frontal lobe.

CONCLUSIONS

Progressive WM degeneration in ALS is most prominent in the CST and frontal lobes and, to a lesser degree, in the corticopontine/corticorubral tracts and corticostriatal pathways. With the use of a harmonized imaging protocol and incorporation of analytic methods to address site-related variances, this study is an important milestone toward developing DTI biomarkers for cerebral degeneration in ALS.

CLINICALTRIALSGOV IDENTIFIER

NCT02405182.

In vivo histopathological staging in C9orf72-associated ALS: A tract of interest DTI study

BACKGROUND

Diffusion tensor imaging (DTI) can identify amyotrophic lateral sclerosis (ALS)-associated patterns of brain alterations at the group level according to a neuropathological staging system.

OBJECTIVE

The study was designed to investigate the in vivo staging in ALS patients with the C9orf72 expansion and potential differences to ALS patients with the SOD1 mutation.

METHODS

DTI-based white matter mapping was performed both by an unbiased voxel-wise statistical comparison and by a hypothesis-guided tract-wise analysis of fractional anisotropy (FA) maps according to the ALS-staging pattern for 27 ALS patients with C9orf72 expansion vs 15 ALS patients with SOD1 mutation vs 32 matched healthy controls. Clinical and neuropsychological data were acquired and correlated to DTI data.

RESULTS

The analysis of white matter integrity demonstrated regional FA reductions along the CST and also in frontal and prefrontal brain areas according to the proposed propagation pattern for the ALS patients with C9orf72 expansion and sporadic patients. This pattern could not be identified for the SOD1 mutation at the group level. In contrast, in the tract-specific analysis according to the neuropathological ALS-staging pattern, C9orf72 expansion ALS patients showed significant alterations of ALS-related tract systems similar to sporadic patients.

CONCLUSIONS

The DTI study including the tract-of-interest-based analysis showed a microstructural corticoefferent involvement pattern according to the staging scheme in C9orf72-associated ALS patients but not in the SOD1 mutation.

Advanced neuroimaging approaches in amyotrophic lateral sclerosis: refining the clinical diagnosis

Introduction: In the last decade, multiparametric magnetic resonance imaging (MRI) has achieved tremendous advances in applications to amyotrophic lateral sclerosis (ALS) to increase the understanding of the associated pathophysiology. The aim of this review is to summarize recent progress in the development of MRI-based techniques aiming to support the clinical diagnosis in ALS.Areas covered: The review of structural and functional MRI applications to ALS and its variants (restricted phenotypes) is focused on the potential of MRI techniques which contribute to the diagnostic work-up of patients with the clinical presentation of a motor neuron disease. The potential of specific MRI methods for patient diagnosis and monitoring is discussed, and the future design of clinical MRI applications to ALS is conceptualized.Expert opinion: Current multiparametric MRI allows for the use as a clinical biological marker and a technical instrument in the clinical diagnosis of patients with ALS and also of patients with ALS variants. Composite neuroimaging indices of specific anatomical areas derived from different MRI techniques might guide in the diagnostic applications to ALS. Such a development of ALS-specific MRI-based composite scores with sufficient discriminative power versus ALS mimics at an individual level requires standardized advanced protocols and comprehensive analysis approaches.

Severe white matter damage in SHANK3 deficiency: a human and translational study

Objective

Heterozygous SHANK3 mutations or partial deletions of the long arm of chromosome 22, also known as Phelan–McDermid syndrome, result in a syndromic form of the autism spectrum as well as in global developmental delay, intellectual disability, and several neuropsychiatric comorbidities. The exact pathophysiological mechanisms underlying the disease are still far from being deciphered but studies of SHANK3 models have contributed to the understanding of how the loss of the synaptic protein SHANK3 affects neuronal function.

Methods and results

Diffusion tensor imaging‐based and automatic volumetric brain mapping were performed in 12 SHANK3‐deficient participants (mean age 19 ± 15 years) versus 14 age‐ and gender‐matched controls (mean age 29 ± 5 years). Using whole brain–based spatial statistics, we observed a highly significant pattern of white matter alterations in participants with SHANK3 mutations with focus on the long association fiber tracts, particularly the uncinate tract and the inferior fronto‐occipital fasciculus. In contrast, only subtle gray matter volumetric abnormalities were detectable. In a back‐translational approach, we observed similar white matter alterations in heterozygous isoform–specific Shank3 knockout (KO) mice. Here, in the baseline data sets, the comparison of Shank3 heterozygous KO vs wildtype showed significant fractional anisotropy reduction of the long fiber tract systems in the KO model. The multiparametric Magnetic Resonance Imaging (MRI) analysis by DTI and volumetry demonstrated a pathology pattern with severe white matter alterations and only subtle gray matter changes in the animal model.

Interpretation

In summary, these translational data provide strong evidence that the SHANK3‐deficiency–associated pathomechanism presents predominantly with a white matter disease. Further studies should concentrate on the role of SHANK3 during early axonal pathfinding/wiring and in myelin formation.

The same cortico-efferent tract involvement in progressive bulbar palsy and in 'classical' ALS: A tract of interest-based MRI study

Background

There is an ongoing debate about the concept of restricted phenotypes of amyotrophic lateral sclerosis (ALS), including progressive bulbar palsy (PBP).

Objective

The study was designed to investigate specific white matter alterations in diffusion tensor imaging (DTI) data from PBP patients using a hypothesis-guided tract-of-interest-based approach (compared with ‘classical’ ALS patients and controls) to identify in vivo microstructural changes according to the neuropathologically defined ALS-related corticoefferent tract pathology.

Methods

DTI-based white matter mapping was performed both by an unbiased voxel-wise statistical comparison and by a hypothesis-guided tract-wise analysis of fractional anisotropy (FA) maps according to the ALS-staging pattern for 23 PBP and 23 ALS patients vs 23 matched controls.

Results

The analysis of white matter integrity demonstrated regional FA reductions along the CST and also in frontal and prefrontal brain areas both in PBP patients and ALS patients with additional regional FA reduction in the pons of the PBP group. In the tract-specific analysis according to the neuropathological ALS-staging pattern, PBP and ALS patients showed identical significant alterations of ALS-related tract systems when compared with controls.

Conclusions

The DTI study including the tract-of-interest-based analysis showed the same microstructural corticoefferent involvement patterns in PBP patients as in ALS, which supports the hypothesis that PBP is a phenotypical variant of ALS.

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Neuropathological ALS-stages can be mapped in vivo in PBP.

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PBP but not classical ALS patients show regional FA reduction in the pons.

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This study supports the hypothesis that PBP is a phenotypical variant of ALS.

Imaging the pathoanatomy of amyotrophic lateral sclerosis in vivo: targeting a propagation-based biological marker

OBJECTIVE

Neuropathological studies in amyotrophic lateral sclerosis (ALS) have shown a dissemination in a regional sequence in four anatomically defined patterns. The aim of this retrospective study was to see whether longitudinal diffusion tensor imaging (DTI) data support the pathological findings.

METHODS

The application of DTI analysis to fibre structures that are prone to be involved at each neuropathological pattern of ALS was performed in a monocentre sample of 67 patients with ALS and 31 controls that obtained at least one follow-up scan after a median of 6 months.

RESULTS

At the group level, longitudinal ALS data showed significant differences for the stage-related tract systems. At the individual level, 27% of the longitudinally scanned patients with ALS showed an increase in ALS stage, while the remaining were stable or were at the highest ALS stage. Longitudinal fractional anisotropy changes in the respective tract systems correlated significantly with the slope of the revised ALS functional rating scale.

INTERPRETATION

The DTI-based protocol was able to image the disease patterns of ALS in vivo cross-sectionally and longitudinally, in support of DTI as a technical marker to image ALS stages.

Longitudinal Diffusion Tensor Imaging Resembles Patterns of Pathology Progression in Behavioral Variant Frontotemporal Dementia (bvFTD)

Objective: Recently, the characteristic longitudinal distribution pattern of the underlying phosphorylated TDP-43 (pTDP-43) pathology in the behavioral variant of frontotemporal dementia (bvFTD) excluding Pick's disease (PiD) across specific brain regions was described. The aim of the present study was to investigate whether in vivo investigations of bvFTD patients by use of diffusion tensor imaging (DTI) were consistent with these proposed patterns of progression.

Methods: Sixty-two bvFTD patients and 47 controls underwent DTI in a multicenter study design. Of these, 49 bvFTD patients and 34 controls had a follow-up scan after ~12 months. Cross-sectional and longitudinal alterations were assessed by a two-fold analysis, i.e., voxelwise comparison of fractional anisotropy (FA) maps and a tract of interest-based (TOI) approach, which identifies tract structures that could be assigned to brain regions associated with disease progression.

Results: Whole brain-based spatial statistics showed white matter alterations predominantly in the frontal lobes cross-sectionally and longitudinally. The TOIs of bvFTD neuroimaging stages 1 and 2 (uncinate fascicle—bvFTD pattern I; corticostriatal pathway—bvFTD pattern II) showed highly significant differences between bvFTD patients and controls. The corticospinal tract-associated TOI (bvFTD pattern III) did not differ between groups, whereas the differences in the optic radiation (bvFTD pattern IV) reached significance. The findings in the corticospinal tract were due to a “dichotomous” behavior of FA changes there.

Conclusion: Longitudinal TOI analysis demonstrated a pattern of white matter pathways alterations consistent with patterns of pTDP-43 pathology.

Longitudinal Diffusion Tensor Imaging-Based Assessment of Tract Alterations: An Application to Amyotrophic Lateral Sclerosis

Objective: The potential of magnetic resonance imaging (MRI) as a technical biomarker for cerebral microstructural alterations in neurodegenerative diseases is under investigation. In this study, a framework for the longitudinal analysis of diffusion tensor imaging (DTI)-based mapping was applied to the assessment of predefined white matter tracts in amyotrophic lateral sclerosis (ALS), as an example for a rapid progressive neurodegenerative disease.

Methods: DTI was performed every 3 months in six patients with ALS (mean (M) = 7.7; range 3 to 15 scans) and in six controls (M = 3; range 2–5 scans) with the identical scanning protocol, resulting in a total of 65 longitudinal DTI datasets. Fractional anisotropy (FA), mean diffusivity (MD), axonal diffusivity (AD), radial diffusivity (RD), and the ratio AD/RD were studied to analyze alterations within the corticospinal tract (CST) which is a prominently affected tract structure in ALS and the tract correlating with Braak’s neuropathological stage 1. A correlation analysis was performed between progression rates based on DTI metrics and the revised ALS functional rating scale (ALS-FRS-R).

Results: Patients with ALS showed an FA and AD/RD decline along the CST, while DTI metrics of controls did not change in longitudinal DTI scans. The FA and AD/RD decrease progression correlated significantly with ALS-FRS-R decrease progression.

Conclusion: On the basis of the longitudinal assessment, DTI-based metrics can be considered as a possible noninvasive follow-up marker for disease progression in neurodegeneration. This finding was demonstrated here for ALS as a fast progressing neurodegenerative disease.

Dynamic changes in diffusion measures improve sensitivity in identifying patients with mild traumatic brain injury

The goal of this study was to investigate patterns of axonal injury in the first week after mild traumatic brain injury (mTBI). We performed a prospective cohort study of 20 patients presenting to the emergency department with mTBI, using 3.0T diffusion tensor MRI immediately after injury and again at 1 week post-injury. Corresponding data were acquired from 16 controls over a similar time interval. Fractional anisotropy (FA) and other diffusion measures were calculated from 11 a priori selected axon tracts at each time-point, and the change across time in each region was quantified for each subject. Clinical outcomes were determined by standardized neurocognitive assessment. We found that mTBI subjects were significantly more likely to have changes in FA in those 11 regions of interest across the one week time period, compared to control subjects whose FA measurements were stable across time. Longitudinal imaging was more sensitive to these subtle changes in white matter integrity than cross-sectional assessments at either of two time points, alone. Analyzing the sources of variance in our control population, we show that this increased sensitivity is likely due to the smaller within-subject variability obtained by longitudinal analysis with each subject as their own control. This is in contrast to the larger between-subject variability obtained by cross-sectional analysis of each individual subject to normalized data from a control group. We also demonstrated that inclusion of all a priori ROIs in an analytic model as opposed to measuring individual ROIs improves detection of white matter changes by overcoming issues of injury heterogeneity. Finally, we employed genetic programming (a bio-inspired computational method for model estimation) to demonstrate that longitudinal changes in FA have utility in predicting the symptomatology of patients with mTBI. We conclude concussive brain injury caused acute, measurable changes in the FA of white matter tracts consistent with evolving axonal injury and/or edema, which may contribute to post-concussive symptoms.

Functional Connectivity Mapping in the Animal Model: Principles and Applications of Resting-State fMRI

"Resting-state" fMRI has substantially contributed to the understanding of human and non-human functional brain organization by the analysis of correlated patterns in spontaneous activity within dedicated brain systems. Spontaneous neural activity is indirectly measured from the blood oxygenation level-dependent signal as acquired by echo planar imaging, when subjects quietly "resting" in the scanner. Animal models including disease or knockout models allow a broad spectrum of experimental manipulations not applicable in humans. The non-invasive fMRI approach provides a promising tool for cross-species comparative investigations. This review focuses on the principles of "resting-state" functional connectivity analysis and its applications to living animals. The translational aspect from in vivo animal models toward clinical applications in humans is emphasized. We introduce the fMRI-based investigation of the non-human brain's hemodynamics, the methodological issues in the data postprocessing, and the functional data interpretation from different abstraction levels. The longer term goal of integrating fMRI connectivity data with structural connectomes obtained with tracing and optical imaging approaches is presented and will allow the interrogation of fMRI data in terms of directional flow of information and may identify the structural underpinnings of observed functional connectivity patterns.

Two step Gaussian mixture model approach to characterize white matter disease based on distributional changes

BACKGROUND

Magnetic resonance imaging reveals macro- and microstructural correlates of neurodegeneration, which are often assessed using voxel-by-voxel t-tests for comparing mean image intensities measured by fractional anisotropy (FA) between cases and controls or regression analysis for associating mean intensity with putative risk factors. This analytic strategy focusing on mean intensity in individual voxels, however, fails to account for change in distribution of image intensities due to disease.

NEW METHOD

We propose a method that aims to facilitate simple and clear characterization of underlying distribution. Our method consists of two steps: subject-level (Step 1) and group-level or a specific risk-level density function estimation across subjects (Step 2).

RESULTS

The proposed method was demonstrated with a simulated data set and real FA data sets from two white matter tracts, where the proposed method successfully detected any departure of the FA distribution from the normal state by disease: p<0.001 for simulated data; p=0.047 for the posterior limb of internal capsule; p=0.06 for the posterior thalamic radiation.

COMPARISON WITH EXISTING METHOD(S)

The proposed method found significant disease effect (p<0.001) while conventional 2-group t-test focused only on mean intensity did not (p=0.61) in a simulation study. While significant age effects were found for each white matter tract from conventional linear model analysis with real FA data, the proposed method further confirmed that aging also triggers distribution-wide change.

CONCLUSION

Our proposed method is powerful for detection of risk factors associated with any type of microstructural neurodegenerations with brain imaging data.

Motor network structure and function are associated with motor performance in Huntington's disease

In Huntington's disease, the relationship of brain structure, brain function and clinical measures remains incompletely understood. We asked how sensory-motor network brain structure and neural activity relate to each other and to motor performance. Thirty-four early stage HD and 32 age- and sex-matched healthy control participants underwent structural magnetic resonance imaging (MRI), diffusion tensor, and intrinsic functional connectivity MRI. Diffusivity patterns were assessed in the cortico-spinal tract and the thalamus-somatosensory cortex tract. For the motor network connectivity analyses the dominant M1 motor cortex region and for the basal ganglia-thalamic network the thalamus were used as seeds. Region to region structural and functional connectivity was examined between thalamus and somatosensory cortex. Fractional anisotropy (FA) was higher in HD than controls in the basal ganglia, and lower in the external and internal capsule, in the thalamus, and in subcortical white matter. Between-group axial and radial diffusivity differences were more prominent than differences in FA, and correlated with motor performance. Within the motor network, the insula was less connected in HD than in controls, with the degree of connection correlating with motor scores. The basal ganglia-thalamic network's connectivity differed in the insula and basal ganglia. Tract specific white matter diffusivity and functional connectivity were not correlated. In HD sensory-motor white matter organization and functional connectivity in a motor network were independently associated with motor performance. The lack of tract-specific association of structure and function suggests that functional adaptation to structural loss differs between participants.

Whole brain fiber-based comparison (FBC)-A tool for diffusion tensor imaging-based cohort studies

We present a novel method for fiber-based comparison of diffusion tensor imaging (DTI) scans of groups of subjects. The method entails initial preprocessing and fiber reconstruction by tractography of each brain in its native coordinate system. Several diffusion parameters are sampled along each fiber and used in subsequent comparisons. A spatial correspondence between subjects is established based on geometric similarity between fibers in a template set (several choices for template are explored), and fibers in all other subjects. Diffusion parameters between groups are compared statistically for each template fiber. Results are presented at single fiber resolution. As an initial exploratory step in neurological population studies this method points to the locations affected by the pathology of interest, without requiring a hypothesis. It does not make any grouping assumptions on the fibers and no manual intervention is needed. The framework was applied here to 18 healthy subjects and 23 amyotrophic lateral sclerosis (ALS) patients. The results are compatible with previous findings and with the tract based spatial statistics (TBSS) method. Hum Brain Mapp 37:477-490, 2016. © 2015 Wiley Periodicals, Inc.

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.

A gaussian mixture model approach for estimating and comparing the shapes of distributions of neuroimaging data: diffusion-measured aging effects in brain white matter

Neuroimaging signal intensity measures underlying physiology at each voxel unit. The brain-wide distribution of signal intensities may be used to assess gross brain abnormality. To compare distributions of brain image data between groups, t-tests are widely applied. This approach, however, only compares group means and fails to consider the shapes of the distributions. We propose a simple approach for estimating both subject- and group-level density functions based on the framework of Gaussian mixture modeling, with mixture probabilities that are testable between groups. We demonstrate this approach by application to the analysis of fractional anisotropy image data for assessment of aging effects in white matter.

Influence of noise correction on intra- and inter-subject variability of quantitative metrics in diffusion kurtosis imaging

Diffusion kurtosis imaging (DKI) is a promising extension of diffusion tensor imaging, giving new insights into the white matter microstructure and providing new biomarkers. Given the rapidly increasing number of studies, DKI has a potential to establish itself as a valuable tool in brain diagnostics. However, to become a routine procedure, DKI still needs to be improved in terms of robustness, reliability, and reproducibility. As it requires acquisitions at higher diffusion weightings, results are more affected by noise than in diffusion tensor imaging. The lack of standard procedures for post-processing, especially for noise correction, might become a significant obstacle for the use of DKI in clinical routine limiting its application. We considered two noise correction schemes accounting for the noise properties of multichannel phased-array coils, in order to improve the data quality at signal-to-noise ratio (SNR) typical for DKI. The SNR dependence of estimated DKI metrics such as mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) is investigated for these noise correction approaches in Monte Carlo simulations and in in vivo human studies. The intra-subject reproducibility is investigated in a single subject study by varying the SNR level and SNR spatial distribution. Then the impact of the noise correction on inter-subject variability is evaluated in a homogeneous sample of 25 healthy volunteers. Results show a strong impact of noise correction on the MK estimate, while the estimation of FA and MD was affected to a lesser extent. Both intra- and inter-subject SNR-related variability of the MK estimate is considerably reduced after correction for the noise bias, providing more accurate and reproducible measures. In this work, we have proposed a straightforward method that improves accuracy of DKI metrics. This should contribute to standardization of DKI applications in clinical studies making valuable inferences in group analysis and longitudinal studies.

Diffusion tensor magnetic resonance imaging in the analysis of neurodegenerative diseases

Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.

Whole brain approaches for identification of microstructural abnormalities in individual patients: comparison of techniques applied to mild traumatic brain injury

PURPOSE

Group-wise analyses of DTI in mTBI have demonstrated evidence of traumatic axonal injury (TAI), associated with adverse clinical outcomes. Although mTBI is likely to have a unique spatial pattern in each patient, group analyses implicitly assume that location of injury will be the same across patients. The purpose of this study was to optimize and validate a procedure for analysis of DTI images acquired in individual patients, which could detect inter-individual differences and be applied in the clinical setting, where patients must be assessed as individuals.

MATERIALS AND METHODS

After informed consent and in compliance with HIPAA, 34 mTBI patients and 42 normal subjects underwent 3.0 Tesla DTI. Four voxelwise assessment methods (standard Z-score, "one vs. many" t-test, Family-Wise Error Rate control using pseudo t-distribution, EZ-MAP) for use in individual patients, were applied to each patient's fractional anisotropy (FA) maps and tested for its ability to discriminate patients from controls. Receiver Operating Characteristic (ROC) analyses were used to define optimal thresholds (voxel-level significance and spatial extent) for reliable and robust detection of mTBI pathology.

RESULTS

ROC analyses showed EZ-MAP (specificity 71%, sensitivity 71%), "one vs. many" t-test and standard Z-score (sensitivity 65%, specificity 76% for both methods) resulted in a significant area under the curve (AUC) score for discriminating mTBI patients from controls in terms of the total number of abnormal white matter voxels detected while the FWER test was not significant. EZ-MAP is demonstrated to be robust to assumptions of Gaussian behavior and may serve as an alternative to methods that require strict Gaussian assumptions.

CONCLUSION

EZ-MAP provides a robust approach for delineation of regional abnormal anisotropy in individual mTBI patients.

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 Huntington's 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.

Robust detection of traumatic axonal injury in individual mild traumatic brain injury patients: intersubject variation, change over time and bidirectional changes in anisotropy

To identify and characterize otherwise occult inter-individual spatial variation of white matter abnormalities across mild traumatic brain injury (mTBI) patients. After informed consent and in compliance with Health Insurance Portability and Accountability Act (HIPAA), Diffusion tensor imaging (DTI) was performed on a 3.0 T MR scanner in 34 mTBI patients (19 women; 19-64 years old) and 30 healthy control subjects. The patients were imaged within 2 weeks of injury, 3 months after injury, and 6 months after injury. Fractional anisotropy (FA) images were analyzed in each patient. To examine white matter diffusion abnormalities across the entire brain of individual patients, we applied Enhanced Z-score Microstructural Assessment for Pathology (EZ-MAP), a voxelwise analysis optimized for the assessment of individual subjects. Our analysis revealed areas of abnormally low or high FA (voxel-wise P-value < 0.05, cluster-wise P-value < 0.01(corrected for multiple comparisons)). The spatial pattern of white matter FA abnormalities varied among patients. Areas of low FA were consistent with known patterns of traumatic axonal injury. Areas of high FA were most frequently detected in the deep and subcortical white matter of the frontal, parietal, and temporal lobes, and in the anterior portions of the corpus callosum. The number of both abnormally low and high FA voxels changed during follow up. Individual subject assessments reveal unique spatial patterns of white matter abnormalities in each patient, attributable to inter-individual differences in anatomy, vulnerability to injury and mechanism of injury. Implications of high FA remain unclear, but may evidence a compensatory mechanism or plasticity in response to injury, rather than a direct manifestation of brain injury.

Neuroimaging of motor neuron diseases

It is agreed that conventional magnetic resonance imaging (MRI) of the brain and spine is one of the core elements in the differential diagnostic work up of patients with clinical signs of motor neuron diseases (MNDs), for example amyotrophic lateral sclerosis (ALS), to exclude MND mimics. However, the sensitivity and specificity of MRI signs in these disorders are moderate to low and do not have an evidence level higher than class IV (good clinical practice point). Currently computerized MRI analyses in ALS and other MNDs are not techniques used for individual diagnosis. However, they have improved the anatomical understanding of pathomorphological alterations in gray and white matter in various MNDs and the changes in functional networks by quantitative comparisons between patients with MND and controls at group level. For multiparametric MRI protocols, including T1-weighted three-dimensional datasets, diffusion-weighted imaging and functional MRI, the potential as a 'dry' surrogate marker is a subject of investigation in natural history studies with well defined patients. The additional value of MRI with respect to early diagnosis at an individual level and for future disease-modifying multicentre trials remains to be defined. There is still the need for more longitudinal studies in the very early stages of disease or when there is clinical uncertainty and for better standardization in the acquisition and postprocessing of computer-based MRI data. These requirements are to be addressed by establishing quality-controlled multicentre neuroimaging databases.

The cerebro-morphological fingerprint of a progeroid syndrome: white matter changes correlate with neurological symptoms in xeroderma pigmentosum

Background

Xeroderma pigmentosum (XP) is a rare autosomal recessive progeroid syndrome. It has recently been shown that the underlying DNA repair defect plays a central role in the aging process. In addition to skin symptoms, various premature neurological abnormalities have been reported.

Methodology/Principal Findings

We present the clinical neurological phenotype in 14 XP patients (seven subtypes), in seven of these patients together with conventional and multiparametric advanced MRI data to assess the macrostructural and microstructural cerebral morphology in comparison to controls, including volumetric measurements, MR spectroscopy (¹H MRS), and diffusion tensor imaging (DTI). Clinical hallmarks were spinocerebellar ataxia, pyramidal tract signs, and mild cognitive deficits. DTI demonstrated significantly reduced WM directionality in all regions investigated, i.e. the thalamus, the corticospinal tracts and the dorsal corpus callosum. Single patients showed a marked relative hippocampal volume reduction, but the patients were not different from controls in the volumetric measurements of hippocampal and whole brain volumes at group level. However, ¹H MRS demonstrated that the hippocampal formation was metabolically altered.

Conclusions

The most prominent feature was the white matter affectation, as assessed by DTI, with volume and directionality reductions of the fiber projections involving both the craniocaudal fibers and the interhemispheric connections. These findings, although heterogeneous among the study sample, could be correlated with the clinico-neurological symptoms. The imaging findings support the position that myelin structures degrade prematurely in the brain of XP patients.

Complementary image analysis of diffusion tensor imaging and 3-dimensional t1-weighted imaging: white matter analysis in amyotrophic lateral sclerosis

INTRODUCTION

in order to obtain detailed information on disease-associated changes in the integrity of cerebral white matter (WM), complementary image analysis (CIA) was applied to patients with amyotrophic lateral sclerosis (ALS) and controls.

METHODS

both diffusion tensor imaging and T1-weighted 3-dimensional data were analyzed with respect to WM microstructure and T1 signal intensity alterations, respectively, in a sample of 19 ALS patients. Covariate information was added in the form of clinical parameters. All results were obtained in one common analysis software environment (Tensor Imaging and Fiber Tracking).

RESULTS

complementary analysis and display were performed for WM directionality and structure. Significant WM differences between ALS patients and controls were observed both in the motor system, that is, the bilateral corticospinal tracts, and in extramotor brain areas, in part correlating with clinical parameters. The performance of all analyses in one software environment enabled the synopsis of results obtained from various analyses.

DISCUSSION/CONCLUSION

within the application of CIA to a neurodegenerative disease for the whole brain-based analysis of WM alterations together with clinical characteristics, it could be demonstrated that ALS was associated with WM changes within and outside the motor system.

Whole brain-based analysis of regional white matter tract alterations in rare motor neuron diseases by diffusion tensor imaging

Different motor neuron disorders (MNDs) are mainly defined by the clinical presentation based on the predominance of upper or lower motor neuron impairment and the course of the disease. Magnetic resonance imaging (MRI) mostly serves as a tool to exclude other pathologies, but novel approaches such as diffusion tensor imaging (DTI) have begun to add information on the underlying pathophysiological processes of these disorders in vivo. The present study was designed to investigate three different rare MNDs, i.e., primary lateral sclerosis (PLS, N = 25), hereditary spastic paraparesis (HSP, N = 24), and X-linked spinobulbar muscular atrophy (X-SBMA, N = 20), by use of whole-brain-based DTI analysis in comparison with matched controls. This analysis of white matter (WM) impairment revealed widespread and characteristic patterns of alterations within the motor system with a predominant deterioration of the corticospinal tract (CST) in HSP and PLS patients according to the clinical presentation and also in patients with X-SBMA to a lesser degree, but also WM changes in projections to the limbic system and within distinct areas of the corpus callosum (CC), the latter both for HSP and PLS. In summary, DTI was able to define a characteristic WM pathoanatomy in motor and extra-motor brain areas, such as the CC and the limbic projectional system, for different MNDs via whole brain-based FA assessment and quantitative fiber tracking. Future advanced MRI-based investigations might help to provide a fingerprint-identification of MNDs.