Voxel-based morphometry and Voxel-based relaxometry in parkinsonian variant of multiple system atrophy

Large-scale activation likelihood estimation meta-analysis of parkinsonian disorders

Parkinsonism is a feature of several neurodegenerative disorders, including Parkinson's disease, progressive supranuclear palsy, corticobasal syndrome and multiple system atrophy. Neuroimaging studies have yielded insights into parkinsonian disorders; however, due to variability in results, the brain regions consistently implicated in these disorders remain to be characterized. The aim of this meta-analysis was to identify consistent brain abnormalities in individual parkinsonian disorders (Parkinson's disease, progressive supranuclear palsy, corticobasal syndrome and multiple system atrophy) and to investigate any shared abnormalities across disorders. A total of 44 591 studies were systematically screened following searches of two databases. A series of whole-brain activation likelihood estimation meta-analyses were performed on 132 neuroimaging studies (69 Parkinson's disease; 23 progressive supranuclear palsy; 17 corticobasal syndrome; and 23 multiple system atrophy) utilizing anatomical MRI, perfusion or metabolism PET and single-photon emission computed tomography. Meta-analyses were performed in each parkinsonian disorder within each imaging modality, as well as across all included disorders. Results in progressive supranuclear palsy and multiple system atrophy aligned with current imaging markers for diagnosis, encompassing the midbrain, and brainstem and putamen, respectively. PET imaging studies of patients with Parkinson's disease most consistently reported abnormality of the middle temporal gyrus. No significant clusters were identified in corticobasal syndrome. When examining abnormalities shared across all four disorders, the caudate was consistently reported in MRI studies, whilst the thalamus, inferior frontal gyrus and middle temporal gyri were commonly implicated by PET. To our knowledge, this is the largest meta-analysis of neuroimaging studies in parkinsonian disorders and the first to characterize brain regions implicated across parkinsonian disorders.

An Integrative Nomogram for Identifying Early-Stage Parkinson's Disease Using Non-motor Symptoms and White Matter-Based Radiomics Biomarkers From Whole-Brain MRI

Purpose: To develop and validate an integrative nomogram based on white matter (WM) radiomics biomarkers and nonmotor symptoms for the identification of early-stage Parkinson's disease (PD).

Methods: The brain magnetic resonance imaging (MRI) and clinical characteristics of 336 subjects, including 168 patients with PD, were collected from the Parkinson's Progress Markers Initiative (PPMI) database. All subjects were randomly divided into training and test sets. According to the baseline MRI scans of patients in the training set, the WM was segmented to extract the radiomic features of each patient and develop radiomics biomarkers, which were then combined with nonmotor symptoms to build an integrative nomogram using machine learning. Finally, the diagnostic accuracy and reliability of the nomogram were evaluated using a receiver operating characteristic curve and test data, respectively. In addition, we investigated 58 patients with atypical PD who had imaging scans without evidence of dopaminergic deficit (SWEDD) to verify whether the nomogram was able to distinguish patients with typical PD from patients with SWEDD. A decision curve analysis was also performed to validate the clinical practicality of the nomogram.

Results: The area under the curve values of the integrative nomogram for the training, testing and verification sets were 0.937, 0.922, and 0.836, respectively; the specificity values were 83.8, 88.2, and 91.38%, respectively; and the sensitivity values were 84.6, 82.4, and 70.69%, respectively. A significant difference in the number of patients with PD was observed between the high-risk group and the low-risk group based on the nomogram (P < 0.05).

Conclusion: This integrative nomogram is a new potential method to identify patients with early-stage PD.

Voxel-Based Meta-Analysis of Gray Matter Abnormalities in Multiple System Atrophy

Purpose: This study aimed to identify consistent gray matter volume (GMV) changes in the two subtypes of multiple system atrophy (MSA), including parkinsonism subtype (MSA-P), and cerebellar subtype (MSA-C), by conducting a voxel-wise meta-analysis of whole brain voxel-based morphometry (VBM) studies.

Method: VBM studies comparing MSA-P or MSA-C and healthy controls (HCs) were systematically searched in the PubMed, Embase, and Web of Science published from 1974 to 20 October 2020. A quantitative meta-analysis of VBM studies on MSA-P or MSA-C was performed using the effect size-based signed differential mapping (ES-SDM) method separately. A complementary analysis was conducted using the Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) method, which allows a familywise error rate (FWE) correction for multiple comparisons of the results, for further validation of the results.

Results: Ten studies were included in the meta-analysis of MSA-P subtype, comprising 136 MSA-P patients and 211 HCs. Five studies were included in the meta-analysis of MSA-C subtype, comprising 89 MSA-C patients and 134 HCs. Cerebellum atrophy was detected in both MSA-P and MSA-C, whereas basal ganglia atrophy was only detected in MSA-P. Cerebral cortex atrophy was detected in both subtypes, with predominant impairment of the superior temporal gyrus, inferior frontal gyrus, temporal pole, insula, and amygdala in MSA-P and predominant impairment of the superior temporal gyrus, middle temporal gyrus, fusiform gyrus, and lingual gyrus in MSA-C. Most of these results survived the FWE correction in the complementary analysis, except for the bilateral amygdala and the left caudate nucleus in MSA-P, and the right superior temporal gyrus and the right middle temporal gyrus in MSA-C. These findings remained robust in the jackknife sensitivity analysis, and no significant heterogeneity was detected.

Conclusion: A different pattern of brain atrophy between MSA-P and MSA-C detected in the current study was in line with clinical manifestations and provided the evidence of the pathophysiology of the two subtypes of MSA.

Structural Imaging in Atypical Parkinsonism

Qualitative and quantitative structural magnetic resonance imaging offer objective measures of the underlying neurodegeneration in atypical parkinsonism. Regional changes in tissue volume, signal changes and increased deposition of iron as assessed with different structural MRI techniques are surrogate markers of underlying neurodegeneration and may reflect cell loss, microglial proliferation and astroglial activation. Structural MRI has been explored as a tool to enhance diagnostic accuracy in differentiating atypical parkinsonian disorders (APDs). Moreover, the longitudinal assessment of serial structural MRI-derived parameters offers the opportunity for robust inferences regarding the progression of APDs. This review summarizes recent research findings as (1) a diagnostic tool for APDs as well as (2) as a tool to assess longitudinal changes of serial MRI-derived parameters in the different APDs.

Diagnosis of multiple system atrophy

Multiple system atrophy (MSA) may be difficult to distinguish clinically from other disorders, particularly in the early stages of the disease. An autonomic-only presentation can be indistinguishable from pure autonomic failure. Patients presenting with parkinsonism may be misdiagnosed as having Parkinson disease. Patients presenting with the cerebellar phenotype of MSA can mimic other adult-onset ataxias due to alcohol, chemotherapeutic agents, lead, lithium, and toluene, or vitamin E deficiency, as well as paraneoplastic, autoimmune, or genetic ataxias. A careful medical history and meticulous neurological examination remain the cornerstone for the accurate diagnosis of MSA. Ancillary investigations are helpful to support the diagnosis, rule out potential mimics, and define therapeutic strategies. This review summarizes diagnostic investigations useful in the differential diagnosis of patients with suspected MSA. Currently used techniques include structural and functional brain imaging, cardiac sympathetic imaging, cardiovascular autonomic testing, olfactory testing, sleep study, urological evaluation, and dysphagia and cognitive assessments. Despite advances in the diagnostic tools for MSA in recent years and the availability of consensus criteria for clinical diagnosis, the diagnostic accuracy of MSA remains sub-optimal. As other diagnostic tools emerge, including skin biopsy, retinal biomarkers, blood and cerebrospinal fluid biomarkers, and advanced genetic testing, a more accurate and earlier recognition of MSA should be possible, even in the prodromal stages. This has important implications as misdiagnosis can result in inappropriate treatment, patient and family distress, and erroneous eligibility for clinical trials of disease-modifying drugs.

Magnetic resonance imaging for the diagnosis of Parkinson's disease

The differential diagnosis of parkinsonian syndromes is considered one of the most challenging in neurology and error rates in the clinical diagnosis can be high even at specialized centres. Despite several limitations, magnetic resonance imaging (MRI) has undoubtedly enhanced the diagnostic accuracy in the differential diagnosis of neurodegenerative parkinsonism over the last three decades. This review aims to summarize research findings regarding the value of the different MRI techniques, including advanced sequences at high- and ultra-high-field MRI and modern image analysis algorithms, in the diagnostic work-up of Parkinson's disease. This includes not only the exclusion of alternative diagnoses for Parkinson's disease such as symptomatic parkinsonism and atypical parkinsonism, but also the diagnosis of early, new onset, and even prodromal Parkinson's disease.

Role of Magnetic Resonance Imaging in the Diagnosis of Multiple System Atrophy

Background

Multiple system atrophy (MSA) is a rapidly progressing neurodegenerative disorder without effective disease-modifying therapies. Because of a lack of reliable diagnostic biomarkers, there has been increasing interest in using magnetic resonance imaging (MRI) to improve the diagnostic accuracy of MSA.

Methods

This review summarizes recent literatures on the role of MRI in the diagnosis of MSA.

Results

Several MRI abnormalities on conventional MRI already are included in the current diagnostic criteria for MSA. Other features on conventional MRI are also used to make a diagnosis of MSA or to rule out alternative diagnoses. On the other hand, some of the MRI findings that were previously considered suggestive of a diagnosis of MSA are now being challenged, because it turned out that they were not as specific to MSA as previously thought. More advanced MRI modalities, including susceptibility-weighted imaging, diffusion-weighted imaging, diffusion tensor imaging, voxel-based morphometry, and cortical thickness analysis, are now used to study the changes in the brains of patients with MSA. Furthermore, studies have produced promising results demonstrating the use of MRI as a tool for monitoring and assessing disease progression in MSA.

Conclusions

MRI is useful and indispensable in the diagnosis of MSA and also possibly for monitoring disease progression. In this regard, well-designed, long-term, prospective studies on large numbers of patients are needed.

The PROMESA-protocol: progression rate of multiple system atrophy under EGCG supplementation as anti-aggregation-approach

Formation of toxic α-synuclein oligomers appears to be a key underlying pathological mechanism of synucleinopathies such as Parkinson's disease or multiple system atrophy (MSA). Given that Epigallocatechin-gallate has been shown to inhibit α-synuclein aggregation, it might represent a causal treatment option. Therefore, we set out to evaluate the safety, tolerability and a potential disease-modifying effect of Epigallocatechin-gallate in patients with MSA after 48 weeks of treatment. Power calculation was performed on existing natural history data on the progression of the Unified MSA Rating Scale as primary readout parameter. To assess the efficacy of Epigallocatechin-gallate versus placebo regarding the reduction of disease progression measured during the study period (80 % power, 5 % p level, 50 % effect size) 36 patients per group are needed. Considering a drop-out rate of 20 % a total of 86 patients will be recruited in this multicentre study. These data provide a solid rationale to investigate whether supplementation of Epigallocatechin-gallate can delay the progression of the MSA-related disability.

Morphological alterations in the caudate, putamen, pallidum, and thalamus in Parkinson's disease

Like many neurodegenerative diseases, the clinical symptoms of Parkinsons disease (PD) do not manifest until significant progression of the disease has already taken place, motivating the need for sensitive biomarkers of the disease. While structural imaging is a potentially attractive method due to its widespread availability and non-invasive nature, global morphometric measures (e.g., volume) have proven insensitive to subtle disease change. Here we use individual surface displacements from deformations of an average surface model to capture disease related changes in shape of the subcortical structures in PD. Data were obtained from both the University of British Columbia (UBC) [n = 54 healthy controls (HC) and n = 55 Parkinsons disease (PD) patients] and the publicly available Parkinsons Progression Markers Initiative (PPMI) [n = 137 (HC) and n = 189 (PD)] database. A high dimensional non-rigid registration algorithm was used to register target segmentation labels (caudate, putamen, pallidum, and thalamus) to a set of segmentation labels defined on the average-template. The vertex-wise surface displacements were significantly different between PD and HC in thalamic and caudate structures. However, overall displacements did not correlate with disease severity, as assessed by the Unified Parkinson's Disease Rating Scale (UPDRS). The results from this study suggest disease-relevant shape abnormalities can be robustly detected in subcortical structures in PD. Future studies will be required to determine if shape changes in subcortical structures are seen in the prodromal phases of the disease.

Voxelwise meta-analysis of gray matter anomalies in Parkinson variant of multiple system atrophy and Parkinson's disease using anatomic likelihood estimation

Numerous voxel-based morphometry (VBM) studies on gray matter (GM) in patients with the Parkinson variant of multiple system atrophy (MSA-P) and Parkinson's disease (PD) have been separately conducted. Identifying the different neuroanatomical changes in GM between MSA-P and PD through meta-analysis may aid the differential diagnosis of MSA-P and PD. A systematic review of VBM studies on patients with MSA-P and PD compared to healthy controls (HC) from the PubMed and Embase databases between January 1995 and June 2014 was conducted. Five studies comparing MSA-P with HC and twenty-three studies comparing PD with HC were included. The anatomical distribution of the coordinates of GM volume (GMV) differences was analyzed using the anatomical likelihood estimation (ALE) method. GMV reductions were present in the bilateral putamen, claustrum, insula, midbrain and left cerebellum in MSA-P. In PD, GMV decreases were present in the frontal, parietal, occipital and limbic lobes. Subtraction meta-analysis was performed to explore the differences in GM abnormalities between MSA-P and PD during the early stage of the disease. For patients with disease duration within 5 years, compared with PD, the decrease in GMV focused on the bilateral putamen and claustrum in MSA-P. In contrast, for patients with disease duration within 3 years, no significant GMV difference was found between MSA-P and PD. Our meta-analysis indicated that the atrophy of bilateral putamen or claustrum is not a neuroanatomical marker for distinguishing MSA-P from PD during the early stage by using the VBM method.

Distinct functional and macrostructural brain changes in Parkinson's disease and multiple system atrophy

Parkinson's disease (PD) and the parkinsonian variant of multiple system atrophy (MSAp) are neurodegenerative disorders that can be difficult to differentiate clinically. This study provides the first characterization of the patterns of task-related functional magnetic resonance imaging (fMRI) changes across the whole brain in MSAp. We used fMRI during a precision grip force task and also performed voxel-based morphometry (VBM) on T1 -weighted images in MSAp patients, PD patients, and healthy controls. All groups were matched on age, and the patient groups had comparable motor symptom durations and severities. There were three main findings. First, MSAp and PD had reduced fMRI activation in motor control areas, including the basal ganglia, thalamus, insula, primary sensorimotor and prefrontal cortices, and cerebellum compared with controls. Second, there were no activation differences among the disease groups in the basal ganglia, thalamus, insula, or primary sensorimotor cortices, but PD had more extensive activation deficits throughout the cerebrum compared with MSAp and controls. Third, VBM revealed reduced volume in the basal ganglia, middle and inferior cerebellar peduncles, pons, and throughout the cerebrum in MSAp compared with controls and PD, and additionally throughout the cerebellar cortex and vermis in MSAp compared with controls. Collectively, these results provide the first evidence that fMRI activation is abnormal in the basal ganglia, cerebellum, and cerebrum in MSAp, and that a key distinguishing feature between MSAp and PD is the extensive and widespread volume loss throughout the brain in MSAp.

Diffusion tensor imaging in idiopathic Parkinson's disease and multisystem atrophy (Parkinsonian type)

BACKGROUND

Differentiation between Parkinson's disease (PD) and atypical Parkinson syndromes (AP) is usually based on clinical examination, but can be challenging especially at early stages of the diseases. Diffusion tensor imaging (DTI) allows for differentiation between PD and AP with good specificity. It is a promising tool for clinical application, but has not been elaborated completely with respect to methodology and validity.

OBJECTIVE

In this study we evaluated differences of the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) within white brain matter between patients with PD and multisystem atrophy of the parkinsonian type (MSAp).

MATERIALS AND METHODS

DTI data of 9 PD and 9 MSAp patients were compared by means of a hypothesis-free whole-brain analysis algorithm (TBSS) focusing on changes within white matter.

RESULTS

We found significantly higher values of the ADC in the MSAp group in the anterior limb of the inner capsule, superior parts of the corona radiata, and lateral periputaminal white matter. Group differences in FA values were not significant.

CONCLUSION

Changes of the ADC close to the putamen proved most consistent and seem to be promising for the ongoing clinical implementation of DTI for the differentiation of hypokinetic-rigid movement disorders.

In vivo evaluation of gray and white matter volume loss in the parkinsonian variant of multiple system atrophy using SPM8 plus DARTEL for VBM

In multiple system atrophy with predominant parkinsonism (MSA-P), several voxel-based morphometry (VBM) studies have revealed gray matter loss; however, the white matter volume changes have been rarely reported. We investigated the volume changes of white matter as well as gray matter by VBM. A retrospective MRI study was performed in 20 patients with MSA-P and 30 age-matched healthy controls. We applied VBM with statistical parametric mapping (SPM8) plus diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) to explore the regional atrophy of gray and white matter in all of the MSA-P patients, 14 patients with left-side dominant and 6 patients with right-side dominant onset as compared to controls. In all of the MSA-P patients, VBM revealed a significant volume reduction of gray matter in the bilateral putamina, cerebellums and dorsal midbrain. White matter loss was located in bilateral globus pallidi, external capsules extending to the midbrain, right subcortical to precentral area through internal capsule, the pons, bilateral middle cerebellar peduncles and left cerebellum. In left-side dominant MSA-P patients, the gray and white matter volume loss was detected predominantly on the right side and vice versa in right-side dominant MSA-P patients. A correlation with disease duration and severity was not detected. VBM using SPM8 plus DARTEL detected significant volume loss not only in the gray but also in the white matter of the area affected by MSA-P.

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Volume changes of gray and white matter were investigated by VBM in MSA-P.

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Volume loss of globus pallidus with each structure was detected.

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Gray and white matter volume loss agreed well with clinical findings in laterality.

Differential diagnosis tool for parkinsonian syndrome using multiple structural brain measures

Clinical differentiation of parkinsonian syndromes such as the Parkinson variant of multiple system atrophy (MSA-P) and cerebellar subtype (MSA-C) from Parkinson's disease is difficult in the early stage of the disease. To identify the correlative pattern of brain changes for differentiating parkinsonian syndromes, we applied discriminant analysis techniques by magnetic resonance imaging (MRI). T1-weighted volume data and diffusion tensor images were obtained by MRI in eighteen patients with MSA-C, 12 patients with MSA-P, 21 patients with Parkinson's disease, and 21 healthy controls. They were evaluated using voxel-based morphometry and tract-based spatial statistics, respectively. Discriminant functions derived by step wise methods resulted in correct classification rates of 0.89. When differentiating these diseases with the use of three independent variables together, the correct classification rate was the same as that obtained with step wise methods. These findings support the view that each parkinsonian syndrome has structural deviations in multiple brain areas and that a combination of structural brain measures can help to distinguish parkinsonian syndromes.

Recent advances in structural MRI in Parkinson’s disease and atypical parkinsonian syndromes

SUMMARY In the past 2 years, technical developments in conventional and advanced MRI, such as ultra-high-field MRI or mapping of brain mineralization, has allowed novel insights into the nature of Parkinson’s disease (PD) and atypical parkinsonian syndromes, which may aid diagnostic accuracy and differential diagnosis. In addition, sophisticated post-processing analyses, such as morphometry- and surface-based classifications and automated whole-brain analyses, have become available; in PD, this has led to direct visualization of structural substantia nigra abnormalities, monitoring disease progression or screening for brain atrophy associated with dementia. Based on conventional MRI, new MRI rating scales have been established for progressive supranuclear palsy and multiple system atrophy and have been further assessed with a view to their diagnostic accuracy. Clinicopathological series of patients with tauopathies imply that correlations between clinical syndromes, imaging patterns and underlying histopathology are not always strong. Here, some of the issues related to conventional and advanced MRI for the diagnostic accuracy of PD and atypical parkinsonian syndromes are reviewed.

CNS involvement in primary Sjogren Syndrome: assessment of gray and white matter changes with MRI and voxel-based morphometry

OBJECTIVE

The purpose of this study was to evaluate with MRI the involvement of gray matter and white matter structures in patients with primary Sjögren syndrome.

SUBJECTS AND METHODS

Fifty-three patients with primary Sjögren syndrome, 18 age- and disease duration-matched patients with systemic sclerosis, and 35 age-matched control subjects were examined for differences in white matter hyperintensities (WMHIs) detected on FLAIR MR images. Differences in brain volume between patients with primary Sjögren syndrome and controls were studied by application of voxel-based morphometry to a 3D T1-weighted sequence.

RESULTS

WMHIs were observed in 38 of the 53 patients with primary Sjögren syndrome, six of 18 patients with systemic sclerosis, and 17 of 35 controls. The numbers of WMHIs 2 mm or larger and the number smaller than 2 mm were higher in patients with primary Sjögren syndrome than in controls (≥ 2 mm, p = 0.004; < 2 mm, p < 0.001). No significant difference was observed in the number of WMHIs in primary Sjögren syndrome patients and that in systemic sclerosis patients. After control for age, a positive relation was found between disease duration and total number of WMHIs (p = 0.037) and number of WMHIs 2 mm or larger (p = 0.023) in patients with primary Sjögren syndrome. In comparison with the controls, patients with primary Sjögren syndrome had decreased gray matter volume in the cortex, deep gray matter, and cerebellum. Associated loss of white matter volume was observed in areas corresponding to gray matter atrophy and in the corpus callosum (p < 0.05).

CONCLUSION

Patients with primary Sjögren syndrome have WMHIs and gray and white matter atrophy, probably related to cerebral vasculitis.

Investigation of unmedicated early onset restless legs syndrome by voxel-based morphometry, T2 relaxometry, and functional MR imaging during the night-time hours

BACKGROUND AND PURPOSE

The pathophysiology of eRLS has not yet been elucidated. The purpose of the study was to assess, in patients with eRLS, the volume, iron content, and activation of the brain during night-time episodes of SLD and PLMs.

MATERIALS AND METHODS

Eleven right-handed unmedicated patients with eRLS (mean age, 55.3 ± 8.4 years; disease duration, 17.5 ± 14.05 years) and 11 matched control subjects were studied with a T1-weighted high-resolution 3D spoiled gradient-echo sequence used for VBM and a multisection spin-echo T2-weighted sequence used for T2 relaxometry. Additionally, a single-shot multisection gradient echo-planar sequence was used for fMRI. Brain activation was recorded during spontaneous SLD and PLMs. SPM software was used for analysis of the functional data.

RESULTS

The patients showed no regional brain volume change, but T2 relaxometry revealed decreased T2 relaxation time in the right globus pallidus internal and the STN, indicating increased iron content. The patients were observed to activate the following areas: in the left hemisphere, the primary motor and somatosensory cortex, the thalamus, the pars opercularis, and the ventral anterior cingulum; and in the right hemisphere, the striatum, the inferior and superior parietal lobules, and the dorsolateral prefrontal cortex. Bilateral activation was observed in the cerebellum, the midbrain, and the pons.

CONCLUSIONS

eRLS is associated with increased iron content of the globus pallidus internal and STN, suggesting dysfunction of the basal ganglia. Activation of the striatofrontolimbic area may represent the neurofunctional substrate mediating the repetitive compulsive movements seen in RLS.

Advances in imaging in Parkinson's disease

Advances in imaging have made it possible to detect functional and, increasingly, structural changes in Parkinson's disease. Although imaging is not yet routinely used for diagnosis, such an application is becoming increasingly feasible. Of potentially greater interest, however, is the use of imaging as a biomarker to detect premotor disease and disease progression. Imaging also provides insights into complications of Parkinson's disease and its long-term treatment, and the role of dopamine in the normal brain. Furthermore, these techniques can be applied to animal models, to help validate these models and allow their use in the study of potential disease-modifying therapies.

Progression of striatal and extrastriatal degeneration in multiple system atrophy: a longitudinal diffusion-weighted MR study

Diffusion-weighted imaging has been largely used to detect and quantify early degenerative changes in patients with multiple system atrophy, but progression of neurodegeneration has been poorly investigated. We performed a serial diffusion-weighted imaging study in a population of multiple system atrophy patients and analyzed the evolution of diffusion properties in striatal and extrastriatal brain regions. Diffusion-weighted imaging was obtained in 11 multiple system atrophy patients at baseline and after a follow-up of 11.7 ± 1.2 months, and Trace (D) changes in different brain regions were correlated with disease duration and severity. A significant increase in Trace (D) was observed at follow-up in the putamen (P < .001), pons (P = .003), cerebellar white matter (P = .03), thalamus (P = .013), and frontal white matter (P = .021). Both Unified Multiple System Atrophy Rating Scale Part II and Unified Parkinson's Disease Rating Scale Part III scores significantly increased at follow-up (P = .003), but percent changes of Unified Parkinson's Disease Rating Scale Part III and Unified Multiple System Atrophy Rating Scale Part II did not correlate with percent changes of Trace (D) values in any brain region. This longitudinal study provides new insights into the progression of neurodegeneration in different brain regions in multiple system atrophy. Our results confirm that abnormal diffusivity in the putamen is sensitive to change over time in multiple system atrophy patients and show for the first time a progression of Trace (D) alterations in specific extrastriatal regions. Diffusivity changes in these regions may be useful for monitoring disease progression even after a short follow-up period. © 2011 Movement Disorder Society.

Shifting from region of interest (ROI) to voxel-based analysis in human brain mapping

Current clinical studies involve multidimensional high-resolution images containing an overwhelming amount of structural and functional information. The analysis of such a wealth of information is becoming increasingly difficult yet necessary in order to improve diagnosis, treatment and healthcare. Voxel-wise analysis is a class of modern methods of image processing in the medical field with increased popularity. It has replaced manual region of interest (ROI) analysis and has provided tools to make statistical inferences at voxel level. The introduction of voxel-based analysis software in all modern commercial scanners allows clinical use of these techniques. This review will explain the main principles, advantages and disadvantages behind these methods of image analysis.