Spatial correlation and segregation of multimodal MRI abnormalities in multiple system atrophy

Lee, Myung Sik; Kim, Tae Hyung; Mun, Chi-Woong; Shin, Hang-Sik; Son, Jongsang; Lee, Jae Hyeok

doi:10.1007/s00415-018-8874-z

Cited by 9 publications

(8 citation statements)

References 31 publications

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“…After hypometabolism maps, they reached the highest accuracy among diseases, and it did not improve after hypermetabolism maps. In both groups, however, the use of hypermetabolism maps increases confidence, maybe because of the confirmation that there is a metabolic sparing of cortical regions [ 24 , 25 ]. In the cases of PSP disease, one of the lowest accuracy levels after qualitative assessment happens in both experts and not experts, improving after hypometabolism maps in both groups and after hypermetabolism maps only in not experts.…”

Section: Discussionmentioning

confidence: 99%

FDG PET in the differential diagnosis of degenerative parkinsonian disorders: usefulness of voxel-based analysis in clinical practice

et al. 2022

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Background The early differential diagnosis among neurodegenerative parkinsonian disorders becomes essential to set up the correct clinical-therapeutic approach. The increased utilization of [18F] fluoro-deoxy-glucose positron emission tomography (FDG PET) and the pressure for cost-effectiveness request a systematic evaluation and a validation of its utility in clinical practice. This retrospective study aims to consider the contribution, in terms of increasing accuracy and increasing diagnostic confidence, of voxel-based FDG PET analyses in the differential diagnosis of these disorders, including Parkinson’s disease, multiple system atrophy, progressive supranuclear palsy, and cortico-basal syndrome. Method Eighty-three subjects with a clinically confirmed diagnosis of degenerative parkinsonian disorders who underwent FDG brain PET/CT were selected. A voxel-based analysis was set up using statistical parametric mapping (SPM) on MATLAB to produce maps of brain hypometabolism and relative hypermetabolism. Four nuclear physicians (two expert and two not expert), blinded to the patients’ symptoms, other physicians’ evaluations, and final clinical diagnosis, independently evaluated all data by visual assessment and by adopting metabolic maps. Results In not-expert evaluators, the support of both hypometabolism and hypermetabolism maps results in a significant increase in diagnostic accuracy as well as clinical confidence. In expert evaluators, the increase in accuracy and in diagnostic confidence is mainly supported by hypometabolism maps alone. Conclusions In this study, we demonstrated the additional value of combining voxel-based analyses with qualitative assessment of brain PET images. Moreover, maps of relative hypermetabolism can also make their contribution in clinical practice, particularly for less experienced evaluators.

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Section: Discussionmentioning

confidence: 99%

FDG PET in the differential diagnosis of degenerative parkinsonian disorders: usefulness of voxel-based analysis in clinical practice

et al. 2022

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“…In a recent study of correlations between R2 * values and the degree of Unified Parkinson's Disease Rating Scale scores in PSP, the burden of iron-related PSP pathologies in the lenticular nucleus was associated with the severity of rigidity, and nigro-striato-pallidal and dentate iron content were associated with the severity of tremors (62). Other studies have failed to show a correlation of iron-sensitive MRI markers with clinical severity scale scores in MSA and PSP (34, 43, 49, 64), but have instead reported that diffusion tensor metrics, such as MD values, are closely correlated with clinical severity (63, 64). Iron-sensitive MRI markers may have less sensitivity to reflect clinical status than diffusion tensor metrics.…”

Section: Clinical Implications Of Brain Iron Deposition In Apsmentioning

confidence: 99%

“…Structural MRI abnormalities in MSA are segregated into basal ganglia and brainstem-cerebellar factors (64). Alterations in the R2 * of the basal ganglia region are not significantly correlated with the MRI variables associated with brainstem-cerebellar degeneration.…”

Section: Clinical Implications Of Brain Iron Deposition In Apsmentioning

confidence: 99%

Brain Iron Accumulation in Atypical Parkinsonian Syndromes: in vivo MRI Evidences for Distinctive Patterns

Lee

2019

Front. Neurol.

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Recent data suggest mechanistic links among perturbed iron homeostasis, oxidative stress, and misfolded protein aggregation in neurodegenerative diseases. Iron overload and toxicity toward dopaminergic neurons have been established as playing a role in the pathogenesis of Parkinson's disease (PD). Brain iron accumulation has also been documented in atypical parkinsonian syndromes (APS), mainly comprising multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). Iron-sensitive magnetic resonance imaging (MRI) has been applied to identify iron-related signal changes for the diagnosis and differentiation of these disorders. Topographic patterns of widespread iron deposition in deep brain nuclei have been described as differing between patients with MSA and PSP and those with PD. A disease-specific increase of iron occurs in the brain regions mainly affected by underlying disease pathologies. However, whether iron changes are a primary pathogenic factor or an epiphenomenon of neuronal degeneration has not been fully elucidated. Moreover, the clinical implications of iron-related pathology in APS remain unclear. In this review study, we collected data from qualitative and quantitative MRI studies on brain iron accumulation in APS to identify disease-related patterns and the potential role of iron-sensitive MRI.

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“…Brain modifications related to neurodegeneration due to aging as well as psychiatric or neurodegenerative diseases can be characterized using multimodal MRI protocols with sequences sensitive to different tissue characteristics (Barbagallo et al, 2016; Cherubini et al, 2016; Eustache et al, 2016; Lee et al, 2018; Nemmi et al, 2015; Péran et al, 2010, Péran et al, 2018; Spoletini et al, 2011). Previous multimodal MRI studies have mainly used structural markers: grey and white matter volume (calculated using T1-weighted imaging), microstructural integrity of the white and grey matter by using diffusion weighted imaging (DWI) related indexes (e.g.…”

Section: Introductionmentioning

confidence: 99%

A totally data-driven whole-brain multimodal pipeline for the discrimination of Parkinson's disease, multiple system atrophy and healthy control

Nemmi

Traon

Phillips

et al. 2019

NeuroImage: Clinical

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Parkinson's Disease (PD) and Multiple System Atrophy (MSA) are two parkinsonian syndromes that share many symptoms, albeit having very different prognosis. Although previous studies have proposed multimodal MRI protocols combined with multivariate analysis to discriminate between these two populations and healthy controls, studies combining all MRI indexes relevant for these disorders (i.e. grey matter volume, fractional anisotropy, mean diffusivity, iron deposition, brain activity at rest and brain connectivity) with a completely data-driven voxelwise analysis for discrimination are still lacking. In this study, we used such a complete MRI protocol and adapted a fully-data driven analysis pipeline to discriminate between these populations and a healthy controls (HC) group. The pipeline combined several feature selection and reduction steps to obtain interpretable models with a low number of discriminant features that can shed light onto the brain pathology of PD and MSA. Using this pipeline, we could discriminate between PD and HC (best accuracy = 0.78), MSA and HC (best accuracy = 0.94) and PD and MSA (best accuracy = 0.88). Moreover, we showed that indexes derived from resting-state fMRI alone could discriminate between PD and HC, while mean diffusivity in the cerebellum and the putamen alone could discriminate between MSA and HC. On the other hand, a more diverse set of indexes derived by multiple modalities was needed to discriminate between the two disorders. We showed that our pipeline was able to discriminate between distinct pathological populations while delivering sparse model that could be used to better understand the neural underpinning of the pathologies.

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Spatial correlation and segregation of multimodal MRI abnormalities in multiple system atrophy

Abstract: Multimodal structural MRI abnormalities in MSA appear to be segregated into BG and stem-CB-related factors that can be associated with the clinical phenotype and motor severity.

Cited by 9 publications

References 31 publications

FDG PET in the differential diagnosis of degenerative parkinsonian disorders: usefulness of voxel-based analysis in clinical practice

FDG PET in the differential diagnosis of degenerative parkinsonian disorders: usefulness of voxel-based analysis in clinical practice

Brain Iron Accumulation in Atypical Parkinsonian Syndromes: in vivo MRI Evidences for Distinctive Patterns

A totally data-driven whole-brain multimodal pipeline for the discrimination of Parkinson's disease, multiple system atrophy and healthy control

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