Automated Analysis of Diffusion-Weighted Magnetic Resonance Imaging for the Differential Diagnosis of Multiple System Atrophy from Parkinson's Disease

Free water imaging in Parkinson's disease and atypical parkinsonian disorders

BACKGROUND

Free water (FW)-corrected diffusion measures are more precise compared to standard diffusion measures. This study comprehensively evaluates FW and corrected diffusion metrics for whole brain white and deep gray matter (WM, GM) structures in patients with Parkinson's disease (PD), progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) and attempts to ascertain the probable patterns of WM abnormalities.

METHOD

Diffusion MRI was acquired for subjects with PD (n = 133), MSA (n = 25), PSP (n = 30) and matched healthy controls (HC) (n = 99, n = 24, n = 12). Diffusion metrics of FA, MD, AD, RD were generated and FW, corrected FA maps were calculated using a bi-tensor model. TBSS was carried out at 5000 permutations with significance at p < 0.05. For GM, diffusivity maps were extracted from the basal ganglia, and analyzed at an FDR with p < 0.05.

RESULTS

Compared to HC, PD showed focal changes in FW. MSA showed changes in the cerebellum and brainstem, and PSP showed increase in FW involving supratentorial WM and midbrain. All three showed increased substantia nigra FW. MSA, PSP demonstrated increased FW in bilateral putamen. PD showed increased FW in left GP externa, and bilateral thalamus. Compared to HC, MSA had increased FW in bilateral GP interna, and left thalamic. PSP had an additional increase in FW of the right GP externa, right GP interna, and bilateral thalamus.

CONCLUSION

The present study demonstrated definitive differences in the patterns of FW alterations between PD and atypical parkinsonian disorders suggesting the possibility of whole brain FW maps being used as markers for diagnosis of these disorders.

A Blinded Evaluation of Brain Morphometry for Differential Diagnosis of Atypical Parkinsonism

BACKGROUND

Advanced imaging techniques have been studied for differential diagnosis between PD, MSA, and PSP.

OBJECTIVES

This study aims to validate the utility of individual voxel-based morphometry techniques for atypical parkinsonism in a blinded fashion.

METHODS

Forty-eight healthy controls (HC) T1-WI were used to develop a referential dataset and fit a general linear model after segmentation into gray matter (GM) and white matter (WM) compartments. Segmented GM and WM with PD (n = 96), MSA (n = 18), and PSP (n = 20) were transformed into z-scores using the statistics of referential HC and individual voxel-based z-score maps were generated. An imaging diagnosis was assigned by two independent raters (trained and untrained) blinded to clinical information and final diagnosis. Furthermore, we developed an observer-independent index for ROI-based automated differentiation.

RESULTS

The diagnostic performance using voxel-based z-score maps by rater 1 and rater 2 for MSA yielded sensitivities: 0.89, 0.94 (95% CI: 0.74-1.00, 0.84-1.00), specificities: 0.94, 0.80 (0.90-0.98, 0.73-0.87); for PSP, sensitivities: 0.85, 0.90 (0.69-1.00, 0.77-1.00), specificities: 0.98, 0.94 (0.96-1.00, 0.90-0.98). Interrater agreement was good for MSA (Cohen's kappa: 0.61), and excellent for PSP (0.84). Receiver operating characteristic analysis using the ROI-based new index showed an area under the curve (AUC): 0.89 (0.77-1.00) for MSA, and 0.99 (0.98-1.00) for PSP.

CONCLUSIONS

These evaluations provide support for the utility of this imaging technique in the differential diagnosis of atypical parkinsonism demonstrating a remarkably high differentiation accuracy for PSP, suggesting potential use in clinical settings in the future.

Pathological Validation of the MDS Criteria for the Diagnosis of Multiple System Atrophy

BACKGROUND

The recent International Parkinson and Movement Disorder Society diagnostic criteria for multiple system atrophy (MDS-MSA) have been developed to improve diagnostic accuracy although their diagnostic properties have not been evaluated.

OBJECTIVES

The aims were to validate the MDS-MSA diagnostic criteria against neuropathological diagnosis and compare their diagnostic performance to previous criteria and diagnosis in clinical practice.

METHODS

Consecutive patients with sporadic, progressive, adult-onset parkinsonism, or cerebellar ataxia from the Queen Square Brain Bank between 2009 and 2019 were selected and divided based on neuropathological diagnosis into MSA and non-MSA. Medical records were systematically reviewed, and clinical diagnosis was documented by retrospectively applying the MDS-MSA criteria, second consensus criteria, and diagnosis according to treating clinicians at early (within 3 years of symptom onset) and final stages. Diagnostic parameters (sensitivity, specificity, positive/negative predictive value, and accuracy) were calculated using neuropathological diagnosis as gold standard and compared between different criteria.

RESULTS

Three hundred eighteen patients (103 MSA and 215 non-MSA) were included, comprising 248 patients with parkinsonism and 70 with cerebellar ataxia. Clinically probable MDS-MSA showed excellent sensitivity (95.1%), specificity (94.0%), and accuracy (94.3%), although their sensitivity at early stages was modest (62.1%). Clinically probable MDS-MSA outperformed diagnosis by clinicians and by second consensus criteria. Clinically established MDS-MSA showed perfect specificity (100%) even at early stages although to the detriment of low sensitivity. MDS-MSA diagnostic accuracy did not differ according to clinical presentation (ataxia vs. parkinsonism).

CONCLUSIONS

MDS-MSA criteria demonstrated excellent diagnostic performance against neuropathological diagnosis and are useful diagnostic tools for clinical practice and research. © 2023 International Parkinson and Movement Disorder Society.

Multiple System Atrophy: Advances in Diagnosis and Therapy

This review summarizes improvements in understanding the pathophysiology and early clinical symptoms of multiple system atrophy (MSA) and advancements in diagnostic methods and disease-modifying therapies for the condition. In 2022, the Movement Disorder Society proposed new diagnostic criteria to develop disease-modifying therapies and promote clinical trials of MSA since the second consensus was proposed in 2008. Regarding pathogenesis, cutting-edge findings have accumulated on the interactions of α-synuclein, neuroinflammation, and oligodendroglia with neurons. In neuroimaging, introducing artificial intelligence, machine learning, and deep learning has notably improved diagnostic accuracy and individual analyses. Advancements in treatment have also been achieved, including immunotherapy therapy against α-synuclein and serotonin-targeted and mesenchymal stem cell therapies, which are thought to affect several aspects of the disease, including neuroinflammation. The accelerated progress in clarifying the pathogenesis of MSA over the past few years and the development of diagnostic techniques for detecting early-stage MSA are expected to facilitate the development of disease-modifying therapies for one of the most intractable neurodegenerative diseases.

Magnetic resonance imaging modalities aid in the differential diagnosis of atypical parkinsonian syndromes

Accurate and timely diagnosis of atypical parkinsonian syndromes (APS) remains a challenge. Especially early in the disease course, the clinical manifestations of the APS overlap with each other and with those of idiopathic Parkinson's disease (PD). Recent advances in magnetic resonance imaging (MRI) technology have introduced promising imaging modalities to aid in the diagnosis of APS. Some of these MRI modalities are also included in the updated diagnostic criteria of APS. Importantly, MRI is safe for repeated use and more affordable and accessible compared to nuclear imaging. These advantages make MRI tools more appealing for diagnostic purposes. As the MRI field continues to advance, the diagnostic use of these techniques in APS, alone or in combination, are expected to become commonplace in clinical practice.

Cerebral Small Vessel Disease Is Associated with Motor, Cognitive, and Emotional Dysfunction in Multiple System Atrophy

BACKGROUND

Cerebral small vessel disease (CSVD) has not been systematically studied in patients with multiple system atrophy (MSA).

OBJECTIVE

We sought to explore whether MSA patients suffer from a heavier CSVD burden relative to healthy individuals and whether CSVD has a relationship with motor, cognitive, and emotional dysfunction in patients with MSA.

METHODS

This study consecutively recruited 190 MSA patients and 190 matched healthy controls whose overall CSVD burden and single CSVD imaging markers (including white matter hyperintensity (WMH), microbleeds, lacunes, and enlarged perivascular spaces (EPVS)) were measured. Of the MSA patients, 118 completed multi-dimensional outcome assessments. Spearman's correlations and multivariable linear regressions were performed.

RESULTS

We observed a greater burden of overall CSVD, WMH, and EPVS in MSA patients compared with controls, but not for microbleeds and lacunes. Motor dysfunction and cognitive impairment were significantly worse in subjects with severe CSVD than those with none-to-mild CSVD. In patients with MSA, the severity of CSVD burden was positively associated with motor impairments as measured by the Unified Multiple System Atrophy Rating Scale-II (β= 2.430, p = 0.039) and Scale for the Assessment and Rating of Ataxia (β= 1.882, p = 0.015). Of CSVD imaging markers, different associations with MSA outcomes were displayed. WMH was associated with motor, cognitive, and emotional deficits, while the EPVS in the centrum semiovale, basal ganglia, and hippocampus regions was correlated only with motor severity, anxiety, and cognition, respectively. Similar findings were noted in MSA-cerebellar and MSA-parkinsonian patients.

CONCLUSIONS

Concomitant CSVD may be correlated with worse multi-dimensional dysfunction in patients with MSA.

Diffusion Magnetic Resonance Imaging Microstructural Abnormalities in Multiple System Atrophy: A Comprehensive Review

Multiple system atrophy (MSA) is a neurodegenerative disease characterized by autonomic failure, ataxia, and/or parkinsonism. Its prominent pathological alterations can be investigated using diffusion magnetic resonance imaging (dMRI), a technique that exploits the characteristics of water random motion inside brain tissue. The aim of this report was to review currently available literature on the application of dMRI in MSA and to describe microstructural abnormalities, diagnostic applications, and pathophysiological correlates. Sixty-four published studies involving microstructural investigation using dMRI in MSA were included. Widespread microstructural abnormalities of white matter were described, especially in the middle cerebellar peduncle, corticospinal tract, and hemispheric fibers. Gray matter degeneration was identified as well, with diffuse involvement of subcortical structures, especially in the putamina. Diagnostic applications of dMRI were mostly explored for the differential diagnosis between MSA parkinsonism and Parkinson's disease. Recently, machine learning algorithms for image processing and disease classification have demonstrated high diagnostic accuracy, showing potential for translation into clinical practice. To a lesser extent, clinical correlates of microstructural abnormalities have also been investigated, and abnormalities related to motor, ocular, and cognitive impairments were described. dMRI in MSA has contributed to in vivo identification of known pathological abnormalities. Translation into clinical practice of the latest advancements for the differential diagnosis between MSA and other forms of parkinsonism seems feasible. Current limitations involve the possibility of correctly diagnosing MSA in the very early stages, when the clinical diagnosis is most uncertain. Furthermore, pathophysiological correlates of microstructural abnormalities remain understudied. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Multimodal striatal neuromarkers in distinguishing parkinsonian variant of multiple system atrophy from idiopathic Parkinson's disease

AIMS

To develop an automatic method of classification for parkinsonian variant of multiple system atrophy (MSA-P) and Idiopathic Parkinson's disease (IPD) in early to moderately advanced stages based on multimodal striatal alterations and identify the striatal neuromarkers for distinction.

METHODS

77 IPD and 75 MSA-P patients underwent 3.0 T multimodal MRI comprising susceptibility-weighted imaging, resting-state functional magnetic resonance imaging, T1-weighted imaging, and diffusion tensor imaging. Iron-radiomic features, volumes, functional and diffusion scalars of bilateral 10 striatal subregions were calculated and provided to the support vector machine for classification RESULTS: A combination of iron-radiomic features, function, diffusion, and volumetric measures optimally distinguished IPD and MSA-P in the testing dataset (accuracy 0.911 and area under the receiver operating characteristic curves [AUC] 0.927). The diagnostic performance further improved when incorporating clinical variables into the multimodal model (accuracy 0.934 and AUC 0.953). The most crucial factor for classification was the functional activity of the left dorsolateral putamen.

CONCLUSION

The machine learning algorithm applied to multimodal striatal dysfunction depicted dorsal striatum and supervening prefrontal lobe and cerebellar dysfunction through the frontostriatal and cerebello-striatal connections and facilitated accurate classification between IPD and MSA-P. The dorsolateral putamen was the most valuable neuromarker for the classification.

Multiple system atrophy

Multiple system atrophy (MSA) is a rare neurodegenerative disease that is characterized by neuronal loss and gliosis in multiple areas of the central nervous system including striatonigral, olivopontocerebellar and central autonomic structures. Oligodendroglial cytoplasmic inclusions containing misfolded and aggregated α-synuclein are the histopathological hallmark of MSA. A firm clinical diagnosis requires the presence of autonomic dysfunction in combination with parkinsonism that responds poorly to levodopa and/or cerebellar ataxia. Clinical diagnostic accuracy is suboptimal in early disease because of phenotypic overlaps with Parkinson disease or other types of degenerative parkinsonism as well as with other cerebellar disorders. The symptomatic management of MSA requires a complex multimodal approach to compensate for autonomic failure, alleviate parkinsonism and cerebellar ataxia and associated disabilities. None of the available treatments significantly slows the aggressive course of MSA. Despite several failed trials in the past, a robust pipeline of putative disease-modifying agents, along with progress towards early diagnosis and the development of sensitive diagnostic and progression biomarkers for MSA, offer new hope for patients.

Quantitative susceptibility mapping and blood neurofilament light chain differentiate between parkinsonian disorders

Objectives

We employed quantitative susceptibility mapping (QSM) to assess iron deposition in parkinsonian disorders and explored whether combining QSM values and neurofilament light (NfL) chain levels can improve the accuracy of distinguishing Parkinson’s disease (PD) from multiple system atrophy (MSA) and progressive supranuclear palsy (PSP).

Materials and methods

Forty-seven patients with PD, 28 patients with MSA, 18 patients with PSP, and 28 healthy controls (HC) were enrolled, and QSM data were reconstructed. Susceptibility values in the bilateral globus pallidus (GP), putamen (PUT), caudate nucleus (CN), red nucleus (RN), substantia nigra (SN), and dentate nucleus (DN) were obtained. Plasma NfL levels of 47 PD, 18 MSA, and 14 PSP patients and 22 HC were measured by ultrasensitive Simoa technology.

Results

The highest diagnostic accuracy distinguishing MSA from PD patients was observed with increased susceptibility values in CN (AUC: 0.740). The susceptibility values in RN yielded the highest diagnostic performance for distinguishing PSP from PD patients (AUC: 0.829). Plasma NfL levels were significantly higher in the MSA and PSP groups than in PD and HC groups. Combining the susceptibility values in the RN and plasma NfL levels improved the diagnostic performance for PSP vs. PD (AUC: 0.904), whereas plasma NfL levels had higher diagnostic accuracy for MSA vs. PD (AUC: 0.877).

Conclusion

The exploratory study indicates different patterns of iron accumulation in deep gray matter nuclei in Parkinsonian disorders. Combining QSM values with NfL levels may be a promising biomarker for distinguishing PSP from PD, whereas plasma NfL may be a reliable biomarker for differentiating MSA from PD. QSM and NfL measures appeared to have low accuracy for separating PD from controls.

Morphometric imaging and quantitative susceptibility mapping as complementary tools in the diagnosis of parkinsonisms

Background and purpose

In the quest for in vivo diagnostic biomarkers to discriminate Parkinson's disease (PD) from progressive supranuclear palsy (PSP) and multiple system atrophy (MSA, mainly p phenotype), many advanced magnetic resonance imaging (MRI) techniques have been studied. Morphometric indices, such as the Magnetic Resonance Parkinsonism Index (MRPI), demonstrated high diagnostic value in the comparison between PD and PSP. The potential of quantitative susceptibility mapping (QSM) was hypothesized, as increased magnetic susceptibility (Δχ) was reported in the red nucleus (RN) and medial part of the substantia nigra (SNImed) of PSP patients and in the putamen of MSA patients. However, disease‐specific susceptibility values for relevant regions of interest are yet to be identified. The aims of the study were to evaluate the diagnostic potential of a multimodal MRI protocol combining morphometric and QSM imaging in patients with determined parkinsonisms and to explore its value in a population of undetermined cases.

Method

Patients with suspected degenerative parkinsonism underwent clinical evaluation, 3 T brain MRI and clinical follow‐up. The MRPI was manually calculated on T1‐weighted images. QSM maps were generated from 3D multi‐echo T2*‐weighted sequences.

Results

In determined cases the morphometric evaluation confirmed optimal diagnostic accuracy in the comparison between PD and PSP but failed to discriminate PD from MSA‐p. Significant nigral and extranigral differences were found with QSM. RN Δχ showed excellent diagnostic accuracy in the comparison between PD and PSP and good accuracy in the comparison of PD and MSA‐p. Optimal susceptibility cut‐off values of RN and SNImed were tested in undetermined cases in addition to MRPI.

Conclusions

A combined use of morphometric imaging and QSM could improve the diagnostic phase of degenerative parkinsonisms.

The Movement Disorder Society Criteria for the Diagnosis of Multiple System Atrophy

BACKGROUND

The second consensus criteria for the diagnosis of multiple system atrophy (MSA) are widely recognized as the reference standard for clinical research, but lack sensitivity to diagnose the disease at early stages.

OBJECTIVE

To develop novel Movement Disorder Society (MDS) criteria for MSA diagnosis using an evidence-based and consensus-based methodology.

METHODS

We identified shortcomings of the second consensus criteria for MSA diagnosis and conducted a systematic literature review to answer predefined questions on clinical presentation and diagnostic tools relevant for MSA diagnosis. The criteria were developed and later optimized using two Delphi rounds within the MSA Criteria Revision Task Force, a survey for MDS membership, and a virtual Consensus Conference.

RESULTS

The criteria for neuropathologically established MSA remain unchanged. For a clinical MSA diagnosis a new category of clinically established MSA is introduced, aiming for maximum specificity with acceptable sensitivity. A category of clinically probable MSA is defined to enhance sensitivity while maintaining specificity. A research category of possible prodromal MSA is designed to capture patients in the earliest stages when symptoms and signs are present, but do not meet the threshold for clinically established or clinically probable MSA. Brain magnetic resonance imaging markers suggestive of MSA are required for the diagnosis of clinically established MSA. The number of research biomarkers that support all clinical diagnostic categories will likely grow.

CONCLUSIONS

This set of MDS MSA diagnostic criteria aims at improving the diagnostic accuracy, particularly in early disease stages. It requires validation in a prospective clinical and a clinicopathological study. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Glia Imaging Differentiates Multiple System Atrophy from Parkinson's Disease: A Positron Emission Tomography Study with [11 C]PBR28 and Machine Learning Analysis

BACKGROUND

The clinical diagnosis of multiple system atrophy (MSA) is challenged by overlapping features with Parkinson's disease (PD) and late-onset ataxias. Additional biomarkers are needed to confirm MSA and to advance the understanding of pathophysiology. Positron emission tomography (PET) imaging of the translocator protein (TSPO), expressed by glia cells, has shown elevations in MSA.

OBJECTIVE

In this multicenter PET study, we assess the performance of TSPO imaging as a diagnostic marker for MSA.

METHODS

We analyzed [¹¹ C]PBR28 binding to TSPO using imaging data of 66 patients with MSA and 24 patients with PD. Group comparisons were based on regional analysis of parametric images. The diagnostic readout included visual reading of PET images against clinical diagnosis and machine learning analyses. Sensitivity, specificity, and receiver operating curves were used to discriminate MSA from PD and cerebellar from parkinsonian variant MSA.

RESULTS

We observed a conspicuous pattern of elevated regional [¹¹ C]PBR28 binding to TSPO in MSA as compared with PD, with "hotspots" in the lentiform nucleus and cerebellar white matter. Visual reading discriminated MSA from PD with 100% specificity and 83% sensitivity. The machine learning approach improved sensitivity to 96%. We identified MSA subtype-specific TSPO binding patterns.

CONCLUSIONS

We found a pattern of significantly increased regional glial TSPO binding in patients with MSA. Intriguingly, our data are in line with severe neuroinflammation in MSA. Glia imaging may have potential to support clinical MSA diagnosis and patient stratification in clinical trials on novel drug therapies for an α-synucleinopathy that remains strikingly incurable. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Is clinical assessment enough? Moving towards early differentiation of neurodegenerative parkinsonisms

This scientific commentary refers to ‘Identification of multiple system atrophy mimicking Parkinson’s disease or progressive supranuclear palsy’ by Miki et al. (doi:10.1093/brain/awab017).