Conventional 3T brain MRI and diffusion tensor imaging in the diagnostic workup of early stage parkinsonism

Distinct patterns of electrophysiologic-neuroimaging correlations between Parkinson's disease and multiple system atrophy

Due to a high degree of symptom overlap in the early stages, with movement disorders predominating, Parkinson's disease (PD) and multiple system atrophy (MSA) may exhibit a similar decline in motor areas, yet they differ in their spread throughout the brain, ultimately resulting in two distinct diseases. Drawing upon neuroimaging analyses and altered motor cortex excitability, potential diffusion mechanisms were delved into, and comparisons of correlations across distinct disease groups were conducted in a bid to uncover significant pathological disparities. We recruited thirty-five PD, thirty-seven MSA, and twenty-eight matched controls to conduct clinical assessments, electromyographic recording, and magnetic resonance imaging scanning during the "on medication" state. Patients with neurodegeneration displayed a widespread decrease in electrophysiology in bilateral M1. Brain function in early PD was still in the self-compensatory phase and there was no significant change. MSA patients demonstrated an increase in intra-hemispheric function coupled with a decrease in diffusivity, indicating a reduction in the spread of neural signals. The level of resting motor threshold in healthy aged showed broad correlations with both clinical manifestations and brain circuits related to left M1, which was absent in disease states. Besides, ICF exhibited distinct correlations with functional connections between right M1 and left middle temporal gyrus in all groups. The present study identified subtle differences in the functioning of PD and MSA related to bilateral M1. By combining clinical information, cortical excitability, and neuroimaging intuitively, we attempt to bring light on the potential mechanisms that may underlie the development of neurodegenerative disease.

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.

Differentiation of Parkinson’s disease and Parkinsonism predominant multiple system atrophy in early stage by morphometrics in susceptibility weighted imaging

Background and purpose

We previously established a radiological protocol to discriminate multiple system atrophy-parkinsonian subtype (MSA-P) from Parkinson’s disease (PD). However, we do not know if it can differentiate early stage disease. This study aimed to investigate whether the morphological and intensity changes in susceptibility weighted imaging (SWI) of the lentiform nucleus (LN) could discriminate MSA-P from PD at early stages.

Methods

We retrospectively enrolled patients with MSA-P, PD and sex- and age-matched controls whose brain MRI included SWI, between January 2015 and July 2020 at the Movement Disorder Center. Two specialists at the center reviewed the medical records and made the final diagnosis, and two experienced neuroradiologists performed MRI analysis, based on a defined and revised protocol for conducting morphological measurements of the LN and signal intensity.

Results

Nineteen patients with MSA-P and 19 patients with PD, with less than 2 years of disease duration, and 19 control individuals were enrolled in this study. We found that patients with MSA- P presented significantly decreased size in the short line (SL) and corrected short line (cSL), ratio of the SL to the long line (SLLr) and corrected SLLr (cSLLr) of the LN, increased standard deviation of signal intensity (SIsd_LN, cSIsd_LN) compared to patients with PD and controls (P < 0.05). With receiver operating characteristic (ROC) analysis, this finding had a sensitivity of 89.5% and a specificity of 73.7% to distinguish MSA- P from PD.

Conclusion

Compared to PD and controls, patients with MSA-P are characterized by a narrowing morphology of the posterior region of the LN. Quantitative morphological changes provide a reference for clinical auxiliary diagnosis.

Cerebellar Microstructural Abnormalities in Parkinson's Disease: a Systematic Review of Diffusion Tensor Imaging Studies

Diffusion tensor imaging (DTI) is now having a strong momentum in research to evaluate the neural fibers of the CNS. This technique can study white matter (WM) microstructure in neurodegenerative disorders, including Parkinson's disease (PD). Previous neuroimaging studies have suggested cerebellar involvement in the pathogenesis of PD, and these cerebellum alterations can correlate with PD symptoms and stages. Using the PRISMA 2020 framework, PubMed and EMBASE were searched to retrieve relevant articles. Our search revealed 472 articles. After screening titles and abstracts, and full-text review, and implementing the inclusion criteria, 68 papers were selected for synthesis. Reviewing the selected studies revealed that the patterns of reduction in cerebellum WM integrity, assessed by fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity measures can differ symptoms and stages of PD. Cerebellar diffusion tensor imaging (DTI) changes in PD patients with "postural instability and gait difficulty" are significantly different from "tremor dominant" PD patients. Freezing of the gate is strongly related to cerebellar involvement depicted by DTI. The "reduced cognition," "visual disturbances," "sleep disorders," "depression," and "olfactory dysfunction" are not related to cerebellum microstructural changes on DTI, while "impulsive-compulsive behavior" can be linked to cerebellar WM alteration. Finally, higher PD stages and longer disease duration are associated with cerebellum white matter alteration depicted by DTI. Depiction of cerebellar white matter involvement in PD is feasible by DTI. There is an association with disease duration and severity and several clinical presentations with DTI findings. This clinical-imaging association may eventually improve disease management.

Diffusion Tensor Imaging Radiomics for Diagnosis of Parkinson’s Disease

Background: Diagnosis of Parkinson’s Disease (PD) based on clinical symptoms and scale scores is mostly objective, and the accuracy of neuroimaging for PD diagnosis remains controversial. This study aims to introduce a radiomic tool to improve the sensitivity and specificity of diagnosis based on Diffusion Tensor Imaging (DTI) metrics. Methods: In this machine learning-based retrospective study, we collected basic clinical information and DTI images from 54 healthy controls (HCs) and 56 PD patients. Among them, 60 subjects (30 PD patients and 30 HCs) were assigned to the training group, whereas the test cohort was 26 PD patients and 24 HCs. After the feature extraction and selection using newly developed image processing software Ray-plus, LASSO regression was used to finalize radiomic features. Results: A total of 4600 radiomic features were extracted, of which 12 were finally selected. The values of the AUC (area under the subject operating curve) in the training group, the validation group, and overall were 0.911, 0.931, and 0.919, respectively. Conclusion: This study introduced a novel radiometric and computer algorithm based on DTI images, which can help increase the sensitivity and specificity of PD screening.

The “Black Straight-Line Sign” in the Putamen in Diffusion-Weighted Imaging: A Potential Diagnostic MRI Marker for Multiple System Atrophy

Background and Purpose

The diagnosis of multiple system atrophy (MSA) remains challenging in clinical practice. This study investigated the value of hypointense signals in the putamen (“black straight-line sign”) in diffusion-weighted imaging (DWI) of brain MRI for distinguishing (MSA) from Parkinson's disease (PD).

Methods

We retrospectively enrolled 30 MSA patients, 30 PD patients, and 30 healthy controls who had undergone brain MRI between 2016 and 2020. Two readers independently assessed the signal intensity of the bilateral putamen on DWI. The putaminal hypointensity was scored using 4-point visual scales. Putaminal hypointensity and the presence of a “black straight-line sign” were statistically compared between MSA and PD or healthy controls.

Results

The mean scores of putaminal hypointensity in DWI in the MSA group were significantly higher than in both the PD (U = 315.5, P = 0.034) and healthy control groups (U = 304.0, P = 0.022). Uni- or bilateral putaminal hypointensity in DWI with a score ≥2 was identified in 53.3% (16/30), 16.7% (5/30), and 13.3% (4/30) of MSA, PD, and healthy controls, respectively, with significant differences between MSA and PD (X² = 8.864, P = 0.003) or healthy controls (X² = 10.800, P = 0.001). Notably, the “black straight-line sign” of the putamen was observed in 16/30 (sensitivity 53.3%) patients with MSA, while it was absent in PD and healthy controls (specificity 100%). There were no significant differences for the presence of “black straight-line sign” in the MSA-P and MSA-C groups (X² = 0.433, P = 0.510).

Conclusion

The “black straight-line sign” of the putamen in DWI of head MRIs has the potential to serve as a diagnostic marker for distinguishing MSA from PD.

Characterization and diagnostic potential of diffusion tractography in multiple system atrophy

INTRODUCTION

Microstructural integrity of the middle cerebellar peduncle (MCP) and the putamen captured by diffusion-tensor imaging (DTI) is differentially affected in the parkinsonian and cerebellar variants of multiple system atrophy (MSA-P, MSA-C) compared to Parkinson's disease (PD). The current study applied DTI and tractography in order to 1) characterize the distribution of DTI metrics along the tracts of the MCP and from the putamen in MSA variants, and 2) evaluate the usefulness of combining these measures for the differential diagnosis of MSA-P against PD in the clinical setting.

METHODS

Twenty-nine MSA patients (MSA-C, n = 10; MSA-P, n = 19), with a mean disease duration of 2.8 ± 1.7 years, 19 PD patients, and 27 healthy controls (HC) were included in the study. Automatized tractography with a masking procedure was employed to isolate the MCP tracts. DTI measures along the tracts of the MCP and within the putamen were acquired and jointly used to classify MSA vs. PD, and MSA-P vs. PD. Putamen volume was additionally tested as classification feature in post hoc analyses.

RESULTS

DTI measures within the MCP and putamen showed significant alterations in MSA variants compared to HC and PD. Classification accuracy for MSA vs. PD and MSA-P vs PD using diffusion measures was 91.7% and 89.5%, respectively. When replacing the putaminal DTI measure by a normalized measure of putamen volume classification accuracy improved to 95.8% and 94.7%, respectively.

CONCLUSION

Multimodal information from MCP tractography and putamen volume yields excellent diagnostic accuracy to discriminate between early-to-moderately advanced patients with MSA and PD.

Substantia nigra micro-haemorrhage causing ipsilateral unilateral Parkinsonism and abnormal dopamine transporter scan uptake

Parkinsonism is a commonly seen movement disorder syndrome with neurodegenerative and non-neurodegenerative causes. Presynaptic dopamine transporter (DaT) single-photon emission computed tomography (SPECT) imaging is the most commonly used imaging technique in clinical practice to differentiate degenerative Parkinson's disease (PD) and PD plus syndromes from other causes such as essential tremor and drug-induced parkinsonism. This can help identify the patients who would benefit from medical therapy due to underlying pre-synaptic dopaminergic deficits. We report a case of unilateral parkinsonism caused by ipsilateral substantia nigra micro-haemorrhage resulting in disruption of the nigrostriatal pathway. This is an unusual case of a 55-year-old male patient who presented with unilateral Parkinsonism a decade after significant head trauma where MRI plays a critical and complementary role in diagnosing complete interruption of the nigrostriatal pathway due to cerebral micro-haemorrhage. The case also beautifully demonstrates the anatomy of the nigrostriatal pathway where a small lesion in the substantia nigra caused complete loss of radioligand uptake in the ipsilateral corpus striatum. Physicians should be aware of the importance of structural imaging in atypical movement disorder cases and, in particular, the routine use of susceptibility-weighted sequences (SWI).

Assessing White Matter Pathology in Early-Stage Parkinson Disease Using Diffusion MRI: A Systematic Review

Structural brain white matter (WM) changes such as axonal caliber, density, myelination, and orientation, along with WM-dependent structural connectivity, may be impacted early in Parkinson disease (PD). Diffusion magnetic resonance imaging (dMRI) has been used extensively to understand such pathological WM changes, and the focus of this systematic review is to understand both the methods utilized and their corresponding results in the context of early-stage PD. Diffusion tensor imaging (DTI) is the most commonly utilized method to probe WM pathological changes. Previous studies have suggested that DTI metrics are sensitive in capturing early disease-associated WM changes in preclinical symptomatic regions such as olfactory regions and the substantia nigra, which is considered to be a hallmark of PD pathology and progression. Postprocessing analytic approaches include region of interest–based analysis, voxel-based analysis, skeletonized approaches, and connectome analysis, each with unique advantages and challenges. While DTI has been used extensively to study WM disorganization in early-stage PD, it has several limitations, including an inability to resolve multiple fiber orientations within each voxel and sensitivity to partial volume effects. Given the subtle changes associated with early-stage PD, these limitations result in inaccuracies that severely impact the reliability of DTI-based metrics as potential biomarkers. To overcome these limitations, advanced dMRI acquisition and analysis methods have been employed, including diffusion kurtosis imaging and q-space diffeomorphic reconstruction. The combination of improved acquisition and analysis in DTI may yield novel and accurate information related to WM-associated changes in early-stage PD. In the current article, we present a systematic and critical review of dMRI studies in early-stage PD, with a focus on recent advances in DTI methodology. Yielding novel metrics, these advanced methods have been shown to detect diffuse WM changes in early-stage PD. These findings support the notion of early axonal damage in PD and suggest that WM pathology may go unrecognized until symptoms appear. Finally, the advantages and disadvantages of different dMRI techniques, analysis methods, and software employed are discussed in the context of PD-related pathology.

Frontrunner in Translation: Progressive Supranuclear Palsy

Progressive supranuclear palsy (PSP) is a four-repeat tau proteinopathy. Abnormal tau deposition is not unique for PSP and is the basic pathologic finding in some other neurodegenerative disorders such as Alzheimer's disease (AD), age-related tauopathy, frontotemporal degeneration, corticobasal degeneration, and chronic traumatic encephalopathy. While AD research has mostly been focused on amyloid beta pathology until recently, PSP as a prototype of a primary tauopathy with high clinical-pathologic correlation and a rapid course is a crucial candidate for tau therapeutic research. Several novel approaches to slow disease progression are being developed. It is expected that the benefits of translational research in this disease will extend beyond the PSP population. This article reviews advances in the diagnosis, epidemiology, pathology, hypothesized etiopathogenesis, and biomarkers and disease-modifying therapeutic approaches of PSP that is leading it to become a frontrunner in translation.

An update on advances in magnetic resonance imaging of multiple system atrophy

In this review, we describe how different neuroimaging tools have been used to identify novel MSA biomarkers, highlighting their advantages and limitations. First, we describe the main structural MRI changes frequently associated with MSA including the 'hot cross-bun' and 'putaminal rim' signs as well as putaminal, pontine, and middle cerebellar peduncle (MCP) atrophy. We discuss the sensitivity and specificity of different supra- and infratentorial changes in differentiating MSA from other disorders, highlighting those that can improve diagnostic accuracy, including the MCP width and MCP/superior cerebellar peduncle (SCP) ratio on T1-weighted imaging, raised putaminal diffusivity on diffusion-weighted imaging, and increased T2* signal in the putamen, striatum, and substantia nigra on susceptibility-weighted imaging. Second, we focus on recent advances in structural and functional MRI techniques including diffusion tensor imaging (DTI), resting-state functional MRI (fMRI), and arterial spin labelling (ASL) imaging. Finally, we discuss new approaches for MSA research such as multimodal neuroimaging strategies and how such markers may be applied in clinical trials to provide crucial data for accurately selecting patients and to act as secondary outcome measures.

Role of Neuroimaging on Differentiation of Parkinson's Disease and Its Related Diseases

An accurate diagnosis of Parkinson's disease (PD) is a prerequisite for therapeutic management. In spite of recent advances in the diagnosis of parkinsonian disorders, PD is misdiagnosed in between 6 and 25% of patients, even in specialized movement disorder centers. Although the gold standard for the diagnosis of PD is a neuropathological assessment, neuroimaging has been playing an important role in the differential diagnosis of PD and is used for clinical diagnostic criteria. In clinical practice, differential diagnoses of PD include atypical parkinsonian syndromes such as dementia with Lewy bodies, multiple system atrophy, progressive supranuclear palsy, corticobasal degeneration, caused by a striatal dopamine deficiency following nigrostrial degeneration. PD may also be mimicked by syndromes not associated with a striatal dopamine deficiency such as essential tremor, drug-induced parkinsonism, and vascular parkinsonism. Moreover, difficulties are associated with the clinical differentiation of patients with parkinsonism from those with Alzheimer's disease. In this review, we summarize the typical imaging findings of PD and its related diseases described above using morphological imaging modalities (conventional MR imaging and neuromelanin MR imaging) and functional imaging modalities (^99mTc-ethyl cysteinate dimer perfusion single photon emission computed tomography, ¹²³I-metaiodobenzylguanidine myocardial scintigraphy, and ¹²³I-FP-CIT dopamine transporter single photon emission computed tomography) that are clinically available in most hospitals. We also attempt to provide a diagnostic approach for the differential diagnosis of PD and its related diseases in clinical practice.

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.

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.

Differential diagnosis of parkinsonism by a combined use of diffusion kurtosis imaging and quantitative susceptibility mapping

PURPOSE

We investigated whether diffusion kurtosis imaging (DKI) and quantitative susceptibility mapping (QSM) could detect pathological changes that occur in Parkinson's disease (PD), multiple system atrophy with predominant parkinsonism (MSA-P) or predominant cerebellar ataxia (MSA-C), and progressive supranuclear palsy syndrome (PSPS) and thus be used for differential diagnosis that is often difficult.

METHODS

Seventy patients (41 with PD, 6 with MSA-P, 7 with MSA-C, 16 with PSPS) and 20 healthy controls were examined using a 3.0 T MRI scanner. From DKI and QSM data, we automatically obtained mean kurtosis (MK), fractional anisotropy (FA), and mean diffusivity (MD) values of the midbrain tegmentum (MBT), pontine crossing tract (PCT), and superior/middle cerebellar peduncles (CPs), which were used to calculate diffusion MBT/PCT ratios (dMPRs) and diffusion superior/middle CP ratios (dCPRs), as well as MS (magnetic susceptibility) values of the anterior/posterior putamen (PUa and PUp) and globus pallidus (GP).

RESULTS

dMPRs of MK were significantly decreased in PSPS and increased in MSA-C compared with the other groups, while dCPRs of MK showed significant differences only between MSA-C and PD, PSPS, or control. MS values were significantly increased in the PUp of MSA-P and in the PUa and GP of PSPS compared with those in PD. The combined use of MK-dMPR and MS-PUp showed sensitivities of 83-100% and specificities of 81-100% for discriminating among the disease groups, respectively.

CONCLUSION

A quantitative assessment using DKI and QSM analyses, particularly MK-dMPR and MS-PUp values, can readily identify patients with parkinsonism.

Radiological biomarkers for diagnosis in PSP: Where are we and where do we need to be?

PSP is a pathologically defined neurodegenerative tauopathy with a variety of clinical presentations including typical Richardson's syndrome and other variant PSP syndromes. A large body of neuroimaging research has been conducted over the past two decades, with many studies proposing different structural MRI and molecular PET/SPECT biomarkers for PSP. These include measures of brainstem, cortical and striatal atrophy, diffusion weighted and diffusion tensor imaging abnormalities, [18F] fluorodeoxyglucose PET hypometabolism, reductions in striatal dopamine imaging and, most recently, PET imaging with ligands that bind to tau. Our aim was to critically evaluate the degree to which structural and molecular neuroimaging metrics fulfill criteria for diagnostic biomarkers of PSP. We queried the PubMed, Cochrane, Medline, and PSYCInfo databases for original research articles published in English over the past 20 years using postmortem diagnosis or the NINDS-SPSP criteria as the diagnostic standard from 1996 to 2016. We define a five-level theoretical construct for the utility of neuroimaging biomarkers in PSP, with level 1 representing group-level findings, level 2 representing biomarkers with demonstrable individual-level diagnostic utility, level 3 representing biomarkers for early disease, level 4 representing surrogate biomarkers of PSP pathology, and level 5 representing definitive PSP biomarkers of PSP pathology. We discuss the degree to which each of the currently available biomarkers fit into this theoretical construct, consider the role of biomarkers in the diagnosis of Richardson's syndrome, variant PSP syndromes and autopsy confirmed PSP, and emphasize current shortfalls in the field. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Imaging biomarkers in Parkinson's disease and Parkinsonian syndromes: current and emerging concepts

Two centuries ago in 1817, James Parkinson provided the first medical description of Parkinson’s disease, later refined by Jean-Martin Charcot in the mid-to-late 19th century to include the atypical parkinsonian variants (also termed, Parkinson-plus syndromes). Today, Parkinson’s disease represents the second most common neurodegenerative disorder with an estimated global prevalence of over 10 million. Conversely, atypical parkinsonian syndromes encompass a group of relatively heterogeneous disorders that may share some clinical features with Parkinson’s disease, but are uncommon distinct clinicopathological diseases. Decades of scientific advancements have vastly improved our understanding of these disorders, including improvements in in vivo imaging for biomarker identification. Multimodal imaging for the visualization of structural and functional brain changes is especially important, as it allows a ‘window’ into the underlying pathophysiological abnormalities. In this article, we first present an overview of the cardinal clinical and neuropathological features of, 1) synucleinopathies: Parkinson’s disease and other Lewy body spectrum disorders, as well as multiple system atrophy, and 2) tauopathies: progressive supranuclear palsy, and corticobasal degeneration. A comprehensive presentation of well-established and emerging imaging biomarkers for each disorder are then discussed. Biomarkers for the following imaging modalities are reviewed: 1) structural magnetic resonance imaging (MRI) using T1, T2, and susceptibility-weighted sequences for volumetric and voxel-based morphometric analyses, as well as MRI derived visual signatures, 2) diffusion tensor MRI for the assessment of white matter tract injury and microstructural integrity, 3) proton magnetic resonance spectroscopy for quantifying proton-containing brain metabolites, 4) single photon emission computed tomography for the evaluation of nigrostriatal integrity (as assessed by presynaptic dopamine transporters and postsynaptic dopamine D2 receptors), and cerebral perfusion, 5) positron emission tomography for gauging nigrostriatal functions, glucose metabolism, amyloid and tau molecular imaging, as well as neuroinflammation, 6) myocardial scintigraphy for dysautonomia, and 7) transcranial sonography for measuring substantia nigra and lentiform nucleus echogenicity. Imaging biomarkers, using the ‘multimodal approach’, may aid in making early, accurate and objective diagnostic decisions, highlight neuroanatomical and pathophysiological mechanisms, as well as assist in evaluating disease progression and therapeutic responses to drugs in clinical trials.

A Fully Automated, Atlas-Based Approach for Superior Cerebellar Peduncle Evaluation in Progressive Supranuclear Palsy Phenotypes

BACKGROUND AND PURPOSE

The superior cerebellar peduncle is damaged in progressive supranuclear palsy. However, alterations differ between progressive supranuclear palsy with Richardson syndrome and progressive supranuclear palsy-parkinsonism. In this study, we propose an automated tool for superior cerebellar peduncle integrity assessment and test its performance in patients with progressive supranuclear palsy with Richardson syndrome, progressive supranuclear palsy-parkinsonism, Parkinson disease, and healthy controls.

MATERIALS AND METHODS

Structural and diffusion MRI was performed in 21 patients with progressive supranuclear palsy with Richardson syndrome, 9 with progressive supranuclear palsy-parkinsonism, 20 with Parkinson disease, and 30 healthy subjects. In a fully automated pipeline, the left and right superior cerebellar peduncles were first identified on MR imaging by using a tractography-based atlas of white matter tracts; subsequently, volume, mean diffusivity, and fractional anisotropy were extracted from superior cerebellar peduncles. These measures were compared across groups, and their discriminative power in differentiating patients was evaluated in a linear discriminant analysis.

RESULTS

Compared with those with Parkinson disease and controls, patients with progressive supranuclear palsy with Richardson syndrome showed alterations of all superior cerebellar peduncle metrics (decreased volume and fractional anisotropy, increased mean diffusivity). Patients with progressive supranuclear palsy-parkinsonism had smaller volumes than those with Parkinson disease and controls and lower fractional anisotropy than those with Parkinson disease. Patients with progressive supranuclear palsy with Richardson syndrome had significantly altered fractional anisotropy and mean diffusivity in the left superior cerebellar peduncle compared with those with progressive supranuclear palsy-parkinsonism. Discriminant analysis with the sole use of significant variables separated progressive supranuclear palsy-parkinsonism from progressive supranuclear palsy with Richardson syndrome with 70% accuracy and progressive supranuclear palsy-parkinsonism from Parkinson disease with 74% accuracy.

CONCLUSIONS

We demonstrate the feasibility of an automated approach for extracting multimodal MR imaging metrics from the superior cerebellar peduncle in healthy subjects and patients with parkinsonian. We provide evidence that structural and diffusion measures of the superior cerebellar peduncle might be valuable for computer-aided diagnosis of progressive supranuclear palsy subtypes and for differentiating patients with progressive supranuclear palsy-parkinsonism from with those with Parkinson disease.

Brain MR Contribution to the Differential Diagnosis of Parkinsonian Syndromes: An Update

Brain magnetic resonance (MR) represents a useful and feasible tool for the differential diagnosis of Parkinson's disease. Conventional MR may reveal secondary forms of parkinsonism and may show peculiar brain alterations of atypical parkinsonian syndromes. Furthermore, advanced MR techniques, such as morphometric-volumetric analyses, diffusion-weighted imaging, diffusion tensor imaging, tractography, proton MR spectroscopy, and iron-content sensitive imaging, have been used to obtain quantitative parameters useful to increase the diagnostic accuracy. Currently, many MR studies have provided both qualitative and quantitative findings, reflecting the underlying neuropathological pattern of the different degenerative parkinsonian syndromes. Although the variability in the methods and results across the studies limits the conclusion about which technique is the best, specific radiologic phenotypes may be identified. Qualitative/quantitative MR changes in the substantia nigra do not discriminate between different parkinsonisms. In the absence of extranigral abnormalities, the diagnosis of PD is more probable, whereas basal ganglia changes (mainly in the putamen) suggest the diagnosis of an atypical parkinsonian syndrome. In this context, changes in pons, middle cerebellar peduncles, and cerebellum suggest the diagnosis of MSA, in midbrain and superior cerebellar peduncles the diagnosis of PSP, and in whole cerebral hemispheres (mainly in frontoparietal cortex with asymmetric distribution) the diagnosis of Corticobasal Syndrome.

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.

Alterations of Diffusion Kurtosis and Neurite Density Measures in Deep Grey Matter and White Matter in Parkinson's Disease

In Parkinson’s disease (PD), pathological microstructural changes occur and such changes might be detected using diffusion magnetic resonance imaging (dMRI). However, it is unclear whether dMRI improves PD diagnosis or helps differentiating between phenotypes, such as postural instability gait difficulty (PIGD) and tremor dominant (TD) PD. We included 105 patients with PD and 44 healthy controls (HC), all of whom underwent dMRI as part of the prospective Swedish BioFINDER study. Diffusion kurtosis imaging (DKI) and neurite density imaging (NDI) analyses were performed using regions of interest in the basal ganglia, the thalamus, the pons and the midbrain as well as tractography of selected white matter tracts. In the putamen, the PD group showed increased mean diffusivity (MD) (p = .003), decreased fractional anisotropy (FA) (p = .001) and decreased mean kurtosis (MK), compared to HC (p = .024). High MD and a low MK in the putamen were associated with more severe motor and cognitive symptomatology (p < .05). Also, patients with PIGD exhibited increased MD in the putamen compared to the TD patients (p = .009). In the thalamus, MD was increased (p = .001) and FA was decreased (p = .032) in PD compared to HC. Increased MD and decreased FA correlated negatively with motor speed and balance (p < .05). In the superior longitudinal fasciculus (SLF), MD (p = .019) and f_iso were increased in PD compared to HC (p = .03). These changes correlated negatively with motor speed (p < .002) and balance (p < .037). However, most of the observed changes in PD were also present in cases with either multiple system atrophy (n = 11) or progressive supranuclear palsy (n = 10). In conclusion, PD patients exhibit microstructural changes in the putamen, the thalamus, and the SLF, which are associated with worse disease severity. However, the dMRI changes are not sufficiently specific to improve the diagnostic work-up of PD. Longitudinal studies should evaluate whether dMRI measures can be used to track disease progression.

Automated Differential Diagnosis of Early Parkinsonism Using Metabolic Brain Networks: A Validation Study

The differentiation of idiopathic Parkinson disease (IPD) from multiple system atrophy (MSA) and progressive supranuclear palsy (PSP), the most common atypical parkinsonian look-alike syndromes (APS), can be clinically challenging. In these disorders, diagnostic inaccuracy is more frequent early in the clinical course when signs and symptoms are mild. Diagnostic inaccuracy may be particularly relevant in trials of potential disease-modifying agents, which typically involve participants with early clinical manifestations. In an initial study, we developed a probabilistic algorithm to classify subjects with clinical parkinsonism but uncertain diagnosis based on the expression of metabolic covariance patterns for IPD, MSA, and PSP. Classifications based on this algorithm agreed closely with final clinical diagnosis. Nonetheless, blinded prospective validation is required before routine use of the algorithm can be considered.

METHODS

We used metabolic imaging to study an independent cohort of 129 parkinsonian subjects with uncertain diagnosis; 77 (60%) had symptoms for 2 y or less at the time of imaging. After imaging, subjects were followed by blinded movement disorders specialists for an average of 2.2 y before final diagnosis was made. When the algorithm was applied to the individual scan data, the probabilities of IPD, MSA, and PSP were computed and used to classify each of the subjects. The resulting image-based classifications were then compared with the final clinical diagnosis.

RESULTS

IPD subjects were distinguished from APS with 94% specificity and 96% positive predictive value (PPV) using the original 2-level logistic classification algorithm. The algorithm achieved 90% specificity and 85% PPV for MSA and 94% specificity and 94% PPV for PSP. The diagnostic accuracy was similarly high (specificity and PPV > 90%) for parkinsonian subjects with short symptom duration. In addition, 25 subjects were classified as level I indeterminate parkinsonism and 4 more subjects as level II indeterminate APS.

CONCLUSION

Automated pattern-based image classification can improve the diagnostic accuracy in patients with parkinsonism, even at early disease stages.