Characteristic diffusion tensor tractography in multiple system atrophy with predominant cerebellar ataxia and cortical cerebellar atrophy

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.

Diffusion tensor imaging pipeline measures of cerebral white matter integrity: An overview of recent advances and prospects

Cerebral small vessel disease (CSVD) is a leading cause of age-related microvascular cognitive decline, resulting in significant morbidity and decreased quality of life. Despite a progress on its key pathophysiological bases and general acceptance of key terms from neuroimaging findings as observed on the magnetic resonance imaging (MRI), key questions on CSVD remain elusive. Enhanced relationships and reliable lesion studies, such as white matter tractography using diffusion-based MRI (dMRI) are necessary in order to improve the assessment of white matter architecture and connectivity in CSVD. Diffusion tensor imaging (DTI) and tractography is an application of dMRI that provides data that can be used to non-invasively appraise the brain white matter connections via fiber tracking and enable visualization of individual patient-specific white matter fiber tracts to reflect the extent of CSVD-associated white matter damage. However, due to a lack of standardization on various sets of software or image pipeline processing utilized in this technique that driven mostly from research setting, interpreting the findings remain contentious, especially to inform an improved diagnosis and/or prognosis of CSVD for routine clinical use. In this minireview, we highlight the advances in DTI pipeline processing and the prospect of this DTI metrics as potential imaging biomarker for CSVD, even for subclinical CSVD in at-risk individuals.

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.

Prominent White Matter Involvement in Multiple System Atrophy of Cerebellar Type

BACKGROUND

Sporadic degenerative ataxia patients fall into 2 major groups: multiple system atrophy with predominant cerebellar ataxia (MSA-C) and sporadic adult-onset ataxia (SAOA). Both groups have cerebellar volume loss, but little is known about the differential involvement of gray and white matter in MSA-C when compared with SAOA.

OBJECTIVES

The objective of this study was to identify structural differences of brain gray and white matter between both patient groups.

METHODS

We used magnetic resonance imaging to acquire T1-weighted images and diffusion tensor images from 12 MSA-C patients, 31 SAOA patients, and 55 healthy controls. Magnetic resonance imaging data were analyzed with voxel-based-morphometry, tract-based spatial statistics, and tractography-based regional diffusion tensor images analysis.

RESULTS

Whole-brain and cerebellar-focused voxel-based-morphometry analysis showed gray matter volume loss in both patient groups when compared with healthy controls, specifically in the cerebellar areas subserving sensorimotor functions. When compared with controls, the SAOA and MSA-C patients showed white matter loss in the cerebellum, whereas brainstem white matter was reduced only in the MSA-C patients. The tract-based spatial statistics revealed reduced fractional anisotropy within the pons and cerebellum in the MSA-C patients both in comparison with the SAOA patients and healthy controls. In addition, tractography-based regional analysis showed reduced fractional anisotropy along the corticospinal tracts in MSA-C, but not SAOA.

CONCLUSION

Although in our cohort extent and distribution of gray and white matter loss were similar between the MSA-C and SAOA patients, magnetic resonance imaging data showed prominent microstructural white matter involvement in the MSA-C patients that was not present in the SAOA patients. Our findings highlight the significance of microstructural white matter changes in the differentiation between both conditions. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Differentiation Between Multiple System Atrophy and Other Spinocerebellar Degenerations Using Diffusion Kurtosis Imaging

RATIONALE AND OBJECTIVE

Differentiation between multiple system atrophy (MSA) and other spinocerebellar degenerations showing cerebellar ataxia is often difficult. Hence, we investigated whether magnetic resonance diffusion kurtosis imaging (DKI) could detect pathological changes that occur in these patients and be used for differential diagnosis.

METHODS

Thirty-six subjects (12 patients with MSA accompanied by predominant cerebellar ataxia [MSA-C], 10 patients with spinocerebellar ataxias [SCAs] or sporadic adult-onset ataxia of unknown etiology [SAOA], and 14 healthy controls) were examined using 1.5- or 3-T magnetic resonance scanners. From the DKI data, the mean kurtosis, fractional anisotropy, and mean diffusivity values of the pontine crossing tract (PCT), middle cerebellar peduncle, and cerebellum were automatically measured, and the ratios against the values of the corpus callosum were calculated.

RESULTS

We found significant decreases in mean kurtosis and fractional anisotropy ratios in the PCT and middle cerebellar peduncle, and a significant increase in the mean diffusivity ratio in the PCT in the MSA-C group, as compared with the SCA/SAOA and control groups (p < 0.027-0.001). Among these metrics, there were no significant differences in the diagnostic performance. By contrast, the ratios in the cerebellum showed no significant differences between the MSA-C and SCA/SAOA groups but were significantly altered when compared with the controls (p < 0.001).

CONCLUSION

Quantitative DKI analyses can be used to differentiate between patients with MSA-C and those with SCA/SAOA.

MRI-based neuroimaging: atypical parkinsonisms and other movement disorders

PURPOSE OF REVIEW

MRI has become a well established technical tool for parkinsonism both in the diagnostic work-up to differentiate between causes and to serve as a neurobiological marker. This review summarizes current developments in the advanced MRI-based assessment of brain structure and function in atypical parkinsonian syndromes and explores their potential in a clinical and neuroscientific setting.

RECENT FINDINGS

Computer-based unbiased quantitative MRI analyses were demonstrated to guide in the discrimination of parkinsonian syndromes at single-patient level, with major contributions when combined with machine-learning techniques/support vector machine classification. These techniques have shown their potential in tracking the disease progression, perhaps also as a read-out in clinical trials. The characterization of different brain compartments at various levels of structural and functional alterations can be provided by multiparametric MRI, including a growing variety of diffusion-weighted imaging approaches and potentially iron-sensitive and functional MRI.

SUMMARY

In case that the recent advances in the MRI-based assessment of atypical parkinsonism will lead to standardized protocols for image acquisition and analysis after the confirmation in large-scale multicenter studies, these approaches may constitute a great achievement in the (operator-independent) detection, discrimination and characterization of degenerative parkinsonian disorders at an individual basis.