Manual MRI morphometry in Parkinsonian syndromes

Simple biomarkers to distinguish Parkinson's disease from its mimics in clinical practice: a comprehensive review and future directions

In the last few years, a plethora of biomarkers have been proposed for the differentiation of Parkinson's disease (PD) from its mimics. Most of them consist of complex measures, often based on expensive technology, not easily employed outside research centers. MRI measures have been widely used to differentiate between PD and other parkinsonism. However, these measurements were often performed manually on small brain areas in small patient cohorts with intra- and inter-rater variability. The aim of the current review is to provide a comprehensive and updated overview of the literature on biomarkers commonly used to differentiate PD from its mimics (including parkinsonism and tremor syndromes), focusing on parameters derived by simple qualitative or quantitative measurements that can be used in routine practice. Several electrophysiological, sonographic and MRI biomarkers have shown promising results, including the blink-reflex recovery cycle, tremor analysis, sonographic or MRI assessment of substantia nigra, and several qualitative MRI signs or simple linear measures to be directly performed on MR images. The most significant issue is that most studies have been conducted on small patient cohorts from a single center, with limited reproducibility of the findings. Future studies should be carried out on larger international cohorts of patients to ensure generalizability. Moreover, research on simple biomarkers should seek measurements to differentiate patients with different diseases but similar clinical phenotypes, distinguish subtypes of the same disease, assess disease progression, and correlate biomarkers with pathological data. An even more important goal would be to predict the disease in the preclinical phase.

Multimodal neuroimaging to characterize symptom-specific networks in movement disorders

Movement disorders, such as Parkinson's disease, essential tremor, and dystonia, are characterized by their predominant motor symptoms, yet diseases causing abnormal movement also encompass several other symptoms, including non-motor symptoms. Here we review recent advances from studies of brain lesions, neuroimaging, and neuromodulation that provide converging evidence on symptom-specific brain networks in movement disorders. Although movement disorders have traditionally been conceptualized as disorders of the basal ganglia, cumulative data from brain lesions causing parkinsonism, tremor and dystonia have now demonstrated that this view is incomplete. Several recent studies have shown that lesions causing a given movement disorder occur in heterogeneous brain locations, but disrupt common brain networks, which appear to be specific to each motor phenotype. In addition, findings from structural and functional neuroimaging in movement disorders have demonstrated that brain abnormalities extend far beyond the brain networks associated with the motor symptoms. In fact, neuroimaging findings in each movement disorder are strongly influenced by the constellation of patients' symptoms that also seem to map to specific networks rather than individual anatomical structures or single neurotransmitters. Finally, observations from deep brain stimulation have demonstrated that clinical changes, including both symptom improvement and side effects, are dependent on the modulation of large-scale networks instead of purely local effects of the neuromodulation. Combined, this multimodal evidence suggests that symptoms in movement disorders arise from distinct brain networks, encouraging multimodal imaging studies to better characterize the underlying symptom-specific mechanisms and individually tailor treatment approaches.

Added value of FDG-PET for detection of progressive supranuclear palsy

BACKGROUND

Diagnostic criteria for progressive supranuclear palsy (PSP) include midbrain atrophy in MRI and hypometabolism in [18F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) as supportive features. Due to limited data regarding their relative and sequential value, there is no recommendation for an algorithm to combine both modalities to increase diagnostic accuracy. This study evaluated the added value of sequential imaging using state-of-the-art methods to analyse the images regarding PSP features.

METHODS

The retrospective study included 41 PSP patients, 21 with Richardson's syndrome (PSP-RS), 20 with variant PSP phenotypes (vPSP) and 46 sex- and age-matched healthy controls. A pretrained support vector machine (SVM) for the classification of atrophy profiles from automatic MRI volumetry was used to analyse T1w-MRI (output: MRI-SVM-PSP score). Covariance pattern analysis was applied to compute the expression of a predefined PSP-related pattern in FDG-PET (output: PET-PSPRP expression score).

RESULTS

The area under the receiver operating characteristic curve for the detection of PSP did not differ between MRI-SVM-PSP and PET-PSPRP expression score (p≥0.63): about 0.90, 0.95 and 0.85 for detection of all PSP, PSP-RS and vPSP. The MRI-SVM-PSP score achieved about 13% higher specificity and about 15% lower sensitivity than the PET-PSPRP expression score. Decision tree models selected the MRI-SVM-PSP score for the first branching and the PET-PSPRP expression score for a second split of the subgroup with normal MRI-SVM-PSP score, both in the whole sample and when restricted to PSP-RS or vPSP.

CONCLUSIONS

FDG-PET provides added value for PSP-suspected patients with normal/inconclusive T1w-MRI, regardless of PSP phenotype and the methods to analyse the images for PSP-typical features.

Planimetric and Volumetric Brainstem MRI Markers in Progressive Supranuclear Palsy, Multiple System Atrophy, and Corticobasal Syndrome. A Systematic Review and Meta-Analysis

BACKGROUND

Various MRI markers-including midbrain and pons areas (Marea, Parea) and volumes (Mvol, Pvol), ratios (M/Parea, M/Pvol), and composite markers (magnetic resonance imaging Parkinsonism Indices 1,2; MRPI 1,2)-have been proposed as imaging markers of Richardson's syndrome (RS) and multiple system atrophy-Parkinsonism (MSA-P). A systematic review/meta-analysis of relevant studies aiming to compare the diagnostic accuracy of these imaging markers is lacking.

METHODS

Pubmed and Scopus were searched for studies with >10 patients (RS, MSA-P or CBS) and >10 controls with data on Marea, Parea, Mvol, Pvol, M/Parea, M/Pvol, MRPI 1, and MRPI 2. Cohen's d, as a measure of effect size, was calculated for all markers in RS, MSA-P, and CBS.

RESULTS

Twenty-five studies on RS, five studies on MSA-P, and four studies on CBS were included. Midbrain area provided the greatest effect size for differentiating RS from controls (Cohen's d = -3.10; p < 0.001), followed by M/Parea and MRPI 1. MSA-P had decreased midbrain and pontine areas. Included studies exhibited high heterogeneity, whereas publication bias was low.

CONCLUSIONS

Midbrain area is the optimal MRI marker for RS, and pons area is optimal for MSA-P. M/Parea and MRPIs produce smaller effect sizes for differentiating RS from controls.

Identification of optimal value of magnetic resonance planimetry and the parkinsonism index for the diagnosis of Parkinson's disease and progressive supranuclear palsy

Objectives

Parkinson's disease (PD) and progressive supranuclear palsy (PSP) are neurodegenerative conditions that have overlapping clinical and imaging features, thus making it difficult to distinguish and diagnose PSP from PD. Therefore, in this study, we aimed to investigate the optimal value of magnetic resonance planimetry and the parkinsonism index to differentiate between PSP and PD.

Methods

In this retrospective study, we recruited a total of 84 patients (27 patients with PSP, 27 patients with PD and 27 normal controls) who underwent MRI brain examinations. For each subject, we calculated the corpus callosum area, midbrain area, pons area, middle cerebellar peduncle (MCP) width and superior cerebellar peduncle (SCP) width on MRI brain images. We also calculated the pons to midbrain area (P/M) ratio, MCP/SCP ratio and magnetic resonance parkinsonism index (MRPI).

Results

Receiver operating characteristic curve (ROC) analysis was used to identify the diagnostic value of each biomarker. MRPI had a sensitivity of 70.4%, a specificity of 88.9%, and a diagnostic accuracy of 79.6% with an optimum cut off of 24.3 for differentiating PSP from PD. P/M ratio had a sensitivity of 74.1%, a specificity of 77.8%, and a diagnostic accuracy of 75.9% with an optimal cutoff of 24.3 for differentiating PSP from PD. The MCP/SCP ratio had a sensitivity of 66.7%, a specificity of 77.8%, and an accuracy of 72.2% with an optimal cut off of 4.65 for differentiating PSP from PD.

Conclusions

The study revealed that MRPI and P/M ratio are accurate markers for differentiating PSP from PD. The optimal cut-off values derived from our study can help in the early diagnosis of PD.

Combining ultrasound and microelectrode recordings for postoperative localization of subthalamic electrodes in Parkinson's disease

OBJECTIVE

To assess transcranial sonography (TCS) as stand-alone tool and in combination with microelectrode recordings (MER) as a method for the postoperative localization of deep brain stimulation (DBS) electrodes in the subthalamic nucleus (STN).

METHODS

Individual dorsal and ventral boundaries of STN (n = 12) were determined on intraoperative MER. Postoperatively, a standardized TCS protocol was applied to measure medio-lateral, anterior-posterior and rostro-caudal electrode position using visualized reference structures (midline, substantia nigra). TCS and combined TCS-MER data were validated using fusion-imaging and clinical outcome data.

RESULTS

Test-retest reliability of standard TCS measures of electrode position was excellent. Computed tomography and TCS measures of distance between distal electrode contact and midline agreed well (Pearson correlation; r = 0.86; p < 0.001). Comparing our "gold standard" of rostro-caudal electrode localization relative to STN boundaries, i.e. combining MRI-based stereotaxy and MER data, with the combination of TCS and MER data, the measures differed by 0.32 ± 0.87 (range, -1.35 to 1.25) mm. Combined TCS-MER data identified the clinically preferred electrode contacts for STN-DBS with high accuracy (Coheńs kappa, 0.86).

CONCLUSIONS

Combined TCS-MER data allow for exact localization of STN-DBS electrodes.

SIGNIFICANCE

Our method provides a new option for monitoring of STN-DBS electrode location and guidance of DBS programming in Parkinson's disease.

Brain MRI in Progressive Supranuclear Palsy with Richardson's Syndrome and Variant Phenotypes

BACKGROUND

Brain magnetic resonance imaging (MRI) is used to support the diagnosis of progressive supranuclear palsy (PSP). However, the value of visual descriptive, manual planimetric, automatic volumetric MRI markers and fully automatic categorization is unclear, particularly regarding PSP predominance types other than Richardson's syndrome (RS).

OBJECTIVES

To compare different visual reading strategies and automatic classification of T1-weighted MRI for detection of PSP in a typical clinical cohort including PSP-RS and (non-RS) variant PSP (vPSP) patients.

METHODS

Forty-one patients (21 RS, 20 vPSP) and 46 healthy controls were included. Three readers using three strategies performed MRI analysis: exclusively visual reading using descriptive signs (hummingbird, morning-glory, Mickey-Mouse), visual reading supported by manual planimetry measures, and visual reading supported by automatic volumetry. Fully automatic classification was performed using a pre-trained support vector machine (SVM) on the results of atlas-based volumetry.

RESULTS

All tested methods achieved higher specificity than sensitivity. Limited sensitivity was driven to large extent by false negative vPSP cases. Support by automatic volumetry resulted in the highest accuracy (75.1% ± 3.5%) among the visual strategies, but performed not better than the midbrain area (75.9%), the best single planimetric measure. Automatic classification by SVM clearly outperformed all other methods (accuracy, 87.4%), representing the only method to provide clinically useful sensitivity also in vPSP (70.0%).

CONCLUSIONS

Fully automatic classification of volumetric MRI measures using machine learning methods outperforms visual MRI analysis without and with planimetry or volumetry support, particularly regarding diagnosis of vPSP, suggesting the use in settings with a broad phenotypic PSP spectrum. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Quantitative MRI protocol and decision model for a 'one stop shop' early-stage Parkinsonism diagnosis: Study design

Differentiating among early-stage parkinsonisms is a challenge in clinical practice. Quantitative MRI can aid the diagnostic process, but studies with singular MRI techniques have had limited success thus far. Our objective is to develop a multi-modal MRI method for this purpose. In this review we describe existing methods and present a dedicated quantitative MRI protocol, a decision model and a study design to validate our approach ahead of a pilot study. We present example imaging data from patients and a healthy control, which resemble related literature.

Whole-Brain Magnetic Resonance Spectroscopy Reveals Distinct Alterations in Neurometabolic Profile in Progressive Supranuclear Palsy

BACKGROUND

Progressive supranuclear palsy (PSP) is an atypical Parkinsonian syndrome characterized by supranuclear gaze palsy, early postural instability, and a frontal dysexecutive syndrome. Contrary to normal brain magnetic resonance imaging in Parkinson's disease (PD), PSP shows specific cerebral atrophy patterns and alterations, but these findings are not present in every patient, and it is still unclear if these signs are also detectable in early disease stages.

OBJECTIVE

The aim of the present study was to analyze the metabolic profile of patients with clinically diagnosed PSP in comparison with matched healthy volunteers and PD patients using whole-brain magnetic resonance spectroscopic imaging (wbMRSI).

METHODS

Thirty-nine healthy controls (HCs), 29 PD, and 22 PSP patients underwent wbMRSI. PSP and PD patients were matched for age and handedness with HCs. Clinical characterization was performed using the Movement Disorder Society Unified Parkinson's Disease Rating Scale, PSP rating scale, and DemTect (test for cognitive assessment).

RESULTS

In PSP patients a significant reduction in N-acetyl-aspartate (NAA) was detected in all brain lobes. Fractional volume of the cerebrospinal fluid significantly increased in PSP patients compared to PD and healthy volunteers.

CONCLUSIONS

In PSP much more neuronal degeneration and cerebral atrophy have been detected compared with PD. The most relevant alteration is the decrease in NAA in all lobes of the brain, which also showed a partial correlation with clinical symptoms. However, more studies are needed to confirm the additional value of wbMRSI in clinical practice. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Midbrain and pons MRI shape analysis and its clinical and CSF correlates in degenerative parkinsonisms: a pilot study

OBJECTIVES

To conduct brainstem MRI shape analysis across neurodegenerative parkinsonisms and control subjects (CS), along with its association with clinical and cerebrospinal fluid (CSF) correlates.

METHODOLOGY

We collected demographic and clinical variables, performed planimetric and shape MRI analyses, and determined CSF neurofilament-light chain (NfL) levels in 84 participants: 11 CS, 12 with Parkinson's disease (PD), 26 with multiple system atrophy (MSA), 21 with progressive supranuclear palsy (PSP), and 14 with corticobasal degeneration (CBD).

RESULTS

MSA featured the most extensive and significant brainstem shape narrowing (that is, atrophy), mostly in the pons. CBD presented local atrophy in several small areas in the pons and midbrain compared to PD and CS. PSP presented local atrophy in small areas in the posterior and upper midbrain as well as the rostral pons compared to MSA. Our findings of planimetric MRI measurements and CSF NfL levels replicated those from previous literature. Brainstem shape atrophy correlated with worse motor state in all parkinsonisms and with higher NfL levels in MSA, PSP, and PD.

CONCLUSION

Atypical parkinsonisms present different brainstem shape patterns which correlate with clinical severity and neuronal degeneration. In MSA, shape analysis could be further explored as a potential diagnostic biomarker. By contrast, shape analysis appears to have a rather limited discriminant value in PSP.

KEY POINTS

• Atypical parkinsonisms present different brainstem shape patterns. • Shape patterns correlate with clinical severity and neuronal degeneration. • In MSA, shape analysis could be further explored as a potential diagnostic biomarker.

The Role of Clinical Assessment in the Era of Biomarkers

Hippocratic Medicine revolved around the three main principles of patient, disease, and physician and promoted the systematic observation of patients, rational reasoning, and interpretation of collected information. Although these remain the cardinal features of clinical assessment today, Medicine has evolved from a more physician-centered to a more patient-centered approach. Clinical assessment allows physicians to encounter, observe, evaluate, and connect with patients. This establishes the patient-physician relationship and facilitates a better understanding of the patient-disease relationship, as the ultimate goal is to diagnose, prognosticate, and treat. Biomarkers are at the core of the more disease-centered approach that is currently revolutionizing Medicine as they provide insight into the underlying disease pathomechanisms and biological changes. Genetic, biochemical, radiographic, and clinical biomarkers are currently used. Here, we define a seven-level theoretical construct for the utility of biomarkers in neurodegenerative diseases. Level 1-3 biomarkers are considered supportive of clinical assessment, capable of detecting susceptibility or risk factors, non-specific neurodegeneration or dysfunction, and/or changes at the individual level which help increase clinical diagnostic accuracy and confidence. Level 4-7 biomarkers have the potential to surpass the utility of clinical assessment through detection of early disease stages and prediction of underlying pathology. In neurodegenerative diseases, biomarkers can potentiate, but cannot substitute, clinical assessment. In this current era, aside from adding to the discovery, evaluation/validation, and implementation of more biomarkers, clinical assessment remains crucial to maintaining the personal, humanistic, and sociocultural aspects of patient care. We would argue that clinical assessment is a custom that should never go obsolete.

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.

Comparative validation of AI and non-AI methods in MRI volumetry to diagnose Parkinsonian syndromes

Automated segmentation and volumetry of brain magnetic resonance imaging (MRI) scans are essential for the diagnosis of Parkinson's disease (PD) and Parkinson's plus syndromes (P-plus). To enhance the diagnostic performance, we adopt deep learning (DL) models in brain MRI segmentation and compared their performance with the gold-standard non-DL method. We collected brain MRI scans of healthy controls ([Formula: see text]) and patients with PD ([Formula: see text]), multiple systemic atrophy ([Formula: see text]), and progressive supranuclear palsy ([Formula: see text]) at Samsung Medical Center from January 2017 to December 2020. Using the gold-standard non-DL model, FreeSurfer (FS), we segmented six brain structures: midbrain, pons, caudate, putamen, pallidum, and third ventricle, and considered them as annotated data for DL models, the representative convolutional neural network (CNN) and vision transformer (ViT)-based models. Dice scores and the area under the curve (AUC) for differentiating normal, PD, and P-plus cases were calculated to determine the measure to which FS performance can be reproduced as-is while increasing speed by the DL approaches. The segmentation times of CNN and ViT for the six brain structures per patient were 51.26 ± 2.50 and 1101.82 ± 22.31 s, respectively, being 14 to 300 times faster than FS (15,735 ± 1.07 s). Dice scores of both DL models were sufficiently high (> 0.85) so their AUCs for disease classification were not inferior to that of FS. For classification of normal vs. P-plus and PD vs. P-plus (except multiple systemic atrophy - Parkinsonian type) based on all brain parts, the DL models and FS showed AUCs above 0.8, demonstrating the clinical value of DL models in addition to FS. DL significantly reduces the analysis time without compromising the performance of brain segmentation and differential diagnosis. Our findings may contribute to the adoption of DL brain MRI segmentation in clinical settings and advance brain research.

Comparison of mean diffusivity, R2* relaxation rate and morphometric biomarkers for the clinical differentiation of parkinsonism

INTRODUCTION

Quantitative biomarkers for clinical differentiation of parkinsonian syndromes are still lacking. Our aim was to evaluate the value of combining clinically feasible manual measurements of R2* relaxation rates and mean diffusivity (MD) in subcortical regions and brainstem morphometric measurements to improve the discrimination of parkinsonian syndromes.

METHODS

Twenty-two healthy controls (HC), 25 patients with Parkinson's disease (PD), 19 with progressive supranuclear palsy (PSP) and 27 with multiple system atrophy (MSA, 21 with the parkinsonian variant -MSAp, 6 with the cerebellar variant -MSAc) were recruited. R2*, MD measurements and morphometric biomarkers including the midbrain to pons area ratio and the Magnetic Resonance Parkinsonism Index (MRPI) were compared between groups and their diagnostic performances were assessed.

RESULTS

Morphometric biomarkers discriminated better patients with PSP (ratio: AUC 0.89, MRPI: AUC 0.89) and MSAc (ratio: AUC 0.82, MRPI: AUC 0.75) from other groups. R2* and MD measurements in the posterior putamen performed better in separating patients with MSAp from PD (R2*: AUC 0.89; MD: AUC 0.89). For the three-class classification "MSA vs PD vs PSP", the combination of MD and R2* measurements in the posterior putamen with morphometric biomarkers (AUC: 0.841) outperformed each marker separately. At the individual-level, there were seven discordances between imaging-based prediction and clinical diagnosis involving MSA. Using the new Movement Disorder Society criteria for the diagnosis of MSA, three of these seven patients were clinically reclassified as predicted by quantitative imaging.

CONCLUSION

Combining R2* and MD measurements in the posterior putamen with morphometric biomarkers improves the discrimination of parkinsonism.

Comparative analysis of machine learning algorithms for multi-syndrome classification of neurodegenerative syndromes

Importance

The entry of artificial intelligence into medicine is pending. Several methods have been used for the predictions of structured neuroimaging data, yet nobody compared them in this context.

Objective

Multi-class prediction is key for building computational aid systems for differential diagnosis. We compared support vector machine, random forest, gradient boosting, and deep feed-forward neural networks for the classification of different neurodegenerative syndromes based on structural magnetic resonance imaging.

Design, setting, and participants

Atlas-based volumetry was performed on multi-centric T1-weighted MRI data from 940 subjects, i.e., 124 healthy controls and 816 patients with ten different neurodegenerative diseases, leading to a multi-diagnostic multi-class classification task with eleven different classes.

Interventions

N.A.

Main outcomes and measures

Cohen’s kappa, accuracy, and F1-score to assess model performance.

Results

Overall, the neural network produced both the best performance measures and the most robust results. The smaller classes however were better classified by either the ensemble learning methods or the support vector machine, while performance measures for small classes were comparatively low, as expected. Diseases with regionally specific and pronounced atrophy patterns were generally better classified than diseases with widespread and rather weak atrophy.

Conclusions and relevance

Our study furthermore underlines the necessity of larger data sets but also calls for a careful consideration of different machine learning methods that can handle the type of data and the classification task best.

Magnetic Resonance Planimetry in the Differential Diagnosis between Parkinson’s Disease and Progressive Supranuclear Palsy

The clinical differential diagnosis between Parkinson’s disease (PD) and progressive supranuclear palsy (PSP) is often challenging. The description of milder PSP phenotypes strongly resembling PD, such as PSP-Parkinsonism, further increased the diagnostic challenge and the need for reliable neuroimaging biomarkers to enhance the diagnostic certainty. This review aims to summarize the contribution of a relatively simple and widely available imaging technique such as MR planimetry in the differential diagnosis between PD and PSP, focusing on the recent advancements in this field. The development of accurate MR planimetric biomarkers, together with the implementation of automated algorithms, led to robust and objective measures for the differential diagnosis of PSP and PD at the individual level. Evidence from longitudinal studies also suggests a role of MR planimetry in predicting the development of the PSP clinical signs, allowing to identify PSP patients before they meet diagnostic criteria when their clinical phenotype can be indistinguishable from PD. Finally, promising evidence exists on the possible association between MR planimetric measures and the underlying pathology, with important implications for trials with new disease-modifying target therapies.

Normative Data for Brainstem Structures, the Midbrain-to-Pons Ratio, and the Magnetic Resonance Parkinsonism Index

BACKGROUND AND PURPOSE

Imaging biomarkers derived from different brainstem structures are suggested to differentiate among parkinsonian disorders, but clinical implementation requires normative data. The main objective was to establish high-quality, sex-specific data for relevant brainstem structures derived from MR imaging in healthy subjects from the general population in their sixth and seventh decades of life.

MATERIALS AND METHODS

3D T1WI acquired on the same 1.5T scanner of 996 individuals (527 women) between 50 and 66 years of age from a prospective population study was used. The area of the midbrain and pons and the widths of the middle cerebellar peduncles and superior cerebellar peduncles were measured, from which the midbrain-to-pons ratio and Magnetic Resonance Parkinsonism Index [MRPI = (Pons Area / Midbrain Area) × (Middle Cerebellar Peduncles / Superior Cerebellar Peduncles)] were calculated. Sex differences in brainstem measures and correlations to age, height, weight, and body mass index were investigated.

RESULTS

Inter- and intrareliability for measuring the different brainstem structures showed good-to-excellent reliability (intraclass correlation coefficient = 0.785-0.988). There were significant sex differences for the pons area, width of the middle cerebellar peduncles and superior cerebellar peduncles, midbrain-to-pons ratio, and MRPI (all, P <  .001; Cohen D = 0.44-0.98), but not for the midbrain area (P = .985). There were significant very weak-to-weak correlations between several of the brainstem measures and age, height, weight, and body mass index in both sexes. However, no systematic difference in distribution caused by these variables was found, and because age had the highest and most consistent correlations, age-/sex-specific percentiles for the brainstem measures were created.

CONCLUSIONS

We present high-quality, sex-specific data and age-/sex-specific percentiles for the mentioned brainstem measures. These normative data can be implemented in the neuroradiologic work-up of patients with suspected brainstem atrophy to avoid the risk of misdiagnosis.

Regional Selectivity of Neuromelanin Changes in the Substantia Nigra in Atypical Parkinsonism

BACKGROUND

Neurodegeneration in the substantia nigra pars compacta (SNc) in parkinsonian syndromes may affect the nigral territories differently.

OBJECTIVE

The objective of this study was to investigate the regional selectivity of neurodegenerative changes in the SNc in patients with Parkinson's disease (PD) and atypical parkinsonism using neuromelanin-sensitive magnetic resonance imaging (MRI).

METHODS

A total of 22 healthy controls (HC), 38 patients with PD, 22 patients with progressive supranuclear palsy (PSP), 20 patients with multiple system atrophy (MSA, 13 with the parkinsonian variant, 7 with the cerebellar variant), 7 patients with dementia with Lewy body (DLB), and 4 patients with corticobasal syndrome were analyzed. volume and signal-to-noise ratio (SNR) values of the SNc were derived from neuromelanin-sensitive MRI in the whole SNc. Analysis of signal changes was performed in the sensorimotor, associative, and limbic territories of the SNc.

RESULTS

SNc volume and corrected volume were significantly reduced in PD, PSP, and MSA versus HC. Patients with PSP had lower volume, corrected volume, SNR, and contrast-to-noise ratio than HC and patients with PD and MSA. Patients with PSP had greater SNR reduction in the associative region than HC and patients with PD and MSA. Patients with PD had reduced SNR in the sensorimotor territory, unlike patients with PSP. Patients with MSA did not differ from patients with PD.

CONCLUSIONS

This study provides the first MRI comparison of the topography of neuromelanin changes in parkinsonism. The spatial pattern of changes differed between PSP and synucleinopathies. These nigral topographical differences are consistent with the topography of the extranigral involvement in parkinsonian syndromes. © 2022 International Parkinson and Movement Disorder Society.

Differentiating Progressive Supranuclear Palsy and Parkinson's Disease With Head-Mounted Displays

Background: Progressive supranuclear palsy (PSP) is a neurodegenerative disorder that, especially in the early stages of the disease, is clinically difficult to distinguish from Parkinson's disease (PD). Objective: This study aimed at assessing the use of eye-tracking in head-mounted displays (HMDs) for differentiating PSP and PD. Methods: Saccadic eye movements of 13 patients with PSP, 15 patients with PD, and a group of 16 healthy controls (HCs) were measured. To improve applicability in an inpatient setting and standardize the diagnosis, all the tests were conducted in a HMD. In addition, patients underwent atlas-based volumetric analysis of various brain regions based on high-resolution MRI. Results: Patients with PSP displayed unique abnormalities in vertical saccade velocity and saccade gain, while horizontal saccades were less affected. A novel diagnostic index was derived, multiplying the ratios of vertical to horizontal gain and velocity, allowing segregation of PSP from PD with high sensitivity (10/13, 77%) and specificity (14/15, 93%). As expected, patients with PSP as compared with patients with PD showed regional atrophy in midbrain volume, the midbrain plane, and the midbrain tegmentum plane. In addition, we found for the first time that oculomotor measures (vertical gain, velocity, and the diagnostic index) were correlated significantly to midbrain volume in the PSP group. Conclusions: Assessing eye movements in a HMD provides an easy to apply and highly standardized tool to differentiate PSP of patients from PD and HCs, which will aid in the diagnosis of PSP.

Brainstem Biomarkers of Clinical Variant and Pathology in Progressive Supranuclear Palsy

BACKGROUND

Magnetic resonance brainstem measurements are useful structural biomarkers in the Richardson's syndrome variant of progressive supranuclear palsy (PSP). However, it is unclear how these biomarkers differ across the phenotypic spectrum of PSP and how they relate to underlying pathology.

OBJECTIVE

The aim of this study was to compare brainstem imaging measures across clinical variants of PSP and determine sensitivity and specificity based on pathologically diagnosed cases.

METHODS

A total of 153 patients with PSP who represented eight clinical variants were recruited at Mayo Clinic (Rochester, MN, USA) and underwent structural magnetic resonance imaging (MRI). Midbrain and pons area and superior and middle cerebellar peduncle width measurements were performed, and midbrain/pons ratio and Magnetic Resonance Parkinsonism Index (MRPI) were calculated. Among the 43 patients who later died, PSP pathology was confirmed in 29, whereas 14 had other pathology.

RESULTS

Brainstem measurements varied across PSP clinical variants and were most abnormal in PSP-Richardson's syndrome and frontal variants, followed by PSP-corticobasal, PSP-speech/language, and PSP-parkinsonism variants. All these variants showed abnormalities compared with controls. The PSP-gait freezing variant and patients with prominent corticospinal tract signs showed normal brainstem measures. Among cases with confirmed PSP pathology, the midbrain area, midbrain/pons ratio, and MRPI were all more abnormal compared to those with other pathologies, with best differentiation obtained with the MRPI (sensitivity = 83%; specificity = 85%).

CONCLUSIONS

MRI brainstem measures show utility as diagnostic biomarkers across PSP clinical variants and have the potential to be useful in predicting underlying pathology. © 2021 International Parkinson and Movement Disorder Society.

Diagnostic Performance of the Magnetic Resonance Parkinsonism Index in Differentiating Progressive Supranuclear Palsy from Parkinson's Disease: An Updated Systematic Review and Meta-Analysis

Progressive supranuclear palsy (PSP) and Parkinson's disease (PD) are difficult to differentiate especially in the early stages. We aimed to investigate the diagnostic performance of the magnetic resonance parkinsonism index (MRPI) in differentiating PSP from PD. A systematic literature search of PubMed-MEDLINE and EMBASE was performed to identify original articles evaluating the diagnostic performance of the MRPI in differentiating PSP from PD published up to 20 February 2021. The pooled sensitivity, specificity, and 95% CI were calculated using the bivariate random-effects model. The area under the curve (AUC) was calculated using a hierarchical summary receiver operating characteristic (HSROC) model. Meta-regression was performed to explain the effects of heterogeneity. A total of 14 original articles involving 484 PSP patients and 1243 PD patients were included. In all studies, T1-weighted images were used to calculate the MRPI. Among the 14 studies, nine studies used 3D T1-weighted images. The pooled sensitivity and specificity for the diagnostic performance of the MRPI in differentiating PSP from PD were 96% (95% CI, 87-99%) and 98% (95% CI, 91-100%), respectively. The area under the HSROC curve was 0.99 (95% CI, 0.98-1.00). Heterogeneity was present (sensitivity: I² = 97.29%; specificity: I² = 98.82%). Meta-regression showed the association of the magnet field strength with heterogeneity. Studies using 3 T MRI showed significantly higher sensitivity (100%) and specificity (100%) than those of studies using 1.5 T MRI (sensitivity of 98% and specificity of 97%) (p < 0.01). Thus, the MRPI could accurately differentiate PSP from PD and support the implementation of appropriate management strategies for patients with PSP.

A Review of Neuroimaging in Rare Neurodegenerative Diseases

PURPOSE

Due to the variety of clinical symptoms that occur in rare neurodegenerative diseases and difficulties in the correct diagnosis, there is a need to learn their characteristic imaging findings by using conventional MRI. That knowledge helps to determine the appropriate differential diagnosis and avoid misdiagnosis. The aim of this review is to present the typical neuroimaging signs of the selected neurodegenerative disorders and to create a practical approach to imaging findings useful in everyday clinical practice. Images: Images of progressive supranuclear palsy (PSP), multiple system atrophy (MSA), corticobasal degeneration (CBD), Creutzfeldt-Jakob disease (CJD), Wilson's disease (WD), and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) are provided to visualize and distinguish the typical features of those diseases and therefore to assist neurologists and neuroradiologists in decision-making process.

CONCLUSIONS

It is important to know the characteristic MRI features of rare neurodegenerative diseases and to use them in everyday clinical practice. MRI is a valuable tool when considering the initial diagnosis because it is proven to be very useful in the differentiation of more advanced stages of the rare neurodegenerative diseases but also from other neurodegenerative disorders.

Evolving concepts in progressive supranuclear palsy and other 4-repeat tauopathies

Tauopathies are classified according to whether tau deposits predominantly contain tau isoforms with three or four repeats of the microtubule-binding domain. Those in which four-repeat (4R) tau predominates are known as 4R-tauopathies, and include progressive supranuclear palsy, corticobasal degeneration, argyrophilic grain disease, globular glial tauopathies and conditions associated with specific MAPT mutations. In these diseases, 4R-tau deposits are found in various cell types and anatomical regions of the brain and the conditions share pathological, pathophysiological and clinical characteristics. Despite being considered 'prototype' tauopathies and, therefore, ideal for studying neuroprotective agents, 4R-tauopathies are still severe and untreatable diseases for which no validated biomarkers exist. However, advances in research have addressed the issues of phenotypic overlap, early clinical diagnosis, pathophysiology and identification of biomarkers, setting a road map towards development of treatments. New clinical criteria have been developed and large cohorts with early disease are being followed up in prospective studies. New clinical trial readouts are emerging and biomarker research is focused on molecular pathways that have been identified. Lessons learned from failed trials of neuroprotective drugs are being used to design new trials. In this Review, we present an overview of the latest research in 4R-tauopathies, with a focus on progressive supranuclear palsy, and discuss how current evidence dictates ongoing and future research goals.

Differentiating PSP from MSA using MR planimetric measurements: a systematic review and meta-analysis

Differential diagnosis of parkinsonian syndromes is considered one of the most challenging in neurology. Quantitative MR planimetric measurements were reported to discriminate between progressive supranuclear palsy (PSP) and non-PSP-parkinsonism. Several studies have used midbrain to pons ratio (M/P) and the Magnetic Resonance Parkinsonism Index (MRPI) in distinguishing PSP patients from those with Parkinson's disease. The current meta-analysis aimed to compare the performance of these measures in discriminating PSP from multiple system atrophy (MSA). A systematic MEDLINE review identified 59 out of 2984 studies allowing a calculation of sensitivity and specificity using the MRPI or M/P. Meta-analyses of results were carried out using random effects modelling. To assess study quality and risk of bias, the QUADAS-2 tool was used. Eight studies were suitable for analysis. The meta-analysis showed a pooled sensitivity and specificity for the MRPI of PSP versus MSA of 79.2% (95% CI 72.7-84.4%) and 91.2% (95% CI 79.5-96.5%), and 84.1% (95% CI 77.2-89.2%) and 89.2% (95% CI 81.8-93.8%), respectively, for the M/P. The QUADAS-2 toolbox revealed a high risk of bias regarding the methodological quality of patient selection and index test, as all patients were seen in a specialized outpatient department without avoiding case control design and no predefined threshold was given regarding MRPI or M/P cut-offs. Planimetric brainstem measurements, in special the MRPI and M/P, yield high diagnostic accuracy for the discrimination of PSP from MSA. However, there is an urgent need for well-designed, prospective validation studies to ameliorate the concerns regarding the risk of bias.

Update on neuroimaging for categorization of Parkinson's disease and atypical parkinsonism

PURPOSE OF REVIEW

Differential diagnosis of Parkinsonism may be difficult. The objective of this review is to present the work of the last three years in the field of imaging for diagnostic categorization of parkinsonian syndromes focusing on progressive supranuclear palsy (PSP) and multiple system atrophy (MSA).

RECENT FINDINGS

Two main complementary approaches are being pursued. The first seeks to develop and validate manual qualitative or semi-quantitative imaging markers that can be easily used in clinical practice. The second is based on quantitative measurements of magnetic resonance imaging abnormalities integrated in a multimodal approach and in automatic categorization machine learning tools.

SUMMARY

These two complementary approaches obtained high diagnostic around 90% and above in the classical Richardson form of PSP and probable MSA. Future work will determine if these techniques can improve diagnosis in other PSP variants and early forms of the diseases when all clinical criteria are not fully met.

Progressive Supranuclear Palsy and Corticobasal Degeneration

Progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) are neurodegenerative tauopathies with neuronal and glial lesions composed of tau that is composed predominantly of isomers with four repeats in the microtubule-binding domain (4R tau). The brain regions vulnerable to pathology in PSP and CBD overlap, but there are differences, particularly with respect to distribution of neuronal loss, the relative abundance of neuronal and glial lesions, the morphologic features of glial lesions, and the frequency of comorbid pathology. Both PSP and CBD have a wide spectrum of clinical manifestations, including disorders of movement and cognition. Recognition of phenotypic diversity in PSP and CBD may improve antemortem diagnostic accuracy, which tends to be very good for the most common presentation of PSP (Richardson syndrome), but poor for the most characteristic presentation of CBD (corticobasal syndrome: CBS). Development of molecular and imaging biomarkers may improve antemortem diagnostic accuracy. Currently, multidisciplinary symptomatic and supportive treatment with pharmacological and non-pharmacological strategies remains the standard of care. In the future, experimental therapeutic trials will be important to slow disease progression.

Association of MRI Measures With Disease Severity and Progression in Progressive Supranuclear Palsy

Objective: To verify the association of midbrain-based MRI measures as well as cortical volumes with disease core features and progression in patients with Progressive Supranuclear Palsy (PSP). Methods: Sixty-seven patients (52.2% with Richardson's syndrome) were included in the present analysis. Available midbrain-based MRI morphometric assessments as well as cortical lobar volumes were computed. Ocular, gait and postural involvement at the time of MRI was evaluated with the PSP rating scale. Specific milestones or death were used to estimate disease progression up to 72 months follow up. Hierarchical regression models and survival analysis were used for analyzing cross-sectional and longitudinal data, respectively. Results: Multivariate models showed vertical supranuclear gaze palsy was associated with smaller midbrain area (OR: 0.02, 95% CI 0.00-0.175, p = 0.006). Cox regression adjusted for age, disease duration, and phenotype demonstrated that lower midbrain area (HR: 0.122, 95% CI 0.030-0.493, p = 0.003) and diameter (HR: 0.313, 95% CI 0.112-0.878, p = 0.027), higher MR Parkinsonism Index (HR: 6.162, 95% CI 1.790-21.209, p = 0.004) and larger third ventricle width (HR: 2.755, 95% CI 1.068-7.108, p = 0.036) were associated with higher risk of dependency on wheelchair. Conclusions: Irrespective of disease features and other MRI parameters, reduced midbrain size is significantly associated with greater ocular motor dysfunction at the time of MRI and more rapid disease progression over follow up. This is the first comprehensive study to systematically assess the association of available midbrain-based MRI measures and cortical volumes with disease severity and progression in a large cohort of patients with PSP in a real-world setting.

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

Background

Manual region‐of‐interest analysis of putaminal and middle cerebellar peduncle diffusivity distinguishes patients with multiple system atrophy (MSA) and Parkinson's disease (PD) with high diagnostic accuracy. However, a recent meta‐analysis found substantial between‐study heterogeneity of diagnostic accuracy due to the lack of harmonized imaging protocols and standardized analyses pipelines.

Objective

Evaluation of diagnostic accuracy of observer‐independent analysis of microstructural integrity as measured by diffusion‐tensor imaging in patients with MSA and PD.

Methods

A total of 29 patients with MSA and 19 patients with PD (matched for age, gender, and disease duration) with 3 years of follow‐up were investigated with diffusion‐tensor imaging and T1‐weighted magnetic resonance imaging. Automated localization of relevant brain regions was obtained, and mean diffusivity and fractional anisotropy values were averaged within the regions of interest. The classification was performed using a C5.0 hierachical decision tree algorithm.

Results

Mean diffusivity of the middle cerebellar peduncle and cerebellar gray and white matter compartment as well as the putamen were significantly increased in patients with MSA and showed superior effect sizes compared to the volumetric analysis of these regions. A classifier model identified mean diffusivity of the middle cerebellar peduncle and putamen as the most predictive parameters. Cross‐validation of the classification model yields a Cohen's κ and overall diagnostic accuracy of 0.823 and 0.914, respectively.

Conclusion

Analysis of microstructural integrity within the middle cerebellar peduncle and putamen yielded a superior effect size compared to the volumetric measures, resulting in excellent diagnostic accuracy to discriminate patients with MSA from PD in the early to moderate disease stages. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Conventional Magnetic Resonance Imaging in the Diagnosis of Parkinsonian Disorders: A Meta-Analysis

Background

Numerous conventional magnetic resonance imaging (cMRI) parameters were previously found to differentiate parkinsonian disorders with statistical significance, but effect size has not been considered.

Objectives

To quantify effect size of previously identified cMRI parameters that differentiated parkinsonian disorders with statistical significance.

Method

A PubMed search limited to studies assessing cMRI parameters in at least 2 of Parkinson's disease, progressive supranuclear palsy, multiple system atrophy, and corticobasal degeneration/syndrome were selected. Either Cohen's d or positive and negative likelihood (LR+/-) as well as diagnostic odds ratios (DORs) were calculated as appropriate. cMRI parameter was considered useful if Cohen's d > 1.94 (<20% overlap) or if LR+ > 10, LR- < 0.1, or DOR > 20.

Results

Literature search identified 8848 publications and 36 were included for analysis. Putaminal (Cohen's d 2.07; DOR 23-infinity), pontine (DOR 32-infinity), and middle cerebellar peduncle (Cohen's d 2.24; DOR infinity) abnormalities were most useful in differentiating multiple system atrophy while reduced midbrain (Cohen's d 2.33-8.69; DOR infinity) and superior cerebellar peduncle (Cohen's d 2.47; DOR 51-infinity) diameters separated progressive supranuclear palsy. Corticobasal degeneration/syndrome does not have any distinguishing cMRI features, but reduced midbrain diameter may help differentiate corticobasal degeneration/syndrome from Parkinson's disease (DOR infinity). When LR- was calculated, all of these features carried a value of <0.1.

Conclusion

A number of cMRI features consistently demonstrated large effect size in separating parkinsonian disorders. However, it is the presence and not absence of these cMRI features that is most useful in patients with low to moderate pretest probability.

Multicenter Validation of Metabolic Abnormalities Related to PSP According to the MDS-PSP Criteria

It remains unclear whether the supportive imaging features described in the diagnostic criteria for progressive supranuclear palsy (PSP) are suitable for the full clinical spectrum. The aim of the current study was to define and cross-validate the pattern of glucose metabolism in the brain associated with a diagnosis of different PSP variants. A retrospective multicenter cohort study performed on 73 PSP patients who were referred for a fluorodeoxyglucose positron emission tomography PET scan: PSP-Richardson's syndrome, n = 47; PSP-parkinsonian variant, n = 18; and progressive gait freezing, n = 8. In addition, we included 55 healthy controls and 58 Parkinson's disease (PD) patients. Scans were normalized by global mean activity. We analyzed the regional differences in metabolism between the groups. Moreover, we applied a multivariate analysis to obtain a PSP-related pattern that was cross-validated in independent populations at the individual level. Group analysis showed relative hypometabolism in the midbrain, basal ganglia, thalamus, and frontoinsular cortices and hypermetabolism in the cerebellum and sensorimotor cortices in PSP patients compared with healthy controls and PD patients, the latter with more severe involvement in the basal ganglia and occipital cortices. The PSP-related pattern obtained confirmed the regions described above. At the individual level, the PSP-related pattern showed optimal diagnostic accuracy to distinguish between PSP and healthy controls (sensitivity, 80.4%; specificity, 96.9%) and between PSP and PD (sensitivity, 80.4%; specificity, 90.7%). Moreover, PSP-Richardson's syndrome and PSP-parkinsonian variant patients showed significantly more PSP-related pattern expression than PD patients and healthy controls. The glucose metabolism assessed by fluorodeoxyglucose PET is a useful and reproducible supportive diagnostic tool for PSP-Richardson's syndrome and PSP-parkinsonian variant. © 2020 International Parkinson and Movement Disorder Society.

The Role of Magnetic Resonance Imaging for the Diagnosis of Atypical Parkinsonism

The diagnosis of Parkinson's disease and atypical Parkinsonism remains clinically difficult, especially at the early stage of the disease, since there is a significant overlap of symptoms. Multimodal MRI has significantly improved diagnostic accuracy and understanding of the pathophysiology of Parkinsonian disorders. Structural and quantitative MRI sequences provide biomarkers sensitive to different tissue properties that detect abnormalities specific to each disease and contribute to the diagnosis. Machine learning techniques using these MRI biomarkers can effectively differentiate atypical Parkinsonian syndromes. Such approaches could be implemented in a clinical environment and improve the management of Parkinsonian patients. This review presents different structural and quantitative MRI techniques, their contribution to the differential diagnosis of atypical Parkinsonian disorders and their interest for individual-level diagnosis.

The path to biomarker-based diagnostic criteria for the spectrum of neurodegenerative diseases

Introduction: The postmortem examination still represents the reference standard for detecting the pathological nature of chronic neurodegenerative diseases (NDD). This approach displays intrinsic conceptual limitations since NDD represent a dynamic spectrum of partially overlapping phenotypes, shared pathomechanistic alterations that often give rise to mixed pathologies.Areas covered: We scrutinized the international clinical diagnostic criteria of NDD and the literature to provide a roadmap toward a biomarker-based classification of the NDD spectrum. A few pathophysiological biomarkers have been established for NDD. These are time-consuming, invasive, and not suitable for preclinical detection. Candidate screening biomarkers are gaining momentum. Blood neurofilament light-chain represents a robust first-line tool to detect neurodegeneration tout court and serum progranulin helps detect genetic frontotemporal dementia. Ultrasensitive assays and retinal scans may identify Aβ pathology early, in blood and the eye, respectively. Ultrasound also represents a minimally invasive option to investigate the substantia nigra. Protein misfolding amplification assays may accurately detect α-synuclein in biofluids.Expert opinion: Data-driven strategies using quantitative rather than categorical variables may be more reliable for quantification of contributions from pathophysiological mechanisms and their spatial-temporal evolution. A systems biology approach is suitable to untangle the dynamics triggering loss of proteostasis, driving neurodegeneration and clinical evolution.

Midbrain/pons area ratio and clinical features predict the prognosis of progressive Supranuclear palsy

Background

Progressive supranuclear palsy (PSP) is a rare movement disorder with poor prognosis. This retrospective study aimed to characterize the natural history of PSP and to find predictors of shorter survival and faster decline of activity of daily living.

Method

All patients recruited fulfilled the movement disorder society (MDS) clinical diagnostic criteria for PSP (MDS-PSP criteria) for probable and possible PSP with median 12 years. Data were obtained including age, sex, date of onset, age at onset (AAO), symptoms reported at first visit and follow-up, date of death and date of institutionalization. Magnetic resonance imaging was collected at the first visit. Endpoints were death and institutionalization. Kaplan-Meier method and Cox proportional hazard model were used to explore factors associated with early death and institutionalization.

Results

Fifty-nine patients fulfilling MDS-PSP criteria were enrolled in our study. Nineteen patients (32.2%) had died and 31 patients (52.5%) were institutionalized by the end of the follow-up. Predictors associated with poorer survival were late-onset PSP and decreased M/P area ratio. Predictors associated with earlier institutionalization were older AAO and decreased M/P area ratio.

Conclusion

Older AAO and decreased M/P area ratio were predictors for earlier dearth and institutionalization in PSP. The neuroimaging biomarker M/P area ratio was a predictor for prognosis in PSP.

Automated MRI Classification in Progressive Supranuclear Palsy: A Large International Cohort Study

BACKGROUND

The Magnetic Resonance Parkinsonism Index is listed as one of the most reliable imaging morphometric markers for diagnosis of progressive supranuclear palsy (PSP). However, the use of this index in diagnostic workup has been limited until now by the low generalizability of published results because of small monocentric patient cohorts, the lack of data validation in independent patient series, and manual measurements used for index calculation. The objectives of this study were to investigate the generalizability of Magnetic Resonance Parkinsonism Index performance validating previously established cutoff values in a large international cohort of PSP patients subclassified into PSP-Richardson's syndrome and PSP-parkinsonism and to standardize the use of the automated Magnetic Resonance Parkinsonism Index by providing a web-based platform to obtain homogenous measures around the world.

METHODS

In a retrospective international multicenter study, a total of 173 PSP patients and 483 non-PSP participants were enrolled. A web-based platform (https://mrpi.unicz.it) was used to calculate automated Magnetic Resonance Parkinsonism Index values.

RESULTS

Magnetic Resonance Parkinsonism Index values showed optimal performance in differentiating PSP-Richardson's syndrome and PSP-parkinsonism patients from non-PSP participants (93.6% and 86.5% of accuracy, respectively). The Magnetic Resonance Parkinsonism Index was also able to differentiate PSP-Richardson's syndrome and PSP-parkinsonism patients in an early stage of the disease from non-PSP participants (90.1% and 85.9%, respectively). The web-based platform provided the automated Magnetic Resonance Parkinsonism Index calculation in 94% of cases.

CONCLUSIONS

Our study provides the first evidence on the generalizability of automated Magnetic Resonance Parkinsonism Index measures in a large international cohort of PSP-Richardson's syndrome and PSP-parkinsonism patients. The web-based platform enables widespread applicability of the automated Magnetic Resonance Parkinsonism Index to different clinical and research settings. © 2020 International Parkinson and Movement Disorder Society.

No effect of age, gender and total intracranial volume on brainstem MR planimetric measurements

Objectives

MR planimetry of brainstem structures can be helpful for the discrimination of Parkinsonian syndromes. It has been suggested that ageing might influence brainstem MR measurements assessed by MR planimetry, while effects of gender and total intracranial volume (TIV) have not been assessed so far. The aim of this study was to evaluate age, gender and TIV effects on brainstem MR planimetric measures.

Methods

Brainstem MR planimetric measures of diameters (midbrain, pons, middle and superior cerebellar peduncle) and areas (pons and midbrain), the derived ratios, and the magnetic resonance Parkinsonism index (MRPI) were assessed on 1.5-T MR images in a large cohort of 97 healthy controls and analysed for the influence of age, gender and TIV with univariate and multivariate linear models.

Results

Neither gender nor age effects on planimetric measurements were observed in the population relevant for the differential diagnosis of neurodegenerative Parkinsonism, aged 50 to 80 years, except for single area-derived measurements, with gender effects on pontine area (p = 0.013) and age effects on midbrain area (p = 0.037). Results were similar upon inclusion of the TIV in the analyses.

Conclusions

There is no need to correct for age, gender or TIV when using brainstem-derived MR planimetric measurements in the differential diagnosis of neurodegenerative Parkinsonism.

Key Points

• There were no gender effects on single or combined imaging measurements of the brainstem in the population aged 50 to 80 years, the age range relevant for the differential diagnosis of neurodegenerative Parkinsonism (except for pontine area).

• There were no age effects on single or combined imaging measurements of the brainstem in the population aged 50 to 80 years, the age range relevant for the differential diagnosis of neurodegenerative Parkinsonism (except for midbrain area).

• There is no need for age- or gender-specific cut-offs for the relevant age group.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06504-1) contains supplementary material, which is available to authorized users.

Differences in cerebellar perfusion between Parkinson's disease and multiple system atrophy

INTRODUCTION

Objective biomarkers are required for differential diagnosis of Parkinson's disease (PD), multiple system atrophy (MSA) and progressive supranuclear palsy (PSP).

OBJECTIVE

We aimed to determine if cerebellar blood flow, measured using N-isopropyl-[¹²³I] p-iodoamphetamine single photon emission computed tomography (¹²³I -IMP-SPECT), was useful for differentiating between PD, MSA and PSP.

METHODS

Twenty-four patients with PD, seventeen patients with MSA with predominant parkinsonian features (MSA-P), sixteenth patients with MSA with predominant cerebellar ataxia (MSA-C) and eight patients with PSP were enrolled. Twenty-seven normal controls' data were used for the calculation of z score. All patients underwent ¹²³I -IMP-SPECT, and data were analyzed using a three-dimensional-stereotactic surface projection program.

RESULTS

Cerebellar perfusion in MSA-P (MSA-P vs PD, P = .002; MSA-P vs PSP, P < .001) and MSA-C (MSA-C vs PD, P < .001; MSA-C vs PSP, P < .001) were significantly decreased compared with PD or PSP. There was no significant difference in perfusion between PD and PSP groups (P = .061). The area under the receiver operating characteristic curve for cerebellar perfusion between MSA-P and PD was 0.858.

CONCLUSION

Our findings revealed that cerebellar perfusion by ¹²³I-IMP-SPECT was useful for differentiating between PD and MSA-P.

Progressive supranuclear palsy

Progressive supranuclear palsy (PSP) is a neurodegenerative disease characterized pathologically by 4 repeat tau deposition in various cell types and anatomical regions. Richardson's syndrome (RS) is the initially described and one of the clinical phenotypes associated with PSP pathology, characterized by vertical supranuclear gaze paly in particular downwards, postural instability with early falls and subcortical frontal dementia. PSP can manifest as several other clinical phenotypes, including PSP-parkinsonism, -pure akinesia with gait freezing, -frontotemporal dementia, - corticobasal syndrome, - speech/language impairment. RS can also have a pathologic diagnosis other than PSP, including corticobasal degeneration, FTD-TDP-43 and others. New clinical diagnostic criteria take into account this phenotypic variability in an attempt to diagnose the disease earlier, given the current lack of a validated biomarker. At present, therapeutic options for PSP are symptomatic and insufficient. Recent large neuroprotective trials have failed to provide a positive clinical outcome, however, have led to the design of better studies that are ongoing and hold promise for a neuroprotective treatment for PSP.

PET Imaging of Astrogliosis and Tau Facilitates Diagnosis of Parkinsonian Syndromes

Neurodegenerative parkinsonian syndromes comprise a number of disorders that are characterized by similar clinical features but are separated on the basis of different pathologies, i.e., aggregates of α-synuclein or tau protein. Due to the overlap of signs and symptoms a precise differentiation is often difficult, especially early in the disease course. Enormous efforts have been taken to develop tau-selective PET imaging agents, but strong off-target binding to monoamine oxidase B (MAO-B) has been observed across first generation ligands. Nonetheless, astrogliosis-related MAO-B elevation is a common histopathological known feature of all parkinsonian syndromes and might be itself an interesting imaging target. Therefore, this study aimed to investigate the performance of [¹⁸F]-THK5351, a combined MAO-B and tau tracer for differential diagnosis of parkinsonian syndromes. [¹⁸F]-THK5351 PET was performed in 34 patients: six with Parkinson's disease (PD), nine with multiple system atrophy with predominant parkinsonism (MSA-P), six with MSA with predominant cerebellar ataxia (MSA-C), and 13 with progressive supranuclear palsy (PSP) Richardson's syndrome. Volume-of-interest-based quantification of standardized-uptake-values was conducted in different parkinsonian syndrome-related target regions. PET results were subjected to multinomial logistic regression to create a prediction model discriminating among groups. Furthermore, we correlated tracer uptake with clinical findings. Elevated [¹⁸F]-THK5351 uptake in midbrain and diencephalon differentiated PSP patients from PD and MSA-C. MSA-C patients were distinguishable by high tracer uptake in the pons and cerebellar deep white matter when compared to PSP and PD patients, whereas MSA-P patients tended to show higher tracer uptake in the lentiform nucleus. A multinomial logistic regression classified 33/34 patients into the correct clinical diagnosis group. Tracer uptake in the pons, cerebellar deep white matter, and striatum was closely associated with the presence of cerebellar and parkinsonian symptoms of MSA patients. The current study demonstrates that combined MAO-B and tau binding of THK5351 facilitates differential diagnosis of parkinsonian syndromes. Furthermore, our data indicate a correlation of MSA phenotype with [¹⁸F]-THK5351 uptake in certain brain regions, illustrating their relevance for the emergence of clinical symptoms and underlining the potential of THK5351 PET as a biomarker that correlates with pathological changes as well as with disease stage.

"One line": A method for differential diagnosis of parkinsonian syndromes

BACKGROUND

Neurological findings are important for the differential diagnosis of Parkinson's disease (PD), multiple system atrophy with predominant parkinsonian features (MSA-P), and progressive supranuclear palsy (PSP). There is currently no fast and reliable method to distinguish these patients.

OBJECTIVES

To address this, we propose a novel approach to measure midbrain and pons size using a longitudinal "one line" method from the mid-sagittal view.

METHODS

Structural images were acquired from 101 subjects who underwent 3.0 T MRI (20 controls, 44 PD, 20 MSA, 12 PSP, and 5 corticobasal syndrome). We measured the middle cerebellar peduncle (MCP), superior cerebellar peduncle (SCP), midbrain, and pons. Brainstem size was measured by area or length of the longitudinal axis, which we named the "one line" method. We conducted intraclass correlation coefficients to assess the extent of agreement and consistency among raters, and receiver operating characteristic curves were used to determine diagnostic accuracy.

RESULTS

Intraclass correlation coefficients (ICC) of MCP width were excellent in sagittal and axial sections while those of SCP width were moderate. There were also excellent ICCs between raters for "one line" method of the midbrain and pons, while areas showed good ICCs. "One line" method and area of the midbrain were better than SCP width for the differential diagnosis of PSP from MSA-P and PD. In contrast, there was no clearly superior measurement for differentially diagnosing MSA-P.

CONCLUSIONS

The "one line" method was comparable with area for inter-rater agreement and diagnostic accuracy even though this was a simple and fast way.

Diagnostic validity of magnetic resonance parkinsonism index in differentiating patients with progressive supranuclear palsy from patients with Parkinson's disease

BACKGROUND

Progressive supranuclear palsy is a neuropathologically defined disease, and many studies worked on detecting the diagnostic use of Magnetic resonance imaging. This article purposed to detect the diagnostic performance of Magnetic resonance parkinsonism index (MRPI).

METHODS

We systematically searched electronic database PubMed for articles published since 1996 using the National Institute of Neurological Disorders and Stroke and Society for PSP (NINDS-SPSP) criteria as the diagnostic standard. Methodological quality was assessed by Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and software Review Manager 5.3, software STATA 14.0 and meta-disc were applied in statistics analysis.

RESULTS

Totally 14 articles were included in this article. MRPI is proved to have pooled sensitivity of 0.98, pooled specificity of 0.99 in differentiating patients with Progressive supranuclear palsy (PSP) from patients with Parkinson's disease (PD) and the area under the Receiver operating characteristic curve value was 1.00.

CONCLUSION

MRPI shows excellent performance in differentiating patients with PSP from patients with PD, the clinical usage of MRPI in auxiliary diagnosis of PSP is recommended.

Midbrain atrophy in patients with presymptomatic progressive supranuclear palsy-Richardson's syndrome

INTRODUCTION

In the present study, midbrain atrophy and the pons-to-midbrain area ratio (P/M ratio) were investigated as diagnostic markers for presymptomatic progressive supranuclear palsy-Richardson's syndrome (Pre-PSP-RS).

METHODS

The present study included 27 patients with probable PSP-RS who underwent brain MRI at least twice before and after the development of clinical symptoms, age- and sex-matched participants with Parkinson's disease (PD, n = 27), and healthy controls (n = 27). The midbrain area, pons area, and P/M ratio of the Pre-PSP-RS, PD, and control subjects were measured using midsagittal images from brain MRI, and the parameters were compared among the groups.

RESULTS

The midbrain area decreased and the P/M ratio increased significantly in the Pre-PSP-RS patients compared with both the PD and control subjects (midbrain, Pre-PSP-RS vs. PD = 1.01 cm²vs. 1.29 cm², p < 0.001, Pre-PSP-RS vs. controls = 1.01 cm²vs. 1.29 cm², p < 0.001; P/M ratio, Pre-PSP-RS vs. PD = 5.27 vs. 4.03, p < 0.001, Pre-PSP-RS vs. controls = 5.27 cm²vs. 4.06 cm², p < 0.001). The P/M ratio had high sensitivity (vs. PD, 96.3%, vs. control, 88.9%) and specificity (vs. PD, 81.5%, vs. control, 96.3%) in differentiating Pre-PSP-RS patients from PD and control subjects.

CONCLUSION

Midbrain atrophy precedes the clinical symptoms of PSP-RS and could be a useful diagnostic imaging biomarker for Pre-PSP-RS. Furthermore, this information could play an important role in the development of future treatment strategies.

Nigrosome 1 imaging: technical considerations and clinical applications

A pathological study by Damier et al demonstrated that nigrosome 1, a dopaminergic neuron-rich region in the substantial nigra, is the most severely affected region in idiopathic Parkinson's disease. Since then, researchers have identified the location of nigrosome 1 in the dorsal aspect of the substantia nigra using susceptibility-weighted imaging in MRI. Although this observation was reconfirmed by various imaging techniques and imaging planes, non-standardized imaging methods may rather limit the generalized use of this imaging finding. The aim of this review is to revisit the anatomical definition of the nigrosome 1 region using high-spatial-resolution susceptibility map-weighted MRI in order to help the readers to determine the presence or absence of an abnormality in the nigrosome 1 region. Thereafter, we discuss the current status of nigrosome 1 imaging at 3 T and show how to improve the imaging quality for better assessment of nigrosome 1. We also illustrate the imaging findings of various patients who presented with parkinsonism, which can help the readers to learn how to use these images in practice. Lastly, we discuss potential future works with nigrosome 1 susceptibility map-weighted MRI.

Progressive supranuclear palsy and multiple system atrophy: clinicopathological concepts and therapeutic challenges

PURPOSE OF REVIEW

This update discusses novel aspects on clinicopathological concepts and therapeutic challenges in progressive supranuclear palsy (PSP) and multiple system atrophy (MSA), arising from publications of the last 1.5 years.

RECENT FINDINGS

The clinical criteria for diagnosis of PSP have been revised. Clinical variability of pathologically defined PSP and MSA makes the development of mature biomarkers for early diagnosis and biomarker-based trial design indispensable. Novel molecular techniques for biomarker supported diagnosis of PSP and MSA and for monitoring disease progression are being studied. Research in the pathophysiology of both diseases generates gradual progress in the understanding of the underlying processes. Several promising disease-modifying therapeutic approaches for PSP and MSA are now moving into clinical trials.

SUMMARY

Recent research generates insights in the pathophysiological relevant processes and raises hope for earlier clinical diagnosis and disease-modifying therapies of patients with PSP and MSA.

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.

Atrophy in midbrain & cerebral/cerebellar pedunculi is characteristic for progressive supranuclear palsy - A double-validation whole-brain meta-analysis

OBJECTIVE

Progressive supranuclear palsy (PSP) is an atypical parkinsonian syndrome characterized by vertical gaze palsy and postural instability. Midbrain atrophy is suggested as a hallmark, but it has not been validated systematically in whole-brain imaging.

METHODS

We conducted whole-brain meta-analyses identifying disease-related atrophy in structural MRI. Eighteen studies were identified (N = 315 PSP, 393 controls) and separated into gray or white matter analyses (15/12). All patients were diagnosed according to the National Institute of Neurological Disorders and Stroke and the Society for PSP (NINDS-SPSP criteria, Litvan et al. (1996a)), which are now considered as PSP-Richardson syndrome (Höglinger et al., 2017). With overlay analyses, we double-validated two meta-analytical algorithms: anatomical likelihood estimation and seed-based D mapping. Additionally, we conducted region-of-interest effect size meta-analyses on radiological biomarkers and subtraction analyses differentiating PSP from Parkinson's disease.

RESULTS

Whole brain meta-analyses revealed consistent gray matter atrophy in bilateral thalamus, anterior insulae, midbrain, and left caudate nucleus. White matter alterations were consistently detected in bilateral superior/middle cerebellar pedunculi, cerebral pedunculi, and midbrain atrophy. Region-of-interest meta-analyses demonstrated that midbrain metrics generally perform very well in distinguishing PSP from other parkinsonian syndromes with strong effect sizes. Subtraction analyses identified the midbrain as differentiating between PSP and Parkinson's disease.

CONCLUSIONS

Our meta-analyses identify gray matter atrophy of the midbrain and white matter atrophy of the cerebral/cerebellar pedunculi and midbrain as characteristic for PSP. Results support the incorporation of structural MRI data, and particularly these structures, into the revised PSP diagnostic criteria.