Accuracy of magnetic resonance parkinsonism index for differentiation of progressive supranuclear palsy from probable or possible Parkinson disease

Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here?

Parkinsonian disorders are a heterogeneous group of incurable neurodegenerative diseases that significantly reduce quality of life and constitute a substantial economic burden. Nuclear imaging (NI) and magnetic resonance imaging (MRI) have played and continue to play a key role in research aimed at understanding and monitoring these disorders. MRI is cheaper, more accessible, nonirradiating, and better at measuring biological structures and hemodynamics than NI. NI, on the other hand, can track molecular processes, which may be crucial for the development of efficient diseasemodifying therapies. Given the strengths and weaknesses of NI and MRI, how can they best be applied to Parkinsonism research going forward? This review aims to examine the effectiveness of NI and MRI in three areas of Parkinsonism research (differential diagnosis, prodromal disease identification, and disease monitoring) to highlight where they can be most impactful. Based on the available literature, MRI can assist with differential diagnosis, prodromal disease identification, and disease monitoring as well as NI. However, more work is needed, to confirm the value of MRI for monitoring prodromal disease and predicting phenoconversion. Although NI can complement or be a substitute for MRI in all the areas covered in this review, we believe that its most meaningful impact will emerge once reliable Parkinsonian proteinopathy tracers become available. Future work in tracer development and high-field imaging will continue to influence the landscape for NI and MRI.

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.

Accurate measurement of magnetic resonance parkinsonism index by a fully automatic and deep learning quantification pipeline

OBJECTIVES

This study aims at a fully automatic pipeline for measuring the magnetic resonance parkinsonism index (MRPI) using deep learning methods.

METHODS

MRPI is defined as the product of the pons area to the midbrain area ratio and the middle cerebellar peduncle (MCP) width to the superior cerebellar peduncle (SCP) width ratio. In our proposed pipeline, we first used nnUNet to segment the brainstem and then employed HRNet to identify two key boundary points so as to sub-divide the whole brainstem into midbrain and pons. HRNet was also employed to predict the MCP endpoints for measuring the MCP width. Finally, we segmented the SCP on an oblique coronal plane and calculated its width. A total of 400 T1-weighted magnetic resonance images (MRIs) were used to train the nnUNet and HRNet models. Five-fold cross-validation was conducted to evaluate our proposed pipeline's performance on the training dataset. We also evaluated the performance of our proposed pipeline on three external datasets. Two of them had two raters manually measuring the MRPI values, providing insights into automatic accuracy versus inter-rater variability.

RESULTS

We obtained average absolute percentage errors (APEs) of 17.21%, 18.17%, 20.83%, and 22.83% on the training dataset and the three external validation datasets, while the inter-rater average APE measured on the first two external validation datasets was 11.31%. Our proposed pipeline significantly improved the MRPI quantification accuracy over a representative state-of-the-art traditional approach (p < 0.001).

CONCLUSION

The proposed automatic pipeline can accurately predict MRPI that is comparable with manual measurement.

CLINICAL RELEVANCE STATEMENT

This study presents an automated magnetic resonance parkinsonism index measurement tool that can analyze large amounts of magnetic resonance images, enhance the efficiency of Parkinsonism-Plus syndrome diagnosis, reduce the workload of clinicians, and minimize the impact of human factors on diagnosis.

KEY POINTS

• We propose an automatic pipeline for measuring the magnetic resonance parkinsonism index from magnetic resonance images. • The effectiveness of the proposed pipeline is successfully established on multiple datasets and comparisons with inter-rater measurements. • The proposed pipeline significantly outperforms a state-of-the-art quantification approach, being much closer to ground truth.

Clinical features of progressive supranuclear palsy

Background

Progressive supranuclear palsy (PSP) is a clinically heterogenous atypical parkinsonian syndrome. Therefore, early recognition and correct diagnosis of PSP is challenging but essential. This study aims to characterize the clinical manifestations, magnetic resonance imaging (MRI), and longitudinal MRI changes of PSP in China.

Method

Clinical and MRI presentations were compared among 150 cases with PSP. Then the longitudinal MRI changes among 20 patients with PSP were further explored. Additionally, a series of midbrain-based MRI parameters was compared between PSP-P and PD.

Results

Throughout the course of the disease, there were differences in the symptoms of the fall and hand tremor between the PSP-RS and PSP-P. There were significant differences in the six midbrain-based MRI parameters between the PSP-RS and the PSP-P, including hummingbird sign, midbrain diameter, midbrain to pons ratio (MTPR), midbrain area, midbrain area to pons area ratio (Ma/Pa), and midbrain tegmental length (MBTegm). Longitudinal MRI studies revealed that the annual rel.ΔMTPR and rel.Δ (Ma/Pa) for PSP were 5.55 and 6.52%, respectively; additionally, PSP-RS presented a higher decline rate than PSP-P. Moreover, MTPR ≤0.56, midbrain diameter ≤ 0.92, midbrain area ≤ 1.00, and third ventricle width ≤ 0.75 could identify PSP-P from PD.

Conclusion

PSP-P differs from PSP-RS regarding clinical manifestations, MRI, and longitudinal MRI changes. MRI parameters could be potential imaging markers to identify PSP-P from PD.

The Role of the Evans Index and the Maximal Width of the Frontal Horns of the Lateral Ventricles in the Diagnostic Imaging of Progressive Supranuclear Palsy and Multiple-System Atrophy

Progressive Supranuclear Palsy and Multiple-System Atrophy are entities within the spectrum of atypical parkinsonism. The role of imaging methods in the diagnosis and differentiation between PSP and MSA is limited and Magnetic Resonance Imaging (MRI) is currently used as a reference modality. In this study, the authors examined a group of patients with atypical parkinsonism using a 1.5 T MRI system and aimed to find simple and repeatable measurements that may be useful to distinguish between these diseases. The results of the study indicate that the maximal width of the frontal horns of the lateral ventricles and Evans' Index may, to some extent, be useful as basic and simple measurements in the diagnostic imaging of patients with atypical parkinsonism.

Imaging Criteria for the Diagnosis of Progressive Supranuclear Palsy: Supportive or Mandatory?

We present the case of a 54-year-old male, without any significant medical history, who insidiously developed speech disturbances and walking difficulties, accompanied by backward falls. The symptoms progressively worsened over time. The patient was initially diagnosed with Parkinson's disease; however, he failed to respond to standard therapy with Levodopa. He came to our attention for worsening postural instability and binocular diplopia. A neurological exam was highly suggestive of a Parkinson-plus disease, most likely progressive supranuclear gaze palsy. Brain MRI was performed and revealed moderate midbrain atrophy with the characteristic "hummingbird" and "Mickey mouse" signs. An increased MR parkinsonism index was also noted. Based on all clinical and paraclinical data, a diagnosis of probable progressive supranuclear palsy was established. We review the main imaging features of this disease and their current role in diagnosis.

Structural MRI Ratios Fail to Distinguish Progressive Supranuclear Palsy From Parkinson Disease in Individual Patients

Background and Objectives

Parkinson disease (PD) and progressive supranuclear palsy (PSP) are often difficult to differentiate in the clinic. The MR parkinsonism index (MRPI) has been recommended to assist in making this distinction. We aimed to assess the usefulness of this tool in our real-world practice of movement disorders.

Methods

We prospectively obtained MRI scans on consecutive patients with movement disorders with a clinical indication for imaging and obtained measures of MRI regions of interest (ROIs) from our neuroradiologists. The authors reviewed all MRI scans and corrected any errors in the original ROI drawings for this analysis. We retrospectively assigned diagnoses using established consensus criteria from progress notes stored in our electronic medical record. We analyzed the data using multinomial logistic regression models and receiver operating curve analysis to determine the predictive accuracy of the MRI ratios.

Results

MRI measures and consensus diagnoses were available on 130 patients with PD, 54 with PSP, and 77 diagnosed as other. The out-of-sample prediction error rate of our 5 regression models ranged from 45% to 59%. The average sensitivity and specificity of the 5 models in the testing sample were 53% and 80%, respectively. The positive predictive value of an MRPI ≥13.55 (the published cutoff) in our patients was 79%.

Discussion

These results indicate that MRI measures of brain structures were not effective at predicting diagnosis in individual patients. We conclude that the search for a biomarker that can differentiate PSP from PD must continue.

Superior cerebellar peduncle atrophy of progressive supranuclear palsy on phase difference enhanced imaging: a comparison with Parkinson's disease

PURPOSE

Phase difference enhanced (PADRE) imaging can enhance myelin density and delineate the superior cerebellar peduncle (SCP). We aimed to determine if SCP atrophy was distinguishable on PADRE imaging and evaluate its diagnostic performance compared with previous MRI progressive supranuclear palsy (PSP) findings.

METHODS

Two reviewers measured the SCP widths on PADRE in 20 PSP and 31 Parkinson's disease (PD) patients. The SCP and middle cerebellar peduncle (MCP) widths and the pons and midbrain areas were measured on 3D-T1WI, and the ratio of the area of the pons to the area of the midbrain, the MCP/SCP ratio, and the magnetic resonance parkinsonism index (MRPI) were calculated. We used the Steel-Dwass test to compare PSP, PD, and HS, and receiver operating characteristic curve (ROC) analyses to assess the sensitivity and specificity for diagnosing PSP from PD. A comparison of ROC curves was performed between the SCP on PADRE and these 3D-T1WI parameters.

RESULTS

In radiologist 1, the SCP on PADRE in PSP (1.1 ± 0.3 mm) was significantly smaller than those in PD (2.4 ± 0.4 mm) (P < 0.001); the area under the curve (AUC) was 0.97. At a 1.75-mm cutoff value, the diagnostic sensitivity and specificity for differentiating PSP from PD were 93.5% and 100%, respectively. The AUC of the SCP on PADRE was significantly higher than the 3D-T1WI parameters (the SCP, MCP, pons area, MCP/SCP ratio, and MRPI).

CONCLUSION

Assessing SCP with PADRE imaging may yield high diagnostic accuracy for discriminating PSP from PD.

Brainstem atrophy in dementia with Lewy bodies compared with progressive supranuclear palsy and Parkinson's disease on MRI

BACKGROUND

Although Dementia with Lewy bodies (DLB) is the second most common form of dementia in elderly patients, it remains underdiagnosed compared with Alzheimer's (AD) and Parkinson's diseases (PD). This may be explained by overlapping clinical symptoms, e.g. Parkinsonism. While current MRI research focuses primarily on atrophy patterns of the frontal and temporal lobes, we focus on brainstem characteristics of DLB. In particular, we focused on brainstem atrophy patterns distinguishing DLB from Progressive Supranuclear Palsy (PSP) and PD based as the most common differential diagnoses.

METHODS

We identified patients diagnosed with DLB, PD, PSP, and a control group (CTRL) in our psychiatric and neurological archives. All patients with competing diagnoses and without a high-quality T1 MPRAGE 3D dataset were excluded. We assessed atrophy patterns in all patients (1) manually and (2) using FastSurfer's segmentation algorithm in combination with FreeSurfer's brainstem volumetric calculations. We compared classical measurement methods and ratios with automated volumetric approaches.

RESULTS

One hundred two patients were enrolled and evaluated in this study. Patients with DLB (n = 37) showed on average less atrophy of the brainstem than patients with PSP (n = 21), but a significantly more pronounced atrophy than patients with PD (n = 36) and the control group (CTRL, n = 8). The mean measured sagittal diameters of the midbrain were 8.17 ± 1.06 mm (mean ± standard deviation) for PSP, 9.45 ± 0.95 mm for DLB, 10.37 ± 0.99 mm for PD and 10.74 ± 0.70 for CTRL. The mean measured areas of the midbrain were 81 ± 18 mm² for PSP, 105 ± 17 mm² for DLB, 130 ± 26 mm² for PD and 135 ± 23 mm² for CTRL. The mean segmented volumes of the midbrain were 5595 ± 680 mm³ for PSP, 6051 ± 566 mm³ for DLB, 6646 ± 802 mm³ for PD and 6882 ± 844 mm³ for CTRL. The calculated midbrain pons ratios did not show superiority over the absolute measurements of the midbrain for distinguishing PSP from DLB. Because of the relatively uniform atrophy throughout the brainstem, the ratios were not suitable for distinguishing DLB from PD.

CONCLUSIONS

DLB patients exhibit homogenous atrophy of the brainstem and can be distinguished from patients with PSP and PD by both manual measurement methods and automated volume segmentation using absolute values or ratios.

Clinical, cognitive, and morphometric profiles of progressive supranuclear palsy phenotypes

The International Parkinson's and Movement Disorder Society (MDS) criteria for progressive supranuclear palsy (PSP) have broadened the clinical spectrum of the disease and established phenotypic characterization according to the predominant manifestation at onset. The objective of this study is to describe clinical/cognitive and imaging features of a monocentric cohort of PSP patients, highlighting different patterns of functional disability according to the assigned phenotype. We retrospectively reviewed clinical/imaging data of 53 PSP patients diagnosed with probable PSP according to the MDS criteria and 40 age/sex-matched healthy controls (HCs). Neurological/neuropsychological assessments were performed using standardized scales, as well as comprehensive magnetic resonance imaging (MRI) morphometric measurements. In our cohort, there were 24/53 PSP-RS (Richardson's syndrome), 13/53 PSP-P (Parkinsonism), 7/53 PSP-PGF (Progressive gait freezing), and 9/53 PSP-Cog (Cognitive impairment). PSP-Cog presented the worst motor profiles, the highest percentages of dementia and impaired functional autonomy; 4/9 PSP-Cog and 2/7 PSP-PGF died. PSP-P had the lowest motor/cognitive burden. All MRI parameters had good discriminative efficacy vs. HCs, with P/M 2.0 discriminating PSP-PGF from PSP-RS and PSP-Cog. We highlighted discrete clinical and imaging patterns that best characterize different PSP phenotypes. PSP-Cog and PSP-PGF/RS manifest greater incidence of dementia and motor disability, respectively, while PSP-P has a more benign course. The identification of different phenotypes may be the expression of different progression patterns requiring tailored approaches in terms of follow-up and treatment. These findings support the concept of discrete patterns of Tau pathology within the PSP spectrum and encourage research for phenotype-specific outcome measures.

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.

Development and Validation of Automated Magnetic Resonance Parkinsonism Index 2.0 to Distinguish Progressive Supranuclear Palsy‐Parkinsonism From Parkinson's Disease

Background

Differentiating progressive supranuclear palsy‐parkinsonism (PSP‐P) from Parkinson's disease (PD) is clinically challenging.

Objective

This study aimed to develop an automated Magnetic Resonance Parkinsonism Index 2.0 (MRPI 2.0) algorithm to distinguish PSP‐P from PD and to validate its diagnostic performance in two large independent cohorts.

Methods

We enrolled 676 participants: a training cohort (n = 346; 43 PSP‐P, 194 PD, and 109 control subjects) from our center and an independent testing cohort (n = 330; 62 PSP‐P, 171 PD, and 97 control subjects) from an international research group. We developed a new in‐house algorithm for MRPI 2.0 calculation and assessed its performance in distinguishing PSP‐P from PD and control subjects in both cohorts using receiver operating characteristic curves.

Results

The automated MRPI 2.0 showed excellent performance in differentiating patients with PSP‐P from patients with PD and control subjects both in the training cohort (area under the receiver operating characteristic curve [AUC] = 0.93 [95% confidence interval, 0.89–0.98] and AUC = 0.97 [0.93–1.00], respectively) and in the international testing cohort (PSP‐P versus PD, AUC = 0.92 [0.87–0.97]; PSP‐P versus controls, AUC = 0.94 [0.90–0.98]), suggesting the generalizability of the results. The automated MRPI 2.0 also accurately distinguished between PSP‐P and PD in the early stage of the diseases (AUC = 0.91 [0.84–0.97]). A strong correlation (r = 0.91, P < 0.001) was found between automated and manual MRPI 2.0 values.

Conclusions

Our study provides an automated, validated, and generalizable magnetic resonance biomarker to distinguish PSP‐P from PD. The use of the automated MRPI 2.0 algorithm rather than manual measurements could be important to standardize measures in patients with PSP‐P across centers, with a positive impact on multicenter studies and clinical trials involving patients from different geographic regions. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

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.

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.

N. BP, Mohamed Ibrahim N, Mustapha M. Aberrant Neurogliovascular Unit Dynamics in Cerebral Small Vessel Disease: A Rheological Clue to Vascular Parkinsonism

The distinctive anatomical assemble and functionally discrete multicellular cerebrovasculature dynamics confer varying rheological and blood-brain barrier permeabilities to preserve the integrity of cerebral white matter and its neural microenvironment. This homeostasis intricately involves the glymphatic system that manages the flow of interstitial solutes, metabolic waste, and clearance through the venous circulation. As a physiologically integrated neurogliovascular unit (NGVU) serving a particularly vulnerable cerebral white matter (from hypoxia, metabolic insults, infection, and inflammation), a likely insidious process over a lifetime could inflict microenvironment damages that may lead to pathological conditions. Two such conditions, cerebral small vessel disease (CSVD) and vascular parkinsonism (VaP), with poorly understood pathomechanisms, are frequently linked to this brain-wide NGVU. VaP is widely regarded as an atypical parkinsonism, described by cardinal motor manifestations and the presence of cerebrovascular disease, particularly white matter hyperintensities (WMHs) in the basal ganglia and subcortical region. WMHs, in turn, are a recognised imaging spectrum of CSVD manifestations, and in relation to disrupted NGVU, also include enlarged perivascular spaces. Here, in this narrative review, we present and discuss on recent findings that argue for plausible clues between CSVD and VaP by focusing on aberrant multicellular dynamics of a unique integrated NGVU-a crossroad of the immune-vascular-nervous system-which may also extend fresher insights into the elusive interplay between cerebral microvasculature and neurodegeneration, and the potential therapeutic targets.

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.

Magnetic Resonance Imaging and Neurofilament Light in the Differentiation of Parkinsonism

OBJECTIVE

Accurate diagnosis is particularly challenging in Parkinson's disease (PD), multiple system atrophy (MSAp), and progressive supranuclear palsy (PSP). We compare the utility of 3 promising biomarkers to differentiate disease state and explain disease severity in parkinsonism: the Automated Imaging Differentiation in Parkinsonism (AID-P), the Magnetic Resonance Parkinsonism Index (MRPI), and plasma-based neurofilament light chain protein (NfL).

METHODS

For each biomarker, the area under the curve (AUC) of receiver operating characteristic curves were quantified for PD versus MSAp/PSP and MSAp versus PSP and statistically compared. Unique combinations of variables were also assessed. Furthermore, each measures association with disease severity was determined using stepwise multiple regression.

RESULTS

For PD versus MSAp/PSP, AID-P (AUC, 0.900) measures had higher AUC compared with NfL (AUC, 0.747) and MRPI (AUC, 0.669), P < 0.05. For MSAp versus PSP, AID-P (AUC, 0.889), and MRPI (AUC, 0.824) measures were greater than NfL (AUC, 0.537), P < 0.05. We then combined measures to determine if any unique combination provided enhanced accuracy and found that no combination performed better than the AID-P alone in differentiating parkinsonisms. Furthermore, we found that the AID-P demonstrated the highest association with the MDS-UPDRS (Radj2 -AID-P, 26.58%; NfL,15.12%; MRPI, 12.90%).

CONCLUSIONS

Compared with MRPI and NfL, AID-P provides the best overall differentiation of PD versus MSAp/PSP. Both AID-P and MRPI are effective in differentiating MSAp versus PSP. Furthermore, combining biomarkers did not improve classification of disease state compared with using AID-P alone. The findings demonstrate in the current sample that the AID-P and MRPI are robust biomarkers for PD, MSAp, and PSP. © 2020 International Parkinson and Movement Disorder Society.

Midbrain morphology in idiopathic normal pressure hydrocephalus: A progressive supranuclear palsy mimic

INTRODUCTION

Various MRI markers have been applied to support the diagnosis of progressive supranuclear palsy (PSP), such as midbrain diameter and surface, superior cerebellar peduncle (SCP) width, midbrain to pons (m/p) diameter and surface ratio and the Magnetic Resonance Parkinsonism Index (MRPI). These markers provide excellent diagnostic accuracy in discriminating Richardson's syndrome from other causes of Parkinsonism. Idiopathic normal pressure hydrocephalus (iNPH) may mimic Richardson's syndrome, particularly in cases of subtle opthalmokinetic abnormalities. The aim of this study was to compare these MRI markers in PSP and iNPH and examine their diagnostic accuracy.

MATERIALS AND METHODS

Forty-three patients with probable PSP, 17 patients with iNPH, and 29 controls were included. Midbrain diameter and surface, SCP width, m/p diameter and surface ratio and the MRPI were recorded. The "hummingbird sign," "morning glory sign" and "mickey mouse sign" were also evaluated. Analysis of covariance, chi-squared test, and ROC curve analysis were used as appropriate.

RESULTS

All MRI measurements differed significantly among the three study groups. Comparison of PSP and iNPH patients produced the following significant differences: midbrain diameter (P < .0001), m/p diameter ratio (P < .0001), SCP width (P = .050), and MRPI (P = .049). None of these markers produced combined high (>80%) specificity and sensitivity. Qualitative MRI signs were specific, but lacked sensitivity.

DISCUSSION

Midbrain morphology in iNPH may resemble that of PSP. Established MRI markers of midbrain and SCP atrophy cannot confidently differentiate PSP from iNPH. MRI markers do not provide combined high sensitivity and specificity for the differential diagnosis of PSP from iNPH.

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.

Midbrain MRI assessments in progressive supranuclear palsy subtypes

OBJECTIVES

To explore the role of the available midbrain-based MRI morphometric assessments in (1) differentiating among progressive supranuclear palsy (PSP) subtypes (PSP Richardson's syndrome (PSP-RS), PSP with predominant parkinsonism (PSP-P) and the other variant syndromes of PSP (vPSP)), and (2) supporting the diagnosis of PSP subtypes compared with Parkinson's disease (PD) and healthy controls (HC).

METHODS

Seventy-eight patients with PSP (38 PSP-RS, 21 PSP-P and 19 vPSP), 35 PD and 38 HC were included in the present analysis. Available midbrain-based MRI morphometric assessments were calculated for all participants.

RESULTS

Current MRI midbrain-based assessments do not display an adequate sensitivity and specificity profile in differentiating PSP subtypes. On the other hand, we confirmed MR Parkinsonism Index (MRPI) and pons area to midbrain area ratio (P/M) have adequate diagnostic value to support PSP-RS clinical diagnosis compared with both PD and HC, but low sensitivity and specificity profile in differentiating PSP-P from PD as well as from HC. The same measures show acceptable sensitivity and specificity profile in supporting clinical diagnosis of vPSP versus HC but not versus PD. Similar findings were detected for the newer MRPI and P/M versions.

CONCLUSIONS

Further studies are warranted to identify neuroimaging biomarkers supporting the clinical phenotypic categorisation of patients with PSP. MRPI and P/M have diagnostic value in supporting the clinical diagnosis of PSP-RS.

CLASSIFICATION OF EVIDENCE

This study provides class III evidence that available MRI midbrain-based assessments do not have diagnostic value in differentiating the Movement Disorder Society PSP subtypes.

Neuroimaging in Vascular Parkinsonism

PURPOSE OF REVIEW

Being a disease with heterogeneous presentations and unclear consensus on its diagnostic criteria, it is difficult to differentiate vascular parkinsonism (VaP) from other neurodegenerative parkinsonism variants. Ongoing research on structural and functional neuroimaging targeting dopaminergic pathway provides us more insight into the pathophysiology of VaP to improve diagnostic accuracy. The aim of this article is to review how the emerging imaging modalities help the diagnostic process and treatment decision in VaP.

RECENT FINDINGS

Dopamine transporter imaging is a promising tool in differentiating presynaptic parkinsonism and VaP. It also predicts the levodopa responders in VaP. Advanced MRI techniques including volumetry, diffusion tensor imaging and sequences visualising substantia nigra are under development, and they are complementary to each other in detecting structural and functional changes in VaP, which is crucial to ensure the quality of future therapeutic trials for VaP. Dopamine transporter imaging is recommended to patients with suspected VaP. Multimodal MRI in VaP would be an important area to be investigated in the near future.

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.

Morphometric MRI profiles of multiple system atrophy variants and implications for differential diagnosis

Background

Manual width measurements of the middle cerebellar peduncle on MRI were shown to improve the accuracy of an imaging‐guided diagnosis of multiple system atrophy (MSA). Recently, automated volume segmentation algorithms were able to reliably differentiate patients with Parkinson's disease (PD) and the parkinsonian variant of MSA. The objective of the current study was to integrate probabilistic information of the middle cerebellar peduncle into an existing MRI atlas for automated subcortical segmentation and to evaluate the diagnostic properties of the novel atlas for the differential diagnosis of MSA (parkinsonian and cerebellar variant) versus PD.

Methods

Three Tesla MRI scans of 48 healthy individuals were used to establish an automated whole‐brain segmentation procedure that includes the volumes of the putamen, cerebellar gray and white matter, and the middle cerebellar peduncles. Classification accuracy of segmented volumes were tested in early‐stage MSA patients (18 MSA‐parkinsonism, 13 MSA‐cerebellar) and 19 PD patients using a C4.5 classifier.

Results

Putaminal and infratentorial atrophy were present in 77.8% and 61.1% of MSA‐parkinsonian patients, respectively. Four of 18 MSA‐parkinsonian patients (22.2%) had infratentorial atrophy without evidence of putaminal atrophy. Infratentorial atrophy was present in all MSA‐cerebellar patients, with concomitant putaminal atrophy in 46.2% of these cases. The diagnostic algorithm using putaminal and infratentorial volumetric information correctly classified all PD patients and 96.8% of MSA patients.

Conclusions

The middle cerebellar peduncle was successfully integrated into a subcortical segmentation atlas, and its excellent diagnostic accuracy outperformed existing volumetric MRI processing strategies in differentiating MSA patients with variable atrophy patterns from PD patients. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Refining initial diagnosis of Parkinson's disease after follow-up: A 4-year prospective clinical and magnetic resonance imaging study

Background

No prospective study of patients with Parkinson's disease (PD) has investigated the appearance of vertical gaze abnormalities, a feature suggestive of progressive supranuclear palsy (PSP).

Objective

To identify, within a cohort of patients with an initial diagnosis of PD, those who developed vertical gaze abnormalities during a 4‐year follow‐up, and to investigate the performance of new imaging biomarkers in predicting vertical gaze abnormalities.

Methods

A total of 110 patients initially classified as PD and 74 controls were enrolled. All patients underwent clinical assessment at baseline and every year up to the end of the follow‐up. The pons/midbrain area ratio 2.0 and the Magnetic Resonance Parkinsonism Index 2.0 were calculated.

Results

After 4‐year follow‐up, 100 of 110 patients maintained the diagnosis of PD, whereas 10 PD patients (9.1%) developed vertical gaze abnormalities, suggesting an alternative diagnosis of PSP‐parkinsonism. At baseline, the Magnetic Resonance Parkinsonism Index 2.0 was the most accurate biomarker in differentiating PD patients who developed vertical gaze abnormalities from those who maintained an initial diagnosis of PD. At the end of follow‐up, both of these biomarkers accurately distinguished PSP‐parkinsonism from PD.

Conclusions

Our results demonstrate that a number of patients with an initial diagnosis of PD developed vertical gaze abnormalities during a 4‐year follow‐up, and the diagnosis was changed from PD to PSP‐parkinsonism. In PD patients, baseline Magnetic Resonance Parkinsonism Index 2.0 showed the best performance in predicting the clinical evolution toward a PSP‐parkinsonism phenotype, enabling PSP‐parkinsonism patients to be identified at the earliest stage of the disease for promising disease‐modifying therapies. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

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.

MRI Planimetry and Magnetic Resonance Parkinsonism Index in the Differential Diagnosis of Patients with Parkinsonism

BACKGROUND AND PURPOSE

Differential diagnosis of multiple system atrophy, progressive supranuclear palsy, and corticobasal degeneration from Parkinson disease on clinical grounds is often difficult. MR imaging biomarkers could assist in a more accurate diagnosis. We examined the utility of MR imaging surface measurements (MR imaging planimetry) in the differential diagnosis of patients with parkinsonism.

MATERIALS AND METHODS

Fifty-two patients with Parkinson-plus (progressive supranuclear palsy, n = 24; corticobasal degeneration, n = 9; multiple system atrophy, n = 19), 18 patients with Parkinson disease, and 15 healthy controls were included. Corpus callosum, midbrain, and pons surfaces; relevant indices; and the Magnetic Resonance Parkinsonism Index were calculated. Corpus callosum subsection analysis was performed, and the corpus callosum posteroanterior gradient was introduced.

RESULTS

A Magnetic Resonance Parkinsonism Index value of >12.6 discriminated progressive supranuclear palsy from other causes of parkinsonism with a 91% sensitivity and 95% specificity. No planimetry measurement could accurately discriminate those with multiple system atrophy with parkinsonism from patients with Parkinson disease. A corpus callosum posteroanterior gradient value of ≤191 was highly specific (97%) and moderately sensitive (75%) for the diagnosis of corticobasal degeneration versus all other groups. A midbrain-to-corpus callosum posteroanterior gradient ratio of ≤0.45 was highly indicative of progressive supranuclear palsy over corticobasal degeneration (sensitivity 86%, specificity 88%).

CONCLUSIONS

MR imaging planimetry measurements are potent imaging markers of progressive supranuclear palsy and promising markers of corticobasal degeneration but do not seem to assist in the diagnosis of multiple system atrophy with parkinsonism.

Differentiation of neurodegenerative parkinsonian syndromes by volumetric magnetic resonance imaging analysis and support vector machine classification

BACKGROUND

Clinical differentiation of parkinsonian syndromes is still challenging.

OBJECTIVES

A fully automated method for quantitative MRI analysis using atlas-based volumetry combined with support vector machine classification was evaluated for differentiation of parkinsonian syndromes in a multicenter study.

METHODS

Atlas-based volumetry was performed on MRI data of healthy controls (n = 73) and patients with PD (204), PSP with Richardson's syndrome phenotype (106), MSA of the cerebellar type (21), and MSA of the Parkinsonian type (60), acquired on different scanners. Volumetric results were used as input for support vector machine classification of single subjects with leave-one-out cross-validation.

RESULTS

The largest atrophy compared to controls was found for PSP with Richardson's syndrome phenotype patients in midbrain (-15%), midsagittal midbrain tegmentum plane (-20%), and superior cerebellar peduncles (-13%), for MSA of the cerebellar type in pons (-33%), cerebellum (-23%), and middle cerebellar peduncles (-36%), and for MSA of the parkinsonian type in the putamen (-23%). The majority of binary support vector machine classifications between the groups resulted in balanced accuracies of >80%. With MSA of the cerebellar and parkinsonian type combined in one group, support vector machine classification of PD, PSP and MSA achieved sensitivities of 79% to 87% and specificities of 87% to 96%. Extraction of weighting factors confirmed that midbrain, basal ganglia, and cerebellar peduncles had the largest relevance for classification.

CONCLUSIONS

Brain volumetry combined with support vector machine classification allowed for reliable automated differentiation of parkinsonian syndromes on single-patient level even for MRI acquired on different scanners. © 2016 International Parkinson and Movement Disorder Society.

Role of magnetic resonance planimetry and magnetic resonance parkinsonism index in discriminating Parkinson's disease and progressive supranuclear palsy: a retrospective study based on 1.5 and 3 T MRI

Objective

The objective of the study was to assess magnetic resonance (MR) planimetric measurements and MR parkinsonism index (MRPI) in differentiating progressive supranuclear palsy (PSP) from Parkinson’s disease (PD) using 1.5 and 3 T MRI scanner.

Subjects and methods

After ethical approval was obtained, analysis of 34 consecutive patients with PSP, 34 patients with PD and 34 healthy controls (HCs) was performed. HCs were age-matched adults without any history of neurodegenerative disease or movement disorders. Retrospective data from the past 10 years (from January 2006 to December 2015) were obtained from the Hospital Information Management System, and informed consent was obtained from all participants. The measurements of pons area–midbrain area ratio (P/M) and MCP width–superior cerebellar peduncle (SCP) width ratio (MCP/SCP) were used, and MRPI was calculated by the formula ([P/M]×[MCP/SCP]).

Results

Midbrain area and SCP width in patients with PSP (19 males, 15 females; mean age =66.7 years) were significantly (P<0.001) smaller than in patients with PD (20 males, 14 females; mean age =66.7 years) and control participants (17 males, 17 females; mean age =66.1 years). P/M and MCP/SCP were significantly higher in patients with PSP than in patients with PD and control participants. All measurements showed some overlap of values between patients with PSP and patients from PD group and control participants. MRPI value was significantly higher in patients with PSP (mean 21.00) than in patients with PD (mean 9.50; P<0.001) and control participants (mean 9.6; P<0.001), without any overlap of values among groups. No correlation was found between the duration of disease, PSP rating scale, PSP staging system and MRPI in this study. No patient with PSP received a misdiagnosis when the index was used (sensitivity and specificity, 100%).

Conclusion

MRPI should be made an essential part of all MRI brain reporting whenever differentiation between PD and PSP is sought for.

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.

Parkinsonian Patients with Striatal Cribriform State Present Rapidly Progressive Axial Parkinsonism

OBJECTIVE

To define the significance of striatal cribriform state (SCS) observed in patients with primary progressive parkinsonism.

METHODS

We reviewed medical records and brain magnetic resonance imaging studies of 1,260 patients with primary progressive parkinsonism. We identified 23 patients with SCS and analyzed their clinical features.

RESULTS

All 23 patients had rapidly progressive parkinsonism predominated by postural instability and gait disturbance. Clinical features of 18 of the 23 patients were compatible with progressive supranuclear palsy (PSP); 2 patients were compatible with parkinsonian type multiple system atrophy; 2 patients were compatible with mixed clinical features of both; and 1 patient had PSP-like clinical features.

CONCLUSIONS

Most parkinsonian patients with SCS present rapidly progressive parkinsonism predominated by postural instability and gait disturbance. SCS observed in patients with parkinsonism does not seem to be a coincidental finding associated with the generalized cerebrovascular process.

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.

Magnetic Resonance Parkinsonism Index: diagnostic accuracy of a fully automated algorithm in comparison with the manual measurement in a large Italian multicentre study in patients with progressive supranuclear palsy

OBJECTIVES

To investigate the reliability of a new in-house automatic algorithm for calculating the Magnetic Resonance Parkinsonism Index (MRPI), in a large multicentre study population of patients affected by progressive supranuclear palsy (PSP) or Parkinson's disease (PD), and healthy controls (HC), and to compare the diagnostic accuracy of the automatic and manual MRPI values.

METHODS

The study included 88 PSP patients, 234 PD patients and 117 controls. MRI was performed using both 3T and 1.5T scanners. Automatic and manual MRPI values were evaluated, and accuracy of both methods in distinguishing PSP from PD and controls was calculated.

RESULTS

No statistical differences were found between automated and manual MRPI values in all groups. The automatic MRPI values differentiated PSP from PD with an accuracy of 95 % (manual MRPI accuracy 96 %) and 97 % (manual MRPI accuracy 100 %) for 1.5T and 3T scanners, respectively.

CONCLUSION

Our study showed that the new in-house automated method for MRPI calculation was highly accurate in distinguishing PSP from PD. Our automatic approach allows a widespread use of MRPI in clinical practice and in longitudinal research studies.

KEY POINTS

• A new automatic method for calculating the MRPI is presented. • Automatic MRPI values are in good agreement with manual values. • Automatic MRPI can distinguish patients with PSP from patients with PD. • The automatic method overcomes MRPI application limitations in routine practice. • The automatic method may allow a more widespread use of MRPI.

Magnetic Resonance Parkinsonism Index and midbrain to pons ratio: Which index better distinguishes Progressive Supranuclear Palsy patients with a low degree of diagnostic certainty from patients with Parkinson Disease?

INTRODUCTION

Several studies have compared the performances of midbrain to pons area ratio (M/P) and the Magnetic Resonance Parkinsonism Index (MRPI) in distinguishing patients with Progressive Supranuclear Palsy (PSP) from those with Parkinson's disease (PD) with conflicting results. The current study aimed to compare the performance of these indexes in a well-characterized sample of PSP patients using either a manual or a fully automated approach to measure the brainstem structures involved in M/P and MRPI calculation.

METHODS

This study involved 179 patients affected by idiopathic PD, 35 patients affected by PSP (15 probable and 20 possible) and 87 healthy controls. Sensitivity, specificity, positive predictive value (PPV) and area under the curve (AUC) of MRPI and M/P in distinguishing possible and probable PSP from PD and controls were calculated.

RESULTS

No significant difference was found between manual and automated values for both MRPI and M/P. MRPI and M/P differentiated probable PSP from PD with similar performance. By contrast, MRPI showed higher sensitivity and specificity than M/P when patients with possible PSP were compared with PD (MRPI, sensitivity 100%, specificity 98.88%; M/P, sensitivity 85%, specificity 93.85%). A significant difference was also observed in AUC between MRPI and M/P in distinguishing possible PSP from PD.

CONCLUSION

Our study demonstrates that MRPI was more accurate than M/P, in differentiating patients with possible PSP from those with PD. In patients suspected of having PSP with a low level of clinic diagnostic accuracy, MRPI should be preferred to M/P for distinguishing these patients from PD.

Manual MRI morphometry in Parkinsonian syndromes

BACKGROUND

Several morphometric magnetic resonance imaging parameters may serve for differential diagnosis of parkinsonism. The objective of this study was to identify which performs best in clinical routine.

METHODS

We acquired multicentric magnetization-prepared rapid gradient echo sequences in patients with Parkinson's disease (n=204), progressive supranuclear palsy (n=106), multiple system atrophy-cerebellar, (n = 21); multiple system atrophy-parkinsonian (n = 60), and healthy controls (n = 73), performed manual planimetric measurements, and calculated receiver operator characteristics with leave-one-out cross-validation to propose cutoff values.

RESULTS

The midsagittal midbrain area was reduced in PSP versus all other groups (P < 0.001). The midsagittal pons area was reduced in MSA-cerebellar, MSA-parkinsonian, and PSP versus PD patients and healthy controls (P < 0.001). The midbrain/pons area ratio was lower in PSP (P < 0.001) and higher in MSA-cerebellar and MSA-parkinsonian versus PD and PSP (P < 0.001).

CONCLUSIONS

The midsagittal midbrain area most reliably identified PSP, the midsagittal pons area MSA-cerebellar. The midbrain/pons area ratio differentiated MSA-cerebellar and PSP better than the magnetic resonance-Parkinson index. © 2017 International Parkinson and Movement Disorder Society.

MRI measurements of brainstem structures in patients with vascular parkinsonism, progressive supranuclear palsy, and Parkinson's disease

Magnetic resonance (MR) measurements of brainstem structures have been reported to be useful in differentiating patients with progressive supranuclear palsy (PSP) from those with Parkinson's disease (PD). The aim of this study was to determine whether quantitative measurements of brainstem structures on MR images can help differentiate vascular parkinsonism (VaP) from degenerative parkinsonism (PD and PSP). Areas of the midbrain and pons, and widths of the superior cerebellar peduncle (SCP) and middle cerebellar peduncle (MCP) were measured in 62 patients with PD, 25 patients with PSP (11 probable and 14 possible), and 24 patients with VaP on T ₁-weighted MR images. The midbrain-to-pons area ratio (M/P ratio), MCP-to-SCP width ratio (MCP/SCP ratio), and MR parkinsonism index (MRPI; P/M × MCP/SCP) were calculated. The midbrain area and M/P ratio of patients with VaP (104 and 0.22 mm², respectively) were smaller than those in patients with PD (121 and 0.24 mm², respectively) and larger than those in patients with PSP (90 and 0.19 mm², respectively). The MRPI was significantly larger in patients with PSP (13.6) in comparison with those with PD (10.1) and VaP (10.7). However, the MRPI of patients with VaP was not significantly different from patients with PD. Our study showed that MRPI was useful in differentiating PSP from VaP or PD. Thus, MR imaging measurements of brainstem structures may help differentiate patients with VaP from those with PD and PSP.

Utility of susceptibility-weighted imaging in Parkinson's disease and atypical Parkinsonian disorders

In the clinic, the diagnosis of Parkinson's disease (PD) largely depends on clinicians' experience. When the diagnosis is made, approximately 80% of dopaminergic cells in the substantia nigra (SN) have been lost. Additionally, it is rather challenging to differentiate PD from atypical parkinsonian disorders (APD). Clinially-available 3T conventional MRI contributes little to solve these problems. The pathologic alterations of parkinsonism show abnormal brain iron deposition, and therefore susceptibility-weighted imaging (SWI), which is sensitive to iron concentration, has been applied to find iron-related lesions for the diagnosis and differentiation of PD in recent decades. Until now, the majority of research has revealed that in SWI the signal intensity changes in deep brain nuclei, such as the SN, the putamen (PUT), the globus pallidus (GP), the thalamus (TH), the red nucleus (RN) and the caudate nucleus (CN), thereby raising the possibility of early diagnosis and differentiation. Furthermore, the signal changes in SN, PUT and TH sub-regions may settle the issues with higher accuracy. In this article, we review the brain iron deposition of PD, MSA-P and PSP in SWI in the hope of exhibiting a profile of SWI features in PD, MSA and PSP and its clinical values.