Contribution of the Mesencephalon Indices to Differential Diagnosis of Parkinsonian Disorders

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.

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.

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.

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.

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.