The role of AI and machine learning in the diagnosis of Parkinson's disease and atypical parkinsonisms.

Parkinson's disease is a neurodegenerative movement disorder associated with motor and non-motor symptoms causing severe disability as the disease progresses. The development of biomarkers for Parkinson's disease to diagnose patients earlier and predict disease progression is imperative. As artificial intelligence and machine learning techniques efficiently process data and can handle multiple data types, we reviewed the literature to determine the extent to which these techniques have been applied to biomarkers for Parkinson's disease and movement disorders. We determined that the most applicable machine learning techniques are support vector machines and neural networks, depending on the size and type of the data being analyzed. Additionally, more complex machine learning techniques showed increased accuracy when compared to less complex techniques, especially when multiple machine learning models were combined. We can conclude that artificial intelligence and machine learning techniques may have the capacity to significantly boost diagnostic capacity in movement disorders and Parkinson's disease.

Multiple system atrophy with amyloid-ß-predominant Alzheimer's disease neuropathologic change.

Multiple system atrophy is a neurodegenerative disease with α-synuclein pathology predominating in the striatonigral and olivopontocerebellar systems. Mixed pathologies are considered to be of low frequency and mostly comprise primary age-related tauopathy or low levels of Alzheimer's disease-related neuropathologic change. Therefore, the concomitant presence of different misfolded proteins in the same brain region is less likely in multiple system atrophy. During the neuropathological evaluation of 21 consecutive multiple system atrophy cases, we identified four cases exhibiting an unusual discrepancy between high Thal amyloid-ß phase and low transentorhinal Braak neurofibrillary tangle stage. We mapped α-synuclein pathology, measured the size and number of glial cytoplasmic inclusions and compared the amyloid-ß peptides between multiple system atrophy and Alzheimer's disease. In addition, we performed α-synuclein seeding assay from the affected putamen samples. We performed genetic testing for APOE, MAPT, PSEN1, PSEN2 and APP. We refer to the four multiple system atrophy cases with discrepancy between amyloid-ß and tau pathology as 'amyloid-ß-predominant Alzheimer's disease neuropathologic change-multiple system atrophy' to distinguish these from multiple system atrophy with primary age-related tauopathy or multiple system atrophy with typical Alzheimer's disease neuropathologic change. As most multiple system atrophy cases with mixed pathologies reported in the literature, these cases did not show a peculiar clinical or MRI profile. Three amyloid-ß-predominant Alzheimer's disease neuropathologic change-multiple system atrophy cases were available for genetic testing, and all carried the APOE ɛ4 allele. The extent and severity of neuronal loss and α-synuclein pathology were not different compared with typical multiple system atrophy cases. Analysis of amyloid-ß peptides revealed more premature amyloid-ß plaques in amyloid-ß-predominant Alzheimer's disease neuropathologic change-multiple system atrophy compared with Alzheimer's disease. α-Synuclein seeding amplification assay showed differences in the kinetics in two cases. This study highlights a rare mixed pathology variant of multiple system atrophy in which there is an anatomical meeting point of amyloid-ß and α-synuclein, i.e. the striatum or cerebellum. Since biomarkers are entering clinical practice, these cases will be recognized, and the clinicians have to be informed that the prognosis is not necessarily different than in pure multiple system atrophy cases but that the effect of potential α-synuclein-based therapies might be influenced by the co-presence of amyloid-ß in regions where α-synuclein also aggregates. We propose that mixed pathologies should be interpreted not only based on differences in the clinical phenotype but also on whether protein depositions regionally overlap, potentially leading to a different response to α-synuclein-targeted therapies.

Longitudinal cerebral perfusion in presymptomatic genetic frontotemporal dementia: GENFI results.

INTRODUCTION: Effective longitudinal biomarkers that track disease progression are needed to characterize the presymptomatic phase of genetic frontotemporal dementia (FTD). We investigate the utility of cerebral perfusion as one such biomarker in presymptomatic FTD mutation carriers. METHODS: We investigated longitudinal profiles of cerebral perfusion using arterial spin labeling magnetic resonance imaging in 42 C9orf72, 70 GRN, and 31 MAPT presymptomatic carriers and 158 non-carrier controls. Linear mixed effects models assessed perfusion up to 5 years after baseline assessment. RESULTS: Perfusion decline was evident in all three presymptomatic groups in global gray matter. Each group also featured its own regional pattern of hypoperfusion over time, with the left thalamus common to all groups. Frontal lobe regions featured lower perfusion in those who symptomatically converted versus asymptomatic carriers past their expected age of disease onset. DISCUSSION: Cerebral perfusion is a potential biomarker for assessing genetic FTD and its genetic subgroups prior to symptom onset. HIGHLIGHTS: Gray matter perfusion declines in at-risk genetic frontotemporal dementia (FTD). Regional perfusion decline differs between at-risk genetic FTD subgroups . Hypoperfusion in the left thalamus is common across all presymptomatic groups. Converters exhibit greater right frontal hypoperfusion than non-converters past their expected conversion date. Cerebral hypoperfusion is a potential early biomarker of genetic FTD.

A multi-site study on sex differences in cortical thickness in non-demented Parkinson's disease.

Clinical, cognitive, and atrophy characteristics depending on sex have been previously reported in Parkinson's disease (PD). However, though sex differences in cortical gray matter measures in early drug naïve patients have been described, little is known about differences in cortical thickness (CTh) as the disease advances. Our multi-site sample comprised 211 non-demented PD patients (64.45% males; mean age 65.58 ± 8.44 years old; mean disease duration 6.42 ± 5.11 years) and 86 healthy controls (50% males; mean age 65.49 ± 9.33 years old) with available T1-weighted 3 T MRI data from four international research centers. Sex differences in regional mean CTh estimations were analyzed using generalized linear models. The relation of CTh in regions showing sex differences with age, disease duration, and age of onset was examined through multiple linear regression. PD males showed thinner cortex than PD females in six frontal (bilateral caudal middle frontal, bilateral superior frontal, left precentral and right pars orbitalis), three parietal (bilateral inferior parietal and left supramarginal), and one limbic region (right posterior cingulate). In PD males, lower CTh values in nine out of ten regions were associated with longer disease duration and older age, whereas in PD females, lower CTh was associated with older age but with longer disease duration only in one region. Overall, male patients show a more widespread pattern of reduced CTh compared with female patients. Disease duration seems more relevant to explain reduced CTh in male patients, suggesting worse prognostic over time. Further studies should explore sex-specific cortical atrophy trajectories using large longitudinal multi-site data.

PET imaging of synaptic density in Parkinsonian disorders.

Synaptic dysfunction and altered synaptic pruning are present in people with Parkinsonian disorders. Dopamine loss and alpha-synuclein accumulation, two hallmarks of Parkinson's disease (PD) pathology, contribute to synaptic dysfunction and reduced synaptic density in PD. Atypical Parkinsonian disorders are likely to have unique spatiotemporal patterns of synaptic density, differentiating them from PD. Therefore, quantification of synaptic density has the potential to support diagnoses, monitor disease progression, and treatment efficacy. Novel radiotracers for positron emission tomography which target the presynaptic vesicle protein SV2A have been developed to quantify presynaptic density. The radiotracers have successfully investigated synaptic density in preclinical models of PD and people with Parkinsonian disorders. Therefore, this review will summarize the preclinical and clinical utilization of SV2A radiotracers in people with Parkinsonian disorders. We will evaluate how SV2A abundance is associated with other imaging modalities and the considerations for interpreting SV2A in Parkinsonian pathology.

Tau in Atypical Parkinsonisms: A Meta-Analysis of in Vivo PET Imaging Findings.

Background: Progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) are atypical parkinsonisms (APs) that are classified as tauopathies. Patients with these APs may present with similar early clinical manifestations to Parkinson's disease (PD), but they prove unresponsive to anti-parkinsonian medications. Objective: The main objective of this meta-analysis was to compare first- and second-generation tau PET tracer efficacy in patients with the APs to identify potential diagnostic biomarkers. Methods: PubMed and Web of Science were searched between January 1, 1999 and December 31, 2022. We included case-control studies that were published in English and report tau PET tracer binding as mean ± SD in at least one region of interest (ROI). Differences in tau PET binding values were meta-analyzed using random-effects meta-analytic models and subgroup analyses based on ROIs in the statistical programming language R (version 4.2.1). Results: Overall, 29 studies with 665 patients were included in the final review. [18F]PI-2620 outperformed first-generation tracers when comparing PSP-HC (g = -1.68, 95% CI: -2.05 to -1.30) and CBD-HC (g = -1.37, 95% CI: -2.25 to -0.49). When comparing PSP-PD, the first-generation tracer, [18F]AV-1451, presented with higher binding to PSP patients (g = -0.80, 95% CI: -1.24 to -0.35). Conclusions: Our results demonstrate the efficacy of [18F]PI-2620 PET in imaging AP-tau. These findings contribute towards identifying a diagnostic imaging biomarker for patients with APs. The main limitation of this study was the heterogeneity of the results. Future studies should conduct AP-PD comparisons with second-generation tracers to confirm the preliminary results found here.

First-in-Human PET Imaging of [18F]SDM-4MP3: A Cautionary Tale.

[18F]SynVesT-1 is a PET radiopharmaceutical that binds to the synaptic vesicle protein 2A (SV2A) and serves as a biomarker of synaptic density with widespread clinical research applications in psychiatry and neurodegeneration. The initial goal of this study was to concurrently conduct PET imaging studies with [18F]SynVesT-1 at our laboratories. However, the data in the first two human PET studies had anomalous biodistribution despite the injected product meeting all specifications during the prerelease quality control protocols. Further investigation, including imaging in rats as well as proton and carbon 2D-NMR spectroscopic studies, led to the discovery that a derivative of the precursor had been received from the manufacturer. Hence, we report our investigation and the first-in-human study of [18F]SDM-4MP3, a structural variant of [18F]SynVesT-1, which does not have the requisite characteristics as a PET radiopharmaceutical for imaging SV2A in the central nervous system.

Preliminary Assessment of Reference Region Quantification and Reduced Scanning Times for [18F]SynVesT-1 PET in Parkinson's Disease.

Synaptic density in the central nervous system can be measured in vivo using PET with [18F]SynVesT-1. While [18F]SynVesT-1 has been proven to be a powerful radiopharmaceutical for PET imaging of neurodegenerative disorders such as Parkinson's disease (PD), its currently validated acquisition and quantification protocols are invasive and technically challenging in these populations due to the arterial sampling and relatively long scanning times. The objectives of this work were to evaluate a noninvasive (reference tissue) quantification method for [18F]SynVesT-1 in PD patients and to determine the minimum scan time necessary for accurate quantification. [18F]SynVesT-1 PET scans were acquired in 5 patients with PD and 3 healthy control subjects for 120 min with arterial blood sampling. Quantification was performed using the one-tissue compartment model (1TCM) with arterial input function, as well as with the simplified reference tissue model (SRTM) to estimate binding potential (BPND) using centrum semiovale (CS) as a reference region. The SRTM2 method was used with k2' fixed to either a sample average value (0.037 min-1) or a value estimated first through coupled fitting across regions for each participant. Direct SRTM estimation and the Logan reference region graphical method were also evaluated. There were no significant group differences in CS volume, radiotracer uptake, or efflux (ps > 0.47). Each fitting method produced BPND estimates in close agreement with those derived from the 1TCM (subject R2s > 0.98, bias < 10%), with no difference in bias between the control and PD groups. With SRTM2, BPND estimates from truncated scan data as short as 80 min produced values in excellent agreement with the data from the full 120 min scans (bias < 6%). While these are preliminary results from a small sample of patients with PD (n = 5), this work suggests that accurate synaptic density quantification may be performed without blood sampling and with scan time under 90 minutes. If further validated, these simplified procedures for [18F]SynVesT-1 PET quantification can facilitate its application as a clinical research imaging technology and allow for larger study samples and include a broader scope of patients including those with neurodegenerative diseases.

Cognition affects gait adaptation after split-belt treadmill training in Parkinson's disease.

BACKGROUND: Split-belt treadmill (SBTM) training has been proposed to improve gait symmetry and overall gait performance of patients with Parkinson's disease (PD). OBJECTIVES: To determine whether patient's baseline features affect gait adaptation to SBTM in PD with freezing of gait (FOG). METHODS: Twenty participants with idiopathic PD and treatment-resistant FOG underwent several clinical assessments including the Toronto Cognitive Assessment (TorCA) prior to treadmill training. Velocity of the treadmill was adjusted to over-ground walking speed. During SBTM training, the belt velocity on the least-affected side was reduced by 25%. RESULTS: Participants who adapted to SBTM training demonstrated cognitively intact TorCA scores (p < 0.001), particularly intact working memory (p < 0.001). After-effects correlated with normal total TorCA (p = 0.02), working memory and visuospatial (p < 0.001) function. CONCLUSIONS: Cognitive impairment, particularly impaired working memory, reduces gait adaptation and after-effects in PD with FOG. This is informative for trials studying prolonged effects of SBTM training in FOG.

Structural and Molecular Imaging for Clinically Uncertain Parkinsonism.

Neuroimaging is an important adjunct to the clinical assessment of Parkinson disease (PD). Parkinsonism can be challenging to differentiate, especially in early disease stages, when it mimics other movement disorders or when there is a poor response to dopaminergic therapies. There is also a discrepancy between the phenotypic presentation of degenerative parkinsonism and the pathological outcome. The emergence of more sophisticated and accessible neuroimaging can identify molecular mechanisms of PD, the variation between clinical phenotypes, and the compensatory mechanisms that occur with disease progression. Ultra-high-field imaging techniques have improved spatial resolution and contrast that can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. We highlight the imaging modalities that can be accessed in clinical practice and recommend an approach to the diagnosis of clinically uncertain parkinsonism.

The challenging quest of neuroimaging: From clinical to molecular-based subtyping of Parkinson disease and atypical parkinsonisms.

The current framework of Parkinson disease (PD) focuses on phenotypic classification despite its considerable heterogeneity. We argue that this method of classification has restricted therapeutic advances and therefore limited our ability to develop disease-modifying interventions in PD. Advances in neuroimaging have identified several molecular mechanisms relevant to PD, variation within and between clinical phenotypes, and potential compensatory mechanisms with disease progression. Magnetic resonance imaging (MRI) techniques can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging have informed the neurotransmitter, metabolic, and inflammatory dysfunctions that could potentially distinguish disease phenotypes and predict response to therapy and clinical outcomes. However, rapid advancements in imaging techniques make it challenging to assess the significance of newer studies in the context of new theoretical frameworks. As such, there needs to not only be a standardization of practice criteria in molecular imaging but also a rethinking of target approaches. In order to harness precision medicine, a coordinated shift is needed toward divergent rather than convergent diagnostic approaches that account for interindividual differences rather than similarities within an affected population, and focus on predictive patterns rather than already lost neural activity.

Multimodal visual system analysis as a biomarker of visual hallucinations in Parkinson's disease.

Visual hallucinations (VH) are present in up to 75% of Parkinson's disease (PD) patients. However, their neural bases and participation of the visual system in VH are not well-understood in PD. Seventy-four participants, 12 PD with VH (PDVH), 35 PD without VH (PDnoVH) and 27 controls underwent a battery of primary visual function and visual cognition tests, retinal optical coherence tomography and structural and resting-state functional brain MRI. We quantified cortical thickness with Freesurfer and functional connectivity (FC) of Visual (VIS), Fronto-Parietal (FP), Ventral Attention (VAN) and Dorsal Attention (DAN) networks with CONN toolbox. Group comparisons were performed with MANCOVA. Area Under the Curve (AUC) was computed to assess the ability of visual variables to differentiate PDVH and PDnoVH. There were no significant PDVH vs PDnoVH differences in disease duration, motor manifestations, general cognition or dopamine agonist therapy (DA) use. Compared to PDnoVH and HC, and regardless of DA use, PDVH showed significantly reduced contrast sensitivity, visuoperceptive and visuospatial abilities, increased retina photoreceptor layer thickness, reduced cortical thickness mostly in right visual associative areas, decreased between-network VIS-VAN and VAN-DAN connectivity and increased within-network DAN connectivity. The combination of clinical and imaging variables that best discriminated PDVH and PDnoVH (highest AUC), where within-network DAN FC, photoreceptor layer thickness and cube analysis test from Visual Object and Space Perception Battery (accuracy of 81.8%). Compared to PDnoVH, PDVH have specific functional and structural abnormalities within the visual system, which can be quantified non-invasively and could potentially constitute biomarkers for VH in PD.

Beta amyloid deposition and cognitive decline in Parkinson's disease: a study of the PPMI cohort.

The accumulation of beta amyloid in the brain has a complex and poorly understood impact on the progression of Parkinson's disease pathology and much controversy remains regarding its role, specifically in cognitive decline symptoms. Some studies have found increased beta amyloid burden is associated with worsening cognitive impairment in Parkinson's disease, especially in cases where dementia occurs, while other studies failed to replicate this finding. To better understand this relationship, we examined a cohort of 25 idiopathic Parkinson's disease patients and 30 healthy controls from the Parkinson's Progression Marker Initiative database. These participants underwent [18F]Florbetaben positron emission tomography scans to quantify beta amyloid deposition in 20 cortical regions. We then analyzed this beta amyloid data alongside the longitudinal Montreal Cognitive Assessment scores across 3 years to see how participant's baseline beta amyloid levels affected their cognitive scores prospectively. The first analysis we performed with these data was a hierarchical cluster analysis to help identify brain regions that shared similarity. We found that beta amyloid clusters differently in Parkinson's disease patients compared to healthy controls. In the Parkinson's disease group, increased beta amyloid burden in cluster 2 was associated with worse cognitive ability, compared to deposition in clusters 1 or 3. We also performed a stepwise linear regression where we found an adjusted R2 of 0.495 (49.5%) in a model explaining the Parkinson's disease group's Montreal Cognitive Assessment score 1-year post-scan, encompassing the left gyrus rectus, the left anterior cingulate cortex, and the right parietal cortex. Taken together, these results suggest regional beta amyloid deposition alone has a moderate effect on predicting future cognitive decline in Parkinson's disease patients. The patchwork effect of beta amyloid deposition on cognitive ability may be part of what separates cognitive impairment from cognitive sparing in Parkinson's disease. Thus, we suggest it would be more useful to measure beta amyloid burden in specific brain regions rather than using a whole-brain global beta amyloid composite score and use this information as a tool for determining which Parkinson's disease patients are most at risk for future cognitive decline.

Neuroimaging of rapid eye movement sleep behavior disorder and its relation to Parkinson's disease.

Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by polysomnography-confirmed REM sleep without atonia and dream-enacting behaviors. This disorder is considered a prodromal syndrome of alpha-synucleinopathies like Parkinson's disease (PD), where it affects more than 50% of PD patients. The underlying pathology of RBD has been generally understood to involve the pontine nuclei within the brainstem. However, the complete pathophysiology beyond the brainstem remains unclear as does its relationship with PD pathology. Therefore, this review aims to survey the neuroimaging literature involving PET, SPECT, and MR imaging techniques to provide an updated understanding of the neuro-chemical, structural, and functional changes in both RBD and PD patients comorbid with RBD. This review found neuroimaging evidence that indicate alterations to the dopaminergic and cholinergic system, blood perfusion, and glucose metabolism in both RBD patients and PD patients with RBD. Beyond the brainstem, structural and functional changes were found to involve the nigrostriatal system, limbic system, and the cortex-suggesting that RBD is a multi-systemic neurodegenerative process. Future investigations are encouraged to follow RBD patients longitudinally using multimodal imaging techniques to enhance our understanding of this parasomnia disorder. Uncovering which individuals are most likely to develop an alpha-synuclein disorder in the prodromal phase will improve patient outcomes and potentially aid in the development of novel treatments for patients affected by RBD.

Imaging pathological tau in atypical parkinsonisms: A review.

Atypical parkinsonisms (APs) are a group of diseases linked to tau pathology. These include progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). In the initial stages, these APs may have similar clinical manifestations to Parkinson's disease (PD) and other parkinsonisms: bradykinesia, postural instability, tremor, and cognitive decline. Because of this, one major hurdle is the accurate early diagnosis of APs. Recent advances in positron emission tomography (PET) radiotracer development have allowed for targeting pathological tau in Alzheimer's disease (AD). Currently, work is still in progress for identifying a first-in-class radiotracer for imaging tau in APs. In this review, we evaluate the literature on in vitro and in vivo testing of current tau PET radiotracers in APs. The tau PET tracers assessed include both first-generation tracers ([18F]AV-1451, [18F]FDDNP, [18F]THK derivatives, and [11C]PBB3) and second-generation tracers ([18F]PM-PBB3, [18F]PI-2620, [18F]RO-948, [18F]JNJ-067, [18F]MK-6240, and [18F]CBD-2115). Concerns regarding off-target binding to cerebral white matter and the basal ganglia are still prominent with first-generation tracers, but this seems to have been mediated in a handful of second-generation tracers, including [18F]PI-2620 and [18F]PM-PBB3. Additionally, these two tracers and [18F]MK-6240 show promising results for imaging PSP- and CBD-tau. Overall, [18F]AV-1451 is the most widely studied tracer but the mixed results regarding its efficacy for use in imaging AP-tau is a cause for concern moving forward. Instead, future work may benefit from focusing on the second-generation radiotracers which seem to have a higher specificity for AP-tau than those originally developed for imaging AD-tau.

Reversible neurological and brain MRI changes following COVID-19 vaccination: A case report.

BACKGROUND: Various neurological sequalae have been described following COVID-19 vaccination. Here we describe the first case of untreated post COVID-19 vaccine encephalitis with spontaneous resolution of contrast enhancing hyperintensities on MRI concomitant with clinical improvement. CASE PRESENTATION: A 59-year-old woman presented with a two-day history of unsteady gait, incoordination, visual symptoms, and lethargy. She had received AZD1222 (AstraZeneca) and mRNA-1273 (Moderna) COVID-19 vaccines at 3 months and 12 days, respectively, before presentation. Brain MRI showed no abnormality on the non-enhanced sequences, but numerous enhancing lesions in the cerebral cortex, deep grey matter, brainstem, and cerebellum. Treatment was expectant, the patient improved clinically over 10 days, and repeat MRI showed near complete resolution of the imaging abnormality. CONCLUSIONS: We describe neurological deterioration 12 days after a second dose of COVID-19 vaccine. There was no evidence of edema or demyelinating lesions in the brain on MRI, but there was extensive contrast-enhancement indicating loss of blood-brain barrier (BBB) integrity. This provides a potential in vivo, clinical-imaging correlate of the post-mortem evidence that SARS-CoV-2 spike protein may induce loss of BBB permeability. While this adds to the list of rare adverse neurological reactions to COVID-19 vaccination, the benefits of receiving the vaccine far outweigh these risks.

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.