Quantifying the Severity of Parkinson Disease by Use of Dopaminergic Neuroimaging

NigraNet: An automatic framework to assess nigral neuromelanin content in early Parkinson's disease using convolutional neural network

BACKGROUND

Parkinson's disease (PD) demonstrates neurodegenerative changes in the substantia nigra pars compacta (SNc) using neuromelanin-sensitive (NM)-MRI. As SNc manual segmentation is prone to substantial inter-individual variability across raters, development of a robust automatic segmentation framework is necessary to facilitate nigral neuromelanin quantification. Artificial intelligence (AI) is gaining traction in the neuroimaging community for automated brain region segmentation tasks using MRI.

OBJECTIVE

Developing and validating AI-based NigraNet, a fully automatic SNc segmentation framework allowing nigral neuromelanin quantification in patients with PD using NM-MRI.

METHODS

We prospectively included 199 participants comprising 144 early-stage idiopathic PD patients (disease duration = 1.5 ± 1.0 years) and 55 healthy volunteers (HV) scanned using a 3 Tesla MRI including whole brain T1-weighted anatomical imaging and NM-MRI. The regions of interest (ROI) were delineated in all participants automatically using NigraNet, a modified U-net, and compared to manual segmentations performed by two experienced raters. The SNc volumes (Vol), volumes corrected by total intracranial volume (C_vol), normalized signal intensity (NSI) and contrast-to-noise ratio (CNR) were computed. One-way GLM-ANCOVA was performed while adjusting for age and sex as covariates. Diagnostic performance measurement was assessed using the receiver operating characteristic (ROC) analysis. Inter and intra-observer variability were estimated using Dice similarity coefficient (DSC). The agreements between methods were tested using intraclass correlation coefficient (ICC) based on a mean-rating, two-way, mixed-effects model estimates for absolute agreement. Cronbach's alpha and Bland-Altman plots were estimated to assess inter-method consistency.

RESULTS

Using both methods, Vol, C_vol, NSI and CNR measurements differed between PD and HV with an effect of sex for C_vol and CNR. ICC values between the methods demonstrated optimal agreement for C_vol and CNR (ICC > 0.9) and high reproducibility (DSC: 0.80) was also obtained. The SNc measurements also showed good to excellent consistency values (Cronbach's alpha > 0.87). Bland-Altman plots of agreement demonstrated no association of SNc ROI measurement differences between the methods and ROI average measurements while confirming that 95 % of the data points were ranging between the limits of mean difference (d ± 1.96xSD). Percentage changes between PD and HV were -27.4 % and -17.7 % for Vol, -30.0 % and -22.2 % for C_vol, -15.8 % and -14.4 % for NSI, -17.1 % and -16.0 % for CNR for automatic and manual measurements respectively. Using automatic method, in the entire dataset, we obtained the areas under the ROC curve (AUC) of 0.83 for Vol, 0.85 for C_vol, 0.79 for NSI and 0.77 for CNR whereas in the training dataset of 0.96 for Vol, 0.95 for C_vol, 0.85 for NSI and 0.85 for CNR. Disease duration correlated negatively with NSI of the patients for both the automatic and manual measurements.

CONCLUSIONS

We presented an AI-based NigraNet framework that utilizes a small MRI training dataset to fully automatize the SNc segmentation procedure with an increased precision and more reproducible results. Considering the consistency, accuracy and speed of our approach, this study could be a crucial step towards the implementation of a time-saving non-rater dependent fully automatic method for studying neuromelanin changes in clinical settings and large-scale neuroimaging studies.

Gray Matter Volume Loss in Proposed Brain-First and Body-First Parkinson's Disease Subtypes

BACKGROUND

α-Synuclein pathology is associated with neuronal degeneration in Parkinson's disease (PD) and considered to sequentially spread across the brain (Braak stages). According to a new hypothesis of distinct α-synuclein spreading directions based on the initial site of pathology, the "brain-first" spreading subtype would be associated with a more asymmetric cerebral and nigrostriatal pathology than the "body-first" subtype.

OBJECTIVE

Here, we tested if proposed markers of brain-first PD (ie, higher dopamine transporter [DaT] asymmetry; absence of rapid eye movement sleep behavior disorder [RBD]) are associated with a greater or more asymmetric reduction in gray matter volume (GMV) in comparison to body-first PD.

METHODS

Data of 255 de novo PD patients and 110 healthy controls (HCs) were retrieved from the Parkinson's Progression Markers Initiative. Structural magnetic resonance images were preprocessed, and GMVs and their hemispherical asymmetry were obtained for each of the neuropathologically defined Braak stages. Group and correlation comparisons were performed to assess differences in GMV and GMV asymmetry between PD subtypes.

RESULTS

PD patients demonstrated significantly smaller bilateral GMVs compared to HCs, in a pattern denoting stage-dependent disease-related brain atrophy. However, the degree of putaminal DaT asymmetry was not associated with reduced GMV or higher GMV asymmetry. Furthermore, RBD-negative and RBD-positive patients did not demonstrate a significant difference in GMV or GMV asymmetry.

CONCLUSIONS

Our findings suggest that putative brain-first and body-first patients do not present diverging brain atrophy patterns. Although certainly not disproving the brain-first/body-first spreading hypothesis, this study fails to provide evidence in support of it. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Longitudinal Changes in Neuromelanin MRI Signal in Parkinson's Disease: A Progression Marker

BACKGROUND

Development of reliable and accurate imaging biomarkers of dopaminergic cell neurodegeneration is necessary to facilitate therapeutic drug trials in Parkinson's disease (PD). Neuromelanin-sensitive MRI techniques have been effective in detecting neurodegeneration in the substantia nigra pars compacta (SNpc). The objective of the current study was to investigate longitudinal neuromelanin signal changes in the SNpc in PD patients.

METHODS

In this prospective, longitudinal, observational case-control study, we included 140 PD patients and 64 healthy volunteers divided into 2 cohorts. Cohort I included 99 early PD patients (disease duration, 1.5 ± 1.0 years) and 41 healthy volunteers analyzed at baseline (V1), where 79 PD patients and 32 healthy volunteers were rescanned after 2.0 ± 0.2 years of follow-up (V2). Cohort II included 41 progressing PD patients (disease duration, 9.3 ± 3.7 years) and 23 healthy volunteers at V1, where 30 PD patients were rescanned after 2.4 ± 0.5 years of follow-up. Subjects were scanned at 3 T MRI using 3-dimensional T1-weighted and neuromelanin-sensitive imaging. Regions of interest were delineated manually to calculate SN volumes, volumes corrected by total intracranial volume, signal-to-noise ratio, and contrast-to-noise ratio.

RESULTS

Results showed (1) significant reduction in volume and volume corrected by total intracranial volume between visits, greater in progressing PD than nonsignificant changes in healthy volunteers; (2) no significant effects of visit for signal intensity (signal-to-noise ratio); (3) significant interaction in volume between group and visit; (4) greater volume corrected by total intracranial volume at baseline in female patients and greater decrease in volume and increase in the contrast-to-noise ratio in progressing female PD patients compared with male patients; and (5) correlations between neuromelanin SN changes and disease severity and duration.

CONCLUSIONS

We observed a progressive and measurable decrease in neuromelanin-based SN signal and volume in PD, which might allow a direct noninvasive assessment of progression of SN loss and could represent a target biomarker for disease-modifying treatments. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Positron emission computed tomography/single photon emission computed tomography in Parkinson disease

Parkinson disease (PD) is the second-most common neurodegenerative disorder. Its main pathological mechanism is the selective degeneration and deletion of dopaminergic neurons in the dense part of the substantia nigra and the damage of dopaminergic neurons caused by the abnormal deposition of a Lewy body, leading to a decreased dopamine level. Positron emission computed tomography (PET)/single photon emission computed tomography (SPECT) is a molecular imaging technology that can directly or indirectly reflect changes in molecular levels by using a specific tracer. With the research and development on the tracers of related enzymes for labeling dopamine transporter and dopamine receptor and for being involved in dopamine formation, this imaging technology has been applied to all aspects of PD research. It not only contributes to clinical work but also provides an important theoretical basis for exploring the pathological mechanism of PD at a molecular level. Therefore, this review discusses the application value of PET/SPECT in PD in terms of early diagnosis, disease severity evaluation, clinical manifestations, differential diagnosis, and pathological mechanism.

MPTP-induced dopaminergic neurotoxicity in mouse brain is attenuated after subsequent intranasal administration of (R)-ketamine: a role of TrkB signaling

RATIONALE

Parkinson's disease (PD) is characterized as a chronic and progressive neurodegenerative disorder, and PD patients have non-motor features such as depressive symptoms. Although there are several available medications to treat PD symptoms, these medications do not prevent the progression of the disease.

OBJECTIVE

(R)-ketamine has greater and longer-lasting antidepressant effects than (S)-ketamine in animal models of depression. This study was undertaken to investigate whether two enantiomers of ketamine and its metabolite norketamine shows neuroprotective effects in an animal model of PD.

METHODS

Effects of (R)-ketamine, (S)-ketamine, and their metabolites on MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine)-induced reduction of dopamine transporter (DAT) and tyrosine hydroxylase (TH) in the mouse striatum and substantia nigra (SNr) were examined.

RESULTS

MPTP-induced reduction of DAT in the striatum was attenuated by subsequent repeated intranasal administration of both enantiomers of ketamine although (R)-ketamine was more potent than (S)-ketamine. MPTP-induced reduction of TH in the striatum and SNr was attenuated by administration of (R)-ketamine, but not (S)-ketamine. Interestingly, MPTP-induced reduction of DAT in the striatum was also attenuated by a single intranasal administration of (R)-ketamine. In contrast, MPTP-induced reduction of DAT in the striatum was not attenuated by repeated intranasal administration of two enantiomers of norketamine. Furthermore, the pretreatment with TrkB antagonist ANA-12 significantly blocked the neuroprotective effects of (R)-ketamine in the MPTP-induced reduction of DAT in the striatum.

CONCLUSIONS

These findings suggest that (R)-ketamine can protect against MPTP-induced neurotoxicity in the mouse brain via TrkB activation. Therefore, (R)-ketamine could represent a therapeutic drug for neurodegenerative disorders such as PD.

The solute carrier transporters and the brain: Physiological and pharmacological implications

Solute carriers (SLCs) are the largest family of transmembrane transporters that determine the exchange of various substances, including nutrients, ions, metabolites, and drugs across biological membranes. To date, the presence of about 287 SLC genes have been identified in the brain, among which mutations or the resultant dysfunctions of 71 SLC genes have been reported to be correlated with human brain disorders. Although increasing interest in SLCs have focused on drug development, SLCs are currently still under-explored as drug targets, especially in the brain. We summarize the main substrates and functions of SLCs that are expressed in the brain, with an emphasis on selected SLCs that are important physiologically, pathologically, and pharmacologically in the blood-brain barrier, astrocytes, and neurons. Evidence suggests that a fraction of SLCs are regulated along with the occurrences of brain disorders, among which epilepsy, neurodegenerative diseases, and autism are representative. Given the review of SLCs involved in the onset and procession of brain disorders, we hope these SLCs will be screened as promising drug targets to improve drug delivery to the brain.