Imaging the Substantia Nigra in Parkinson Disease and Other Parkinsonian Syndromes

Decoding the role of the CCL2/CCR2 axis in Alzheimer's disease and innovating therapeutic approaches: Keeping All options open

Alzheimer's disease (AD), as a neurodegenerative disorder, distresses the elderly in large numbers and is characterized by β-amyloid (Aβ) accumulation, elevated tau protein levels, and chronic inflammation. The brain's immune system is aided by microglia and astrocytes, which produce chemokines and cytokines. Nevertheless, dysregulated expression can cause hyperinflammation and lead to neurodegeneration. CCL2/CCR2 chemokines are implicated in neurodegenerative diseases exacerbating. Inflicting damage on nerves and central nervous system (CNS) cells is the function of this axis, which recruits and migrates immune cells, including monocytes and macrophages. It has been shown that targeting the CCL2/CCR2 axis may be a therapeutic option for inflammatory diseases. Using the current knowledge about the involvement of the CCL2/CCR2 axis in the immunopathogenesis of AD, this comprehensive review synthesizes existing information. It also explores potential therapeutic options, including modulation of the CCL2/CCR2 axis as a possible strategy in AD.

Ferroptosis inhibitors: past, present and future

Ferroptosis is a non-apoptotic mode of programmed cell death characterized by iron dependence and lipid peroxidation. Since the ferroptosis was proposed, researchers have revealed the mechanisms of its formation and continue to explore effective inhibitors of ferroptosis in disease. Recent studies have shown a correlation between ferroptosis and the pathological mechanisms of neurodegenerative diseases, as well as diseases involving tissue or organ damage. Acting on ferroptosis-related targets may provide new strategies for the treatment of ferroptosis-mediated diseases. This article specifically describes the metabolic pathways of ferroptosis and summarizes the reported mechanisms of action of natural and synthetic small molecule inhibitors of ferroptosis and their efficacy in disease. The paper also describes ferroptosis treatments such as gene therapy, cell therapy, and nanotechnology, and summarises the challenges encountered in the clinical translation of ferroptosis inhibitors. Finally, the relationship between ferroptosis and other modes of cell death is discussed, hopefully paving the way for future drug design and discovery.

Neuroprotective effects of cordycepin on MPTP-induced Parkinson's disease mice via suppressing PI3K/AKT/mTOR and MAPK-mediated neuroinflammation

Parkinson's disease (PD) is a prevalent progressive and multifactorial neurodegenerative disorder. Cordycepin is known to exhibit antitumor, anti-inflammatory, antioxidative stress, and neuroprotective effects; however, few studies have explored the neuroprotective mechanism of cordycepin in PD. Using a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mouse model, we investigated the impact of cordycepin on PD and its underlying molecular mechanisms. The findings indicated that cordycepin significantly mitigated MPTP-induced behavior disorder and neuroapoptosis, diminished the loss of dopaminergic neurons in the striatum-substantia nigra pathway, elevated striatal monoamine levels and its metabolites, and inhibited the polarization of microglia and the expression of pro-inflammatory factors. Subsequent proteomic and phosphoproteomic analyses revealed the involvement of the MAPK, mTOR, and PI3K/AKT signaling pathways in the protective mechanism of cordycepin. Cordycepin treatment inhibited the activation of the PI3K/AKT/mTOR signaling pathway and enhanced the expression of autophagy proteins in the striatum and substantia nigra. We also demonstrated the in vivo inhibition of the ERK/JNK signaling pathway by cordycepin treatment. In summary, our investigation reveals that cordycepin exerts neuroprotective effects against PD by promoting autophagy and suppressing neuroinflammation and neuronal apoptosis by inhibiting the PI3K/AKT/mTOR and ERK/JNK signaling pathways. This finding highlights the favorable characteristics of cordycepin in neuroprotection and provides novel molecular insights into the neuroprotective role of natural products in PD.

Structural neuroimaging markers of normal pressure hydrocephalus versus Alzheimer's dementia and Parkinson's disease, and hydrocephalus versus atrophy in chronic TBI-a narrative review

Introduction

Normal Pressure Hydrocephalus (NPH) is a prominent type of reversible dementia that may be treated with shunt surgery, and it is crucial to differentiate it from irreversible degeneration caused by its symptomatic mimics like Alzheimer's Dementia (AD) and Parkinson's Disease (PD). Similarly, it is important to distinguish between (normal pressure) hydrocephalus and irreversible atrophy/degeneration which are among the chronic effects of Traumatic Brain Injury (cTBI), as the former may be reversed through shunt placement. The purpose of this review is to elucidate the structural imaging markers which may be foundational to the development of accurate, noninvasive, and accessible solutions to this problem.

Methods

By searching the PubMed database for keywords related to NPH, AD, PD, and cTBI, we reviewed studies that examined the (1) distinct neuroanatomical markers of degeneration in NPH versus AD and PD, and atrophy versus hydrocephalus in cTBI and (2) computational methods for their (semi-) automatic assessment on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans.

Results

Structural markers of NPH and those that can distinguish it from AD have been well studied, but only a few studies have explored its structural distinction between PD. The structural implications of cTBI over time have been studied. But neuroanatomical markers that can predict shunt response in patients with either symptomatic idiopathic NPH or post-traumatic hydrocephalus have not been reliably established. MRI-based markers dominate this field of investigation as compared to CT, which is also reflected in the disproportionate number of MRI-based computational methods for their automatic assessment.

Conclusion

Along with an up-to-date literature review on the structural neurodegeneration due to NPH versus AD/PD, and hydrocephalus versus atrophy in cTBI, this article sheds light on the potential of structural imaging markers as (differential) diagnostic aids for the timely recognition of patients with reversible (normal pressure) hydrocephalus, and opportunities to develop computational tools for their objective assessment.

Changes in iron load in specific brain areas lead to neurodegenerative diseases of the central nervous system

The causes of neurodegenerative diseases remain largely elusive, increasing their personal and societal impacts. To reveal the causal effects of iron load on Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis and multiple sclerosis, we used Mendelian randomisation and brain imaging data from a UK Biobank genome-wide association study of 39,691 brain imaging samples (predominantly of European origin). Using susceptibility-weighted images, which reflect iron load, we analysed genetically significant brain regions. Inverse variance weighting was used as the main estimate, while MR Egger and weighted median were used to detect heterogeneity and pleiotropy. Nine clear associations were obtained. For AD and PD, an increased iron load was causative: the right pallidum for AD and the right caudate, left caudate and right accumbens for PD. However, a reduced iron load was identified in the right and left caudate for multiple sclerosis, the bilateral hippocampus for mixed vascular dementia and the left thalamus and bilateral accumbens for subcortical vascular dementia. Thus, changes in iron load in different brain regions have causal effects on neurodegenerative diseases. Our results are crucial for understanding the pathogenesis and investigating the treatment of these diseases.

Practical Overview of 123I-Ioflupane Imaging in Parkinsonian Syndromes

Parkinsonian syndromes are a heterogeneous group of progressive neurodegenerative disorders involving the nigrostriatal dopaminergic pathway and are characterized by a wide spectrum of motor and nonmotor symptoms. These syndromes are quite common and can profoundly impact the lives of patients and their families. In addition to classic Parkinson disease, parkinsonian syndromes include multiple additional disorders known collectively as Parkinson-plus syndromes or atypical parkinsonism. These are characterized by the classic parkinsonian motor symptoms with additional distinguishing clinical features. Dopamine transporter SPECT has been developed as a diagnostic tool to assess the levels of dopamine transporters in the striatum. This imaging assessment, which uses iodine 123 (123I) ioflupane, can be useful to differentiate parkinsonian syndromes caused by nigrostriatal degeneration from other clinical mimics such as essential tremor or psychogenic tremor. Dopamine transporter imaging plays a crucial role in diagnosing parkinsonian syndromes, particularly in patients who do not clearly fulfill the clinical criteria for diagnosis. Diagnostic clarification can allow early treatment in appropriate patients and avoid misdiagnosis. At present, only the qualitative interpretation of dopamine transporter SPECT is approved by the U.S. Food and Drug Administration, but quantitative interpretation is often used to supplement qualitative interpretation. The authors provide an overview of patient preparation, common imaging findings, and potential pitfalls that radiologists and nuclear medicine physicians should know when performing and interpreting dopamine transporter examinations. Alternatives to 123I-ioflupane imaging for the evaluation of nigrostriatal degeneration are also briefly discussed. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Intenzo and Colarossi in this issue.

Neuromelanin-sensitive MRI as a promising biomarker of catecholamine function

Disruptions to dopamine and noradrenergic neurotransmission are noted in several neurodegenerative and psychiatric disorders. Neuromelanin-sensitive (NM)-MRI offers a non-invasive approach to visualize and quantify the structural and functional integrity of the substantia nigra and locus coeruleus. This method may aid in the diagnosis and quantification of longitudinal changes of disease and could provide a stratification tool for predicting treatment success of pharmacological interventions targeting the dopaminergic and noradrenergic systems. Given the growing clinical interest in NM-MRI, understanding the contrast mechanisms that generate this signal is crucial for appropriate interpretation of NM-MRI outcomes and for the continued development of quantitative MRI biomarkers that assess disease severity and progression. To date, most studies associate NM-MRI measurements to the content of the neuromelanin pigment and/or density of neuromelanin-containing neurons, while recent studies suggest that the main source of the NM-MRI contrast is not the presence of neuromelanin but the high-water content in the dopaminergic and noradrenergic neurons. In this review, we consider the biological and physical basis for the NM-MRI contrast and discuss a wide range of interpretations of NM-MRI. We describe different acquisition and image processing approaches and discuss how these methods could be improved and standardized to facilitate large-scale multisite studies and translation into clinical use. We review the potential clinical applications in neurological and psychiatric disorders and the promise of NM-MRI as a biomarker of disease, and finally, we discuss the current limitations of NM-MRI that need to be addressed before this technique can be utilized as a biomarker and translated into clinical practice and offer suggestions for future research.

Progressive supranuclear palsy: A case report and brief review of the literature

Atypical Parkinsonian syndromes are a subset of progressive neurodegenerative disorders that present with signs of Parkinson's disease. However, due to multisystem degeneration, the atypical Parkinsonian syndromes have additional symptoms that are often referred to as Parkinson-plus syndromes. The most well-studied subsets include progressive supranuclear palsy (PSP), multiple system atrophy (MSA), corticobasal degeneration (CBD), and Lewy body dementia. Specifically, progressive supranuclear palsy is a tauopathy neurodegenerative disorder that presents with parkinsonism symptoms along with postural instability, vertical saccade, and vertical gaze palsy. Here, we present a case of PSP and provide a brief review of the literature.

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

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

Lunapark deficiency leads to an autosomal recessive neurodevelopmental phenotype with a degenerative course, epilepsy and distinct brain anomalies

LNPK encodes a conserved membrane protein that stabilizes the junctions of the tubular endoplasmic reticulum network playing crucial roles in diverse biological functions. Recently, homozygous variants in LNPK were shown to cause a neurodevelopmental disorder (OMIM#618090) in four patients displaying developmental delay, epilepsy and nonspecific brain malformations including corpus callosum hypoplasia and variable impairment of cerebellum. We sought to delineate the molecular and phenotypic spectrum of LNPK-related disorder. Exome or genome sequencing was carried out in 11 families. Thorough clinical and neuroradiological evaluation was performed for all the affected individuals, including review of previously reported patients. We identified 12 distinct homozygous loss-of-function variants in 16 individuals presenting with moderate to profound developmental delay, cognitive impairment, regression, refractory epilepsy and a recognizable neuroimaging pattern consisting of corpus callosum hypoplasia and signal alterations of the forceps minor ('ear-of-the-lynx' sign), variably associated with substantia nigra signal alterations, mild brain atrophy, short midbrain and cerebellar hypoplasia/atrophy. In summary, we define the core phenotype of LNPK-related disorder and expand the list of neurological disorders presenting with the 'ear-of-the-lynx' sign suggesting a possible common underlying mechanism related to endoplasmic reticulum-phagy dysfunction.

Substantia nigra nigrosome-1 imaging correlates with the severity of motor symptoms in Parkinson's disease

BACKGROUND

Nigrosome-1 imaging has been used for assisting the diagnosis of Parkinson's disease (PD). We aimed to examine the diagnostic performance of loss of nigrosome-1 in PD and the correlation between the size of the nigrosome-1 and motor severity of PD.

METHODS

We included 237 patients with PD and 165 controls. The motor severity of PD was assessed with the Unified Parkinson's Disease Rating Scale (UPDRS) part III score and Hoehn-Yahr staging. The 3 or 1.5 Tesla susceptibility-weighted imaging combined with a deep-learning algorithm was applied for detecting the loss and the size of nigrosome-1. Clinical correlations and diagnostic performance of size of nigrosome-1 were also investigated.

RESULTS

The mean nigrosome-1 size was significantly smaller in PD patients than in controls (0.06 ± 0.07 cm² vs. 0.20 ± 0.05 cm², P < 0.001). The area under the receiver operating characteristic curve (AUC) of the established model showed 0.94 accuracy (95% confidence interval [CI]: 0.87, 1.01, P < 0.01) in differentiating between the PD and control groups. Moreover, the partial loss of nigrosome-1 detected with SWI had an AUC of 0.96 in discriminating early-stage PD from controls (95% CI: 0.88, 1.02, P < 0.001). After adjusting for age, sex, disease duration, and levodopa equivalent daily dose, the estimated size of nigrosome-1 was negatively associated with the UPDRS part III motor score (ρ = -0.433, P < 0.001), but not with Mini-Mental State Examination scores (ρ = 0.006, P = 0.894).

CONCLUSIONS

The extent of loss and the size of nigrosome-1 may potentially assist in the diagnosis of PD. Nigrosome-1 size reflects the motor severity of PD.

Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake

PURPOSE

Nigrosome imaging using susceptibility-weighted imaging (SWI) and dopamine transporter imaging using ¹²³I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (¹²³I-FP-CIT) single-photon emission computerized tomography (SPECT) can evaluate Parkinsonism. Nigral hyperintensity from nigrosome-1 and striatal dopamine transporter uptake are reduced in Parkinsonism; however, quantification is only possible with SPECT. Here, we aimed to develop a deep-learning-based regressor model that can predict striatal ¹²³I-FP-CIT uptake on nigrosome magnetic resonance imaging (MRI) as a biomarker for Parkinsonism.

METHODS

Between February 2017 and December 2018, participants who underwent 3 T brain MRI including SWI and ¹²³I-FP-CIT SPECT based on suspected Parkinsonism were included. Two neuroradiologists evaluated the nigral hyperintensity and annotated the centroids of nigrosome-1 structures. We used a convolutional neural network-based regression model to predict striatal specific binding ratios (SBRs) measured via SPECT using the cropped nigrosome images. The correlation between measured and predicted SBRs was evaluated.

RESULTS

We included 367 participants (203 women (55.3%); age, 69.0 ± 9.2 [range, 39-88] years). Random data from 293 participants (80%) were used for training. In the test set (74 participants [20%]), the measured and predicted ¹²³I-FP-CIT SBRs were significantly lower with the loss of nigral hyperintensity (2.31 ± 0.85 vs. 2.44 ± 0.90) than with intact nigral hyperintensity (4.16 ± 1.24 vs. 4.21 ± 1.35, P < 0.01). The sorted measured ¹²³I-FP-CIT SBRs and the corresponding predicted values were significantly and positively correlated (ρ_c = 0.7443; 95% confidence interval, 0.6216-0.8314; P < 0.01).

CONCLUSION

A deep learning-based regressor model effectively predicted striatal ¹²³I-FP-CIT SBRs based on nigrosome MRI with high correlation using manually-measured values, enabling nigrosome MRI as a biomarker for nigrostriatal dopaminergic degeneration in Parkinsonism.

Application value of peripheral blood IgG and IgM combined with ultrasonic echo parameters of substantia nigra in the diagnosis of Parkinson's disease

We study the clinical value of peripheral blood immunoglobulin G (IgG) and immunoglobulin M (IgM) combined with ultrasonic echo parameters of substantia nigra (SN) in the diagnosis of Parkinson's disease (PD). The clinical data of 121 patients with PD (case group) in our hospital from November 2020 to November 2022 were selected for retrospective analysis, and 9 patients with poor sound transmission of temporal window were excluded. Finally, this study included 112 patients with PD and selected 108 health examination population in the same period (control group). The levels of IgG and IgM in both groups were detected, and ultrasound examination was carried out to observe the structure of SN and obtain strong echo area of SN, midbrain area and strong echo area of SN/midbrain area. The receiver operator characteristic curve of serum IgG and IgM combined with ultrasonic echo parameters of SN in the diagnosis of PD was drawn to evaluate the clinical efficacy of single diagnosis and combined diagnosis. Compared with the control group, the serum levels of IgG and IgM, strong echo area of SN, midbrain area and strong echo area of SN/midbrain area in the case group were obviously higher (P < 0.001), while the folic acid level was notably lower (P < 0.05). The AUC value, Youden index and sensitivity of combined diagnosis were higher than those of single detection. Peripheral blood IgG and IgM combined with ultrasonic echo parameters of SN have high clinical value in the diagnosis of PD, which can provide a new direction for the subsequent diagnosis of PD.

A vision of 14 T MR for fundamental and clinical science

OBJECTIVE

We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set.

RESEARCH FIELDS

The 14 Tesla system can be considered a 'mesocope': a device capable of measuring on biologically relevant scales. In neuroscience the increased spatial resolution will anatomically resolve all layers of the cortex, cerebellum, subcortical structures, and inner nuclei. Spectroscopic imaging will simultaneously measure excitatory and inhibitory activity, characterizing the excitation/inhibition balance of neural circuits. In medical research (including brain disorders) we will visualize fine-grained patterns of structural abnormalities and relate these changes to functional and molecular changes. The significantly increased spectral resolution will make it possible to detect (dynamic changes in) individual metabolites associated with pathological pathways including molecular interactions and dynamic disease processes.

CONCLUSIONS

The 14 Tesla system will offer new perspectives in neuroscience and fundamental research. We anticipate that this initiative will usher in a new era of ultra-high-field MR.

Restraint Stress Exacerbates Apoptosis in a 6-OHDA Animal Model of Parkinson Disease

Activation of the apoptotic pathway has been associated with promoting neuronal cell death in the pathophysiology of Parkinson disease (PD). Nonetheless, the mechanisms by which it may occur remain unclear. It has been suggested that stress-induced oxidation and potential apoptosis may play a major role in the progression of PD. Thus, in this study, we aimed to investigate the effect of subchronic restraint stress on striatal dopaminergic activity, iron, p53, caspase-3, and plasmatic acetylcholinesterase (AChE) levels in male Wistar rat model of PD induced by administration of 6-hydroxydopamine (6-OHDA) in the medial forebrain bundle (MFB). The obtained results showed that restraint stress exacerbates motor coordination deficits and anxiety in animals treated with 6-OHDA in comparison to animals receiving saline, and it had no effect on object recognition memory. On another hand, 6-OHDA decreased dopamine (DA) levels, increased iron accumulation, and induced overexpression of the pro-apoptotic factors caspase-3, p53, and AChE. More interestingly, post-lesion restraint stress exacerbated the expression of caspase-3 and AChE without affecting p53 expression. These findings suggest that subchronic stress may accentuate apoptosis and may contribute to DA neuronal loss in the striatal regions and possibly exacerbate the progression of PD.

MR-self Noise2Noise: self-supervised deep learning-based image quality improvement of submillimeter resolution 3D MR images

OBJECTIVES

The study aimed to develop a deep neural network (DNN)-based noise reduction and image quality improvement by only using routine clinical scans and evaluate its performance in 3D high-resolution MRI.

METHODS

This retrospective study included T1-weighted magnetization-prepared rapid gradient-echo (MP-RAGE) images from 185 clinical scans: 135 for DNN training, 11 for DNN validation, 20 for qualitative evaluation, and 19 for quantitative evaluation. Additionally, 18 vessel wall imaging (VWI) data were included to evaluate generalization. In each scan of the DNN training set, two noise-independent images were generated from the k-space data, resulting in an input-label pair. 2.5D U-net architecture was utilized for the DNN model. Qualitative evaluation between conventional MP-RAGE and DNN-based MP-RAGE was performed by two radiologists in image quality, fine structure delineation, and lesion conspicuity. Quantitative evaluation was performed with full sampled data as a reference by measuring quantitative error metrics and volumetry at 7 different simulated noise levels. DNN application on VWI was evaluated by two radiologists in image quality.

RESULTS

Our DNN-based MP-RAGE outperformed conventional MP-RAGE in all image quality parameters (average scores = 3.7 vs. 4.9, p < 0.001). In the quantitative evaluation, DNN showed better error metrics (p < 0.001) and comparable (p > 0.09) or better (p < 0.02) volumetry results than conventional MP-RAGE. DNN application to VWI also revealed improved image quality (3.5 vs. 4.6, p < 0.001).

CONCLUSION

The proposed DNN model successfully denoises 3D MR image and improves its image quality by using routine clinical scans only.

KEY POINTS

• Our deep learning framework successfully improved conventional 3D high-resolution MRI in all image quality parameters, fine structure delineation, and lesion conspicuity. • Compared to conventional MRI, the proposed deep neural network-based MRI revealed better quantitative error metrics and comparable or better volumetry results. • Deep neural network application to 3D MRI whose pulse sequences and parameters were different from the training data showed improvement in image quality, revealing the potential to generalize on various clinical MRI.

Quantification of Movement Error from Spiral Drawing Test

Parkinson's disease is a neurodegenerative disease that often comes with symptoms such as muscle stiffness, slowness of movement, and tremors at rest. Since this disease negatively influences the quality of life in patients, an early and accurate diagnosis is important for slowing the progression of the disease and providing effective treatment to patients. One of the quick and easy methods for diagnosing is the spiral drawing test and the differences between the target spiral picture and the drawing by patients can be used as an indicator of movement error. Simply, the average distance between paired samples of the target spiral and the drawing can be easily calculated and used as the level of movement error. However, finding the correct pair of samples between the target spiral and the drawing is relatively difficult, and the accurate algorithm to quantify the movement error has not been thoroughly studied. In this study, we propose algorithms applicable to the spiral drawing test, that ultimately can be used to measure the level of movement error in Parkinson's disease patients. They are equivalent inter-point distance (ED), shortest distance (SD), varying inter-point distance (VD), and equivalent angle (EA). To evaluate the performance and sensitivity of the methods, we collected data from simulation and experiments with healthy subjects and evaluated the four methods. As a result, in normal (good drawing) and severe symptom (poor drawing) conditions, the calculated errors were 3.67/5.48 from ED, 0.11/1.21 from SD, 0.38/1.46 from VD and 0.01/0.02 from EA, meaning that ED, SD, and VD measure movement error with high noise while EA is sensitive to even small symptom levels. Similarly, in the experiment data, only EA shows the linear increase of error distance to changing symptom levels from 1 to 3. In summary, we found that EA is the most effective algorithm in finding the correct pair of samples between the spiral and the drawing, and consequently yields low errors and high sensitivity to symptom levels.

Benefits of high-dielectric pad for neuroimaging study in 7-Tesla MRI

This study aimed to evaluate whether the use of a high-dielectric pad is effective in increasing transmit and receive sensitivity in areas of low signal intensity in the human brain at high magnetic fields and assess its usefulness in neuroimaging studies. The novelty of this study lies in the first reported use of diffusion tensor imaging (DTI) results to evaluate the effect of the pad on neuroimaging. Six volunteers underwent MR scanning using a 7 T MR system. T1-weighted images (T1w) and diffusion-weighted images (DWI) were acquired to demonstrate the benefits of a high-dielectric pad made of barium titanate (BaTiO3). For all imaging experiments, two datasets were acquired per person, one with and one without a high-dielectric pad. Enhancement of signal sensitivity in neuroimaging has been analyzed by DTI study. Higher signal intensities and spatial contrast were demonstrated in the in T1w images acquired using high-dielectric pad than in those acquired without high-dielectric pad. Especially in DTI studies, increased quantitative anisotropy (QA) signals were observed in the corticospinal tract (CST), frontopontine tract (FPT), splenium of corpus callosum (SCC), fornix (FX), inferior fronto-occipital fasciculus (IFOF), cerebellum (CB), middle cerebellar peduncle (MCP), and body of corpus callosum (BCC) (FDR < 0.05). The signal differences accounted for an overall 20% increase. A high-dielectric pad is effective in enhancing signal intensity in human brain images acquired using 7 T MRI. Our results show that the use of such pad can increase the spatial resolution, tissue contrast, and signal intensity in neuroimaging studies. These findings suggest that high-dielectric pads may provide a relatively simple and low-cost method for spatiotemporal brain imaging studies.

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.

Susceptibility Magnetic Resonance Imaging Correlates with Glial Density and Tau in the Substantia Nigra Pars Compacta

BACKGROUND

Susceptibility magnetic resonance imaging (MRI) is sensitive to iron-related changes in the substantia nigra pars compacta (SNc), the key pathologic locus of parkinsonisms. It is unclear, however, if iron deposition in the SNc is associated with its neurodegeneration.

OBJECTIVE

The objective of this study was to test whether susceptibility MRI metrics in parkinsonisms are associated with SNc neuropathologic features of dopaminergic neuron loss, gliosis, and α-synuclein and tau burden.

METHODS

This retrospective study included 27 subjects with both in vivo MRI and postmortem data. Multigradient echo imaging was used to derive the apparent transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM) in the SNc. Archived midbrain slides that were stained with hematoxylin and eosin, anti-α-synuclein, and anti-tau were digitized to quantify neuromelanin-positive neuron density, glial density, and the percentages of area occupied by positive α-synuclein and tau staining. MRI-histology associations were examined using Pearson correlations and regression.

RESULTS

Twenty-four subjects had postmortem parkinsonism diagnoses (Lewy body disorder, progressive supranuclear palsy, multiple system atrophy, and corticobasal degeneration), two had only Alzheimer's neuropathology, and one exhibited only mild atrophy. Among all subjects, both R2* and QSM were associated with glial density (r ≥ 0.67; P < 0.001) and log-transformed tau burden (r ≥ 0.53; P ≤ 0.007). Multiple linear regression identified glial density and log-transformed tau as determinants for both MRI metrics (R2 ≥ 0.580; P < 0.0001). Neither MRI metric was associated with neuron density or α-synuclein burden.

CONCLUSIONS

R2* and QSM are associated with both glial density and tau burden, key neuropathologic features in the parkinsonism SNc. © 2023 International Parkinson and Movement Disorder Society.

Neuromelanin magnetic resonance imaging of substantia nigra and locus coeruleus in Parkinson's disease with freezing of gait

Background

The downregulation of monoamines, especially dopamine in substantia nigra (SN) and norepinephrine in locus coeruleus (LC), may be responsible for freezing of gait (FOG) pathological basis in Parkinson's disease (PD).

Methods

Thirty-two Parkinson's disease patients with freezing of gait (PD-FOG), 32 Parkinson's disease patients without freezing of gait (PD-NFOG) and 32 healthy controls (HC) underwent neuromelanin magnetic resonance imaging (NM-MRI). The volume, surface area and contrast to noise ratio (CNR) of SN and LC were measured and compared. The correlation analyses were conducted between the measurements of SN and LC with clinical symptoms. We plotted the receiver operating characteristic (ROC) curve and determined the sensitivity and specificity of the CNR of SN and LC for discriminating the PD-FOG from the PD-NFOG.

Results

Both PD-FOG and PD-NFOG showed decreased volume, surface area and CNR of SN compared with HC. The PD-FOG exhibited decreased volume and surface area of LC compared with both PD-NFOG and HC groups, and decreased CNR of LC compared with HC group. The volume, surface area and CNR of SN were negatively correlated with the Unified Parkinson's Disease Rating Scale part III scores. The illness durations in PD patients were negatively correlated with the volume, surface area of SN, while not the CNR. And the volume and surface area of LC were negatively correlated with new freezing of gait questionnaire scores. ROC analyses indicated that the area under the curve (AUC) was 0.865 and 0.713 in the CNR of SN and LC, respectively, in PD versus HC, whereas it was 0.494 and 0.637 respectively, in PD-FOG versus PD-NFOG. Among these, for discriminating the PD from the HC, the sensitivity and specificity in the CNR of the SN was 90.6 and 71.9%, respectively, when the cut-off value was set at 2.101; the sensitivity and specificity in the CNR of the LC was 90.6 and 50.0%, respectively, when the cut-off value for CNR was set at 1.411.

Conclusion

The dopaminergic changes in the SN were found across both PD-FOG and PD-NFOG, whilst LC noradrenergic neuron reduction was more evident in PD-FOG.

Differential Effects of Tau Stage, Lewy Body Pathology, and Substantia Nigra Degeneration on 18F-FDG PET Patterns in Clinical Alzheimer Disease

Comorbid Lewy body (LB) pathology is common in Alzheimer disease (AD). The effect of LB copathology on ¹⁸F-FDG PET patterns in AD is yet to be studied. We analyzed associations of neuropathologically assessed tau pathology, LB pathology, and substantia nigra neuronal loss (SNnl) with antemortem ¹⁸F-FDG PET hypometabolism in patients with a clinical AD presentation. Methods: Twenty-one patients with autopsy-confirmed AD without LB neuropathologic changes (LBNC) (pure-AD), 24 with AD and LBNC copathology (AD-LB), and 7 with LBNC without fulfilling neuropathologic criteria for AD (pure-LB) were studied. Pathologic groups were compared regarding regional and voxelwise ¹⁸F-FDG PET patterns, the cingulate island sign ratio (CISr), and neuropathologic ratings of SNnl. Additional analyses assessed continuous associations of Braak tangle stage and SNnl with ¹⁸F-FDG PET patterns. Results: Pure-AD and AD-LB showed highly similar patterns of AD-typical temporoparietal hypometabolism and did not differ in CISr, regional ¹⁸F-FDG SUVR, or SNnl. By contrast, pure-LB showed the expected pattern of pronounced posterior-occipital hypometabolism typical for dementia with LB (DLB), and both CISr and SNnl were significantly higher compared with the AD groups. In continuous analyses, Braak tangle stage correlated significantly with more AD-like, and SNnl with more DLB-like, ¹⁸F-FDG PET patterns. Conclusion: In autopsy-confirmed AD dementia patients, comorbid LB pathology did not have a notable effect on the regional ¹⁸F-FDG PET pattern. A more DLB-like ¹⁸F-FDG PET pattern was observed in relation to SNnl, but advanced SNnl was mostly limited to relatively pure LB cases. AD pathology may have a dominant effect over LB pathology in determining the regional neurodegeneration phenotype.

On the Chemical and Biological Characteristics of Multifunctional Compounds for the Treatment of Parkinson's Disease

Protein aggregation, mitochondrial dysfunction, iron dyshomeostasis, increased oxidative damage and inflammation are pathognomonic features of Parkinson's disease (PD) and other neurodegenerative disorders characterized by abnormal iron accumulation. Moreover, the existence of positive feed-back loops between these pathological components, which accelerate, and sometimes make irreversible, the neurodegenerative process, is apparent. At present, the available treatments for PD aim to relieve the symptoms, thus improving quality of life, but no treatments to stop the progression of the disease are available. Recently, the use of multifunctional compounds with the capacity to attack several of the key components of neurodegenerative processes has been proposed as a strategy to slow down the progression of neurodegenerative processes. For the treatment of PD specifically, the necessary properties of new-generation drugs should include mitochondrial destination, the center of iron-reactive oxygen species interaction, iron chelation capacity to decrease iron-mediated oxidative damage, the capacity to quench free radicals to decrease the risk of ferroptotic neuronal death, the capacity to disrupt α-synuclein aggregates and the capacity to decrease inflammatory conditions. Desirable additional characteristics are dopaminergic neurons to lessen unwanted secondary effects during long-term treatment, and the inhibition of the MAO-B and COMPT activities to increase intraneuronal dopamine content. On the basis of the published evidence, in this work, we review the molecular basis underlying the pathological events associated with PD and the clinical trials that have used single-target drugs to stop the progress of the disease. We also review the current information on multifunctional compounds that may be used for the treatment of PD and discuss the chemical characteristics that underlie their functionality. As a projection, some of these compounds or modifications could be used to treat diseases that share common pathology features with PD, such as Friedreich's ataxia, Multiple sclerosis, Huntington disease and Alzheimer's disease.

Detection and modulation of neurodegenerative processes using graphene-based nanomaterials: Nanoarchitectonics and applications

Neurodegenerative disorders (NDDs) are caused by progressive loss of functional neurons following the aggregation and fibrillation of proteins in the central nervous system. The incidence rate continues to rise alarmingly worldwide, particularly in aged population, and the success of treatment remains limited to symptomatic relief. Graphene nanomaterials (GNs) have attracted immense interest on the account of their unique physicochemical and optoelectronic properties. The research over the past two decades has recognized their ability to interact with aggregation-prone neuronal proteins, regulate autophagy and modulate the electrophysiology of neuronal cells. Graphene can prevent the formation of higher order protein aggregates and facilitate the clearance of such deposits. In this review, after highlighting the role of protein fibrillation in neurodegeneration, we have discussed how GN-protein interactions can be exploited for preventing neurodegeneration. A comprehensive understanding of such interactions would contribute to the exploration of novel modalities for controlling neurodegenerative processes.

Galvanic vestibular stimulation down-regulated NMDA receptors in vestibular nucleus of PD model

Parkinsonian symptoms relief by electrical stimulation is constructed by modulating neural network activity, and Galvanic vestibular stimulation (GVS) is known to affect the neural activity for motor control by activating the vestibular afferents. However, its underlying mechanism is still elusive. Due to the tight link from the peripheral vestibular organ to vestibular nucleus (VN), the effect by GVS was investigated to understand the neural mechanism. Using Sprague Dawley (SD) rats, behavioral response, extracellular neural recording, and immunohistochemistry in VN were conducted before and after the construction of Parkinson's disease (PD) model. Animals' locomotion was tested using rota-rod, and single extracellular neuronal activity was recorded in VN. The immunohistochemistry detected AMPA and NMDA receptors in VN to assess the effects by different amounts of electrical charge (0.018, 0.09, and 0.18 coulombs) as well as normal and PD with no GVS. All PD models showed the motor impairment, and the loss of TH⁺ neurons in medial forebrain bundle (mfb) and striatum was observed. Sixty-five neuronal extracellular activities (32 canal & 33 otolith) were recorded, but no significant difference in the resting firing rates and the kinetic responding gain were found in the PD models. On the other hand, the numbers of AMPA and NMDA receptors increased after the construction of PD model, and the effect by GVS was significantly evident in the change of NMDA receptors (p < 0.018). In conclusion, the increased glutamate receptors in PD models were down-regulated by GVS, and the plastic modulation mainly occurred through NMDA receptor in VN.

DBSegment: Fast and robust segmentation of deep brain structures considering domain generalization

Segmenting deep brain structures from magnetic resonance images is important for patient diagnosis, surgical planning, and research. Most current state-of-the-art solutions follow a segmentation-by-registration approach, where subject magnetic resonance imaging (MRIs) are mapped to a template with well-defined segmentations. However, registration-based pipelines are time-consuming, thus, limiting their clinical use. This paper uses deep learning to provide a one-step, robust, and efficient deep brain segmentation solution directly in the native space. The method consists of a preprocessing step to conform all MRI images to the same orientation, followed by a convolutional neural network using the nnU-Net framework. We use a total of 14 datasets from both research and clinical collections. Of these, seven were used for training and validation and seven were retained for testing. We trained the network to segment 30 deep brain structures, as well as a brain mask, using labels generated from a registration-based approach. We evaluated the generalizability of the network by performing a leave-one-dataset-out cross-validation, and independent testing on unseen datasets. Furthermore, we assessed cross-domain transportability by evaluating the results separately on different domains. We achieved an average dice score similarity of 0.89 ± 0.04 on the test datasets when compared to the registration-based gold standard. On our test system, the computation time decreased from 43 min for a reference registration-based pipeline to 1.3 min. Our proposed method is fast, robust, and generalizes with high reliability. It can be extended to the segmentation of other brain structures. It is publicly available on GitHub, and as a pip package for convenient usage.

Novel nested patch-based feature extraction model for automated Parkinson's Disease symptom classification using MRI images

OBJECTIVE

Parkinson's disease (PD) is a common neurological disorder with variable clinical manifestations and magnetic resonance imaging (MRI) findings. We propose a handcrafted image classification model that can accurately (i) classify different PD stages, (ii) detect comorbid dementia, and (iii) discriminate PD-related motor symptoms.

METHODS

Selected image datasets from three PD studies were used to develop the classification model. Our proposed novel automated system was developed in four phases: (i) texture features are extracted from the non-fixed size patches. In the feature extraction phase, a pyramid histogram-oriented gradient (PHOG) image descriptor is used. (ii) In the feature selection phase, four feature selectors: neighborhood component analysis (NCA), Chi2, minimum redundancy maximum relevancy (mRMR), and ReliefF are used to generate four feature vectors. (iii) Two classifiers: k-nearest neighbor (kNN) and support vector machine (SVM) are used in the classification step. A ten-fold cross-validation technique is used to validate the results. (iv) Eight predicted vectors are generated using four selected feature vectors and two classifiers. Finally, iterative majority voting (IMV) is used to attain general classification results. Therefore, this model is named nested patch-PHOG-multiple feature selectors and multiple classifiers-IMV (NP-PHOG-MFSMCIMV).

RESULTS

Our presented NP-PHOG-MFSMCIMV model achieved 99.22, 98.70, and 99.53% accuracies for the collected PD stages, PD dementia, and PD symptoms classification datasets, respectively.

SIGNIFICANCE

The obtained accuracies (over 98% for all states) demonstrated the performance of developed NP-PHOG-MFSMCIMV model in automated PD state classification.

MRI-Visible Anatomy of the Brainstem

Human brainstem internal anatomy is intricate, complex, and essential to normal brain function. The brainstem is affected by stroke, multiple sclerosis, and most neurodegenerative diseases-a 1-mm focus of pathologic condition can have profound clinical consequences. Unfortunately, detailed internal brainstem anatomy is difficult to see with conventional MRI sequences. We review normal brainstem anatomy visualized on widely available clinical 3-T MRI scanners using fast gray matter acquisition T1 inversion recovery, probabilistic diffusion tractography, neuromelanin, and susceptibility-weighted imaging. Better anatomic localization using these recent innovations improves our ability to diagnose, localize, and treat brainstem diseases. We aim to provide an accessible review of the most clinically relevant brainstem neuroanatomy.

Identification of Immune-Related Hub Genes in Parkinson’s Disease

Background: Parkinson’s disease (PD) is a common, age-related, and progressive neurodegenerative disease. Growing evidence indicates that immune dysfunction plays an essential role in the pathogenic process of PD. The objective of this study was to explore potential immune-related hub genes and immune infiltration patterns of PD.

Method: The microarray expression data of human postmortem substantia nigra samples were downloaded from GSE7621, GSE20141, and GSE49036. Key module genes were screened via weighted gene coexpression network analysis, and immune-related genes were intersected to obtain immune-key genes. Functional enrichment analysis was performed on immune-key genes of PD. In addition to, immune infiltration analysis was applied by a single-sample gene set enrichment analysis algorithm to detect differential immune cell types in the substantia nigra between PD samples and control samples. Least absolute shrinkage and selection operator analysis was performed to further identify immune-related hub genes for PD. Receiver operating characteristic curve analysis of the immune-related hub genes was used to differentiate PD patients from healthy controls. Correlations between immune-related hub genes and differential immune cell types were assessed.

Result: Our findings identified four hub genes (SLC18A2, L1CAM, S100A12, and CXCR4) and seven immune cell types (neutrophils, T follicular helper cells, myeloid-derived suppressor cells, type 1 helper cells, immature B cells, immature dendritic cells, and CD56 bright natural killer cells). The area under the curve (AUC) value of the four-gene-combined model was 0.92. The AUC values of each immune-related hub gene (SLC18A2, L1CAM, S100A12, and CXCR4) were 0.81, 0.78, 0.78, and 0.76, respectively.

Conclusion: In conclusion, SLC18A2, L1CAM, S100A12, and CXCR4 were identified as being associated with the pathogenesis of PD and should be further researched.

Neuroimaging at 7 Tesla: a pictorial narrative review

Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.

[Brain Iron Imaging in Aging and Cognitive Disorders: MRI Approaches]

Iron has a vital role in the human body, including the central nervous system. Increased deposition of iron in the brain has been reported in aging and important neurodegenerative diseases. Owing to the unique magnetic resonance properties of iron, MRI has great potential for in vivo assessment of iron deposition, distribution, and non-invasive quantification. In this paper, we will review the MRI methods for iron assessment and their changes in aging and neurodegenerative diseases, focusing on Alzheimer's disease. In addition, we will summarize the limitations of current approaches and introduce new areas and MRI methods for iron imaging that are expected in the future.

Neuromelanin accumulation in patients with schizophrenia: A systematic review and meta-analysis

Although schizophrenia is associated with increased presynaptic dopamine function in the striatum, it remains unclear if neuromelanin levels, which are thought to serve as a biomarker for midbrain dopamine neuron function, are increased in patients with schizophrenia. We conducted a systematic review and meta-analysis of magnetic resonance imaging (MRI) and postmortem studies comparing neuromelanin (NM) levels between patients with schizophrenia and healthy controls (HCs). Standard mean differences were calculated to assess group differences in NM accumulation levels between patients with schizophrenia and HCs. This study included 7 articles in total. Five studies employed NM-sensitive MRI (NM-MRI) and two were postmortem brain studies. The patient group (n = 163) showed higher NM levels in the substantia nigra (SN) than HCs (n = 228) in both the analysis of the seven studies and the subgroup analysis of the 5 NM-MRI studies. This analysis suggest increased NM levels in the SN may be a potential biomarker for stratifying schizophrenia, warranting further research that accounts for the heterogeneity of this disorder.

Dopamine Transporter Imaging, Current Status of a Potential Biomarker: A Comprehensive Review

A major goal of current clinical research in Parkinson's disease (PD) is the validation and standardization of biomarkers enabling early diagnosis, predicting outcomes, understanding PD pathophysiology, and demonstrating target engagement in clinical trials. Molecular imaging with specific dopamine-related tracers offers a practical indirect imaging biomarker of PD, serving as a powerful tool to assess the status of presynaptic nigrostriatal terminals. In this review we provide an update on the dopamine transporter (DAT) imaging in PD and translate recent findings to potentially valuable clinical practice applications. The role of DAT imaging as diagnostic, preclinical and predictive biomarker is discussed, especially in view of recent evidence questioning the incontrovertible correlation between striatal DAT binding and nigral cell or axon counts.

A Parkinson's disease patient displaying increased neuromelanin-sensitive areas in the substantia nigra after rehabilitation with tDCS: a case report

Previous studies have reported that transcranial direct current stimulation (tDCS) of the frontal polar area (FPA) ameliorated motor disability in patients with Parkinson's disease (PD). Here we report changes in neuromelanin (NM) imaging of dopaminergic neurons before and after rehabilitation combined with anodal tDCS over the FPA for 2 weeks in a PD patient. After the intervention, the patient showed clinically meaningful improvements while the NM-sensitive area in the SN increased by 18.8%. This case study is the first report of NM imaging of the SN in a PD patient who received tDCS.Abbreviations FPA: front polar area; PD: Parkinson's disease; NM: neuromelanin; DCI: DOPA decarboxylase inhibitor; STEF: simple test for evaluating hand function; TUG: timed up and go test; TMT: trail-making test; SN: substantia nigra; NM-MRI: neuromelanin magnetic resonance imaging; MCID: the minimal clinically important difference; SNpc: substantia nigra pars compacta; VTA: ventral tegmental area; LC: locus coeruleus; PFC: prefrontal cortex; M1: primary motor cortex; MDS: Movement Disorder Society; MIBG: ¹²³I-metaiodobenzylguanidine; SBR: specific binding ratio; SPECT: single-photon emission computed tomography; DAT: dopamine transporter; NIBS: noninvasive brain stimulation; tDCS: transcranial direct current stimulation; MAOB: monoamine oxidase B; DCI: decarboxylase inhibitor; repetitive transcranial magnetic stimulation: rTMS; diffusion tensor imaging: DTI; arterial spin labeling: ASL.