Imaging the Substantia Nigra in Parkinson Disease and Other Parkinsonian Syndromes

The Role of ETNPPL in Dopaminergic Neuron Stability: Insights from Neuromelanin-Associated Protein Expression in Parkinson's Disease

More than six million people worldwide are affected by Parkinson's disease (PD), a multifactorial disorder characterized by the progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNc). Several immunohistochemical studies suggest that neuromelanin (NM), found in these neurons, plays a key role in their degeneration. In this study, twelve formalin-fixed, paraffin-embedded (FFPE) brain sections were analyzed, comprising six samples from PD patients and six from healthy controls. Immunohistochemistry (IHC) was conducted to assess the expression of the ETNPPL protein in these samples. ETNPPL was detected in both PD and control samples. Additionally, we examined the expression of ETNPPL mRNA using Quantitative Real-Time PCR (qRT-PCR) in the same sample set. Notably, in control samples, ETNPPL protein was closely associated with the dark NM pigment in the cytoplasm of SNc dopaminergic neurons. In contrast, PD samples showed weak cytoplasmic expression of ETNPPL, with no association with the NM pigment. No nuclear ETNPPL signal was detected in dopaminergic neurons from either PD patients or controls. qRT-PCR results revealed lower ETNPPL mRNA expression in individual PD patients compared to controls. Importantly, we observed a higher concentration of ETNPPL protein at the NM level in the SNc neurons of controls, consistent with mRNA expression patterns. These findings suggest a potential role for ETNPPL in the normal function of dopaminergic neurons and underscore its altered expression in Parkinson's disease.

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 comprehensive benchmarking of a U-Net based model for midbrain auto-segmentation on transcranial sonography

BACKGROUND AND OBJECTIVE

Transcranial sonography-based grading of Parkinson's Disease has gained increasing attention in recent years, and it is currently used for assistive differential diagnosis in some specialized centers. To this end, accurate midbrain segmentation is considered an important initial step. However, current practice is manual, time-consuming, and bias-prone due to the subjective nature. Relevant studies in the literature are scarce and lacks comprehensive model evaluations from application perspectives. Herein, we aimed to benchmark the best-performing U-Net model for objective, stable and robust midbrain auto-segmentation using transcranial sonography images.

METHODS

A total of 584 patients who were suspected of Parkinson's Disease were retrospectively enrolled from Beijing Tiantan Hospital. The dataset was divided into training (n = 416), validation (n = 104), and testing (n = 64) sets. Three state-of-the-art deep-learning networks (U-Net, U-Net+++, and nnU-Net) were utilized to develop segmentation models, under 5-fold cross-validation and three randomization seeds for safeguarding model validity and stability. Model evaluation was conducted in testing set in three key aspects: (i) segmentation agreement using DICE coefficients (DICE), Intersection over Union (IoU), and Hausdorff Distance (HD); (ii) model stability using standard deviations of segmentation agreement metrics; (iii) prediction time efficiency, and (iv) model robustness against various degrees of ultrasound imaging noise produced by the salt-and-pepper noise and Gaussian noise.

RESULTS

The nnU-Net achieved the best segmentation agreement (averaged DICE: 0.910, IoU: 0.836, HD: 2.793-mm) and time efficiency (1.456-s). Under mild noise corruption, the nnU-Net outperformed others with averaged scores of DICE (0.904), IoU (0.827), HD (2.941 mm) in the salt-and-pepper noise (signal-to-noise ratio, SNR = 0.95), and DICE (0.906), IoU (0.830), HD (2.967 mm) in the Gaussian noise (sigma value, σ = 0.1); by contrast, intriguingly, performance of the U-Net and U-Net+++ models were remarkably degraded. Under increasing levels of simulated noise corruption (SNR decreased from 0.95 to 0.75; σ increased from 0.1 to 0.5), the nnU-Net network exhibited marginal decline in segmentation agreement meanwhile yielding decent performance as if there were absence of noise corruption.

CONCLUSIONS

The nnU-Net model was the best-performing midbrain segmentation model in terms of segmentation agreement, stability, time efficiency and robustness, providing the community with an objective, effective and automated alternative. Moving forward, a multi-center multi-vendor study is warranted when it comes to clinical implementation.

Neuromelanin-sensitive MRI for mechanistic research and biomarker development in psychiatry

Neuromelanin-sensitive MRI is a burgeoning non-invasive neuroimaging method with an increasing number of applications in psychiatric research. This MRI modality is sensitive to the concentration of neuromelanin, which is synthesized from intracellular catecholamines and accumulates in catecholaminergic nuclei including the dopaminergic substantia nigra and the noradrenergic locus coeruleus. Emerging data suggest the utility of neuromelanin-sensitive MRI as a proxy measure for variability in catecholamine metabolism and function, even in the absence of catecholaminergic cell loss. Given the importance of catecholamine function to several psychiatric disorders and their treatments, neuromelanin-sensitive MRI is ideally positioned as an informative and easy-to-acquire catecholaminergic index. In this review paper, we examine basic aspects of neuromelanin and neuromelanin-sensitive MRI and focus on its psychiatric applications in the contexts of mechanistic research and biomarker development. We discuss ongoing debates and state-of-the-art research into the mechanisms of the neuromelanin-sensitive MRI contrast, standardized protocols and optimized analytic approaches, and application of cutting-edge methods such as machine learning and artificial intelligence to enhance the feasibility and predictive power of neuromelanin-sensitive-MRI-based tools. We finally lay out important future directions to allow neuromelanin-sensitive-MRI to fulfill its potential as a key component of the research, and ultimately clinical, toolbox in psychiatry.

Hippocampus and olfactory impairment in Parkinson disease: a comparative exploratory combined volumetric/functional MRI study

INTRODUCTION

Patients with Parkinson's Disease (PD) commonly experience Olfactory Dysfunction (OD). Our exploratory study examined hippocampal volumetric and resting-state functional magnetic resonance imaging (rs-fMRI) variations in a Healthy Control (HC) group versus a cognitively normal PD group, further categorized into PD with No/Mild Hyposmia (PD-N/MH) and PD with Severe Hyposmia (PD-SH).

METHODS

We calculated participants' relative Total Hippocampal Volume (rTHV) and performed Spearman's partial correlations, controlled for age and gender, to examine the correlation between rTHV and olfactory performance assessed by the Odor Stick Identification Test for the Japanese (OSIT-J) score. Mann-Whitney U tests assessed rTHV differences across groups and subgroups, rejecting the null hypothesis for p < 0.05. Furthermore, a seed-based rs-fMRI analysis compared hippocampal connectivity differences using a one-way ANCOVA covariate model with controls for age and gender.

RESULTS

Spearman's partial correlations indicated a moderate positive correlation between rTHV and OSIT-J in the whole study population (ρ = 0.406; p = 0.007), PD group (ρ = 0.493; p = 0.008), and PD-N/MH subgroup (ρ = 0.617; p = 0.025). Mann-Whitney U tests demonstrated lower rTHV in PD-SH subgroup compared to both HC group (p = 0.013) and PD-N/MH subgroup (p = 0.029). Seed-to-voxel rsfMRI analysis revealed reduced hippocampal connectivity in PD-SH subjects compared to HC subjects with a single cluster of voxels.

CONCLUSIONS

Although the design of the study do not allow to make firm conclusions, it is reasonable to speculate that the progressive involvement of the hippocampus in PD patients is associated with the progression of OD.

Substantia nigra alterations in mice modeling Parkinson's disease

Parkinson's disease (PD) is an age-related neurodegenerative pathology of the central nervous system. The well-known abnormalities characteristic of PD are dysfunctions in the nigrostriatal system including the substantia nigra of the midbrain and the striatum. Moreover, in PD persons, alpha-synucleinopathy is associated with abnormalities in the dopaminergic brain system. To study the mechanisms of this pathology, genetic models in mice have been designed. Transgenic mice of the B6.Cg-Tg(Prnp-SNCA*A53T)23Mkle/J strain (referred to as B6.Cg-Tg further in the text) possess the A53T mutation in the human alpha-synuclein SNCA gene. The density of neurons in the prefrontal cortex, hippocampus, substantia nigra and striatum in B6.Cg-Tg mice was assessed in our previous work, but the dopaminergic system was not studied there, although it plays a key role in the development of PD. The aim of the current study was to investigate motor coordination and body balance, as well as dopaminergic neuronal density and alpha-synuclein accumulation in the substantia nigra in male B6.Cg-Tg mice at the age of six months. Wild-type mice of the same sex and age, siblings of the B6.Cg-Tg mice from the same litters, lacking the SNCA gene with the A53T mutation, but expressing murine alpha-synuclein, were used as controls (referred to as the wild type further in the text). Motor coordination and body balance were assessed with the rota-rod test; the density of dopaminergic neurons and accumulation of alpha-synuclein in the substantia nigra were evaluated by the immunohistochemical method. There was no difference between B6.Cg-Tg mice and WT siblings in motor coordination and body balance. However, accumulation of alpha-synuclein and a decrease in the number of dopaminergic neurons in the substantia nigra were found in the B6.Cg-Tg mouse strain. Thus, the mice of the B6.Cg-Tg strain at the age of six months have some symptoms of the onset of PD, such as the accumulation of mutant alpha-synuclein and a decrease in the number of dopaminergic neurons in the substantia nigra. Taken together, the results obtained in our work qualify the B6.Cg-Tg strain as a pertinent model for studying the early stage of human PD already at the age of six months.

Ferroptosis in Parkinson's disease -- The iron-related degenerative disease

Parkinson's disease (PD) is a prevalent and advancing age-related neurodegenerative disorder, distinguished by the degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNpc). Iron regional deposit in SNpc is a significant pathological characteristic of PD. Brain iron homeostasis is precisely regulated by iron metabolism related proteins, whereas disorder of these proteins can damage neurons and glial cells in the brain. Additionally, growing studies have reported iron metabolism related proteins are involved in the ferroptosis progression in PD. However, the effect of these proteins in the ferroptosis of PD has not been systematically summarized. This review focuses on the roles of iron metabolism related proteins in the ferroptosis of PD. Finally, we put forward the iron early diagnosis according to the observation of iron deposits in the brain and showed the recent advances in iron chelation therapy in PD.

Clinical significance of MRI-measured olfactory bulb height as an imaging biomarker of idiopathic Parkinson's disease

OBJECTIVES

This study aimed to determine whether the olfactory bulb height (OBH) measured using magnetic resonance imaging (MRI) has clinical utility as an imaging biomarker in the evaluation of patients with idiopathic Parkinson's disease (iPD) through its correlation with movement impairment.

METHODS

This retrospective study included cognitively intact patients with suspected parkinsonism. All participants underwent T2-weighted imaging to measure OBH. Logistic regression was used to determine whether OBH was an independent risk factor for distinguishing iPD patients from disease controls, and its relation with clinical parameters related to motor impairment, including clinical laterality, modified Hoehn and Yahr (HY) stage, and Unified Parkinson's Disease Rating Scale (UPDRS) III score, was investigated.

RESULTS

Based on the final clinical diagnosis, 79 patients with iPD and 16 disease controls were included. The mean OBH was significantly smaller in iPD than in disease controls (p < 0.0001). OBH was a significant independent predictor of iPD, with a cutoff of 1.52 mm. In the comparison among the ipsilateral, contralateral side of iPD with clinical laterality, and disease control group, the OBH of the disease control group was significantly larger than both the ipsilateral and contralateral sides (P < 0.05). However, there was no significant difference in OBH between the ipsilateral and contralateral sides (p > 0.05). OBH according to HY stage was significantly smaller in HY stage 2-3 groups than in the disease control group (p < 0.001). The correlation analysis between UPDRS III and OBH showed a mild negative correlation (r = -0.32, p = 0.013).

CONCLUSIONS

MRI-measured OBH is decreased in iPD regardless of age and sex and may be correlated with the progression of motor symptoms in the iPD.

Orphan GPCRs in Neurodegenerative Disorders: Integrating Structural Biology and Drug Discovery Approaches

Neurodegenerative disorders, particularly Alzheimer's and Parkinson's diseases, continue to challenge modern medicine despite therapeutic advances. Orphan G-protein-coupled receptors (GPCRs) have emerged as promising targets in the central nervous system, offering new avenues for drug development. This review focuses on the structural biology of orphan GPCRs implicated in these disorders, providing a comprehensive analysis of their molecular architecture and functional mechanisms. We examine recent breakthroughs in structural determination techniques, such as cryo-electron microscopy and X-ray crystallography, which have elucidated the intricate conformations of these receptors. The review highlights how structural insights inform our understanding of orphan GPCR activation, ligand binding and signaling pathways. By integrating structural data with molecular pharmacology, we explore the potential of structure-guided approaches in developing targeted therapeutics toward orphan GPCRs. This structural-biology-centered perspective aims to deepen our comprehension of orphan GPCRs and guide future drug discovery efforts in neurodegenerative disorders.

Dynamic cerebellar and sensorimotor network compensation in tremor-dominated Parkinson's disease

AIM

Parkinson's disease (PD) tremor is associated with dysfunction in the basal ganglia (BG), cerebellum (CB), and sensorimotor networks (SMN). We investigated tremor-related static functional network connectivity (SFNC) and dynamic functional network connectivity (DFNC) in PD patients.

METHODS

We analyzed the resting-state functional MRI data of 21 tremor-dominant Parkinson's disease (TDPD) patients and 29 healthy controls. We compared DFNC and SFNC between the three networks and assessed their associations with tremor severity.

RESULTS

TDPD patients exhibited increased SFNC between the SMN and BG networks. In addition, they spent more mean dwell time (MDT) in state 2, characterized by sparse connections, and less MDT in state 4, indicating stronger connections. Furthermore, enhanced DFNC between the CB and SMN was observed in state 2. Notably, the MDT of state 2 was positively associated with tremor scores.

CONCLUSION

The enhanced dynamic connectivity between the CB and SMN in TDPD patients suggests a potential compensatory mechanism. However, the tendency to remain in a state of sparse connectivity may contribute to the severity of tremor symptoms.

Advancements in Single-Cell RNA Sequencing and Spatial Transcriptomics for Central Nervous System Disease

The incidence of central nervous system (CNS) disease has persistently increased over the last several years. There is an urgent need for effective methods to improve the cure rates of CNS disease. However, the precise molecular basis underlying the development and progression of major CNS diseases remains elusive. A complete molecular map will contribute to research on CNS disease treatment strategies. Emerging technologies such as single-cell RNA sequencing (scRNA-seq) and Spatial Transcriptomics (ST) are potent tools for exploring the molecular complexity, cell heterogeneity, and functional specificity of CNS disease. scRNA-seq and ST can provide insights into the disease at cellular and spatial transcription levels. This review presents a survey of scRNA-seq and ST studies on CNS diseases, such as chronic neurodegenerative diseases, acute CNS injuries, and others. These studies offer novel perspectives in treating and diagnosing CNS diseases by discovering new cell types or subtypes associated with the disease, proposing new pathophysiological mechanisms, uncovering novel therapeutic targets, and identifying putative biomarkers.

The epigenetic modification of DNA methylation in neurological diseases

Methylation, a key epigenetic modification, is essential for regulating gene expression and protein function without altering the DNA sequence, contributing to various biological processes, including gene transcription, embryonic development, and cellular functions. Methylation encompasses DNA methylation, RNA methylation and histone modification. Recent research indicates that DNA methylation is vital for establishing and maintaining normal brain functions by modulating the high-order structure of DNA. Alterations in the patterns of DNA methylation can exert significant impacts on both gene expression and cellular function, playing a role in the development of numerous diseases, such as neurological disorders, cardiovascular diseases as well as cancer. Our current understanding of the etiology of neurological diseases emphasizes a multifaceted process that includes neurodegenerative, neuroinflammatory, and neurovascular events. Epigenetic modifications, especially DNA methylation, are fundamental in the control of gene expression and are critical in the onset and progression of neurological disorders. Furthermore, we comprehensively overview the role and mechanism of DNA methylation in in various biological processes and gene regulation in neurological diseases. Understanding the mechanisms and dynamics of DNA methylation in neural development can provide valuable insights into human biology and potentially lead to novel therapies for various neurological diseases.

Bibliometric analysis of global research trends in magnetic resonance imaging studies of substantia nigra in Parkinson's disease (2001-2024)

Background

Parkinson's disease (PD) is a globally prevalent neurodegenerative disorder, primarily characterized by muscle rigidity, resting tremor, and bradykinesia. The incidence of PD is rapidly escalating worldwide. Numerous studies have been conducted on the application of magnetic resonance imaging (MRI) in investigating the substantia nigra (SN) in PD patients. However, to date, no bibliometric analysis has been performed on this specific research area. Therefore, this study aimed to provide a comprehensive analysis of the current status in MRI research on the SN in PD patients.

Materials and methods

MRI study records related to the SN in PD patients from 2001 to 2024 were searched by using the Web of Science Core Collection (WOSCC) database and then the CiteSpace and VOSviewer were used to conduct bibliometric analysis.

Results

Our analysis found that the number of published articles related studies on MRI of the SN in PD showed an overall upward trend over the past decade, in which Lehericy, Stephane, Du, Guangwei, and Huang, Xuemei are the top three authors with the most articles. Additionally, United States, China and Germany are the main contributors to MRI studies of SN in PD. And Shanghai Jiao Tong University, University of Florida and Seoul National University are the leading institutions in the field. Finally, the keyword analysis showed that the hotspots and trends of research in this field are mainly concentrated in quantitative susceptibility mapping, neuroimaging, and neuromelanin-sensitive MRI.

Conclusion

These analysis identified the most influential authors, institutions, countries and research hotspots in the field of SN-MRI research in PD, which has reference significance for the research interest in this field and provides a new idea for PD prevention.

Precision Imaging in Neurodegeneration: The Superiority of Diffusion Tensor Imaging Over Conventional MRI in Differentiating Parkinson's Disease From Atypical Parkinsonian Syndromes

Background Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the degeneration of dopaminergic neurons in the substantia nigra, leading to motor and non-motor symptoms. Atypical parkinsonian syndromes (APS), including progressive supranuclear palsy (PSP) and essential tremor (ET), present with overlapping clinical features, making differential diagnosis challenging. Conventional MRI has limitations in distinguishing PD from APS, necessitating advanced imaging techniques like diffusion tensor imaging (DTI) for more accurate diagnosis. Objectives This retrospective study aimed to evaluate the diagnostic accuracy of DTI in diagnosing PD and APS, particularly assessing its ability to differentiate these conditions from each other compared to conventional MRI. Additionally, the study sought to determine if DTI could diagnose PD in cases where conventional MRI results were normal, thereby highlighting the potential role of DTI in enhancing diagnostic precision in neurodegenerative disorders. Methodology The study included 30 patients with clinically diagnosed PD or APS who underwent both conventional MRI and DTI. Data were collected retrospectively. Imaging was performed using a Philips Multiva 1.5-Tesla MRI scanner (Philips, Amsterdam, Netherlands). DTI sequences were analyzed for fractional anisotropy (FA) values in the substantia nigra, superior cerebellar peduncle, middle cerebellar peduncle, transverse pontine fibers, and dentate nucleus. The FA values were compared with established normal values, and the findings from DTI were correlated with clinical diagnoses and conventional MRI results. Results Among the 30 patients, 53.3% were clinically diagnosed with PD and 46.7% with APS, including PSP and ET. Conventional MRI findings were normal in 46.7% of cases, indicating its limitations in detecting early or subtle changes in neurodegenerative disorders. In contrast, DTI identified abnormalities in 83.3% of cases, demonstrating its superior diagnostic sensitivity. DTI detected significant FA value reductions in the substantia nigra in PD patients (mean FA: 0.440), which is consistent with the degeneration of dopaminergic neurons characteristic of PD. In PSP patients, the superior cerebellar peduncle showed marked FA reductions (mean FA: 0.523), correlating with the clinical features of PSP, such as bradykinesia and postural instability. ET was identified by reduced FA values in the superior cerebellar peduncle and dentate nucleus, distinguishing it from other forms of parkinsonism. DTI was particularly effective in cases where conventional MRI results were inconclusive or normal, identifying early-stage PD and differentiating it from APS with greater accuracy. The study demonstrated a sensitivity of 95.8% and specificity of 93.8% for DTI in differentiating PD from APS compared to conventional MRI. Conclusion This study highlights DTI as a superior imaging modality for the early diagnosis and differentiation of parkinsonian disorders, particularly when conventional MRI results are inconclusive. DTI's ability to detect significant microstructural changes in specific brain regions, evidenced by FA value reductions, enhances diagnostic accuracy. Incorporating DTI into routine clinical practice is essential for accurate differentiation between PD and APS, facilitating better patient management.

Automatic Transcranial Sonography-Based Classification of Parkinson's Disease Using a Novel Dual-Channel CNXV2-DANet

Transcranial sonography (TCS) has been introduced to assess hyper-echogenicity in the substantia nigra of the midbrain for Parkinson's disease (PD); however, its subjective and resource-demanding nature has impeded its widespread application. An AI-empowered TCS-based PD classification tool is greatly demanding, yet relevant research is severely scarce. Therefore, we proposed a novel dual-channel CNXV2-DANet for TCS-based PD classification using a large cohort. A total of 1176 TCS images from 588 subjects were retrospectively enrolled from Beijing Tiantan Hospital, encompassing both the left and right side of the midbrain for each subject. The entire dataset was divided into a training/validation/testing set at a ratio of 70%/15%/15%. Development of the proposed CNXV2-DANet was performed on the training set with comparisons between the single-channel and dual-channel input settings; model evaluation was conducted on the independent testing set. The proposed dual-channel CNXV2-DANet was compared against three state-of-the-art networks (ConvNeXtV2, ConvNeXt, Swin Transformer). The results demonstrated that both CNXV2-DANet and ConvNeXt V2 performed more superiorly under dual-channel inputs than the single-channel input. The dual-channel CNXV2-DANet outperformed the single-channel, achieving superior average metrics for accuracy (0.839 ± 0.028), precision (0.849 ± 0.014), recall (0.845 ± 0.043), F1-score (0.820 ± 0.038), and AUC (0.906 ± 0.013) compared with the single channel metrics for accuracy (0.784 ± 0.037), precision (0.817 ± 0.090), recall (0.748 ± 0.093), F1-score (0.773 ± 0.037), and AUC (0.861 ± 0.047). Furthermore, the dual-channel CNXV2-DANet outperformed all other networks (all p-values < 0.001). These findings suggest that the proposed dual-channel CNXV2-DANet may provide the community with an AI-empowered TCS-based tool for PD assessment.

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.

Striatonigrostriatal connectivity-based cross-species parcellation of human and macaque substantia nigra

Anatomical and functional heterogeneous substantia nigra (SN) has been extensively studied in humans and animals like rhesus monkeys given its crucial role in modulating a broad range of behaviors. Increasingly important cross-species research of SN may require connectionally homogeneous and homologous subregions of SN as objective and stable starting points from which the evolutionary characteristics of brain could be inspected. However, existing atlases of SN were all inaccurate mappings as a cross-species connectome atlas due to inadequate homology constraint during their constructions, and arbitrary paired use of these atlases might cause unreliable findings. In this study, a reliable blind-source cross-species parcellation of SN was developed based on the following rationale: striatonigrostriatal circuits form major structure of nigral connectivity; different nigral components have unique striatonigrostriatal connectivity; and inter-species corresponding human and macaque nigral components have similar striatonigrostriatal connectivity. Specifically, all voxels in human and macaque SN were grouped together and then classified based on inter-species identically characterized striatonigrostriatal connectivity attributes. Our results delineated a pars compacta-pars reticulate-like parcellation and further demonstrated its reliability by illustrating best-matched whole-brain structural and functional connectivity profiles of inter-species corresponding nigral subregions. Detailed inter-species and inter-regional differences in multi-aspect connectivities of these nigral subregions were inspected. It is expected that this cross-species connectome atlas of SN can offer biologically reliable cornerstones and important information to facilitate future cross-species research.

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.

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.

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.

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.

The Treatment of Parkinson's Disease with Sodium Oxybate

Sodiun Oxybate (SO) has a number of attributes that may mitigate the metabolic stress on the substantia nigra pars compacta (SNpc) dopaminergic (DA) neurons in Parkinson's disease (PD). These neurons function at the borderline of energy sufficiency. SO is metabolized to succinate and supplies energy to the cell by generating ATP. SO is a GABAB agonist and, as such, also arrests the high energy requiring calcium pace-making activity of these neurons. In addition, blocking calcium entry impedes the synaptic release and subsequent neurotransmission of aggregated synuclein species. As DA neurons degenerate, a homeostatic failure exposes these neurons to glutamate excitotoxicity, which in turn accelerates the damage. SO inhibits the neuronal release of glutamate and blocks its agonistic actions. Most important, SO generates NADPH, the cell's major antioxidant cofactor. Excessive free radical production within DA neurons and even more so within activated microglia are early and key features of the degenerative process that are present long before the onset of motor symptoms. NADPH maintains cell glutathione levels and alleviates oxidative stress and its toxic consequences. SO, a histone deacetylase inhibitor also suppresses the expression of microglial NADPH oxidase, the major source of free radicals in Parkinson brain. The acute clinical use of SO at night has been shown to reduce daytime sleepiness and fatigue in patients with PD. With long-term use, its capacity to supply energy to DA neurons, impede synuclein transmission, block excitotoxicity and maintain an anti-oxidative redox environment throughout the night may delay the onset of PD and slow its progress.

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.

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.