Iron-sensitive magnetic resonance imaging in Parkinson's disease: a systematic review and meta-analysis

Mapping the Research of Ferroptosis in Parkinson's Disease from 2013 to 2023: A Scientometric Review

Methods

Related studies on PD and ferroptosis were searched in Web of Science Core Collection (WOSCC) from inception to 2023. VOSviewer, CiteSpace, RStudio, and Scimago Graphica were employed as bibliometric analysis tools to generate network maps about the collaborations between authors, countries, and institutions and to visualize the co-occurrence and trends of co-cited references and keywords.

Results

A total of 160 original articles and reviews related to PD and ferroptosis were retrieved, produced by from 958 authors from 162 institutions. Devos David was the most prolific author, with 9 articles. China and the University of Melbourne had leading positions in publication volume with 84 and 12 publications, respectively. Current hot topics focus on excavating potential new targets for treating PD based on ferroptosis by gaining insight into specific molecular mechanisms, including iron metabolism disorders, lipid peroxidation, and imbalanced antioxidant regulation. Clinical studies aimed at treating PD by targeting ferroptosis remain in their preliminary stages.

Conclusion

A continued increase was shown in the literature within the related field over the past decade. The current study suggested active collaborations among authors, countries, and institutions. Research into the pathogenesis and treatment of PD based on ferroptosis has remained a prominent topic in the field in recent years, indicating that ferroptosis-targeted therapy is a potential approach to halting the progression of PD.

Enhancing Nigrosome-1 Sign Identification via Interpretable AI using True Susceptibility Weighted Imaging

BACKGROUND

Nigrosome 1 (N1), the largest nigrosome region in the ventrolateral area of the substantia nigra pars compacta, is identifiable by the "N1 sign" in long echo time gradient echo MRI. The N1 sign's absence is a vital Parkinson's disease (PD) diagnostic marker. However, it is challenging to visualize and assess the N1 sign in clinical practice.

PURPOSE

To automatically detect the presence or absence of the N1 sign from true susceptibility weighted imaging by using deep-learning method.

STUDY TYPE

Prospective.

POPULATION/SUBJECTS

453 subjects, including 225 PD patients, 120 healthy controls (HCs), and 108 patients with other movement disorders, were prospectively recruited including 227 males and 226 females. They were divided into training, validation, and test cohorts of 289, 73, and 91 cases, respectively.

FIELD STRENGTH/SEQUENCE

3D gradient echo SWI sequence at 3T; 3D multiecho strategically acquired gradient echo imaging at 3T; NM-sensitive 3D gradient echo sequence with MTC pulse at 3T.

ASSESSMENT

A neuroradiologist with 5 years of experience manually delineated substantia nigra regions. Two raters with 2 and 36 years of experience assessed the N1 sign on true susceptibility weighted imaging (tSWI), QSM with high-pass filter, and magnitude data combined with MTC data. We proposed NINet, a neural model, for automatic N1 sign identification in tSWI images.

STATISTICAL TESTS

We compared the performance of NINet to the subjective reference standard using Receiver Operating Characteristic analyses, and a decision curve analysis assessed identification accuracy.

RESULTS

NINet achieved an area under the curve (AUC) of 0.87 (CI: 0.76-0.89) in N1 sign identification, surpassing other models and neuroradiologists. NINet localized the putative N1 sign within tSWI images with 67.3% accuracy.

DATA CONCLUSION

Our proposed NINet model's capability to determine the presence or absence of the N1 sign, along with its localization, holds promise for enhancing diagnostic accuracy when evaluating PD using MR images.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Clinical biomarkers for Lewy body diseases

Synucleinopathies are a group of neurodegenerative disorders characterized by pathologic aggregates of neural and glial α-synuclein (α-syn) in the form of Lewy bodies (LBs), Lewy neurites, and cytoplasmic inclusions in both neurons and glia. Two major classes of synucleinopathies are LB disease and multiple system atrophy. LB diseases include Parkinson's disease (PD), PD with dementia, and dementia with LBs. All are increasing in prevalence. Effective diagnostics, disease-modifying therapies, and therapeutic monitoring are urgently needed. Diagnostics capable of differentiating LB diseases are based on signs and symptoms which might overlap. To date, no specific diagnostic test exists despite disease-specific pathologies. Diagnostics are aided by brain imaging and cerebrospinal fluid evaluations, but more accessible biomarkers remain in need. Mechanisms of α-syn evolution to pathologic oligomers and insoluble fibrils can provide one of a spectrum of biomarkers to link complex neural pathways to effective therapies. With these in mind, we review promising biomarkers linked to effective disease-modifying interventions.

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.

Outcome Measures for Disease-Modifying Trials in Parkinson's Disease: Consensus Paper by the EJS ACT-PD Multi-Arm Multi-Stage Trial Initiative

BACKGROUND

Multi-arm, multi-stage (MAMS) platform trials can accelerate the identification of disease-modifying treatments for Parkinson's disease (PD) but there is no current consensus on the optimal outcome measures (OM) for this approach.

OBJECTIVE

To provide an up-to-date inventory of OM for disease-modifying PD trials, and a framework for future selection of OM for such trials.

METHODS

As part of the Edmond J Safra Accelerating Clinical Trials in Parkinson Disease (EJS ACT-PD) initiative, an expert group with Patient and Public Involvement and Engagement (PPIE) representatives' input reviewed and evaluated available evidence on OM for potential use in trials to delay progression of PD. Each OM was ranked based on aspects such as validity, sensitivity to change, participant burden and practicality for a multi-site trial. Review of evidence and expert opinion led to the present inventory.

RESULTS

An extensive inventory of OM was created, divided into: general, motor and non-motor scales, diaries and fluctuation questionnaires, cognitive, disability and health-related quality of life, capability, quantitative motor, wearable and digital, combined, resource use, imaging and wet biomarkers, and milestone-based. A framework for evaluation of OM is presented to update the inventory in the future. PPIE input highlighted the need for OM which reflect their experience of disease progression and are applicable to diverse populations and disease stages.

CONCLUSION

We present a range of OM, classified according to a transparent framework, to aid selection of OM for disease-modifying PD trials, whilst allowing for inclusion or re-classification of relevant OM as new evidence emerges.

Iron Brain Menace: The Involvement of Ferroptosis in Parkinson Disease

Parkinson disease (PD) is the second-most common neurodegenerative disease. The characteristic pathology of progressive dopaminergic neuronal loss in people with PD is associated with iron accumulation and is suggested to be driven in part by the novel cell death pathway, ferroptosis. A unique modality of cell death, ferroptosis is mediated by iron-dependent phospholipid peroxidation. The mechanisms of ferroptosis inhibitors enhance antioxidative capacity to counter the oxidative stress from lipid peroxidation, such as through the system x_c^-/glutathione (GSH)/glutathione peroxidase 4 (GPX4) axis and the coenzyme Q10 (CoQ10)/FSP1 pathway. Another means to reduce ferroptosis is with iron chelators. To date, there is no disease-modifying therapy to cure or slow PD progression, and a recent topic of research seeks to intervene with the development of PD via regulation of ferroptosis. In this review, we provide a discussion of different cell death pathways, the molecular mechanisms of ferroptosis, the role of ferroptosis in blood-brain barrier damage, updates on PD studies in ferroptosis, and the latest progress of pharmacological agents targeting ferroptosis for the intervention of PD in clinical trials.

Iron- and Neuromelanin-Weighted Neuroimaging to Study Mitochondrial Dysfunction in Patients with Parkinson's Disease

The underlying causes of Parkinson's disease are complex, and besides recent advances in elucidating relevant disease mechanisms, no disease-modifying treatments are currently available. One proposed pathophysiological hallmark is mitochondrial dysfunction, and a plethora of evidence points toward the interconnected nature of mitochondria in neuronal homeostasis. This also extends to iron and neuromelanin metabolism, two biochemical processes highly relevant to individual disease manifestation and progression. Modern neuroimaging methods help to gain in vivo insights into these intertwined pathways and may pave the road to individualized medicine in this debilitating disorder. In this narrative review, we will highlight the biological rationale for studying these pathways, how distinct neuroimaging methods can be applied in patients, their respective limitations, and which challenges need to be overcome for successful implementation in clinical studies.

MRI Findings in Parkinson’s Disease: Radiologic Assessment of Nigrostriatal Degeneration

파킨슨병은 중뇌 흑질에 위치한 도파민성 신경세포의 퇴행성 소실로 인해 발생하는 이상운동질환이다. 최근 다양한 자기공명영상기법의 발전으로 파킨슨병에서 일어나는 병리생태학적인 변화를 반영하는 여러 영상 소견들이 보고되었다. 여러 연구에서 이러한 영상 소견들은 파킨슨병의 진단 및 비정형 파킨슨증과의 감별 등에 유의미한 도움을 줄 수 있는 것이 밝혀졌다. 본 종설에서는, 파킨슨병에서 일어나는 흑질선조체 변성의 병태생리를 나타낼 수 있는 나이그로좀 영상 및 뉴로멜라닌 영상 등을 포함한 자기공명영상기법들과 각 영상에서 나타나는 소견에 대하여 자세히 다루었다.