Utility of neuromelanin-sensitive MRI in the diagnosis of dementia with Lewy bodies

OBJECTIVE

Dementia with Lewy bodies (DLB) is recognized as the second most common cause of degenerative dementia in older people with Alzheimer's disease (AD), and distinguishing between these 2 diseases may be challenging in clinical practice. However, accurate differentiation is important because these 2 diseases have different prognoses and require different care. Recently, several studies have reported that neuromelanin-sensitive MRI can detect neurodegeneration in the substantia nigra pars compacta (SNc). DLB patients are considered to demonstrate degeneration and a reduction of dopaminergic neurons in the SNc. Therefore, neuromelanin-sensitive MRI may be useful for the diagnosis of DLB. Therefore, in this study, we aimed to investigate the usefulness of neuromelanin-sensitive MRI in the distinguishing DLB from AD.

METHODS

A total of 21 probable DLB and 22 probable AD patients were enrolled. All participants underwent both DaT-SPECT and neuromelanin-sensitive MRI. A combined model of neuromelanin-sensitive MRI and Dopamine transporter single-photon emission computed tomography (DaT-SPECT) was created using logistic regression analysis (forced entry method).

RESULTS

There was no difference in the diagnostic utility of neuromelanin-sensitive MRI and DaT-SPECT in distinguishing DLB from AD. There was no significant correlation between the results of neuromelanin-sensitive MRI and DaT-SPECT in DLB patients. The combination of neuromelanin-sensitive MRI and DaT-SPECT demonstrated higher diagnostic performance in distinguishing between DLB and AD compared with neuromelanin-sensitive MRI alone. Additionally, although the combination of both modalities showed a larger AUC compared with DaT-SPECT alone, the difference was not statistically significant.

CONCLUSIONS

Neuromelanin-sensitive MRI may be equally or even more useful than DaT-SPECT in the clinical differentiation of DLB from AD. Furthermore, the combination of neuromelanin-sensitive MRI and DaT-SPECT may be a highly sensitive imaging marker for distinguishing DLB from AD.

An automated hybrid approach via deep learning and radiomics focused on the midbrain and substantia nigra to detect early-stage Parkinson's disease

Objectives

The altered neuromelanin in substantia nigra pars compacta (SNpc) is a valuable biomarker in the detection of early-stage Parkinson's disease (EPD). Diagnosis via visual inspection or single radiomics based method is challenging. Thus, we proposed a novel hybrid model that integrates radiomics and deep learning methodologies to automatically detect EPD based on neuromelanin-sensitive MRI, namely short-echo-time Magnitude (setMag) reconstructed from quantitative susceptibility mapping (QSM).

Methods

In our study, we collected QSM images including 73 EPD patients and 65 healthy controls, which were stratified into training-validation and independent test sets with an 8:2 ratio. Twenty-four participants from another center were included as the external validation set. Our framework began with the detection of the brainstem utilizing YOLO-v5. Subsequently, a modified LeNet was applied to obtain deep learning features. Meanwhile, 1781 radiomics features were extracted, and 10 features were retained after filtering. Finally, the classified models based on radiomics features, deep learning features, and the hybrid of both were established through machine learning algorithms, respectively. The performance was mainly evaluated using accuracy, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). The saliency map was used to visualize the model.

Results

The hybrid feature-based support vector machine (SVM) model showed the best performance, achieving ACC of 96.3 and 95.8% in the independent test set and external validation set, respectively. The model established by hybrid features outperformed the one radiomics feature-based (NRI: 0.245, IDI: 0.112). Furthermore, the saliency map showed that the bilateral "swallow tail" sign region was significant for classification.

Conclusion

The integration of deep learning and radiomic features presents a potent strategy for the computer-aided diagnosis of EPD. This study not only validates the accuracy of our proposed model but also underscores its interpretability, evidenced by differential significance across various anatomical sites.

Neuromelanin-sensitive magnetic resonance imaging: Possibilities and promises as an imaging biomarker for Parkinson's disease

Parkinson's disease (PD) is an age-related progressive neurodegenerative disorder characterized by both motor and non-motor symptoms resulting from the death of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and noradrenergic neurons in the locus coeruleus (LC). The current diagnosis of PD primarily relies on motor symptoms, often leading to diagnoses in advanced stages, where a significant portion of SNpc dopamine neurons has already succumbed. Therefore, the identification of imaging biomarkers for early-stage PD diagnosis and disease progression monitoring is imperative. Recent studies propose that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) holds promise as an imaging biomarker. In this review, we summarize the latest findings concerning NM-MRI characteristics at various stages in patients with PD and those with atypical parkinsonism. In conclusion, alterations in neuromelanin within the LC are associated with non-motor symptoms and prove to be a reliable imaging biomarker in the prodromal phase of PD. Furthermore, NM-MRI demonstrates efficacy in differentiating progressive supranuclear palsy (PSP) from PD and multiple system atrophy with predominant parkinsonism. The spatial patterns of changes in the SNpc can be indicative of PD progression and aid in distinguishing between PSP and synucleinopathies. We recommend that patients with PD and individuals at risk for PD undergo regular NM-MRI examinations. This technology holds the potential for widespread use in PD diagnosis.

Direct comparison between 18F-Flortaucipir tau PET and quantitative susceptibility mapping in progressive supranuclear palsy

PURPOSE

The pattern of flortaucipir tau PET uptake is topographically similar to the pattern of magnetic susceptibility in progressive supranuclear palsy (PSP); both with increased signal in subcortical structures such as the basal ganglia and midbrain, suggesting that they may be closely related. However, their relationship remains unknown since no studies have directly compared these two modalities in the same PSP cohort. We hypothesized that some flortaucipir uptake in PSP is associated with magnetic susceptibility, and hence iron deposition. The aim of this study was to evaluate the regional relationship between flortaucipir uptake and magnetic susceptibility and to examine the effects of susceptibility on flortaucipir uptake in PSP.

METHODS

Fifty PSP patients and 67 cognitively normal controls were prospectively recruited and underwent three Tesla MRI and flortaucipir tau PET scans. Quantitative susceptibility maps were reconstructed from multi-echo gradient-echo MRI images. Region of interest (ROI) analysis was performed to obtain flortaucipir and susceptibility values in the subcortical regions. Relationships between flortaucipir and susceptibility signals were evaluated using partial correlation analysis in the subcortical ROIs and voxel-based analysis in the whole brain. The effects of susceptibility on flortaucipir uptake were examined by using the framework of mediation analysis.

RESULTS

Both flortaucipir and susceptibility were greater in PSP compared to controls in the putamen, pallidum, subthalamic nucleus, red nucleus, and cerebellar dentate (p<0.05). The ROI-based and voxel-based analyses showed that these two signals were positively correlated in these five regions (r = 0.36-0.59, p<0.05). Mediation analysis showed that greater flortaucipir uptake was partially explained by susceptibility in the putamen, pallidum, subthalamic nucleus, and red nucleus, and fully explained in the cerebellar dentate.

CONCLUSIONS

These results suggest that some of the flortaucipir uptake in subcortical regions in PSP is related to iron deposition. These findings will contribute to our understanding of the mechanisms underlying flortaucipir tau PET findings in PSP and other neurodegenerative diseases.

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.

Unravelling the Parkinson's puzzle, from medications and surgery to stem cells and genes: a comprehensive review of current and future management strategies

Parkinson's disease (PD) is a neurodegenerative disorder, prevalent in the elderly population. Neuropathological hallmarks of PD include loss of dopaminergic cells in the nigro-striatal pathway and deposition of alpha-synuclein protein in the neurons and synaptic terminals, which lead to a complex presentation of motor and non-motor symptoms. This review focuses on various aspects of PD, from clinical diagnosis to currently accepted treatment options, such as pharmacological management through dopamine replacement and surgical techniques such as deep brain stimulation (DBS). The review discusses in detail the potential of emerging stem cell-based therapies and gene therapies to be adopted as a cure, in contrast to the present symptomatic treatment in PD. The potential sources of stem cells for autologous and allogeneic stem cell therapy have been discussed, along with the progress evaluation of pre-clinical and clinical trials. Even though recent techniques hold great potential to improve the lives of PD patients, we present the importance of addressing the safety, efficacy, ethical, cost, and regulatory concerns before scaling them to clinical use.

Comparison of automated and manual quantification methods for neuromelanin-sensitive MRI in Parkinson's disease

Neuromelanin-sensitive magnetic resonance imaging quantitative analysis methods have provided promising biomarkers that can noninvasively quantify degeneration of the substantia nigra in patients with Parkinson's disease. However, there is a need to systematically evaluate the performance of manual and automated quantification approaches. We evaluate whether spatial, signal-intensity, or subject specific abnormality measures using either atlas based or manually traced identification of the substantia nigra better differentiate patients with Parkinson's disease from healthy controls using logistic regression models and receiver operating characteristics. Inference was performed using bootstrap analyses to calculate 95% confidence interval bounds. Pairwise comparisons were performed by generating 10,000 permutations, refitting the models, and calculating a paired difference between metrics. Thirty-one patients with Parkinson's disease and 22 healthy controls were included in the analyses. Signal intensity measures significantly outperformed spatial and subject specific abnormality measures, with the top performers exhibiting excellent ability to differentiate patients with Parkinson's disease and healthy controls (balanced accuracy = 0.89; area under the curve = 0.81; sensitivity =0.86; and specificity = 0.83). Atlas identified substantia nigra metrics performed significantly better than manual tracing metrics. These results provide clear support for the use of automated signal intensity metrics and additional recommendations. Future work is necessary to evaluate whether the same metrics can best differentiate atypical parkinsonism, perform similarly in de novo and mid-stage cohorts, and serve as longitudinal monitoring biomarkers.

Diagnostic performance of a high-spatial-resolution voxelwise analysis of neuromelanin-sensitive imaging in early-stage idiopathic Parkinson's disease

BACKGROUND

Quantitative assessments of neuromelanin (NM) of the substantia nigra pars compacta (SNpc) in neuromelanin-sensitive MRI (NM-MRI) to determine its abnormality have been conducted by measuring either the volume or contrast ratio (CR) of the SNpc. A recent study determined the regions in the SNpc that are significantly different between early-stage idiopathic Parkinson's disease (IPD) patients and healthy controls (HCs) using a high spatial-resolution NM-MRI template, which enables a template-based voxelwise analysis to overcome the susceptibility of CR measurement to inter-rater discrepancy. We aimed to assess the diagnostic performance, which has not been reported, of the CRs between early-stage IPD patients and HCs using a NM-MRI template.

METHODS

We retrospectively enrolled early-stage IPD patients (n = 50) and HCs (n = 50) who underwent 0.8-mm isovoxel NM-MRI and dopamine-transporter PET as the standard of reference. A template-based voxelwise analysis revealed two regions in nigrosomes 1 and 2 (N1 and N2, respectively), with significant differences in each substantia nigra (SNpc) between IPD and HCs. The mean CR values of N1, N2, volume-weighted mean of N1 and N2 (N1 + N2), and whole SNpc on each side were compared between IPD and HC using the independent t-test or the Mann-Whitney U test. The diagnostic performance was compared in each region using receiver operating characteristic curves.

RESULTS

The mean CR values in the right N1 (0.149459 vs. 0.194505), left N1 (0.133328 vs. 0.169160), right N2 (0.230245 vs. 0.278181), left N2 (0.235784 vs. 0.314169), right N1 + N2 (0.155322 vs. 0.278143), left N1 + N2 (0.140991 vs. 0.276755), right whole SNpc (0.131397 vs. 0.141422), and left whole SNpc (0.127099 vs. 0.137873) significantly differed between IPD patients and HCs (all p < 0.001). The areas under the curve of the left N1 + N2, right N1 + N2, left N1, right N1, left N2, right N2, left whole SNpc, and right whole SNpc were 0.994 (sensitivity, 98.0%; specificity, 94.0%), 0.985, 0.804, 0.802, 0.777, 0.766, 0.632, and 0.606, respectively.

CONCLUSION

Our NM-MRI template-based CR measurements revealed significant differences between early-stage IPD patients and HCs. The CR values of the left N1 + N2 demonstrated the highest diagnostic performance.

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.

Regional age-related changes of neuromelanin and iron in the substantia nigra based on neuromelanin accumulation and iron deposition

OBJECTIVES

To investigate age-related neuromelanin signal variation and iron content changes in the subregions of substantia nigra (SN) using magnetization transfer contrast neuromelanin-sensitive multi-echo fast field echo sequence in a normal population.

METHODS

In this prospective study, 115 healthy volunteers between 20 and 86 years of age were recruited and scanned using 3.0-T MRI. We manually delineated neuromelanin accumulation and iron deposition regions in neuromelanin image and quantitative susceptibility mapping, respectively. We calculated the overlap region using the two measurements mentioned above. Partial correlation analysis was used to evaluate the correlations between volume, contrast ratio (CR), susceptibility of three subregions of SN, and age. Curve estimation models were used to find the best regression model.

RESULTS

CR increased with age (r = 0.379, p < 0.001; r = 0.371, p < 0.001), while volume showed an age-related decline (r =  -0.559, p < 0.001; r =  -0.410, p < 0.001) in the neuromelanin accumulation and overlap regions. Cubic polynomial regression analysis found a small increase in neuromelanin accumulation volume with age until 34, followed by a significant decrease until the 80 s (R² = 0.358, p < 0.001). No significant correlations were found between susceptibility and age in any subregion. No correlation was found between CR and susceptibility in the overlap region.

CONCLUSIONS

Our results indicated that CR increased with age, while volume showed an age-related decline in the overlap region. We further found that the neuromelanin accumulation region volume increased until the 30 s and decreased into the 80 s. This study may provide a reference for future neurodegenerative elucidations of substantia nigra.

KEY POINTS

• Our results define the regional changes in neuromelanin and iron in the substantia nigra with age in the normal population, especially in the overlap region. • The contrast ratio increased with age in the neuromelanin accumulation and overlap regions, and volume showed an age-related decline, while contrast ratio and volume do not affect each other indirectly. • The contrast ratio of hyperintense neuromelanin in the overlap region was unaffected by iron content.

Automated volumetric determination of high R2 * regions in substantia nigra: A feasibility study of quantifying substantia nigra atrophy in progressive supranuclear palsy

The establishment of an unbiased protocol for the automated volumetric measurement of iron-rich regions in the substantia nigra (SN) is clinically important for diagnosing neurodegenerative diseases exhibiting midbrain atrophy, such as progressive supranuclear palsy (PSP). This study aimed to automatically quantify the volume and surface properties of the iron-rich 3D regions in the SN using the quantitative MRI-R₂ ^* map. Three hundred and sixty-seven slices of R₂ ^* map and susceptibility-weighted imaging (SWI) at 3-T MRI from healthy control (HC) individuals and Parkinson's disease (PD) patients were used to train customized U-net++ convolutional neural network based on expert-segmented masks. Age- and sex-matched participants were selected from HC, PD, and PSP groups to automate the volumetric determination of iron-rich areas in the SN. Dice similarity coefficient values between expert-segmented and detected masks from the proposed network were 0.91 ± 0.07 for R₂ ^* maps and 0.89 ± 0.08 for SWI. Reductions in iron-rich SN volume from the R₂ ^* map (SWI) were observed in PSP with area under the receiver operating characteristic curve values of 0.96 (0.89) and 0.98 (0.92) compared with HC and PD, respectively. The mean curvature of the PSP showed SN deformation along the side closer to the red nucleus. We demonstrated the automated volumetric measurement of iron-rich regions in the SN using deep learning can quantify the SN atrophy in PSP compared with PD and HC.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Magnetic resonance and dopamine transporter imaging for the diagnosis of Parkinson´s disease: a narrative review

BACKGROUND

the diagnosis of Parkinson's disease (PD) can be challenging, especially in the early stages, albeit its updated and validated clinical criteria. Recent developments on neuroimaging in PD, altogether with its consolidated role of excluding secondary and other neurodegenerative causes of parkinsonism, provide more confidence in the diagnosis across the different stages of the disease. This review highlights current knowledge and major recent advances in magnetic resonance and dopamine transporter imaging in aiding PD diagnosis.

OBJECTIVE

This study aims to review current knowledge about the role of magnetic resonance imaging and neuroimaging of the dopamine transporter in diagnosing Parkinson's disease.

METHODS

We performed a non-systematic literature review through the PubMed database, using the keywords "Parkinson", "magnetic resonance imaging", "diffusion tensor", "diffusion-weighted", "neuromelanin", "nigrosome-1", "single-photon emission computed tomography", "dopamine transporter imaging". The search was restricted to articles written in English, published between January 2010 and February 2022.

RESULTS

The diagnosis of Parkinson's disease remains a clinical diagnosis. However, new neuroimaging biomarkers hold promise for increased diagnostic accuracy, especially in earlier stages of the disease.

CONCLUSION

Future validation of new imaging biomarkers bring the expectation of an increased neuroimaging role in the diagnosis of PD in the following years.

Regional Selectivity of Neuromelanin Changes in the Substantia Nigra in Atypical Parkinsonism

BACKGROUND

Neurodegeneration in the substantia nigra pars compacta (SNc) in parkinsonian syndromes may affect the nigral territories differently.

OBJECTIVE

The objective of this study was to investigate the regional selectivity of neurodegenerative changes in the SNc in patients with Parkinson's disease (PD) and atypical parkinsonism using neuromelanin-sensitive magnetic resonance imaging (MRI).

METHODS

A total of 22 healthy controls (HC), 38 patients with PD, 22 patients with progressive supranuclear palsy (PSP), 20 patients with multiple system atrophy (MSA, 13 with the parkinsonian variant, 7 with the cerebellar variant), 7 patients with dementia with Lewy body (DLB), and 4 patients with corticobasal syndrome were analyzed. volume and signal-to-noise ratio (SNR) values of the SNc were derived from neuromelanin-sensitive MRI in the whole SNc. Analysis of signal changes was performed in the sensorimotor, associative, and limbic territories of the SNc.

RESULTS

SNc volume and corrected volume were significantly reduced in PD, PSP, and MSA versus HC. Patients with PSP had lower volume, corrected volume, SNR, and contrast-to-noise ratio than HC and patients with PD and MSA. Patients with PSP had greater SNR reduction in the associative region than HC and patients with PD and MSA. Patients with PD had reduced SNR in the sensorimotor territory, unlike patients with PSP. Patients with MSA did not differ from patients with PD.

CONCLUSIONS

This study provides the first MRI comparison of the topography of neuromelanin changes in parkinsonism. The spatial pattern of changes differed between PSP and synucleinopathies. These nigral topographical differences are consistent with the topography of the extranigral involvement in parkinsonian syndromes. © 2022 International Parkinson and Movement Disorder Society.

Deep Learning-Based Neuromelanin MRI Changes of Isolated REM Sleep Behavior Disorder

Background

Isolated REM sleep behavior disorder (iRBD) is considered a prodromal stage of parkinsonism. Neurodegenerative changes in the substantia nigra pars compacta (SNc) in parkinsonism can be detected using neuromelanin‐sensitive MRI.

Objective

To investigate SNc neuromelanin changes in iRBD patients using fully automatic segmentation.

Methods

We included 47 iRBD patients, 134 early Parkinson's disease (PD) patients and 55 healthy volunteers (HVs) scanned at 3 Tesla. SNc regions‐of‐interest were delineated automatically using convolutional neural network. SNc volumes, volumes corrected by total intracranial volume, signal‐to‐noise ratio (SNR) and contrast‐to‐noise ratio were computed. One‐way general linear models (GLM) analysis of covariance (ANCOVA) was conducted while adjusting for age and sex.

Results

All SNc measurements differed significantly between the three groups (except SNR in iRBD). Changes in iRBD were intermediate between those in PD and HVs.

Conclusions

Using fully automated SNc segmentation method and neuromelanin‐sensitive imaging, iRBD patients showed neurodegenerative changes in the SNc at a lower level than in PD patients. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Pragmatic Approach on Neuroimaging Techniques for the Differential Diagnosis of Parkinsonisms

Background

Rapid advances in neuroimaging technologies in the exploration of the living human brain also apply to movement disorders. However, the accurate diagnosis of Parkinson's disease (PD) and atypical parkinsonian disorders (APDs) still remains a challenge in daily practice.

Methods

We review the literature and our own experience as the Movement Disorder Society-Neuroimaging Study Group in Movement Disorders with the aim of providing a practical approach to the use of imaging technologies in the clinical setting.

Results

The enormous amount of articles published so far and our increasing recognition of imaging technologies contrast with a lack of imaging protocols and updated algorithms for differential diagnosis. The distinctive pathological involvement in different brain structures and the correlation with imaging findings obtained with magnetic resonance, positron emission tomography, or single-photon emission computed tomography illustrate what qualitative and quantitative measures may be useful in the clinical setting.

Conclusion

We delineate a pragmatic approach to discuss imaging technologies, updated imaging algorithms, and their implications for differential diagnoses in PD and APDs.

Diagnostic Performance of the Magnetic Resonance Parkinsonism Index in Differentiating Progressive Supranuclear Palsy from Parkinson's Disease: An Updated Systematic Review and Meta-Analysis

Progressive supranuclear palsy (PSP) and Parkinson's disease (PD) are difficult to differentiate especially in the early stages. We aimed to investigate the diagnostic performance of the magnetic resonance parkinsonism index (MRPI) in differentiating PSP from PD. A systematic literature search of PubMed-MEDLINE and EMBASE was performed to identify original articles evaluating the diagnostic performance of the MRPI in differentiating PSP from PD published up to 20 February 2021. The pooled sensitivity, specificity, and 95% CI were calculated using the bivariate random-effects model. The area under the curve (AUC) was calculated using a hierarchical summary receiver operating characteristic (HSROC) model. Meta-regression was performed to explain the effects of heterogeneity. A total of 14 original articles involving 484 PSP patients and 1243 PD patients were included. In all studies, T1-weighted images were used to calculate the MRPI. Among the 14 studies, nine studies used 3D T1-weighted images. The pooled sensitivity and specificity for the diagnostic performance of the MRPI in differentiating PSP from PD were 96% (95% CI, 87-99%) and 98% (95% CI, 91-100%), respectively. The area under the HSROC curve was 0.99 (95% CI, 0.98-1.00). Heterogeneity was present (sensitivity: I² = 97.29%; specificity: I² = 98.82%). Meta-regression showed the association of the magnet field strength with heterogeneity. Studies using 3 T MRI showed significantly higher sensitivity (100%) and specificity (100%) than those of studies using 1.5 T MRI (sensitivity of 98% and specificity of 97%) (p < 0.01). Thus, the MRPI could accurately differentiate PSP from PD and support the implementation of appropriate management strategies for patients with PSP.

Is Generalized and Segmental Dystonia Accompanied by Impairments in the Dopaminergic System?

Background: The pathogenesis of dystonia is remarkably diverse. Some types of dystonia, such as DYT5 (DYT-GCH1) and tardive dystonia, are related to dysfunction of the dopaminergic system. Furthermore, on pathological examination, cell loss in the substantia nigra (SN) of patients with dystonia has been reported, suggesting that impaired dopamine production may be involved in DYT5 and in other types of dystonia.

Objectives: To investigate functional dopaminergic impairments, we compared patients with dystonia and those with Parkinson's disease (PD) with normal controls using neuromelanin-sensitive magnetic resonance imaging (NM-MRI) and dopamine transporter single photon emission computed tomography (DAT SPECT).

Methods: A total of 18, 18, and 27 patients with generalized or segmental dystonia, patients with PD, and healthy controls, respectively, were examined using NM-MRI. The mean area corresponding to NM in the SN (NM-SN) was blindly quantified. DAT SPECT was performed on 17 and eight patients with dystonia and PD, respectively. The imaging data of DAT SPECT were harmonized with the Japanese database using striatum phantom calibration. These imaging data were compared between patients with dystonia or PD and controls from the Japanese database in 256 healthy volunteers using the calibrated specific binding ratio (cSBR). The symptoms of dystonia were evaluated using the Fahn–Marsden Dystonia Rating Scale (FMDRS), and the correlation between the results of imaging data and FMDRS was examined.

Results: The mean areas corresponding to NM in the SN (NM-SN) were 31 ± 4.2, 28 ± 3.8, and 43 ± 3.8 pixels in patients with dystonia, PD, and in healthy controls, respectively. The mean cSBRs were 5 ± 0.2, 2.8 ± 0.2, 9.2 (predictive) in patients with dystonia, PD, and in healthy controls, respectively. The NM-SN area (r = −0.49, p < 0.05) and the cSBR (r = −0.54, p < 0.05) were inversely correlated with the FMDRS. There was no significant difference between the dystonia and PD groups regarding NM-SN (p = 0.28). In contrast, the cSBR was lower in patients with PD than in those with dystonia (p < 0.5 × 10⁻⁶).

Conclusions: Impairments of the dopaminergic system may be involved in developing generalized and segmental dystonia. SN abnormalities in patients with dystonia were supposed to be different from degeneration in PD.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Update on neuroimaging for categorization of Parkinson's disease and atypical parkinsonism

PURPOSE OF REVIEW

Differential diagnosis of Parkinsonism may be difficult. The objective of this review is to present the work of the last three years in the field of imaging for diagnostic categorization of parkinsonian syndromes focusing on progressive supranuclear palsy (PSP) and multiple system atrophy (MSA).

RECENT FINDINGS

Two main complementary approaches are being pursued. The first seeks to develop and validate manual qualitative or semi-quantitative imaging markers that can be easily used in clinical practice. The second is based on quantitative measurements of magnetic resonance imaging abnormalities integrated in a multimodal approach and in automatic categorization machine learning tools.

SUMMARY

These two complementary approaches obtained high diagnostic around 90% and above in the classical Richardson form of PSP and probable MSA. Future work will determine if these techniques can improve diagnosis in other PSP variants and early forms of the diseases when all clinical criteria are not fully met.

Neuromelanin-sensitive magnetic resonance imaging in disease differentiation for parkinsonism or neurodegenerative disease affecting the basal ganglia

INTRODUCTION

Several reports have shown that neuromelanin-sensitive magnetic resonance imaging (NMI) using 3T magnetic resonance imaging is useful for the differential diagnosis of Parkinson's disease (PD), progressive supranuclear palsy (PSP), and other neurological diseases. However, the number of cases in previous studies has been insufficient. We aimed to determine the relationship between NMI and severity of PD and related disorders, and thereby establish the diagnostic utility of NMI for diagnosing neurological diseases.

METHODS

We enrolled 591 patients (531 subjects after removal of duplicates) with parkinsonism who underwent NMI. The contrast ratio of the locus coeruleus (LC-CR) and the area of the substantia nigra pars compacta (SNc) were analyzed in each patient.

RESULTS

The patients' clinical diagnoses were as follows: 11 patients in the disease control group (DCG), 244 patients with PD, 49 patients with PSP, and 19 patients with multiple system atrophy with predominant parkinsonism. Additionally, some patients were diagnosed with dementia with Lewy bodies, vascular parkinsonism, and drug-induced parkinsonism. SNc in the patients with PD and PSP was significantly smaller than that in DCG. LC-CR in the patients with PD was lower than that in DCG; furthermore, LC-CR in the patients with PD was significantly lower than that in the patients with PSP. We found that an area under the receiver-operating characteristic curve, indicating diagnostic efficacy, of 0.85 for LC-CR is a promising biomarker for differentiating PD from PSP.

CONCLUSION

NMI effectively contributes to differentiating neurodegenerative diseases, such as PD and PSP.

Early-stage Parkinson's disease: Abnormal nigrosome 1 and 2 revealed by a voxelwise analysis of neuromelanin-sensitive MRI

Previous pathologic studies evaluated the substantia nigra pars compacta (SNpc) of a limited number of idiopathic Parkinson's disease (IPD) patients with relatively longer disease durations. Therefore, it remains unknown which region of the SNpc is most significantly affected in early‐stage IPD. We hypothesized that a voxelwise analysis of thin‐section neuromelanin‐sensitive MRI (NM‐MRI) may help determine the significantly affected regions of the SNpc in early‐stage IPD and localize these areas in each nigrosome on high‐spatial‐resolution susceptibility map‐weighted imaging (SMwI). Ninety‐six healthy subjects and 50 early‐stage IPD patients underwent both a 0.8 × 0.8 × 0.8 mm³ NM‐MRI and a 0.5 × 0.5 × 1.0 mm³ multi‐echo gradient‐recalled echo imaging for SMwI. Both NM‐MRI and SMwI templates were created by using image data from the 96 healthy subjects. Permutation‐based nonparametric tests were conducted to investigate spatial differences between the two groups in NM‐MRI, and the results were displayed on both NM‐MRI and SMwI templates. The posterolateral and anteromedial regions of the SNpc in NM‐MRI were significantly different between the two groups, corresponding to the nigrosome 1 and nigrosome 2 regions, respectively, on the SMwI template. There were the areas of significant spatial difference in the hypointense SN on SMwI between early‐stage IPD patients and healthy subjects. These areas on SMwI were slightly greater than those on NM‐MRI, including the areas showing group difference on NM‐MRI. Our voxelwise analysis of NM‐MRI suggests that two regions (nigrosome 1 and nigrosome 2) of the SNpc are separately affected in early‐stage IPD.

A novel diagnostic marker for progressive supranuclear palsy targeting atrophy of the subthalamic nucleus

INTRODUCTION

Despite great progress in radiological diagnostic tools for neurodegenerative disorders, their diagnostic accuracy has been unsatisfactory. One of the pathological hallmarks of progressive supranuclear palsy (PSP) is atrophy of the subthalamic nucleus, which has not attracted much attention for imaging analysis.

METHODS

The clinical data of patients with PSP, multiple system atrophy (MSA), Parkinson's disease (PD), and corticobasal syndrome (CBS) who underwent brain magnetic resonance imaging at our department between June 2019 and March 2020 were retrospectively reviewed. The volumes of the subthalamic nucleus and of the whole cerebrum were then analyzed and compared among the disorders.

RESULTS

Fourteen PSP-Richardson syndrome (RS), 14 MSA, 14 PD, and 8 CBS patients were assessed. The mean volume of the bilateral subthalamic nuclei was smaller in PSP patients (0.148 ± 0.012 cm³) than in MSA (0.183 ± 0.026 cm³; p < 0.001), PD (0.209 ± 0.031 cm³; p < 0.001), and CBS (0.180 ± 0.056 cm³; p < 0.001) patients. The volume of the whole cerebrum was not significantly different among the disorders. Using an STN volume cut-off of 0.01925, the sensitivity and specificity for differential diagnosis between PSP and the other disorders were 0.846 and 0.972, respectively.

CONCLUSION

Subthalamic nucleus volume may be a useful diagnostic marker for PSP; it may easily differentiate it from other neurodegenerative parkinsonian disorders.

Imaging iron and neuromelanin simultaneously using a single 3D gradient echo magnetization transfer sequence: Combining neuromelanin, iron and the nigrosome-1 sign as complementary imaging biomarkers in early stage Parkinson's disease

Diagnosing early stage Parkinson's disease (PD) is still a clinical challenge. Previous studies using iron, neuromelanin (NM) or the Nigrosome-1 (N1) sign in the substantia nigra (SN) by themselves have been unable to provide sufficiently high diagnostic performance for these methods to be adopted clinically. Our goal in this study was to extract the NM complex volume, iron content and volume representing the entire SN, and the N1 sign as potential complementary imaging biomarkers using a single 3D magnetization transfer contrast (MTC) gradient echo sequence and to evaluate their diagnostic performance and clinical correlations in early stage PD. A total of 40 early stage idiopathic PD subjects and 40 age- and sex-matched healthy controls (HCs) were imaged at 3T. NM boundaries (representing the SN pars compacta (SNpc) and parabrachial pigmented nucleus) and iron boundaries representing the total SN (SNpc and SN pars reticulata) were determined semi-automatically using a dynamic programming (DP) boundary detection algorithm. Receiver operating characteristic analyses were performed to evaluate the utility of these imaging biomarkers in diagnosing early stage PD. A correlation analysis was used to study the relationship between these imaging measures and the clinical scales. We also introduced the concept of NM and total iron overlap volumes to demonstrate the loss of NM relative to the iron containing SN. Furthermore, all 80 cases were evaluated for the N1 sign independently. The NM and SN volumes were lower while the iron content was higher in the SN for PD subjects compared to HCs. Interestingly, the PD subjects with bilateral loss of the N1 sign had the highest iron content. The area under the curve (AUC) values for the average of both hemispheres for single measures were: .960 for NM complex volume; .788 for total SN volume; .740 for SN iron content and .891 for the N1 sign. Combining NM complex volume with each of the following measures through binary logistic regression led to AUC values for the averaged right and left sides of: .976 for total iron content; .969 for total SN volume, .965 for overlap volume and .983 for the N1 sign. We found a negative correlation between SN volume and UPDRS-III (R² = .22, p = .002). While the N1 sign performed well, it does not contain any information about iron content or NM quantitatively, therefore, marrying this sign with the NM and iron measures provides a better physiological explanation of what is happening when the N1 sign disappears in PD subjects. In summary, the combination of NM complex volume, SN volume, iron content and the N1 sign as derived from a single MTC sequence provides complementary information for understanding and diagnosing early stage PD.

Diagnostic performance of neuromelanin-sensitive magnetic resonance imaging for patients with Parkinson's disease and factor analysis for its heterogeneity: a systematic review and meta-analysis

OBJECTIVE

To determine the diagnostic performance of neuromelanin-sensitive magnetic resonance imaging discriminating between patients with Parkinson's disease and normal healthy controls and to identify factors causing heterogeneity influencing the diagnostic performance.

METHODS

A systematic literature search in the Ovid-MEDLINE and EMBASE databases was performed for studies reporting the relevant topic before February 17, 2020. The pooled sensitivity and specificity values with their 95% confidence intervals were calculated using bivariate random-effects modeling. Subgroup and meta-regression analyses were also performed to determine factors influencing heterogeneity.

RESULTS

Twelve articles including 403 patients with Parkinson's disease and 298 control participants were included in this systematic review and meta-analysis. Neuromelanin-sensitive magnetic resonance imaging showed a pooled sensitivity of 89% (95% confidence interval, 86-92%) and a pooled specificity of 83% (95% confidence interval, 76-88%). In the subgroup and meta-regression analysis, a disease duration longer than 5 and 10 years, comparisons using measured volumes instead of signal intensities, a slice thickness in terms of magnetic resonance imaging parameters of more than 2 mm, and semi-/automated segmentation methods instead of manual segmentation improved the diagnostic performance.

CONCLUSION

Neuromelanin-sensitive magnetic resonance imaging had a favorable diagnostic performance in discriminating patients with Parkinson's disease from healthy controls. To improve diagnostic accuracy, further investigations directly comparing these heterogeneity-affecting factors and optimizing these parameters are necessary.

KEY POINTS

• Neuromelanin-sensitive MRI favorably discriminates patients with Parkinson's disease from healthy controls. • Disease duration, parameters used for comparison, magnetic resonance imaging slice thickness, and segmentation methods affected heterogeneity across the studies.

Spatiotemporal changes in substantia nigra neuromelanin content in Parkinson’s disease

This study aimed to investigate the spatiotemporal changes in neuromelanin-sensitive MRI signal in the substantia nigra and their relation to clinical scores of disease severity in patients with early or progressing Parkinson’s disease and patients with idiopathic rapid eye movement sleep behaviour disorder (iRBD) exempt of Parkinsonian signs compared to healthy control subjects. Longitudinal T1-weighted anatomical and neuromelanin-sensitive MRI was performed in two cohorts, including patients with iRBD, patients with early or progressing Parkinson’s disease, and control subjects. Based on the aligned substantia nigra segmentations using a study-specific brain anatomical template, parametric maps of the probability of a voxel belonging to the substantia nigra were calculated for patients with various degrees of disease severity and controls. For each voxel in the substantia nigra, probability map of controls, correlations between signal-to-noise ratios on neuromelanin-sensitive MRI in patients with iRBD and Parkinson’s disease and clinical scores of motor disability, cognition and mood/behaviour were calculated. Our results showed that in patients, compared to the healthy control subjects, the volume of the substantia nigra was progressively reduced for increasing disease severity. The neuromelanin signal changes appeared to start in the posterolateral motor areas of the substantia nigra and then progressed to more medial areas of this region. The ratio between the volume of the substantia nigra in patients with Parkinson’s disease relative to the controls was best fitted by a mono-exponential decay. Based on this model, the pre-symptomatic phase of the disease started at 5.3 years before disease diagnosis, and 23.1% of the substantia nigra volume was lost at the time of diagnosis, which was in line with previous findings using post-mortem histology of the human substantia nigra and radiotracer studies of the human striatum. Voxel-wise patterns of correlation between neuromelanin-sensitive MRI signal-to-noise ratio and motor, cognitive and mood/behavioural clinical scores were localized in distinct regions of the substantia nigra. This localization reflected the functional organization of the nigrostriatal system observed in histological and electrophysiological studies in non-human primates (motor, cognitive and mood/behavioural domains). In conclusion, neuromelanin-sensitive MRI enabled us to assess voxel-wise modifications of substantia nigra’s morphology in vivo in humans, including healthy controls, patients with iRBD and patients with Parkinson’s disease, and identify their correlation with nigral function across all motor, cognitive and behavioural domains. This insight could help assess disease progression in drug trials of disease modification.

Short-echo-time magnitude image derived from quantitative susceptibility mapping could resemble neuromelanin-sensitive MRI image in substantia nigra

Background

In this study, we explored whether the proposed short-echo-time magnitude (setMag) image derived from quantitative susceptibility mapping (QSM) could resemble NM-MRI image in substantia nigra (SN), by quantitatively comparing the spatial similarity and diagnosis performances for Parkinson’s disease (PD).

Methods

QSM and NM-MRI were performed in 18 PD patients and 15 healthy controls (HCs). The setMag images were calculated using the short-echo-time magnitude images. Bilateral hyperintensity areas of SN (SN_hyper) were manually segmented on setMag and NM-MRI images by two raters in a blinded manner. The inter-rater reliability was evaluated by the intraclass correlation coefficients (ICC) and the Dice similarity coefficient (DSC). Then the inter-modality (i.e. setMag and NM-MRI) spatial similarity was quantitatively assessed using DSC and volume of the consensual voxels identified by both of two raters. The performances of mean SN_hyper volume for PD diagnosis on setMag and NM-MRI images were evaluated using receiver operating characteristic (ROC) analysis.

Results

The SN_hyper segmented by two raters showed substantial to excellent inter-rater reliability for both setMag and NM-MRI images. The DSCs of SN_hyper between setMag and NM-MRI images showed substantial to excellent voxel-wise overlap in HCs (0.80 ~ 0.83) and PD (0.73 ~ 0.76), and no significant difference was found between the SN_hyper volumes of setMag and NM-MRI images in either HCs or PD (p > 0.05). The mean SN_hyper volume was significantly decreased in PD patients in comparison with HCs on both setMag images (77.61 mm³ vs 95.99 mm³, p < 0.0001) and NM-MRI images (79.06 mm³ vs 96.00 mm³, p < 0.0001). Areas under the curve (AUCs) of mean SN_hyper volume for PD diagnosis were 0.904 on setMag and 0.906 on NM-MRI images. No significant difference was found between the two curves (p = 0.96).

Conclusions

SN_hyper on setMag derived from QSM demonstrated substantial spatial overlap with that on NM-MRI and provided comparable PD diagnostic performance, providing a new QSM-based multi-contrast imaging strategy for future PD studies.

MRI biomarkers of motor and non-motor symptoms in Parkinson's disease

Parkinson's disease is a heterogeneous disorder with both motor and non-motor symptoms that contribute to functional impairment. To develop effective, disease modifying treatments for these symptoms, biomarkers are necessary to detect neuropathological changes early in the disease course and monitor changes over time. Advances in MRI scan sequences and analytical techniques present numerous promising metrics to detect changes within the nigrostriatal system, implicated in the cardinal motor symptoms of the disease, and detect broader dysfunction involved in the non-motor symptoms, such as cognitive impairment. There is emerging evidence that iron sensitive, neuromelanin sensitive, diffusion sensitive, and resting state functional magnetic imaging measures can capture changes within the nigrostriatal system. Iron, neuromelanin, and diffusion sensitive measures demonstrate high specificity and sensitivity in distinguishing Parkinson's disease relative to controls, with inconsistent results differentiating Parkinson's disease relative to atypical parkinsonian disorders. They may also serve as useful monitoring biomarkers, with each possibly detecting different aspects of the disease course (early nigrosome changes versus broader substantia nigra changes). Investigations of non-motor symptoms, such as cognitive impairment, require careful consideration of the nature of cognitive deficits to characterize regional and network specific impairment. While the early, executive dysfunction observed is consistent with nigrostriatal degeneration, the memory and visuospatial impairments, the harbingers of a dementia process reflect dopaminergic independent dysfunction involving broader regions of the brain.

[Method for Quantitative Evaluation of the Substantia Nigra Using Phase-sensitive Inversion Recovery in 1.5 T Magnetic Resonance Imaging]

PURPOSE

Parkinson's disease is a neurodegenerative disease with movement disorders caused by degeneration of the substantia nigra (SN) in the midbrain. Magnetic resonance imaging (MRI) is used to exclude similar diseases. Recently, neuro-melanin imaging (NMI) has been proposed as an imaging method for evaluating the SN. However, the evaluation of the image using this is qualitative, and normal SN cannot be visualized at 1.5 T. This study aimed to investigate whether the SN can be quantitatively evaluated by using phase-sensitive inversion recovery (PSIR) at 1.5 T.

METHOD

The phantom was imaged by PSIR and the accuracy of T₁ value was verified. Next, the healthy volunteers were imaged by PSIR, and the T₁ value and area of the SN were measured.

RESULT

As a result of the phantom study, the difference of the T₁value between PSIR and inversion recovery spin-echo in the range of the T₁ value the SN and the cerebral peduncle (500 to 1000 ms) was lesser than ±10%. The difference between the average of T₁ values of the SN measured by PSIR and the previously reported T₁ values of the SN was about 1.1%. Furthermore, the average of the area of the SN measured by PSIR was measured independently of imaging parameters by using the T₁ value as a reference.

CONCLUSION

These results indicate the possibility of a quantitative evaluation of the SN by measuring its area and T₁ value by using PSIR at 1.5 T.

Semi-Automatic Signature-Based Segmentation Method for Quantification of Neuromelanin in Substantia Nigra

In Parkinson's disease (PD), there is a reduction of neuromelanin (NM) in the substantia nigra (SN). Manual quantification of the NM volume in the SN is unpractical and time-consuming; therefore, we aimed to quantify NM in the SN with a novel semi-automatic segmentation method. Twenty patients with PD and twelve healthy subjects (HC) were included in this study. T1-weighted spectral pre-saturation with inversion recovery (SPIR) images were acquired on a 3T scanner. Manual and semi-automatic atlas-free local statistics signature-based segmentations measured the surface and volume of SN, respectively. Midbrain volume (MV) was calculated to normalize the data. Receiver operating characteristic (ROC) analysis was performed to determine the sensitivity and specificity of both methods. PD patients had significantly lower SN mean surface (37.7 ± 8.0 vs. 56.9 ± 6.6 mm²) and volume (235.1 ± 45.4 vs. 382.9 ± 100.5 mm³) than HC. After normalization with MV, the difference remained significant. For surface, sensitivity and specificity were 91.7 and 95 percent, respectively. For volume, sensitivity and specificity were 91.7 and 90 percent, respectively. Manual and semi-automatic segmentation methods of the SN reliably distinguished between PD patients and HC. ROC analysis shows the high sensitivity and specificity of both methods.

Neuromelanin or DaT-SPECT: which is the better marker for discriminating advanced Parkinson's disease?

Background and purpose

Whether the neuromelanin‐positive substantia nigra pars compacta area (NM‐SNc) on neuromelanin magnetic resonance imaging (NM‐MRI) and the specific binding ratio (SBR) on ¹²³I‐N‐v‐fluoropropyl‐2b‐carbomethoxy3b‐(4‐iodophenyl)nortropane single photon emission computed tomography (DaT‐SPECT) can be correlated with motor fluctuations (MFs) in advanced Parkinson's disease (PD) was investigated.

Methods

Thirty‐five PD patients (60 ± 13 years) and 23 healthy individuals as controls (59 ± 19 years) were enrolled. The relationships between NM‐MRI and DaT‐SPECT were prospectively examined in two subgroups divided according to the presence or absence of MFs. Multivariate analysis was performed using the Cox proportional hazard model to screen for association factors.

Results

The NM‐SNc size was correlated with the SBR (Spearman's ρ = 0.43, P < 0.05). The NM‐SNc size was significantly reduced in PD with MFs compared with the subgroup without (P < 0.001), whereas the SBR did not significantly differ between the groups. NM‐SNc size was a significant association factor for MFs (hazard ratio 0.94, P = 0.04). In receiver operating characteristic analysis of the factors for MF occurrence, the area under the receiver operating characteristic curve of the NM‐SNc size showed a significant difference of 0.89 (P < 0.05) but no significant difference was found in the SBR.

Conclusions

NM‐SNc size was significantly correlated with the SBR in PD, but several factors in advanced PD were more closely associated with NM‐SNc size than the SBR. NM‐MRI might reflect the status of advanced PD more accurately than DaT‐SPECT. Therefore, NM‐MRI appears to provide a better marker for discriminating advanced PD than DaT‐SPECT.