Imaging the Nigrosome 1 in the substantia nigra using susceptibility weighted imaging and quantitative susceptibility mapping: An application to Parkinson's disease

Iron and neuromelanin imaging in basal ganglia circuitry in Parkinson's disease with freezing of gait

OBJECTIVE

This study aimed to examine the structural alterations of the deep gray matter (DGM) in the basal ganglia circuitry of Parkinson's disease (PD) patients with freezing of gait (FOG) using quantitative susceptibility mapping (QSM) and neuromelanin-sensitive magnetic resonance imaging (NM-MRI).

METHODS

Twenty-five (25) PD patients with FOG (PD-FOG), 22 PD patients without FOG (PD-nFOG), and 30 age- and sex-matched healthy controls (HCs) underwent 3-dimensional multi-echo gradient recalled echo and NM-MRI scanning. The mean volume and susceptibility of the DGM on QSM data and the relative contrast (NMRC-SNpc) and volume (NMvolume-SNpc) of the substantia nigra pars compacta on NM-MRI were analyzed among groups. A multiple linear regression analysis was performed to explore the associations of FOG severity with MRI measurements and disease stage.

RESULTS

The PD-FOG group showed higher susceptibility in the bilateral caudal substantia nigra (SN) compared to the HC group. Both the PD-FOG and PD-nFOG groups showed lower volumes than the HC group in the bilateral caudate and putamen as determined from the QSM data. The NMvolume-SNpc on NM-MRI in the PD-FOG group was significantly lower than in the HC and PD-nFOG groups. Both the PD-FOG and PD-nFOG groups showed significantly decreased NMRC-SNpc.

CONCLUSIONS

The PD-FOG patients showed abnormal neostriatum atrophy, increases in iron deposition in the SN, and lower NMvolume-SNpc. The structural alterations of the DGM in the basal ganglia circuits could lead to the abnormal output of the basal ganglia circuit to trigger the FOG in PD patients.

Automatic Segmentation and Quantification of Nigrosome-1 Neuromelanin and Iron in MRI: A Candidate Biomarker for Parkinson's Disease

BACKGROUND

There is a lack of automated tools for the segmentation and quantification of neuromelanin (NM) and iron in the nigrosome-1 (N1). Existing tools evaluate the N1 sign, i.e., the presence or absence of the "swallow-tail" in iron-sensitive MRI, or globally analyze the MRI signal in an area containing the N1, without providing a volumetric delineation.

PURPOSE

Present an automated method to segment the N1 and quantify differences in N1's NM and iron content between Parkinson's disease (PD) patients and healthy controls (HCs). Study whether N1 degeneration is clinically related to PD and could be used as a biomarker of the disease.

STUDY TYPE

Prospective.

SUBJECTS

Seventy-one PD (65.3 ± 10.3 years old, 34 female/37 male); 30 HC (62.7 ± 7.8 years old, 17 female/13 male).

FIELD STRENGTH/SEQUENCE

3 T Anatomical T1-weighted MPRAGE, NM-MRI T1-weighted gradient with magnetization transfer, susceptibility-weighted imaging (SWI).

ASSESSMENT

N1 was automatically segmented in SWI images using a multi-image atlas, populated with healthy N1 structures manually annotated by a neurologist. Relative NM and iron content were quantified and their diagnostic performance assessed and compared with the substantia nigra pars compacta (SNc). The association between image parameters and clinically relevant variables was studied.

STATISTICAL TESTS

Nonparametric tests were used (Mann-Whitney's U, chi-square, and Friedman tests) at P = 0.05.

RESULTS

N1's relative NM content decreased and relative iron content increased in PD patients compared with HCs (NM-CRHC = 22.55 ± 1.49; NM-CRPD = 19.79 ± 1.92; NM-nVolHC = 2.69 × 10-5 ± 1.02 × 10-5; NM-nVolPD = 1.18 × 10-5 ± 0.96 × 10-5; Iron-CRHC = 10.51 ± 2.64; Iron-CRPD = 19.35 ± 7.88; Iron-nVolHC = 0.72 × 10-5 ± 0.81 × 10-5; Iron-nVolPD = 2.82 × 10-5 ± 2.04 × 10-5). Binary logistic regression analyses combining N1 and SNc image parameters yielded a top AUC = 0.955. Significant correlation was found between most N1 parameters and both disease duration (ρNM-CR = -0.31; ρiron-CR = 0.43; ρiron-nVol = 0.46) and the motor status (ρNM-nVol = -0.27; ρiron-CR = 0.33; ρiron-nVol = 0.28), suggesting NM reduction along with iron accumulation in N1 as the disease progresses.

DATA CONCLUSION

This method provides a fully automatic N1 segmentation, and the analyses performed reveal that N1 relative NM and iron quantification improves diagnostic performance and suggest a relative NM reduction along with a relative iron accumulation in N1 as the disease progresses.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.

Distinguishing essential tremor from Parkinson's disease: clinical and experimental tools

INTRODUCTION

Essential tremor (ET) and Parkinson's disease (PD) are the most common causes of tremor and the most prevalent movement disorders, with overlapping clinical features that can lead to diagnostic challenges, especially in the early stages.

AREAS COVERED

In the present paper, the authors review the clinical and experimental studies and emphasized the major aspects to differentiate between ET and PD, with particular attention to cardinal phenomenological features of these two conditions. Ancillary and experimental techniques, including neurophysiology, neuroimaging, fluid biomarker evaluation, and innovative methods, are also discussed for their role in differential diagnosis between ET and PD. Special attention is given to investigations and tools applicable in the early stages of the diseases, when the differential diagnosis between the two conditions is more challenging. Furthermore, the authors discuss knowledge gaps and unsolved issues in the field.

EXPERT OPINION

Distinguishing ET and PD is crucial for prognostic purposes and appropriate treatment. Additionally, accurate diagnosis is critical for optimizing clinical and experimental research on pathophysiology and innovative therapies. In a few years, integrated technologies could enable accurate, reliable diagnosis from early disease stages or prodromal stages in at-risk populations, but further research combining different techniques is needed.

Parkinson's image detection and classification based on deep learning

OBJECTIVE

There are two major issues in the MRI image diagnosis task for Parkinson's disease. Firstly, there are slight differences in MRI images between healthy individuals and Parkinson's patients, and the medical field has not yet established precise lesion localization standards, which poses a huge challenge for the effective prediction of Parkinson's disease through MRI images. Secondly, the early diagnosis of Parkinson's disease traditionally relies on the subjective judgment of doctors, which leads to insufficient accuracy and consistency. This article proposes an improved YOLOv5 detection algorithm based on deep learning for predicting and classifying Parkinson's images.

METHODS

This article improves the YOLOv5s network as the basic framework. Firstly, the CA attention mechanism was introduced to enable the model to dynamically adjust attention based on local features of the image, significantly enhancing the sensitivity of the model to PD related small pathological features; Secondly, replace the dynamic full dimensional convolution module to optimize the multi-level extraction of image features; Finally, the coupling head strategy is adopted to improve the execution efficiency of classification and localization tasks separately.

RESULTS

We validated the effectiveness of the proposed method using a dataset of 582 MRI images from 108 patients. The results show that the proposed method achieves 0.961, 0.974, and 0.986 in Precision, Recall, and mAP, respectively, and the experimental results are superior to other algorithms.

CONSLUSION

The improved model has achieved high accuracy and detection accuracy, and can accurately detect and recognize complex Parkinson's MRI images.

SIGNIFICANCE

This algorithm has shown good performance in the early diagnosis of Parkinson's disease and can provide clinical assistance for doctors in early diagnosis. It compensates for the limitations of traditional methods.

Loss of the "swallow tail sign" on susceptibility-weighted imaging in the diagnosis of dementia with Lewy bodies: a systematic review and meta-analysis

INTRODUCTION

Loss of dorsolateral nigral hyperintensity (DNH) on iron-sensitive brain MRI is useful for Parkinson's disease detection. DNH loss could also be of diagnostic value in dementia with Lewy bodies (DLB), an a-synuclein-related pathology. We aim to quantitatively synthesize evidence, investigating the role of MRI, a first-line imaging modality, in early DLB detection and differentiation from other dementias.

METHODS

Our study was conducted according to the PRISMA statement. MEDLINE, Scopus, Web of Science, and Cochrane Library were searched using the terms like "dementia with Lewy bodies", "dorsolateral nigral hyperintensity", and "MRI". Only English-written peer-reviewed diagnostic accuracy studies were included. We used QUADAS-2 for quality assessment.

RESULTS

Our search yielded 363 search results. Three studies were eligible, all with satisfying, high quality. The total population of 227 patients included 63 with DLB and 164 with other diseases (Alzheimer disease, frontotemporal dementia, mild cognitive impairment). Using a univariate random-effects logistic regression model, our meta-analysis resulted in pooled sensitivity, specificity and DOR of 0.82 [0.62; 0.92], 0.79 [0.70; 0.86] and 16.26 ([3.3276; 79.4702], p = 0.0006), respectively, for scans with mixed field strength (1.5 and 3 T). Subgroup analysis of 3 T scans showed pooled sensitivity, specificity and DOR of 0.82 [0.61; 0.93], 0.82 [0.72; 0.89] and 18.36 ([4.24; 79.46], p < 0.0001), respectively.

DISCUSSION

DNH loss on iron-sensitive MRI might comprise a supportive biomarker for DLB detection, that could augment the value of the DLB diagnostic criteria. Further evaluation using standardized protocols is needed, as well as direct comparison to other supportive and indicative biomarkers.

Increased mean diffusivity of the caudal motor SNc identifies patients with REM sleep behaviour disorder and Parkinson's disease

Idiopathic rapid eye movement sleep behaviour disorder (iRBD)-a Parkinson's disease (PD) prodrome-might exhibit neural changes similar to those in PD. Substantia nigra pars compacta (SNc) degeneration underlies motor symptoms of PD. In iRBD and early PD (ePD), we measured diffusion MRI (dMRI) in the caudal motor SNc, which overlaps the nigrosome-1-the earliest-degenerating dopaminergic neurons in PD-and in the striatum. Nineteen iRBD, 26 ePD (1.7 ± 0.03 years), and 46 age-matched healthy controls (HCs) were scanned at Western University, and 47 iRBD, 115 ePD (0.9 ± 0.01 years), and 56 HCs were scanned through the Parkinson's Progression Markers Initiative, using 3T MRI. We segmented the SNc and striatum into subregions using automated probabilistic tractography to the cortex. We measured mean diffusivity (MD) and fractional anisotropy (FA) along white-matter bundles and subregional surfaces. We performed group-level and classification analyses. Increased caudal motor SNc surface MD was the only iRBD-HCs and ePD-HCs difference replicating across datasets (padj < 0.05). No iRBD-ePD differences emerged. Caudal motor SNc surface MD classified patient groups from HCs at the single-subject level with good-to-excellent balanced accuracy in an independent sample (0.91 iRBD and 0.86 iRBD and ePD combined), compared to fair performance for total SNc surface MD (0.72 iRBD and ePD). Caudal motor SNc surface MD correlated significantly with MDS-UPDRS-III scores in ePD patients. Using dMRI and automated segmentation, we detected changes suggesting altered microstructural integrity in iRBD and ePD in the nigrostriatal subregion known to degenerate first in PD. Surface MD of the caudal motor SNc presents a potential measure for inclusion in neuroimaging biomarkers of iRBD and PD.

Simultaneous time-of-flight MR angiography and quantitative susceptibility mapping with key time-of-flight features

A technique for combined time-of-flight (TOF) MR angiography (MRA) and quantitative susceptibility mapping (QSM) was developed with key features of standard three-dimensional (3D) TOF acquisitions, including multiple overlapping thin slab acquisition (MOTSA), ramped RF excitation, and venous saturation. The developed triple-echo 3D TOF-QSM sequence enabled TOF-MRA, susceptibility-weighted imaging (SWI), QSM, and R2* mapping. The effects of ramped RF, resolution, flip angle, venous saturation, and MOTSA were studied on QSM. Six volunteers were scanned at 3 T with the developed sequence, conventional TOF-MRA, and conventional SWI. Quantitative comparison of susceptibility values on QSM and normalized arterial and venous vessel-to-background contrasts on TOF and SWI were performed. The ramped RF excitation created an inherent phase variation in the raw phase. A generic correction factor was computed to remove the phase variation to obtain QSM without artifacts from the TOF-QSM sequence. No statistically significant difference was observed between the developed and standard QSM sequence for susceptibility values. However, maintaining standard TOF features led to compromises in signal-to-noise ratio for QSM and SWI, arising from the use of MOTSA rather than one large 3D slab, higher TOF spatial resolution, increased TOF background suppression due to larger flip angles, and reduced venous signal from venous saturation. In terms of vessel contrast, veins showed higher normalized contrast on SWI derived from TOF-QSM than the standard SWI sequence. While fast flowing arteries had reduced contrast compared with standard TOF-MRA, no statistical difference was observed for slow flowing arteries. Arterial contrast differences largely arise from the longer TR used in TOF-QSM over standard TOF-MRA to accommodate additional later echoes for SWI. In conclusion, although the sequence has a longer TR and slightly lower arterial contrast, provided an adequate correction is made for ramped RF excitation effects on phase, QSM may be performed from a multiecho sequence that includes all key TOF features, thus enabling simultaneous TOF-MRA, SWI, QSM, and R2* map computation.

Neuroimaging of Parkinson's disease by quantitative susceptibility mapping

Parkinson's disease (PD) is a common neurodegenerative disease, and apart from a few rare genetic causes, its pathogenesis remains largely unclear. Recent scientific interest has been captured by the involvement of iron biochemistry and the disruption of iron homeostasis, particularly within the brain regions specifically affected in PD. The advent of Quantitative Susceptibility Mapping (QSM) has enabled non-invasive quantification of brain iron in vivo by MRI, which has contributed to the understanding of iron-associated pathogenesis and has the potential for the development of iron-based biomarkers in PD. This review elucidates the biochemical underpinnings of brain iron accumulation, details advancements in iron-sensitive MRI technologies, and discusses the role of QSM as a biomarker of iron deposition in PD. Despite considerable progress, several challenges impede its clinical application after a decade of QSM studies. The initiation of multi-site research is warranted for developing robust, interpretable, and disease-specific biomarkers for monitoring PD disease progression.

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.

How should we be using biomarkers in trials of disease modification in Parkinson's disease?

The recent validation of the α-synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson's disease has formed the backbone for a proposed staging system for incorporation in Parkinson's disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson's disease patients into trials (as distinct from patients with non-Parkinson's disease parkinsonism or non-Parkinson's disease tremors). There remain, however, further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson's disease, namely: optimizing the distinction between different α-synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; a sensitive means of confirming target engagement; and the early prediction of longer-term clinical benefit. For example, levels of CSF proteins such as the lysosomal enzyme β-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer's disease-like pathology (detectable through CSF levels of amyloid-β42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline in Parkinson's disease even in its later stages. The exploitation of additional biomarkers to the α-synuclein seed amplification assay will, therefore, greatly add to our ability to plan trials and assess the disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson's disease. However, correlation with clinical progression does not necessarily equate to causation, and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson's disease.

Simple quantitative planimetric measurement of nigrosome-1 for clinical settings

INTRODUCTION

Loss of MRI hyperintense signal in nigrosome-1 (assessed with susceptibility-weighted imaging) is a biomarker for Parkinson's disease (PD). Current clinical practice involves subjectively rating the appearance of nigrosome-1 which is challenging. The study aimed to test and compare a simple method for quantifying nigrosome-1 with the current subjective rating method.

METHODS

Two experienced neuroradiologists measured area of hyperintense signal in nigrosome-1 (quantitative method) and rated nigrosome-1 appearance (as normal, attenuated, or absent; subjective method) in 42 patients encompassing the full spectrum of nigrosome-1 integrity (21 patients aged 55.5 ± 20.9 years with Essential tremor (ET) and a subset of 21 patients aged 69.6 ± 8.6 years with PD). Neuroradiologists were blinded to each other's measurements, clinical notes, and patient group.

RESULTS

Both methods yielded a significant difference between the groups (PD vs ET; p < 0.001). Pooled (across sides) area of nigrosome-1 hyperintense signal was significantly smaller in the PD group (median = 2.1 mm2, range = 0-15.8 mm2) than ET group (median = 8.3 mm2, range = 0-15.7 mm2; p < 0.001). Inter-rater reliability was high to very high for both methods (subjective: weighted kappa = 0.640, p < 0.001; quantitative: W = 0.733, p = 0.004). Our primary hypothesis that area of nigrosome-1 hyperintense signal exhibits higher inter-rater reliability than subjective rating of nigrosome-1 appearance was not supported.

CONCLUSION

The simple quantitative method, used with subjectively rated nigrosome-1 appearance, may improve confidence in longitudinal clinical reporting, when nigrosome-1 is attenuated. However, further work on the incremental diagnostic value of planimetry and bias, repeatability and reproducibility are needed before it can be recommended in clinical practice.

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.

Diagnosing Parkinson's disease by combining neuromelanin and iron imaging features using an automated midbrain template approach

BACKGROUND AND PURPOSE

Early diagnosis of Parkinson's disease (PD) is still a clinical challenge. Most previous studies using manual or semi-automated methods for segmenting the substantia nigra (SN) are time-consuming and, despite raters being well-trained, individual variation can be significant. In this study, we used a template-based, automatic, SN subregion segmentation pipeline to detect the neuromelanin (NM) and iron features in the SN and SN pars compacta (SNpc) derived from a single 3D magnetization transfer contrast (MTC) gradient echo (GRE) sequence in an attempt to develop a comprehensive imaging biomarker that could be used to diagnose PD.

MATERIALS AND METHODS

A total of 100 PD patients and 100 age- and sex-matched healthy controls (HCs) were imaged on a 3T scanner. NM-based SN (SN_NM) boundaries and iron-based SN (SN_QSM) boundaries and their overlap region (representing the SNpc) were delineated automatically using a template-based SN subregion segmentation approach based on quantitative susceptibility mapping (QSM) and NM images derived from the same MTC-GRE sequence. All PD and HC subjects were evaluated for the nigrosome-1 (N1) sign by two raters independently. Receiver Operating Characteristic (ROC) analyses were performed to evaluate the utility of SN_NM volume, SN_QSM volume, SNpc volume and iron content with a variety of thresholds as well as the N1 sign in diagnosing PD. Correlation analyses were performed to study the relationship between these imaging measures and the clinical scales in PD.

RESULTS

In this study, we verified the value of the fully automatic template based midbrain deep gray matter mapping approach in differentiating PD patients from HCs. The automatic segmentation of the SN in PD patients led to satisfactory DICE similarity coefficients and volume ratio (VR) values of 0.81 and 1.17 for the SN_NM, and 0.87 and 1.05 for the SN_QSM, respectively. For the HC group, the average DICE similarity coefficients and VR values were 0.85 and 0.94 for the SN_NM, and 0.87 and 0.96 for the SN_QSM, respectively. The SN_QSM volume tended to decrease with age for both the PD and HC groups but was more severe for the PD group. For diagnosing PD, the N1 sign performed reasonably well by itself (Area Under the Curve (AUC) = 0.783). However, combining the N1 sign with the other quantitative measures (SN_NM volume, SN_QSM volume, SNpc volume and iron content) resulted in an improved diagnosis of PD with an AUC as high as 0.947 (using an SN threshold of 50ppb and an NM threshold of 0.15). Finally, the SN_QSM volume showed a negative correlation with the MDS-UPDRS III (R² = 0.1, p = 0.036) and the Hoehn and Yahr scale (R² = 0.04, p = 0.013) in PD patients.

CONCLUSION

In summary, this fully automatic template based deep gray matter mapping approach performs well in the segmentation of the SN and its subregions for not only HCs but also PD patients with SN degeneration. The combination of the N1 sign with other quantitative measures (SN_NM volume, SN_QSM volume, SNpc volume and iron content) resulted in an AUC of 0.947 and provided a comprehensive set of imaging biomarkers that, potentially, could be used to diagnose PD clinically.

Application of Neuromelanin MR Imaging in Parkinson Disease

MRI has been used to develop biomarkers for movement disorders such as Parkinson disease (PD) and other neurodegenerative disorders with parkinsonism such as progressive supranuclear palsy and multiple system atrophy. One of these imaging biomarkers is neuromelanin (NM), whose integrity can be assessed from its contrast and volume. NM is found mainly in certain brain stem structures, namely, the substantia nigra pars compacta (SNpc), the ventral tegmental area, and the locus coeruleus. Another major biomarker is brain iron, which often increases in concert with NM degeneration. These biomarkers have the potential to improve diagnostic certainty in differentiating between PD and other neurodegenerative disorders similar to PD, as well as provide a better understanding of pathophysiology. Mapping NM in vivo has clinical importance for gauging the premotor phase of PD when there is a greater than 50% loss of dopaminergic SNpc melanized neurons. As a metal ion chelator, NM can absorb iron. When NM is released from neurons, it deposits iron into the intracellular tissues of the SNpc; the result is iron that can be imaged and measured using quantitative susceptibility mapping. An increase of iron also leads to the disappearance of the nigrosome-1 sign, another neuroimage biomarker for PD. Therefore, mapping NM and iron changes in the SNpc are a practical means for improving early diagnosis of PD and in monitoring disease progression. In this review, we discuss the functions and location of NM, how NM-MRI is performed, the automatic mapping of NM and iron content, how NM-related imaging biomarkers can be used to enhance PD diagnosis and differentiate it from other neurodegenerative disorders, and potential advances in NM imaging methods. With major advances currently evolving for rapid imaging and artificial intelligence, NM-related biomarkers are likely to have increasingly important roles for enhancing diagnostic capabilities in PD. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

In vivo detection of substantia nigra and locus coeruleus volume loss in Parkinson's disease using neuromelanin-sensitive MRI: Replication in two cohorts

Patients with Parkinson's disease undergo a loss of melanized neurons in substantia nigra pars compacta and locus coeruleus. Very few studies have assessed substantia nigra pars compacta and locus coeruleus pathology in Parkinson's disease simultaneously with magnetic resonance imaging (MRI). Neuromelanin-sensitive MRI measures of substantia nigra pars compacta and locus coeruleus volume based on explicit magnetization transfer contrast have been shown to have high scan-rescan reproducibility in controls, but no study has replicated detection of Parkinson's disease-associated volume loss in substantia nigra pars compacta and locus coeruleus in multiple cohorts with the same methodology. Two separate cohorts of Parkinson's disease patients and controls were recruited from the Emory Movement Disorders Clinic and scanned on two different MRI scanners. In cohort 1, imaging data from 19 controls and 22 Parkinson's disease patients were acquired with a Siemens Trio 3 Tesla scanner using a 2D gradient echo sequence with magnetization transfer preparation pulse. Cohort 2 consisted of 33 controls and 39 Parkinson's disease patients who were scanned on a Siemens Prisma 3 Tesla scanner with a similar imaging protocol. Locus coeruleus and substantia nigra pars compacta volumes were segmented in both cohorts. Substantia nigra pars compacta volume (Cohort 1: p = 0.0148; Cohort 2: p = 0.0011) and locus coeruleus volume (Cohort 1: p = 0.0412; Cohort 2: p = 0.0056) were significantly reduced in the Parkinson's disease group as compared to controls in both cohorts. This imaging approach robustly detects Parkinson's disease effects on these structures, indicating that it is a promising marker for neurodegenerative neuromelanin loss.

Magnetic resonance imaging modalities aid in the differential diagnosis of atypical parkinsonian syndromes

Accurate and timely diagnosis of atypical parkinsonian syndromes (APS) remains a challenge. Especially early in the disease course, the clinical manifestations of the APS overlap with each other and with those of idiopathic Parkinson's disease (PD). Recent advances in magnetic resonance imaging (MRI) technology have introduced promising imaging modalities to aid in the diagnosis of APS. Some of these MRI modalities are also included in the updated diagnostic criteria of APS. Importantly, MRI is safe for repeated use and more affordable and accessible compared to nuclear imaging. These advantages make MRI tools more appealing for diagnostic purposes. As the MRI field continues to advance, the diagnostic use of these techniques in APS, alone or in combination, are expected to become commonplace in clinical practice.

Magnetic Resonance Imaging Studies of Neurodegenerative Disease: From Methods to Translational Research

Neurodegenerative diseases (NDs) have become a significant threat to an aging human society. Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomarkers. Magnetic resonance imaging (MRI) is a powerful tool for investigating structural and functional brain alterations in NDs. With the advantages of being non-invasive and non-radioactive, it has been frequently used in both animal research and large-scale clinical investigations. MRI may serve as a bridge connecting micro- and macro-level analysis and promoting bench-to-bed translational research. Nevertheless, due to the abundance and complexity of MRI techniques, exploiting their potential is not always straightforward. This review aims to briefly introduce research progress in clinical imaging studies and discuss possible strategies for applying MRI in translational ND research.

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.

Nigrosome and Neuromelanin Imaging as Tools to Differentiate Parkinson's Disease and Parkinsonism

Parkinson's disease (PD) lacks a definitive diagnosis due to a lack of pathological validation of patients at antemortem. The risk of misdiagnosis is high in the early stages of PD, often eluded by atypical parkinsonian symptoms. Neuroimaging and laboratory biomarkers are being sought to aid in the clinical diagnosis of PD. Nigrosome imaging and neuromelanin (NM)-sensitive magnetic resonance imaging (MRI) are the new emerging tools, both technically simple plus cost-effective for studying nigral pathology, and have shown potential for authenticating the clinical diagnosis of PD. Visual assessment of the nigrosome-1 appearance, at 3 or 7 Tesla, yields excellent diagnostic accuracy for differentiating idiopathic PD from healthy controls. Moreover, midbrain atrophy and putaminal hypointensity in nigrosome-1 imaging are valid pointers in distinguishing PD from allied parkinsonian disorders. The majority of studies employed T2 and susceptibility-weighted imaging MRI sequences to visualize nigrosome abnormalities, whereas T1-weighted fast-spin echo sequences were used for NM imaging. The diagnostic performance of NM-sensitive MRI in discriminating PD from normal HC can be improved further. Longitudinal studies with adequate sampling of varied uncertain PD cases should be designed to accurately evaluate the sensitivity and diagnostic potential of nigrosome and NM imaging techniques. Equal weightage is to be given to uniformity and standardization of protocols, data analysis, and interpretation of results. There is tremendous scope for identifying disease-specific structural changes in varied forms of parkinsonism with these low-cost imaging tools. Nigrosome-1 and midbrain NM imaging may not only provide an accurate diagnosis of PD but could mature into tools for personally tailored treatment and prognosis.

Evaluation of iron overload in nigrosome 1 via quantitative susceptibility mapping as a progression biomarker in prodromal stages of synucleinopathies

Idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies, such as Parkinson's disease (PD), which are characterized by the loss of dopaminergic neurons in substantia nigra, associated with abnormal iron load. The assessment of presymptomatic biomarkers predicting the onset of neurodegenerative disorders is critical for monitoring early signs, screening patients for neuroprotective clinical trials and understanding the causal relationship between iron accumulation processes and disease development. Here, we used Quantitative Susceptibility Mapping (QSM) and 7T MRI to quantify iron deposition in Nigrosome 1 (N1) in early PD (ePD) patients, iRBD patients and healthy controls and investigated group differences and correlation with disease progression. We evaluated the radiological appearance of N1 and analyzed its iron content in 35 ePD, 30 iRBD patients and 14 healthy controls via T2*-weighted sequences and susceptibility (χ) maps. N1 regions of interest (ROIs) were manually drawn on control subjects and warped onto a study-specific template to obtain probabilistic N1 ROIs. For each subject the N1 with the highest mean χ was considered for statistical analysis. The appearance of N1 was rated pathological in 45% of iRBD patients. ePD patients showed increased N1 χ compared to iRBD patients and HC but no correlation with disease duration, indicating that iron load remains stable during the early stages of disease progression. Although no difference was reported in iron content between iRBD and HC, N1 χ in the iRBD group increases as the disease evolves. QSM can reveal temporal changes in N1 iron content and its quantification may represent a valuable presymptomatic biomarker to assess neurodegeneration in the prodromal stages of PD.

Quantitative susceptibility-weighted imaging in presence of strong susceptibility sources: Application to hemorrhage

PURPOSE

To optimize quantitative susceptibility-weighted imaging also known as true susceptibility-weighted imaging (tSWI) for strong susceptibility sources like hemorrhage and compare to standard susceptibility-weighted imaging (SWI) and quantitative susceptibility mapping (QSM).

METHODS

Ten patients with known intracerebral hemorrhage were scanned using a 3D SWI sequence. The magnitude and phase images were utilized to compute QSM, tSWI and SWI images. tSWI parameters including the upper threshold for creating susceptibility-weighted masks and the multiplication factor were optimized for hemorrhage depiction. Combined tSWI was also computed with independent optimized parameters for both veins and hemorrhagic regions. tSWI results were compared to SWI and QSM utilizing region-of-interest measurements, Pearson's correlation and Kruskal-Wallis test.

RESULTS

Fifteen hemorrhages were found, with mean susceptibility 0.81 ± 0.37 ppm. Unlike SWI which utilizes a phase mask, tSWI uses a mask computed from QSM. In tSWI, the weighted mask required an extended upper threshold far beyond the standard level for more effective visualization of hemorrhage texture. The upper threshold was set to the mean maximum susceptibility in the hemorrhagic region (3.24 ppm) with a multiplication factor of 2. The blooming effect, seen in SWI, was observed to be larger in hemorrhages with higher susceptibility values (r = 0.78, p < 0.001) with reduced blooming on tSWI. On SWI, 4 out of 15 hemorrhages showed phase wrap artifacts in the hemorrhagic region and all patients showed some phase wraps in the air-tissue interface near the auditory and frontal sinuses. These phase wrap artifacts were absent on tSWI. In hemorrhagic region, a higher correlation was observed between the actual susceptibility values and mean gray value for tSWI (r = -0.93, p < 0.001) than SWI (r = -0.87, p < 0.001).

CONCLUSION

In hemorrhage, tSWI minimizes both blooming effects and phase wrap artifacts observed in SWI. However, unlike SWI, tSWI requires an altered upper threshold for best hemorrhage depiction that greatly differs from the standard value. tSWI can be used as a complementary technique for visualizing hemorrhage along with SWI.

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.

Multimodal brain and retinal imaging of dopaminergic degeneration in Parkinson disease

Parkinson disease (PD) is a progressive disorder characterized by dopaminergic neurodegeneration in the brain. The development of parkinsonism is preceded by a long prodromal phase, and >50% of dopaminergic neurons can be lost from the substantia nigra by the time of the initial diagnosis. Therefore, validation of in vivo imaging biomarkers for early diagnosis and monitoring of disease progression is essential for future therapeutic developments. PET and single-photon emission CT targeting the presynaptic terminals of dopaminergic neurons can be used for early diagnosis by detecting axonal degeneration in the striatum. However, these techniques poorly differentiate atypical parkinsonian syndromes from PD, and their availability is limited in clinical settings. Advanced MRI in which pathological changes in the substantia nigra are visualized with diffusion, iron-sensitive susceptibility and neuromelanin-sensitive sequences potentially represents a more accessible imaging tool. Although these techniques can visualize the classic degenerative changes in PD, they might be insufficient for phenotyping or prognostication of heterogeneous aspects of PD resulting from extranigral pathologies. The retina is an emerging imaging target owing to its pathological involvement early in PD, which correlates with brain pathology. Retinal optical coherence tomography (OCT) is a non-invasive technique to visualize structural changes in the retina. Progressive parafoveal thinning and fovea avascular zone remodelling, as revealed by OCT, provide potential biomarkers for early diagnosis and prognostication in PD. As we discuss in this Review, multimodal imaging of the substantia nigra and retina is a promising tool to aid diagnosis and management of PD.

Visual analysis of nigrosome-1 in the differential diagnosis of Parkinson's disease and essential tremor

Differentiation between Parkinson’s disease, especially in its early stages, and essential tremor, which is a phenotypically similar movement disorder, still remains an unsolved challenge for neurology. The aim of this study was to assess the diagnostic significance of nigrosome imaging (nigrosomes are dopaminergic neuron clusters in the substantia nigra of the midbrain) using 3T high-resolution SW-MRI. The study was conducted in 20 patients with Parkinson’s disease and 10 patients with essential tremor. Visual analysis of the acquired nigrosome-1 images was performed using a 4-point ordinal rating scale. Differences in sex, age and duration of the disease were calculated using the Fisher exact test and the Mann–Whitney U test. The diagnostic value of the method was assessed using Pearson’s chisquared test. Nigrosome-1 was bilaterally or unilaterally absent in 70% of parkinsonian patients. Less specific changes to the substantia nigra (SN) were observed in two more parkinsonian patients (10%), whose nigrosome-1 appeared reduced in size. By contrast, nigrosome-1 was bilaterally intact in all patients (100%) with essential tremor (p < 0.001). Our preliminary findings demonstrate the high potential of noninvasive nigrosome-1 imaging in the differential diagnosis of Parkinson’s disease and essential tremor.

Nigral diffusivity, but not free water, correlates with iron content in Parkinson's disease

The loss of melanized neurons in the substantia nigra pars compacta is a primary feature in Parkinson's disease. Iron deposition occurs in conjunction with this loss. Loss of nigral neurons should remove barriers for diffusion and increase diffusivity of water molecules in regions undergoing this loss. In metrics from single-compartment diffusion tensor imaging models, these changes should manifest as increases in mean diffusivity and reductions in fractional anisotropy as well as increases in the free water compartment in metrics derived from bi-compartment models. However, studies examining nigral diffusivity changes from Parkinson's disease with single-compartment models have yielded inconclusive results and emerging evidence in control subjects indicates that iron corrupts diffusivity metrics derived from single-compartment models. We aimed to examine Parkinson's disease-related changes in nigral iron and diffusion measures from single- and bi-compartment models as well as assess the effect of iron on these diffusion measures in two separate Parkinson's cohorts. Iron-sensitive data and diffusion data were analysed in two cohorts: First, a discovery cohort consisting of 71 participants (32 control participants and 39 Parkinson's disease participants) was examined. Second, an external validation cohort, obtained from the Parkinson's Progression Marker's Initiative, consisting of 110 participants (58 control participants and 52 Parkinson's disease participants) was examined. The effect of iron on diffusion measures from single- and bi-compartment models was assessed in both cohorts. Measures sensitive to the free water compartment (discovery cohort: P = 0.006; external cohort: P = 0.01) and iron content (discovery cohort: P < 0.001; validation cohort: P = 0.02) were found to increase in substantia nigra of the Parkinson's disease group in both cohorts. However, diffusion markers derived from the single-compartment model (i.e. mean diffusivity and fractional anisotropy) were not replicated across cohorts. Correlations were seen between single-compartment diffusion measures and iron markers in the discovery cohort (iron-mean diffusivity: r = -0.400, P = 0.006) and validation cohort (iron-mean diffusivity: r = -0.387, P = 0.003) but no correlation was observed between a measure from the bi-compartment model related to the free water compartment and iron markers in either cohort. In conclusion, the variability of nigral diffusion metrics derived from the single-compartment model in Parkinson's disease may be attributed to competing influences of increased iron content, which tends to drive diffusivity down, and increases in the free water compartment, which tends to drive diffusivity up. In contrast to diffusion metrics derived from the single-compartment model, no relationship was seen between iron and the free water compartment in substantia nigra.

The calcium-iron connection in ferroptosis-mediated neuronal death

Iron, through its participation in oxidation/reduction processes, is essential for the physiological function of biological systems. In the brain, iron is involved in the development of normal cognitive functions, and its lack during development causes irreversible cognitive damage. Yet, deregulation of iron homeostasis provokes neuronal damage and death. Ferroptosis, a newly described iron-dependent cell death pathway, differs at the morphological, biochemical, and genetic levels from other cell death types. Ferroptosis is characterized by iron-mediated lipid peroxidation, depletion of the endogenous antioxidant glutathione and altered mitochondrial morphology. Although iron promotes the emergence of Ca²⁺ signals via activation of redox-sensitive Ca²⁺ channels, the role of Ca²⁺ signaling in ferroptosis has not been established. The early dysregulation of the cellular redox state observed in ferroptosis is likely to disturb Ca²⁺ homeostasis and signaling, facilitating ferroptotic neuronal death. This review presents an overview of the role of iron and ferroptosis in neuronal function, emphasizing the possible involvement of Ca²⁺ signaling in these processes. We propose, accordingly, that the iron-ferroptosis-Ca²⁺ association orchestrates the progression of cognitive dysfunctions and memory loss that occurs in neurodegenerative diseases. Therefore, to prevent iron dyshomeostasis and ferroptosis, we suggest the use of drugs that target the abnormal Ca²⁺ signaling caused by excessive iron levels as therapy for neurological disorders.

Emerging Neuroimaging Biomarkers Across Disease Stage in Parkinson Disease: A Review

Importance

Imaging biomarkers in Parkinson disease (PD) are increasingly important for monitoring progression in clinical trials and also have the potential to improve clinical care and management. This Review addresses a critical need to make clear the temporal relevance for diagnostic and progression imaging biomarkers to be used by clinicians and researchers over the clinical course of PD. Magnetic resonance imaging (diffusion imaging, neuromelanin-sensitive imaging, iron-sensitive imaging, T1-weighted imaging), positron emission tomography/single-photon emission computed tomography dopaminergic, serotonergic, and cholinergic imaging as well as metabolic and cerebral blood flow network neuroimaging biomarkers in the preclinical, prodromal, early, and moderate to late stages are characterized.

Observations

If a clinical trial is being carried out in the preclinical and prodromal stages, potentially useful disease-state biomarkers include dopaminergic imaging of the striatum; metabolic imaging; free-water, neuromelanin-sensitive, and iron-sensitive imaging in the substantia nigra; and T1-weighted structural magnetic resonance imaging. Disease-state biomarkers that can distinguish atypical parkinsonisms are metabolic imaging, free-water imaging, and T1-weighted imaging; dopaminergic imaging and other molecular imaging track progression in prodromal patients, whereas other established progression biomarkers need to be evaluated in prodromal cohorts. Progression in early-stage PD can be monitored using dopaminergic imaging in the striatum, metabolic imaging, and free-water and neuromelanin-sensitive imaging in the posterior substantia nigra. Progression in patients with moderate to late-stage PD can be monitored using free-water imaging in the anterior substantia nigra, R2* of substantia nigra, and metabolic imaging. Cortical thickness and gyrification might also be useful markers or predictors of progression. Dopaminergic imaging and free-water imaging detect progression over 1 year, whereas other modalities detect progression over 18 months or longer. The reliability of progression biomarkers varies with disease stage, whereas disease-state biomarkers are relatively consistent in individuals with preclinical, prodromal, early, and moderate to late-stage PD.

Conclusions and Relevance

Imaging biomarkers for various stages of PD are readily available to be used as outcome measures in clinical trials and are potentially useful in multimodal combination with routine clinical assessment. This Review provides a critically important template for considering disease stage when implementing diagnostic and progression biomarkers in both clinical trials and clinical care settings.

The evaluation of the swallow tail sign in patients with parkinsonism and gait disorders

BACKGROUND

Swallow tail sign (STS), which represents nigrosome-1 in the substantia nigra on 3 Tesla (T) susceptibility-weighted imaging (SWI), has attracted attention as a promising magnetic resonance imaging (MRI) biomarker for idiopathic Parkinson's disease (iPD). Some reports have shown high sensitivity and specificity-both above 94%-for distinguishing iPD from healthy controls. However, abnormal STS has been observed in many neurodegenerative parkinsonisms and even in multiple sclerosis.

METHODS

All patients with parkinsonism who had 3 T MRI were included in a retrospective chart review from a single movement disorders clinic. All subjects were evaluated by a single movement disorder specialist, using Movement Disorders Society diagnostic criteria and American Academy of Neurology consensus guidelines for diagnoses. All MRIs were interpreted by a single neuroradiologist who was blinded to the diagnosis.

RESULTS

Twenty patients were included in the study. Twelve had abnormal STS: iPD (n = 2), probable multiple system atrophy (n = 3), vascular parkinsonism (n = 1), psychogenic gait disorder (n = 1), neuroleptic parkinsonism (n = 2), cervical dystonia (n = 1), static encephalopathy (n = 1) and gait disorder of unknown etiology (n = 1). Eight had normal STS: iPD (n = 1), probable progressive supranuclear palsy (n = 1), vascular parkinsonism (n = 2), transient parkinsonism of unknown etiology (n = 2), valproic acid induced parkinsonism (n = 1), and essential tremor with parkinsonism (n = 1). ¹²³I-Ioflupane SPECT dopamine transporter (DaT) scan results were available on seven subjects; four subjects had incongruency between DaT and MRI.

CONCLUSION

Our results suggest that the abnormal STS is not, in isolation, a reliable biomarker of idiopathic Parkinson's disease.

Imaging the Pathophysiology of Essential Tremor-A Systematic Review

Background: The pathophysiology underlying essential tremor (ET) still is poorly understood. Recent research suggests a pivotal role of the cerebellum in tremor genesis, and an ongoing controversy remains as to whether ET constitutes a neurodegenerative disorder. In addition, mounting evidence indicates that alterations in the gamma-aminobutyric acid neurotransmitter system are involved in ET pathophysiology. Here, we systematically review structural, functional, and metabolic neuroimaging studies and discuss current concepts of ET pathophysiology from an imaging perspective.

Methods: We conducted a PubMed and Scopus search from 1966 up to December 2020, entering essential tremor in combination with any of the following search terms and their corresponding abbreviations: positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and gamma-aminobutyric acid (GABA).

Results: Altered functional connectivity in the cerebellum and cerebello-thalamico-cortical circuitry is a prevalent finding in functional imaging studies. Reports from structural imaging studies are less consistent, and there is no clear evidence for cerebellar neurodegeneration. However, diffusion tensor imaging robustly points toward microstructural cerebellar changes. Radiotracer imaging suggests that the dopaminergic axis is largely preserved in ET. Similarly, measurements of nigral iron content and neuromelanin are unremarkable in most studies; this is in contrast to Parkinson's disease (PD). PET and MRS studies provide limited evidence for cerebellar and thalamic GABAergic dysfunction.

Conclusions: There is robust evidence indicating that the cerebellum plays a key role within a multiple oscillator tremor network which underlies tremor genesis. However, whether cerebellar dysfunction relies on a neurodegenerative process remains unclear. Dopaminergic and iron imaging do not suggest a substantial overlap of ET with PD pathophysiology. There is limited evidence for alterations of the GABAergic neurotransmitter system in ET. The clinical, demographical, and genetic heterogeneity of ET translates into neuroimaging and likely explains the various inconsistencies reported.

Imaging of Substantia Nigra in Parkinson's Disease: A Narrative Review

Parkinson's disease (PD) is a progressive neurodegenerative disorder, characterized by motor and non-motor symptoms due to the degeneration of the pars compacta of the substantia nigra (SNc) with dopaminergic denervation of the striatum. Although the diagnosis of PD is principally based on a clinical assessment, great efforts have been expended over the past two decades to evaluate reliable biomarkers for PD. Among these biomarkers, magnetic resonance imaging (MRI)-based biomarkers may play a key role. Conventional MRI sequences are considered by many in the field to have low sensitivity, while advanced pulse sequences and ultra-high-field MRI techniques have brought many advantages, particularly regarding the study of brainstem and subcortical structures. Nowadays, nigrosome imaging, neuromelanine-sensitive sequences, iron-sensitive sequences, and advanced diffusion weighted imaging techniques afford new insights to the non-invasive study of the SNc. The use of these imaging methods, alone or in combination, may also help to discriminate PD patients from control patients, in addition to discriminating atypical parkinsonian syndromes (PS). A total of 92 articles were identified from an extensive review of the literature on PubMed in order to ascertain the-state-of-the-art of MRI techniques, as applied to the study of SNc in PD patients, as well as their potential future applications as imaging biomarkers of disease. Whilst none of these MRI-imaging biomarkers could be successfully validated for routine clinical practice, in achieving high levels of accuracy and reproducibility in the diagnosis of PD, a multimodal MRI-PD protocol may assist neuroradiologists and clinicians in the early and differential diagnosis of a wide spectrum of neurodegenerative disorders.

Imaging the Substantia Nigra in Parkinson Disease and Other Parkinsonian Syndromes

Parkinson disease is characterized by dopaminergic cell loss in the substantia nigra of the midbrain. There are various imaging markers for Parkinson disease. Recent advances in MRI have enabled elucidation of the underlying pathophysiologic changes in the nigral structure. This has contributed to accurate and early diagnosis and has improved disease progression monitoring. This article aims to review recent developments in nigral imaging for Parkinson disease and other parkinsonian syndromes, including nigrosome imaging, neuromelanin imaging, quantitative iron mapping, and diffusion-tensor imaging. In particular, this article examines nigrosome imaging using 7-T MRI and 3-T susceptibility-weighted imaging. Finally, this article discusses volumetry and its clinical importance related to symptom manifestation. This review will improve understanding of recent advancements in nigral imaging of Parkinson disease. Published under a CC BY 4.0 license.

Assessing brain iron and volume of subcortical nuclei in idiopathic rapid eye movement sleep behavior disorder

STUDY OBJECTIVES

The relationship of iron with cognitive and motor impairment in idiopathic rapid eye movement sleep behavior disorder (iRBD) remains unknown.

METHODS

Twenty-nine (29) patients and 28 healthy controls (HCs) underwent susceptibility weighted imaging and susceptibility mapping. These images were used to evaluate the nigrosome-1 (N1) sign in the substantia nigra (SN), global and regional high-iron (RII) content and volume of subcortical nuclei.

RESULTS

The number of iRBD patients with N1 loss (12) was significantly higher than HCs (2) (P=0.005). Compared with HCs, the iRBD patients had reduced volume of the right caudate nucleus (RCN) (P<0.05, FDR correction) but no significant changes in global and RII iron of the subcortical nuclei (all P>0.05, FDR correction). Multiple regression analysis revealed that: for cognitive function, the RII iron of the RCN was significantly correlated with visuospatial function and the global iron of the right dentate nucleus (RDN) was correlated with memory function; for motor function, the RII iron of the left DN (LDN) and global iron of the left CN correlated with the Alternate-Tap test (left, average), the global iron of the LDN correlated with the Alternate-Tap test (right), and the global iron of the left GP correlated with the 3-meter Timed Up and Go test (all P<0.05, FDR correction).

CONCLUSIONS

Our exploratory analysis found that iRBD patients had a higher incidence of N1 loss and reduced RCN volume after FDR correction. Cognitive and motor impairment were associated with iron deposition in several cerebral nuclei after FDR correction.

Neuroimaging Assessment of Nigrosome 1 with a Multiecho Gre Magnetic Resonance Sequence in the Differentiation Between Parkinsons Disease from Essential Tremor and Healthy Individuals

Background and purpose

Parkinsonism is commonly seen in many clinical conditions, and the establishment of its etiology may take many years. The possible development of neuroprotective treatments for Parkinsons disease (PD) in the near future will require correct and early diagnosis. This study aims to analyze the accuracy of a low-cost MRI sequence to differentiate PD from patients with essential tremor (ET) and healthy control (HC) individuals.

Material and methods

We recruited 70 individuals with clinical diagnoses of PD (38 patients), ET (11 patients) and healthy volunteers (21 individuals), all of whom underwent 3T MRI multiecho GRE sequence. Two blinded neuroradiologists independently evaluated the presence or absence of nigrosome-1(N1). We considered the unilateral or bilateral absence of nigrosome 1 signal as indicative of PD.

Results

The absence of at least one N1 could differentiate with 98% accuracy patients with clinical established PD from healthy controls. The presence of both nigrosomes was 96% accurate as a sign to differentiate PD from ET patients.

Conclusion

The 3T MRI with multiecho GRE is a simple and universally available technique and it can be used as a good auxiliary tool to differentiate PD from ET patients and controls.

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

OBJECTIVE

To evaluate the diagnostic performance of iron-sensitive sequences targeting the substantia nigra for distinguishing patients with Parkinson's disease from control participants and to identify factors causing heterogeneity.

METHODS

A systematic literature search in the Ovid-MEDLINE and EMBASE databases was performed for studies reporting the relevant topic before March 6, 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 affecting the diagnostic performance among the clinical, MRI, and analytic characteristics.

RESULTS

A total of 22 articles including 1126 patients with Parkinson's disease and 933 control participants were enrolled in this systematic review and meta-analysis. Of those, 12 studies used objective analyses of quantitative susceptibility measurements, and 10 visually assessed the nigrosome-1 in subjective analyses. Iron-sensitive nigral magnetic resonance imaging showed a pooled sensitivity of 92% (95% confidence interval 88-95%) and a pooled specificity of 90% (95% confidence interval 81-95%). According to subgroup and meta-regression analyses, a longer mean disease duration in patients with Parkinson's disease (≥ 5 years), subjective analysis, a smaller size of pixel (< 0.6 mm²), a larger flip angle (> 15°), a smaller slice thickness (≤ 1 mm), and specific targeting of the substantia nigra pars compacta improved the diagnostic performance.

CONCLUSION

Iron-sensitive nigral magnetic resonance imaging had a favorable diagnostic performance in discriminating patients with Parkinson's disease from control participants. Subjective analytic methods remain superior to objective approaches. Further improvements of the spatial resolution and contrast-to-noise ratio to specifically target the nigrosome-1 with objective analytic methods will be needed.

Susceptibility-Weighted Imaging in Neurodegenerative Disorders: A Review

As human life expectancy increases, there is an increased prevalence of neurodegenerative disorders and dementia. There are many ongoing research trials for early diagnosis and management of dementia, and neuroimaging is a critical part of such studies. However, conventional neuroimaging often fails to provide enough diagnostic findings in patients with neurodegenerative disorders. In this context, different MRI sequences are currently under investigation to facilitate the accurate diagnosis of such disorders. Susceptibility-weighted imaging (SWI) is an innovative MRI technique that utilizes "magnitude" and "phase" images to produce an image contrast that is sensitive for the detection of susceptibility differences of the tissues. As many neurodegenerative disorders are associated with accelerated iron deposition and/or microhemorrhages in different parts of the brain, SWI can be applied to detect these diagnostic clues. For instance, in cerebral amyloid angiopathy, SWI can demonstrate cortical microhemorrhages, which are predominantly in the frontal and parietal regions. Or in Parkinson disease, abnormal swallow-tail sign on high-resolution SWI is highly diagnostic. Also, SWI is a useful sequence to detect the low signal intensity of precentral cortices in patients with amyotrophic lateral sclerosis. Being familiar with SWI findings in neurodegenerative disorders is critical for an accurate diagnosis. In this paper, the authors review the technical parameters of SWI, physiologic, and pathologic iron deposition in the brain, and the role of SWI in the evaluation of neurodegenerative disorders in daily practice.

Susceptibility-weighted Imaging: Technical Essentials and Clinical Neurologic Applications

Susceptibility-weighted imaging (SWI) evolved from simple two-dimensional T2*-weighted sequences to three-dimensional sequences with improved spatial resolution and enhanced susceptibility contrast. SWI is an MRI sequence sensitive to compounds that distort the local magnetic field (eg, calcium and iron), in which the phase information can differentiate. But the term SWI is colloquially used to denote high-spatial-resolution susceptibility-enhanced sequences across different MRI vendors and sequences even when phase information is not used. The imaging appearance of SWI and related sequences strongly depends on the acquisition technique. Initially, SWI and related sequences were mostly used to improve the depiction of findings already known from standard two-dimensional T2*-weighted neuroimaging: more microbleeds in patients who are aging or with dementia or mild brain trauma; increased conspicuity of superficial siderosis in Alzheimer disease and amyloid angiopathy; and iron deposition in neurodegenerative diseases or abnormal vascular structures, such as capillary telangiectasia. But SWI also helps to identify findings not visible on standard T2*-weighted images: the nigrosome 1 in Parkinson disease and dementia with Lewy bodies, the central vein and peripheral rim signs in multiple sclerosis, the peripheral rim sign in abscesses, arterial signal loss related to thrombus, asymmetrically prominent cortical veins in stroke, and intratumoral susceptibility signals in brain neoplasms.

Comparison of 6-[18F]FDOPA PET with Nigrosome 1 detection in patients with parkinsonism

Background

The functional 6-[¹⁸F]FDOPA positron emission tomography (PET) can be a helpful tool in differentiating parkinsonism with dopaminergic deficiency from clinically similar differential diagnoses. Furthermore, in T2*/susceptibility-weighted imaging (SWI) magnetic resonance imaging (MRI) sequences the structural integrity of the Nigrosome 1 (N1) can be assessed by checking the presence of the swallow tail sign (STS). We therefore retrospectively compared the performance of the 6-[¹⁸F]FDOPA PET with the N1 detection in patients suspected with parkinsonian diseases. Forty-three consecutive patients (m: 23, f: 20, mean age: 63 ± 12 years) were included in the study. They underwent clinically indicated 6-[¹⁸F]FDOPA PET/MRI scans as part of their neurological evaluation of uncertain parkinsonian syndromes. Visual and semi-quantitative PET imaging results were statistically compared with visual N1 assessment on 3 T SWI. As the gold standard, we defined the clinical diagnosis at the last follow-up, which included idiopathic Parkinson syndrome (IPS; n = 18), atypical parkinsonian syndromes (APS; n = 9) and other neurological diseases without dopaminergic deficit (n = 16).

Results

Thirty-five of 43 patients (81%, Kappa 0.611) had corresponding results in 6-[¹⁸F]FDOPA PET and SWI. Seven of the remaining 8 patients were correctly diagnosed by 6-[¹⁸F]FDOPA PET alone. Sensitivity, specificity and accuracy for 6-[¹⁸F]FDOPA and N1 imaging were 93%, 94%, 93% and 82%, 75%, 79%, respectively.

Conclusions

6-[¹⁸F]FDOPA PET and Nigrosome 1 evaluation had an overall good intermodality agreement. Diagnostic agreement was very good in cases of clinically suspected idiopathic Parkinson syndrome and fair in atypical parkinsonian syndromes, but poor in patients with non-parkinsonian disorders. 6-[¹⁸F]FDOPA PET showed higher sensitivity, specificity and accuracy in discriminating parkinsonian syndromes from non-parkinsonian disorders than the N1 evaluation. In summary, the additional benefit of N1 assessment in patients with APS or parkinsonism without dopaminergic deficit needs to be proven by prospective studies.

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 loss of nigral hyperintensity on susceptibility-weighted imaging in parkinsonism: an updated meta-analysis

OBJECTIVES

To evaluate diagnostic performance of loss of nigral hyperintensity on SWI in differentiating idiopathic Parkinson's disease (IPD) or primary parkinsonism (including IPD and Parkinson-plus syndrome) from healthy/disease controls.

METHODS

MEDLINE/PubMed and EMBASE databases were searched to identify original articles investigating the diagnostic performance of loss of nigral hyperintensity for differentiating IPD or primary parkinsonism from healthy/disease control, up to April 3, 2020. Pooled sensitivity and specificity were calculated using a bivariate random-effects model. The proportion of nondiagnostic scan, inter- and intrareader agreement, and the proportion of concordance between clinical laterality and imaging asymmetry were also pooled.

RESULTS

Nineteen articles covering 2125 patients (1097 with primary parkinsonism, 1028 healthy/disease controls) were included. For discrimination between IPD and healthy/disease controls, pooled sensitivity and specificity were 0.96 (95% CI, 0.91-0.98) and 0.95 (95% CI, 0.92-0.97). For discrimination between primary parkinsonism and healthy/disease controls, pooled sensitivity and specificity were 0.87 (95% CI, 0.75-0.94) and 0.93 (95% CI, 0.85-0.97). The pooled proportion of non-diagnostic scans on random-effects modeling was 4.2% (95% CI, 2.5-6.9%). The inter- and intrareader agreements were almost perfect, with the pooled coefficients being 0.84 (95% CI, 0.78-0.89) and 0.96 (95% CI, 0.89-0.99), respectively. The pooled proportion of concordant cases was 69.3% (95% CI, 58.4-78.4%).

CONCLUSIONS

Loss of nigral hyperintensity on SWI can differentiate IPD or primary parkinsonism from a healthy/disease control group with high accuracy. However, the proportion of non-diagnostic scans is not negligible and must be taken into account.

KEY POINTS

• For discrimination between idiopathic Parkinson's disease and healthy/disease controls, pooled sensitivity and specificity of loss of nigral hyperintensity were 0.96 and 0.95. • For discrimination between primary parkinsonism and healthy/disease controls, pooled sensitivity and specificity of loss of nigral hyperintensity were 0.87 and 0.93. • The pooled proportion of non-diagnostic scans on random-effects modeling was 4.2%.

Fast 3 T nigral hyperintensity magnetic resonance imaging in Parkinson's disease

The absence of nigral hyperintensity is a promising MR marker for Parkinson’s disease (PD), but its small size imposes limitations on its routine use. Our aim was to compare Multi Echo Data Image Combination (MEDIC), segmented echo-planar imaging (EPISEG) and fluid-attenuated inversion recovery (FLAIR) sequences, as well as both magnitude (MAG) and susceptibility-weighted imaging (SWI) reconstructions of single-echo gradient echo for nigral hyperintensity imaging. Twenty-five healthy and twenty PD subjects were included. Sensitivity to motion artefacts, confidence of the radiologist in interpretation, rate of nondiagnostic scans and diagnostic accuracy were assessed. EPISEG was less motion-sensitive than MEDIC, MAG, and SWI, while FLAIR was less motion-sensitive than MAG and SWI. The reviewers were more confident when using EPISEG compared to any other techniques and MEDIC was superior to FLAIR. The proportions of nondiagnostic scans were lower for EPISEG than for other sequences. The best diagnostic performance was achieved for EPISEG (sensitivity = 65%, specificity = 96%). Using EPISEG, the absence of nigral hyperintensity in PD was associated with higher Hoehn-Yahr stage and MDS-UPDRS II + III. Nigral hyperintensity may be intact at the very early stages of PD. The promising properties of EPISEG may help the transfer of nigral hyperintensity imaging into daily clinical practice.

Iron Chelation in Movement Disorders: Logical or Ironical

Iron is probably as old as the universe itself and is essential for sustaining biological processes. The remarkable property of iron complexes to facilitate electron transfer makes it a significant component of redox reactions that drive the essential steps in nucleic acid biosynthesis and cellular functions. This, however, also generates potentially harmful hydroxyl radicals causing cell damage. In the movement disorder world, iron accumulation is well known to occur in neurodegeneration with brain iron accumulation, while dysfunctional iron homeostasis has been linked with neurodegenerative diseases like Parkinson's disease and Huntington's disease to name a few. Targeting excess iron in these patients with chelation therapy has been attempted over the last few decades, though the results have not been that promising. In this review, we have discussed iron, its metabolism, and proposed mechanisms causing movement disorder abnormalities. We have reviewed the available literature on attempts to treat these movement disorders with chelation therapy. Finally, based on our understanding of the pathogenic role of iron, we have critically analyzed the limitations of chelation therapy in the current scenario and the various unmet needs that should be addressed for selecting the patient population amenable to this therapy.

Using Artificial Neural Network to Discriminate Parkinson's Disease from Other Parkinsonisms by Focusing on Putamen of Dopamine Transporter SPECT Images

Background: The challenge of differentiating, at an early stage, Parkinson’s disease from parkinsonism caused by other disorders remains unsolved. We proposed using an artificial neural network (ANN) to process images of dopamine transporter single-photon emission computed tomography (DAT-SPECT). Methods: Abnormal DAT-SPECT images of subjects with Parkinson’s disease and parkinsonism caused by other disorders were divided into training and test sets. Striatal regions of the images were segmented by using an active contour model and were used as the data to perform transfer learning on a pre-trained ANN to discriminate Parkinson’s disease from parkinsonism caused by other disorders. A support vector machine trained using parameters of semi-quantitative measurements including specific binding ratio and asymmetry index was used for comparison. Results: The predictive accuracy of the ANN classifier (86%) was higher than that of the support vector machine classifier (68%). The sensitivity and specificity of the ANN classifier in predicting Parkinson’s disease were 81.8% and 88.6%, respectively. Conclusions: The ANN classifier outperformed classical biomarkers in differentiating Parkinson’s disease from parkinsonism caused by other disorders. This classifier can be readily included into standalone computer software for clinical application.

Comparison of susceptibility-weighted imaging and susceptibility map-weighted imaging for the diagnosis of Parkinsonism with nigral hyperintensity

OBJECTIVE

To determine whether susceptibility map-weighted imaging (SMWI) was superior to conventional susceptibility-weighted imaging (SWI) in the diagnosis of Parkinson's disease (PD) and in its correlation with ¹²³I-2bcarbomethoxy-3b-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane single photon emission computerized tomography (¹²³I-FP-CIT SPECT).

METHODS

Between May 2017 and February 2018, 125 consecutive patients diagnosed with idiopathic PD, vascular pseudoparkinsonism, essential tremor, or drug-induced parkinsonism and who underwent ¹²³I-FP-CIT SPECT imaging and 3 T SWI on the same day or within 3 months were included in this retrospective study. In all patients, SMWI images were generated from SWI images. On both MRIs, two neuroradiologists independently evaluated the status of nigral hyperintensity on each side of substantia nigra. Inter-observer agreements for the nigral hyperintensity were tested. Using consensus reading, concordance between SWI, SMWI, and ¹²³I-FP-CIT SPECT were evaluated, and the diagnostic performance between SWI and SMWI for PD was compared.

RESULTS

Inter-observer agreement for the nigral hyperintensity was higher for SMWI (right, κ = 0.919; left, κ = 0.984) than for SWI (right, κ = 0.918; left, κ = 0.902). SMWI (right 67.2 %, left 68.0 %) showed a higher concordance rate with the results of ¹²³I-FP-CIT SPECT than SWI (right 60.0 %, left 59.2 %). SMWI (area under curve [AUC], 0.791) provided significantly higher diagnostic performance for PD than SWI (AUC, 0.720; P = 0.0005).

CONCLUSION

SMWI may be a superior assessment tool for nigral hyperintensity than SWI and may be an improved diagnostic imaging modality for patients with suspected PD.

Different iron deposition patterns in Parkinson's disease subtypes: a quantitative susceptibility mapping study

Background

Parkinson's disease (PD) is a heterogeneous neurodegenerative disorder with various subtypes and uncertain pathogenesis. Iron deposition is considered to be involved in the pathological mechanisms of PD. The present study aimed to investigate the iron deposition in deep gray matter in patients with different PD subtypes using quantitative susceptibility mapping (QSM).

Methods

Forty-six PD patients and 22 healthy controls (HCs) were recruited for the study. PD patients were allocated to the tremor-dominant (TD) group (n=22), postural instability and gait disorder-dominant (PIGD) group (n=19), and intermediate group (n=5). Susceptibility values in deep gray matter nuclei measured by QSM among the PD-TD and PD-PIGD groups and the HCs, as well as the relationship between iron accumulation and clinical motor features, were investigated.

Results

Susceptibility values in the dentate nucleus (DN) were greater in the PD-TD (118.73±70.45) group than in the PD-PIGD (72.14±39.85, P=0.02) group and HCs (78.26±41.38, P=0.042). Further, a significant positive correlation was observed between the DN susceptibility values and tremor scores (r=0.324, P=0.028). Compared with the HCs (182.60±85.35), both the PD-TD (282.00±102.49, P=0.006) and PD-PIGD groups (284.91±118.54, P=0.007) exhibited greater susceptibility values in the substantia nigra (SN) pars reticulata. The susceptibility values in the SN pars compacta were also greater in the PD-PIGD group (164.51±89.44) than in the HCs (107.78±63.11, P=0.048).

Conclusions

The present study demonstrated various iron deposition patterns in different PD phenotypes. These findings give insight into the pathophysiology underlying different PD phenotypes, and potentially illustrate the involvement of iron deposition in the PD-TD and PD-PIGD subtypes.

Utility of Imaging of Nigrosome-1 on 3T MRI and Its Comparison with 18F-DOPA PET in the Diagnosis of Idiopathic Parkinson Disease and Atypical Parkinsonism

Background

Loss of nigrosome-1 on 3T and 7T magnetic resonance imaging (MRI) is a recently explored imaging biomarker in the diagnosis of neurodegenerative parkinsonism.

Objectives

This study was undertaken to evaluate the utility of imaging of nigrosome in the diagnosis of neurodegenerative parkinsonism on 3T MRI.

Methods

An institution-based prospective case-control study was conducted at a tertiary care center in North India. 3T venous blood oxygen level-dependent (VenoBOLD) and high-resolution susceptibility-weighted imaging (SWI) imaging sequences in MRI were performed in 100 patients with parkinsonism (56 with idiopathic Parkinson's disease [IPD], 30 with young onset Parkinson's disease [YOPD], 12 with progressive supranuclear palsy, and 2 patients with multiple system atrophy) and 15 controls. Grading of nigrosome was done in both the sequences. Each patient underwent 18F-DOPA positron emission tomography (PET), detailed neurological examination including Hoen and Yahr (H&Y) staging and Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scoring.

Results

The diagnostic sensitivity and specificity of the detection of loss of nigrosome-1 on VenoBOLD and SWI sequence at 3T MR imaging were 90% and 66.7% and 94% and 80%, respectively. A weak negative correlation was found between the grading of the nigrosome and clinical parameters (H&Y and UPDRS III). There was no correlation between the side of nigrosome loss and clinical asymmetry. However, nigrosome imaging was not able to differentiate between Parkinson's disease and atypical parkinsonism.

Conclusions

The loss of nigrosome-1 on 3T MRI on SWI and VenoBOLD sequences may serve as a potential imaging marker in the diagnosis of degenerative parkinsonian syndromes. However, it cannot differentiate between idiopathic Parkinson's disease and atypical parkinsonian syndromes.