Visualization of nigrosome 1 and its loss in PD: pathoanatomical correlation and in vivo 7 T MRI

High resolution multi-parametric probabilistic in vivo atlas of dorsolateral nigral hyperintensity via 7 T MRI

The role of Nigrosome 1 (N1) in neurodegeneration and motor disorders, particularly in Parkinson's disease (PD), is increasingly recognized. The study of this region using quantitative measures, such as iron quantification through Quantitative Susceptibility Mapping (QSM), can provide enlightening insights into some pathological features of these diseases representing important biomarkers. However, the small size and the vanishing contrast with respect to the surrounding substantia nigra in PD patients make the segmentation of N1 challenging. For this reason, we provide a probabilistic atlas of the N1 portion corresponding to the swallow-tail hyperintensity, hereafter referred to as the Dorsolateral Nigral Hyperintensity (DNH), created on a high-resolution multi-parametric template from T1-weighted, T2*-weighted, and QSM images acquired in vivo at 7 T. The atlas also includes quantitative T2* and R2* templates and is provided in the MNI standard space. It aims to facilitate the study of N1, avoiding operator-dependent biases in segmentations, and allowing the standardisation of the quantitative assessment.

Systematic Review and Network Meta-Analysis of Retinal Imaging Biomarkers in Neurodegenerative Diseases: Correlation with Brain Changes

INTRODUCTION

The retina and brain share a common embryonic origin and neural composition. Both undergo structural, vascular, and physiological changes in neurodegenerative diseases (NDs). This Systematic and network meta-analysis (NMA) aims to identify retinal-brain biomarkers across the spectrum of NDs.

METHODS

We conducted an NMA using random-effects models to assess retinal layer thickness changes in Alzheimer's disease (AD) and mild cognitive impairment (MCI). Data from 225 AD patients, 97 MCI patients, and 345 cognitively normal (CN) individuals, published between 2016 and 2023, were analyzed. Brain imaging findings were also evaluated for comparison.

RESULTS

Compared to controls, the MCI group exhibited significant thinning in the inferior and superior peripapillary retinal nerve fiber layer (pRNFL) and inner macular thickness. Specifically, reductions were observed in Right Eye Inferior pRNFL (SMD = -21.5306), Right Eye Superior pRNFL (SMD = -11.5011), Left Eye Inferior pRNFL (SMD = -27.6244), Left Eye Superior pRNFL (SMD = -9.8137), and Inner Macular Thickness (SMD = -4.8791). When comparing AD to MCI, Right Eye Nasal pRNFL (SMD = 5.95), Left Eye Superior pRNFL (SMD = -9.1786), and Outer Macular Thickness (SMD = -4.1046) were significantly thinner in AD. No significant differences were found between AD and CN in most retinal regions.

CONCLUSION

Thinning of the superior and inferior pRNFL and inner macular layer may serve as early biomarkers of MCI. In AD, retinal layer thinning is accompanied by hippocampal, entorhinal cortex, and temporal lobe atrophy, with macular volume (EZ-RPE) correlating with total brain volume.

High-resolution mapping of substantia nigra in Parkinson's disease using 7 tesla magnetic resonance imaging

Parkinson's disease causes a progressive loss of dopaminergic neurons and iron accumulation in the substantia nigra pars compacta. Using ultra-high field magnetic resonance imaging (MRI) at 7 tesla in 43 Parkinson's patients and 24 healthy controls, we analyzed the voxel-wise pattern of structural disintegration of dopamine neurons with neuromelanin-sensitive MRI, along with assessing iron accumulation using R2* and quantitative susceptibility mapping (QSM). We also explored correlations between these measures and the severity of residual motor symptoms in the on-medication state and other clinical variables. Differences were most notable in the nigrosomes within the pars compacta, with patients showing reduced neuromelanin signals and increased QSM values. Severity and asymmetry of motor symptoms correlated with higher R2* and QSM values in nigrosome N1. Thus, ultra-high field MRI provides high-resolution maps of various aspects of the underlying neurodegenerative process which reflect individual motor impairment in Parkinson's disease.

Deep Learning-Based Algorithm for Automatic Quantification of Nigrosome-1 and Parkinsonism Classification Using Susceptibility Map-Weighted MRI

BACKGROUND AND PURPOSE

The diagnostic performance of deep learning model that simultaneously detecting and quantifying nigrosome-1 abnormality by using susceptibility map-weighted imaging (SMwI) remains unexplored. This study aimed to develop and validate a deep learning-based automatic quantification for nigral hyperintensity and a classification algorithm for neurodegenerative parkinsonism.

MATERIALS AND METHODS

We retrospectively collected 450 participants (210 with idiopathic Parkinson disease [IPD] and 240 individuals in the control group) for training data between November 2022 and May 2023, and 237 participants (168 with IPD, 58 with essential tremor, and 11 with drug-induced parkinsonism) for validation data between July 2021 and January 2022. SMwI data were reconstructed from multiecho gradient echo. Diagnostic performance for diagnosing IPD was assessed by using deep learning-based automatic quantification (Heuron NI) and classification (Heuron IPD) models. Reference standard for IPD was based on N-3-fluoropropyl-2-β-carbomethoxy-3-β-(4-iodophenyl) nortropane PET finding. Additionally, the correlation between the Hoehn and Yahr (H&Y) stage and volume of nigral hyperintensity in patients with IPD was assessed.

RESULTS

Quantification of nigral hyperintensity by using Heuron NI showed an area under the curve (AUC) of 0.915 (95% CI, 0.872-0.947) and 0.928 (95% CI, 0.887-0.957) on the left and right, respectively. Classification of nigral hyperintensity abnormality by using Heuron IPD showed area under the curve of 0.967 (95% CI, 0.936-0.986) and 0.976 (95% CI, 0.948-0.992) on the left and right, respectively. H&Y score ≥3 showed smaller nigral hyperintensity volume (1.43 ± 1.19 mm3) compared with H&Y score 1-2.5 (1.98 ± 1.63 mm3; P = .008).

CONCLUSIONS

Our deep learning-based model proves rapid, accurate automatic quantification of nigral hyperintensity, facilitating IPD diagnosis, symptom severity prediction, and patient stratification for personalized therapy. Further study is warranted to validate the findings across various clinical settings.

Clinical Neuroimaging Over the Last Decade: Achievements and What Lies Ahead

ABSTRACT

The past decade has witnessed notable advancements in clinical neuroimaging facilitated by technological innovations and significant scientific discoveries. In conjunction with Investigative Radiology's 60th anniversary, this review examines key contributions from the past 10 years, emphasizing the journal's most accessed articles and their impact on clinical practice and research. Advances in imaging technologies, including photon-counting computed tomography, and innovations in low-field and high-field magnetic resonance imaging systems have expanded diagnostic capabilities. Progress in the development and translation of contrast media and rapid quantitative imaging techniques has further improved diagnostic accuracy. Additionally, the integration of advanced data analysis methods, particularly deep learning and medical informatics, has improved image interpretation and operational efficiency. Beyond technological developments, this review highlights basic neuroscience findings, such as the discovery and characterization of the glymphatic system. These insights have provided a deeper understanding of central nervous system physiology and pathology, bridging the gap between research and clinical applications. This review integrates these advancements to provide an overview of the progress and ongoing challenges in clinical neuroimaging, offering insights into its current state and potential future directions within the broader field of radiology.

The innovation and practice of the "hand as foot" teaching method in the teaching of Parkinson's disease

Background

Based on years of clinical teaching experience, the orthopedic team pioneered the "hand as foot" teaching method, initially applied in orthopedic teaching. The advantage of "hand as foot" teaching lies in the high similarity of anatomical structures between upper and lower limbs, joints, nerves, blood vessels, etc., This method allows using feet to explain knowledge instead of hands. It has since expanded to internal medicine, surgery, obstetrics, and gynecology, significantly impacting clinical teaching and medical education across departments. Utilizing simple gestures or body language to grasp clinical knowledge intuitively and repeatedly has proven effective. Over years of theoretical teaching, understanding brain anatomy, particularly the anatomy and communication of Parkinson's disease (PD), has posed challenges. Recently, after consulting relevant literature and articles on the application of the "hand as foot" teaching method in clinical teaching, I have been inspired. The invisibility and inaccessibility of brain anatomy make it challenging for students to comprehend and retain knowledge of basal ganglia anatomy. Through numerous clinical teaching experiences, we have discovered that using "hand as foot" is well-suited to address these teaching difficulties. Although there are many existing articles on manualized teaching methods in various disciplines, there is a gap in research on the impact of "hand as foot" method on students' academic performance. The aim of this study was to investigate the impact of the "hand as foot" teaching method on knowledge related to PD.

Methods

A self-designed questionnaire was used to validate the effectiveness of the "Hand and Foot" teaching method for teaching key points to undergraduate clinical medical students in Inner Mongolia Medical University.

Results

There were a total of 81 participants of which 41 were in class 1 (students using "hand as foot" teaching method) and 40 were in class 2 (students using "hand as foot" teaching method), 75.61% of the students in class 1 found the "hand as foot" method useful and only 19.51% found the "hand as foot" method average. Of the students who were taught "hand as foot," 80.49% correctly answered the option "Main pathological changes in PD." A total of 70.73% correctly answered the option "Main components of the basal ganglia." A total of 82.93% correctly answered the option "Typical symptoms of PD." A total of 51.22% correctly answered the question related to the swallow tail sign. The percentage of correct answers was much higher than that of the students in the class 2. From the questionnaire survey of medical students' knowledge of PD, we can draw several important conclusions. A total of 75.61% of the students in class 1 who had used the "hand as foot" method teaching in PD found the method helpful. The results with statistical difference (P < 0.05) showed that the "hand as foot" teaching method directly affected the students' knowledge about PD.

Conclusion

The "hand as foot" teaching method is generally well-received by medical students. The teacher-student interaction is good, and the understanding and memorization of difficult knowledge points are effective. It also helps visualize knowledge and strengthens students' understanding and memory of complex concepts. This teaching approach has garnered positive feedback from both teachers and students. As basic education evolves, classroom teaching methods are continuously being reformed and advanced. Therefore, it is crucial to establish engaging teaching methods in the classroom. The analogy teaching method effectively stimulates students' interest in learning and encourages their self-directed learning. In comparison to the indoctrination teaching model, which focuses on rote memorization, this teaching method is more likely to spark students' interest in knowledge and boost their enthusiasm for learning. The results showed that the "hand as foot" teaching method significantly improved the correctness of the knowledge related to PD. In general, the use of "hand as foot" in the classroom can enliven the educational environment and enhance students' understanding and retention of abstract concepts. It aids in consolidation and review after class, simplifying complex questions into an intuitive and concrete form, which is highly beneficial for clinical teaching.

Gradients of Nigrostriatal Iron Deposition in Healthy Aging and Synucleinopathies

AIMS

To investigate the gradients of nigrostriatal iron deposition in aging, Parkinson's disease (PD), and multiple system atrophy (MSA).

METHODS

This study included 100 young healthy controls, 171 old healthy controls (OHC), 231 PD, and 24 MSA patients. The brain iron content was quantified by quantitative susceptibility mapping. A spatial function method was employed to map the iron gradient along the principal axis of the subcortical structure. General linear models were used to compare differences in iron gradients between groups. Partial correlation was used to analyze the relationship between iron content and symptoms of synucleinopathies.

RESULTS

Nigrostriatal iron deposition in all gradient directions was observed during aging (p < 0.05). Compared to OHC, iron deposition was significant in nearly all substantia nigra (SN) segments in both PD and MSA (p < 0.05). MSA showed significant iron deposition in the posterolateral putamen compared to PD (p < 0.05). Iron deposition in the SN in PD and putamen in MSA correlated with disease severity.

CONCLUSION

Iron deposition in all gradient directions occurred in the nigrostriatal system during healthy aging, and this was more evident in the SN in both PD and MSA, with MSA displaying additional iron deposition in the posterolateral putamen.

Clinical 7 Tesla magnetic resonance imaging: Impact and patient value in neurological disorders

Magnetic resonance imaging (MRI) is a cornerstone of non-invasive diagnostics and treatment monitoring, particularly for diseases of the central nervous system. Although 1.5- and 3 Tesla (T) field strengths remain the clinical standard, the advent of 7 T MRI represents a transformative step forward, offering superior spatial resolution, contrast, and sensitivity for visualizing neuroanatomy, metabolism, and function. Recent innovations, including parallel transmission and deep learning-based reconstruction, have resolved many prior technical challenges of 7 T MRI, enabling its routine clinical use. This review examines the diagnostic impact, patient value, and practical considerations of 7 T MRI, emphasizing its role in facilitating earlier diagnoses and improving care in conditions, such as amyotrophic lateral sclerosis (ALS), epilepsy, multiple sclerosis (MS), dementia, parkinsonism, tumors, and vascular diseases. Based on insights from over 1200 clinical scans with a second-generation 7 T system, the review highlights disease-specific biomarkers such as the motor band sign in ALS and the new diagnostic markers in MS, the central vein sign, and paramagnetic rim lesions. The unparalleled ability of 7 T MRI to study neurological diseases ex vivo at ultra-high resolution is also explored, offering new opportunities to understand pathophysiology and identify novel treatment targets. Additionally, the review provides a clinical perspective on patient handling and safety considerations, addressing challenges and practicalities associated with clinical 7 T MRI. By bridging research and clinical practice, 7 T MRI has the potential to redefine neuroimaging and advance the understanding and management of complex neurological disorders.

Is the Swallow Tail Sign a Useful Imaging Biomarker in Clinical Neurology? A Systematic Review

BACKGROUND

Loss of dorsolateral nigral hyperintensity (DNH) in iron-sensitive sequences of Magnetic Resonance Imaging (MRI), also described as "swallow tail sign" (STS) loss, has shown promising diagnostic value in Parkinson's Disease (PD) and Atypical Parkinsonian Syndromes (APS).

OBJECTIVE

To conduct a bibliometric analysis on substantia nigra MRI and a systematic review on the clinical utility of STS visual assessment on Susceptibility-Weighted Imaging in various clinical entities.

METHODS

VOSviewer's keyword co-occurrence network was employed using Web of Science (WOS). Complying with the PRISMA statement, we searched MEDLINE, WOS, SCOPUS, ProQuest and Google Scholar for peer-reviewed studies conducted in vivo, excluding quantitative imaging techniques.

RESULTS

DNH is a relatively novel parameter in substantia nigra MRI literature. Our SWI-focused review included 42 studies (3281 patients). Diagnostic accuracy of STS loss for PD/APS differentiation from controls and for Lewy Body Dementia differentiation from other dementias was 47.8-98.5% and 76-90%, respectively, with poorer capacity, however, in delineating PD from APS. STS evaluation in idiopathic REM sleep behavior disorder, a sign of prodromal PD, was typically concordant with nuclear scans, identifying subjects with high conversion risk. Iron deposition can affect STS in Multiple Sclerosis and STS loss in Amyotrophic Lateral Sclerosis is linked with multisystem degeneration, with poorer prognosis. In healthy individuals iron-induced microvessel changes are suspected for false positive results.

CONCLUSION

STS assessment exhibits potential in different settings, with a possibly intermediate role in the diagnostic work-up of various conditions. Its clinical utility should be explored further, through standardized MRI protocols on larger cohorts.

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.

Simple biomarkers to distinguish Parkinson's disease from its mimics in clinical practice: a comprehensive review and future directions

In the last few years, a plethora of biomarkers have been proposed for the differentiation of Parkinson's disease (PD) from its mimics. Most of them consist of complex measures, often based on expensive technology, not easily employed outside research centers. MRI measures have been widely used to differentiate between PD and other parkinsonism. However, these measurements were often performed manually on small brain areas in small patient cohorts with intra- and inter-rater variability. The aim of the current review is to provide a comprehensive and updated overview of the literature on biomarkers commonly used to differentiate PD from its mimics (including parkinsonism and tremor syndromes), focusing on parameters derived by simple qualitative or quantitative measurements that can be used in routine practice. Several electrophysiological, sonographic and MRI biomarkers have shown promising results, including the blink-reflex recovery cycle, tremor analysis, sonographic or MRI assessment of substantia nigra, and several qualitative MRI signs or simple linear measures to be directly performed on MR images. The most significant issue is that most studies have been conducted on small patient cohorts from a single center, with limited reproducibility of the findings. Future studies should be carried out on larger international cohorts of patients to ensure generalizability. Moreover, research on simple biomarkers should seek measurements to differentiate patients with different diseases but similar clinical phenotypes, distinguish subtypes of the same disease, assess disease progression, and correlate biomarkers with pathological data. An even more important goal would be to predict the disease in the preclinical phase.

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.

Classification of Parkinson's disease by deep learning on midbrain MRI

Purpose

Susceptibility map weighted imaging (SMWI), based on quantitative susceptibility mapping (QSM), allows accurate nigrosome-1 (N1) evaluation and has been used to develop Parkinson's disease (PD) deep learning (DL) classification algorithms. Neuromelanin-sensitive (NMS) MRI could improve automated quantitative N1 analysis by revealing neuromelanin content. This study aimed to compare classification performance of four approaches to PD diagnosis: (1) N1 quantitative "QSM-NMS" composite marker, (2) DL model for N1 morphological abnormality using SMWI ("Heuron IPD"), (3) DL model for N1 volume using SMWI ("Heuron NI"), and (4) N1 SMWI neuroradiological evaluation.

Method

PD patients (n = 82; aged 65 ± 9 years; 68% male) and healthy-controls (n = 107; 66 ± 7 years; 48% male) underwent 3 T midbrain MRI with T2*-SWI multi-echo-GRE (for QSM and SMWI), and NMS-MRI. AUC was used to compare diagnostic performance. We tested for correlation of each imaging measure with clinical parameters (severity, duration and levodopa dosing) by Spearman-Rho or Kendall-Tao-Beta correlation.

Results

Classification performance was excellent for the QSM-NMS composite marker (AUC = 0.94), N1 SMWI abnormality (AUC = 0.92), N1 SMWI volume (AUC = 0.90), and neuroradiologist (AUC = 0.98). Reasons for misclassification were right-left asymmetry, through-plane re-slicing, pulsation artefacts, and thin N1. In the two DL models, all 18/189 (9.5%) cases misclassified by Heuron IPD were controls with normal N1 volumes. We found significant correlation of the SN QSM-NMS composite measure with levodopa dosing (rho = -0.303, p = 0.006).

Conclusion

Our data demonstrate excellent performance of a quantitative QSM-NMS marker and automated DL PD classification algorithms based on midbrain MRI, while suggesting potential further improvements. Clinical utility is supported but requires validation in earlier stage PD cohorts.

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.

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.

Distinctive Pattern of Metal Deposition in Neurologic Wilson Disease: Insights From 7T Susceptibility-Weighted Imaging

BACKGROUND AND OBJECTIVES

Noninvasive and accurate biomarkers of neurologic Wilson disease (NWD), a rare inherited disorder, could reduce diagnostic error or delay. Excessive subcortical metal deposition seen on susceptibility imaging has suggested a characteristic pattern in NWD. With submillimeter spatial resolution and increased contrast, 7T susceptibility-weighted imaging (SWI) may enable better visualization of metal deposition in NWD. In this study, we sought to identify a distinctive metal deposition pattern in NWD using 7T SWI and investigate its diagnostic value and underlying pathophysiologic mechanism.

METHODS

Patients with WD, healthy participants with monoallelic ATP7B variant(s) on a single chromosome, and health controls (HCs) were recruited. NWD and non-NWD (nNWD) were defined according to the presence or absence of neurologic symptoms during investigation. Patients with other diseases with comparable clinical or imaging manifestations, including early-onset Parkinson disease (EOPD), multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and neurodegeneration with brain iron accumulation (NBIA), were additionally recruited and assessed for exploratory comparative analysis. All participants underwent 7T T1, T2, and high-resolution SWI scanning. Quantitative susceptibility mapping and principal component analysis were performed to illustrate metal distribution.

RESULTS

We identified a linear signal intensity change consisting of a hyperintense strip at the lateral border of the globus pallidus in patients with NWD. We termed this feature "hyperintense globus pallidus rim sign." This feature was detected in 38 of 41 patients with NWD and was negative in all 31 nNWD patients, 15 patients with EOPD, 30 patients with MSA, 15 patients with PSP, and 12 patients with NBIA; 22 monoallelic ATP7B variant carriers; and 41 HC. Its sensitivity to differentiate between NWD and HC was 92.7%, and specificity was 100%. Severity of the hyperintense globus pallidus rim sign measured by a semiquantitative scale was positively correlated with neurologic severity (ρ = 0.682, 95% CI 0.467-0.821, p < 0.001). Patients with NWD showed increased susceptibility in the lenticular nucleus with high regional weights in the lateral globus pallidus and medial putamen.

DISCUSSION

The hyperintense globus pallidus rim sign showed high sensitivity and excellent specificity for diagnosis and differential diagnosis of NWD. It is related to a special metal deposition pattern in the lenticular nucleus in NWD and can be considered as a novel neuroimaging biomarker of NWD.

CLASSIFICATION OF EVIDENCE

The study provides Class II evidence that the hyperintense globus pallidus rim sign on 7T SWI MRI can accurately diagnose neurologic WD.

Neurovascular and immune factors of vulnerability of substantia nigra dopaminergic neurons in non-human primates

Dopaminergic neurons in the ventral tier of the substantia nigra pars compacta (SNc) degenerate prominently in Parkinson's disease (PD), while those in the dorsal tier and ventral tegmental area are relatively spared. The factors determining why these neurons are more vulnerable than others are still unrevealed. Neuroinflammation and immune cell infiltration have been demonstrated to be a key feature of neurodegeneration in PD. However, the link between selective dopaminergic neuron vulnerability, glial and immune cell response, and vascularization and their interactions has not been deciphered. We aimed to investigate the contribution of glial cell activation and immune cell infiltration in the selective vulnerability of ventral dopaminergic neurons within the midbrain in a non-human primate model of PD. Structural characteristics of the vasculature within specific regions of the midbrain were also evaluated. Parkinsonian monkeys exhibited significant microglial and astroglial activation in the whole midbrain, but no major sub-regional differences were observed. Remarkably, the ventral substantia nigra was found to be typically more vascularized compared to other regions. This feature might play some role in making this region more susceptible to immune cell infiltration under pathological conditions, as greater infiltration of both T- and B- lymphocytes was observed in parkinsonian monkeys. Higher vascular density within the ventral region of the SNc may be a relevant factor for differential vulnerability of dopaminergic neurons in the midbrain. The increased infiltration of T- and B- cells in this region, alongside other molecules or toxins, may also contribute to the susceptibility of dopaminergic neurons in PD.

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.

Neuromelanin-sensitive magnetic resonance imaging in the study of mental disorder: A systematic review

Dopamine and norepinephrine are implicated in the pathophysiology of mental disorders, but non-invasive study of their neuronal function remains challenging. Recent research suggests that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) techniques may overcome this limitation by enabling the non-invasive imaging of the substantia nigra (SN)/ ventral tegmental area (VTA) dopaminergic and locus coeruleus (LC) noradrenergic systems. A review of 19 studies that met the criteria for NM-MRI application in mental disorders found that despite the use of heterogeneous sequence parameters and metrics, nearly all studies reported differences in contrast ratio (CNR) of LC or SN/VTA between patients with mental disorders and healthy controls. These findings suggest that NM-MRI is a valuable tool in psychiatry, but the differences in sequence parameters across studies hinder comparability, and a standardized analysis pipeline is needed to improve the reliability of results. Further research using standardized methods is needed to better understand the role of dopamine and norepinephrine in mental disorders.

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.

Morphometric similarity differences in drug-naive Parkinson's disease correlate with transcriptomic signatures

BACKGROUND

Differences in cortical morphology have been reported in individuals with Parkinson's disease (PD). However, the pathophysiological mechanism of transcriptomic vulnerability in local brain regions remains unclear.

OBJECTIVE

This study aimed to characterize the morphometric changes of brain regions in early drug-naive PD patients and uncover the brain-wide gene expression correlates.

METHODS

The morphometric similarity (MS) network analysis was used to quantify the interregional structural similarity from multiple magnetic resonance imaging anatomical indices measured in each brain region of 170 early drug-naive PD patients and 123 controls. Then, we applied partial least squares regression to determine the relationship between regional changes in MS and spatial transcriptional signatures from the Allen Human Brain Atlas dataset, and identified the specific genes related to MS differences in PD. We further investigated the biological processes by which the PD-related genes were enriched and the cellular characterization of these genes.

RESULTS

Our results showed that MS was mainly decreased in cingulate, frontal, and temporal cortical areas and increased in parietal and occipital cortical areas in early drug-naive PD patients. In addition, genes whose expression patterns were associated with regional MS changes in PD were involved in astrocytes, excitatory, and inhibitory neurons and were functionally enriched in neuron-specific biological processes related to trans-synaptic signaling and nervous system development.

CONCLUSIONS

These findings advance our understanding of the microscale genetic and cellular mechanisms driving macroscale morphological abnormalities in early drug-naive PD patients and provide potential targets for future therapeutic trials.

Improved diagnostic performance of susceptibility-weighted imaging with compressed sensing-sensitivity encoding and neuromelanin-sensitive MRI for Parkinson's disease and atypical Parkinsonism

AIM

To verify the diagnostic performance of the loss of nigrosome-1 on susceptibility-weighted imaging (SWI) with compressed sensing-sensitivity encoding (CS-SENSE) and neuromelanin on neuromelanin-sensitive (NM) magnetic resonance imaging (MRI) for the diagnosis of Parkinson's disease (PD) and atypical Parkinsonism.

MATERIALS AND METHODS

A total of 195 patients who underwent MRI between October 2019 and February 2020, including SWI, with or without CS-SENSE, and NM-MRI, were reviewed retrospectively. Two neuroradiologists assessed the loss of nigrosome-1 on SWI and neuromelanin on the NM-MRI. The result of N-3-fluoropropyl-2-beta-carbomethoxy-3-beta-(4-iodophenyl) nortropane positron-emission tomography (PET) was set as the reference standard.

RESULTS

When CS-SENSE was applied for nigrosome-1 imaging on SWI, the non-diagnostic scan rate was lowered significantly from 19.3% (17/88) to 5.6% (6/107; p=0.004). Diagnosis of PD and atypical Parkinsonism based on the loss of nigrosome-1 on SWI and based on NM-MRI showed good diagnostic value (area under the curve [AUC] 0.821, 95% confidence interval [CI] = 0.755-0.875: AUC 0.832, 95% CI = 0.771-0.882, respectively) with a substantial inter-reader agreement (κ = 0.791 and 0.681, respectively). Combined SWI and neuromelanin had a similar discriminatory ability (AUC 0.830, 95% CI = 0.770-0.880). Similarly, the diagnosis of PD was excellent.

CONCLUSIONS

CS-SENSE may add value to the diagnostic capability of nigrosome-1 on SWI to reduce the nondiagnostic scan rates. Furthermore, loss of nigrosome-1 on SWI or volume loss of neuromelanin on NM-MRI may be helpful for diagnosing PD.

Brainstem anatomy with 7-T MRI: in vivo assessment and ex vivo comparison

BACKGROUND

The brainstem contains grey matter nuclei and white matter tracts to be identified in clinical practice. The small size and the low contrast among them make their in vivo visualisation challenging using conventional magnetic resonance imaging (MRI) sequences at high magnetic field strengths. Combining higher spatial resolution, signal- and contrast-to-noise ratio and sensitivity to magnetic susceptibility (χ), susceptibility-weighted 7-T imaging could improve the assessment of brainstem anatomy.

METHODS

We acquired high-resolution 7-T MRI of the brainstem in a 46-year-old female healthy volunteer (using a three-dimensional multi-echo gradient-recalled-echo sequence; spatial resolution 0.3 × 0.3 × 1.2 mm3) and in a brainstem sample from a 48-year-old female body donor that was sectioned and stained. Images were visually assessed; nuclei and tracts were labelled and named according to the official nomenclature.

RESULTS

This in vivo imaging revealed structures usually evaluated through light microscopy, such as the accessory olivary nuclei, oculomotor nucleus and the medial longitudinal fasciculus. Some fibre tracts, such as the medial lemniscus, were visible for most of their course. Overall, in in vivo acquisitions, χ and frequency maps performed better than T2*-weighted imaging and allowed for the evaluation of a greater number of anatomical structures. All the structures identified in vivo were confirmed by the ex vivo imaging and histology.

CONCLUSIONS

The use of multi-echo GRE sequences at 7 T allowed the visualisation of brainstem structures that are not visible in detail at conventional magnetic field and opens new perspectives in the diagnostic and therapeutical approach to brain disorders.

RELEVANCE STATEMENT

In vivo MR imaging at UHF provides detailed anatomy of CNS substructures comparable to that obtained with histology. Anatomical details are fundamentals for diagnostic purposes but also to plan a direct targeting for a minimally invasive brain stimulation or ablation.

KEY POINTS

• The in vivo brainstem anatomy was explored with ultrahigh field MRI (7 T). • In vivo T2*-weighted magnitude, χ, and frequency images revealed many brainstem structures. • Ex vivo imaging and histology confirmed all the structures identified in vivo. • χ and frequency imaging revealed more brainstem structures than magnitude imaging.

Ultra-high-field 7T MRI in Parkinson's disease: ready for clinical use?-a narrative review

Background and Objective

The maturation of ultra-high-field magnetic resonance imaging (MRI) [≥7 Tesla (7T)] has improved our capability to depict and characterise brain structures efficiently, with better signal-to-noise ratio (SNR) and spatial resolution. We evaluated whether these improvements benefit the clinical detection and management of Parkinson's disease (PD).

Methods

We performed a literature search in March 2023 in PubMed (MEDLINE), EMBASE and Google Scholar for articles on "7T MRI" AND "Parkinson*", written in English, published between inception and 1st March, 2023, which we synthesised in narrative form.

Key Content and Findings

In deep-brain stimulation (DBS) surgical planning, early studies show that 7T MRI can distinguish anatomical substructures, and that this results in reduced adverse effects. In other areas, while there is strong evidence for improved accuracy and precision of 7T MRI-based measurements for PD, there is limited evidence for meaningful clinical translation. In particular, neuromelanin-iron complex quantification and visualisation in midbrain nuclei is enhanced, enabling depiction of nigrosomes 1-5, improved morphometry and vastly improved radiological assessments; however, studies on the related clinical outcomes, diagnosis, subtyping, differentiation of atypical parkinsonisms, and monitoring of treatment response using 7T MRI are lacking. Moreover, improvements in clinical utility must be great enough to justify the additional costs.

Conclusions

Together, current evidence supports feasible future clinical implementation of 7T MRI for PD. Future impacts to clinical decision making for diagnosis, differentiation, and monitoring of progression or treatment response are likely; however, to achieve this, further longitudinal studies using 7T MRI are needed in prodromal, early-stage PD and parkinsonism cohorts focusing on clinical translational potential.

The applied value in brain gray matter nuclei of patients with early-stage Parkinson's disease : a study based on multiple magnetic resonance imaging techniques

PURPOSE

This study compares the observation efficiency of brain gray matter nuclei of patients with early-stage Parkinson's disease among various Magnetic Resonance Imaging techniques, which include susceptibility weighted imaging (SWI), quantitative susceptibility imaging (QSM), diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI). Based on the findings, this study suggests an efficient combination of scanning techniques for brain gray matter nuclei observation, aiming to provide an opportunity to advance the understanding of clinical diagnosis of early-stage Parkinson's disease.

METHODS

Forty examinees, including twenty patients who were clinically diagnosed with early Parkinson's disease with a course of 0.5-6 years (PD group) and twenty healthy controls (HC group), underwent head MRI examination. Philips 3.0T (tesla) MR machine was used to measure the imaging indexes of gray matter nuclei in patients with early Parkinson's disease. SWI, QSM, DTI and DKI were used for diagnosis. SPSS (Statistical Product and Service Solutions) 21.0 was used for data analysis.

RESULTS

When SWI was used, fifteen PD patients and six healthy volunteers were diagnosed correctly. The sensitivity, specificity, positive predictive value, negative predictive value and diagnostic coincidence rate about the diagnosis of nigrosome-1 on imaging were 75.0%, 30.0%, 51.7%, 54.5% and 52.5% respectively. By contrast, when QSM was used, 19 PD patients and 11 healthy volunteers were diagnosed correctly. The sensitivity, specificity, positive predictive value, negative predictive value and diagnostic coincidence rate about the diagnosis of Nigrosome-one on imaging were 95.0%, 55.0%, 67.9%, 91.7% and 75.0% respectively. The mean kurtosis (MK) value within both the substantia nigra and thalamus, together with the mean diffusivity (MD) within both the substantia nigra and the head of caudate nucleus in PD group was greater than that of HC group. The susceptibility values within the substantia nigra, red nucleus, head of caudate nucleus and putamen of PD group was greater than that of HC group. The MD value in substantia nigra reveals the optimal diagnostic efficiency to distinguish the HC group and the PD group, followed by the MK value in substantia nigra. Specifically, the maximum area under ROC curve (AUC) of the MD value was 0.823, the sensitivity 70.0%, the specificity 85.0%, and the diagnostic threshold 0.414. The area under ROC curve (AUC) of the MK value was 0.695, the sensitivity 95.0%, the specificity 50.0%, and the diagnostic threshold was 0.667. Both of them were statistically significant.

CONCLUSIONS

In the early diagnosis of Parkinson's disease, QSM is more efficient than SWI in observing nigrosome-1 in substantia nigra. In the early diagnosis of Parkinson's disease, MD and MK values of substantia nigra in DKI parameters have higher diagnostic efficiency. The combined scanning of DKI and QSM has the highest diagnostic efficiency and provides imaging basis for clinical diagnosis of early Parkinson's disease.

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.

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.

The challenging quest of neuroimaging: From clinical to molecular-based subtyping of Parkinson disease and atypical parkinsonisms

The current framework of Parkinson disease (PD) focuses on phenotypic classification despite its considerable heterogeneity. We argue that this method of classification has restricted therapeutic advances and therefore limited our ability to develop disease-modifying interventions in PD. Advances in neuroimaging have identified several molecular mechanisms relevant to PD, variation within and between clinical phenotypes, and potential compensatory mechanisms with disease progression. Magnetic resonance imaging (MRI) techniques can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging have informed the neurotransmitter, metabolic, and inflammatory dysfunctions that could potentially distinguish disease phenotypes and predict response to therapy and clinical outcomes. However, rapid advancements in imaging techniques make it challenging to assess the significance of newer studies in the context of new theoretical frameworks. As such, there needs to not only be a standardization of practice criteria in molecular imaging but also a rethinking of target approaches. In order to harness precision medicine, a coordinated shift is needed toward divergent rather than convergent diagnostic approaches that account for interindividual differences rather than similarities within an affected population, and focus on predictive patterns rather than already lost neural activity.

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.

Imaging in Movement Disorders

OBJECTIVE

This article reviews commonly used imaging modalities in movement disorders, particularly parkinsonism. The review includes the diagnostic utility, role in differential diagnosis, reflection of pathophysiology, and limitations of neuroimaging in the setting of movement disorders. It also introduces promising new imaging modalities and describes the current status of research.

LATEST DEVELOPMENTS

Iron-sensitive MRI sequences and neuromelanin-sensitive MRI can be used to directly assess the integrity of nigral dopaminergic neurons and thus may reflect disease pathology and progression throughout the full range of severity in Parkinson disease (PD). The striatal uptake of presynaptic radiotracers in their terminal axons as currently assessed using clinically approved positron emission tomography (PET) or single-photon emission computed tomography (SPECT) imaging correlates with nigral pathology and disease severity only in early PD. Cholinergic PET, using radiotracers that target the presynaptic vesicular acetylcholine transporter, constitutes a substantial advance and may provide crucial insights into the pathophysiology of clinical symptoms such as dementia, freezing, and falls.

ESSENTIAL POINTS

In the absence of valid, direct, objective biomarkers of intracellular misfolded α-synuclein, PD remains a clinical diagnosis. The clinical utility of PET- or SPECT-based striatal measures is currently limited given their lack of specificity and inability to reflect nigral pathology in moderate to severe PD. These scans may be more sensitive than clinical examination to detect nigrostriatal deficiency that occurs in multiple parkinsonian syndromes and may still be recommended for clinical use in the future to identify prodromal PD if and when disease-modifying treatments become available. Multimodal imaging to evaluate underlying nigral pathology and its functional consequences may hold the key to future advances.

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.

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.

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.

Morphometric imaging and quantitative susceptibility mapping as complementary tools in the diagnosis of parkinsonisms

Background and purpose

In the quest for in vivo diagnostic biomarkers to discriminate Parkinson's disease (PD) from progressive supranuclear palsy (PSP) and multiple system atrophy (MSA, mainly p phenotype), many advanced magnetic resonance imaging (MRI) techniques have been studied. Morphometric indices, such as the Magnetic Resonance Parkinsonism Index (MRPI), demonstrated high diagnostic value in the comparison between PD and PSP. The potential of quantitative susceptibility mapping (QSM) was hypothesized, as increased magnetic susceptibility (Δχ) was reported in the red nucleus (RN) and medial part of the substantia nigra (SNImed) of PSP patients and in the putamen of MSA patients. However, disease‐specific susceptibility values for relevant regions of interest are yet to be identified. The aims of the study were to evaluate the diagnostic potential of a multimodal MRI protocol combining morphometric and QSM imaging in patients with determined parkinsonisms and to explore its value in a population of undetermined cases.

Method

Patients with suspected degenerative parkinsonism underwent clinical evaluation, 3 T brain MRI and clinical follow‐up. The MRPI was manually calculated on T1‐weighted images. QSM maps were generated from 3D multi‐echo T2*‐weighted sequences.

Results

In determined cases the morphometric evaluation confirmed optimal diagnostic accuracy in the comparison between PD and PSP but failed to discriminate PD from MSA‐p. Significant nigral and extranigral differences were found with QSM. RN Δχ showed excellent diagnostic accuracy in the comparison between PD and PSP and good accuracy in the comparison of PD and MSA‐p. Optimal susceptibility cut‐off values of RN and SNImed were tested in undetermined cases in addition to MRPI.

Conclusions

A combined use of morphometric imaging and QSM could improve the diagnostic phase of degenerative parkinsonisms.

Histogram Analysis of Quantitative Susceptibility Mapping for the Diagnosis of Parkinson's Disease

RATIONALE AND OBJECTIVES

To investigate the diagnostic performance of histogram analysis combined with quantitative susceptibility mapping (QSM) for differentiating Parkinson's disease (PD) patients from healthy controls.

METHODS

We included 35 patients with PD diagnosed by two neurologists from August 2019 to January 2020 in our hospital in this prospective study. The clinical diagnosis was based on the Movement Disorder Society Clinical Diagnostic Criteria for PD. At the same time, 23 healthy volunteers matched for age and sex were recruited as controls. The Mini Mental State Examination, the third part of the Parkinson's Disease Rating Scale, the Hoehn & Yahr stages, and disease duration (year) were used to assess the PD patients. QSM was performed using a 3T MR scanner. The regions of interest were depicted according to the head of the caudate nucleus(CN), globus pallidus(GP), putamina (PUT), thalmus(TH), substantia nigra (SN), red nucleus(RN), and dentate nucleus. Then the corresponding histogram features were extracted. The Mann-Whitney U test was used to identify significant histogram features for differentiating PD patients from healthy controls. Area under the receiver operating characteristics curve (AUC) analysis was conducted to evaluate the diagnostic performance of all significant histogram features. Multivariate logistic regression analysis was performed to identify the best combined model for all seven nuclei. Differences among the AUCs were compared pairwise.

RESULTS

Histogram features in all nuclei except TH showed significant differences between the groups. Among the single features, the 10th percentile of SN (SN_P10) yielded the highest AUC of 0.894, with the highest specificity of 86.86% for differentiating PD patients from healthy controls. The 75th percentile of PUT (PUT_P75) yielded the highest sensitivity of 97.14%. In the multivariate logistic regression analysis, SN_P10 combined with PUT_P75 yielded the highest diagnostic performance with the highest AUC of 0.911, the highest specificity of 91.30% and an excellent sensitivity of 92.40%.

CONCLUSION

QSM combined with histogram analysis successfully distinguished PD patients from healthy controls, and the result was notably superior to the mean value.

An Updated Overview of the Magnetic Resonance Imaging of Brain Iron in Movement Disorders

Brain iron load is one of the most important neuropathological hallmarks in movement disorders. Specifically, the iron provides most of the paramagnetic metal signals in the brain and its accumulation seems to play a key role, although not completely explained, in the degeneration of the basal ganglia, as well as other brain structures. Moreover, iron distribution patterns have been implicated in depicting different movement disorders. This work reviewed current literature on Magnetic Resonance Imaging for Brain Iron Detection and Quantification (MRI-BIDQ) in neurodegenerative processes underlying movement disorders.

The Swallow Tail Sign of Substantia Nigra: A Case–Control Study to Establish Its Role in Diagnosis of Parkinson Disease on 3T MRI

Background and Objectives The loss of swallow tail sign (STS) has been studied for the diagnosis of Parkinson's disease (PD). The study aims to establish the role of STS on high-resolution 3D susceptibility-weighted images (SWI) on 3T MRI in clinically diagnosed cases of PD and compare with control population.

Methods and Materials Forty-five patients with clinically diagnosed PD and Parkinson plus syndrome (PPS) formed the study group and were compared with 45 controls without any neurological disease and normal brain magnetic resonance imaging (MRI). Presence or absence of STS was studied on 1-mm thick axial 3D SWI images in bilateral substantia nigra by two radiologists independently, followed by consensus reading. Bilateral absent, unilateral absent, and faintly present STS were considered as absent STS and predicted PD or PPS, and bilateral presence was considered as a positive STS, and was assessed keeping the clinical diagnosis as the gold standard.

Results The sensitivity of the absent STS was 75.55%, specificity 97.77%, positive predictive value 97.14%, negative predictive value 80% and accuracy 86.66%, in the diagnosis of PD or PPS, with odd ratio of 132 (confidence interval 15.97–1098.75). Kappa coefficient was 0.80 (p < 0.001) for both inter- and intrarater agreement, suggesting high reproducibility for the detection of STS.

Conclusions Absence of the STS is a good predictor of degeneration of the nigrosome 1 in the substantia nigra in the PD or PPS patients; hence, it can act as a useful marker of these diseases.

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.

Automatic detection of neuromelanin and iron in the midbrain nuclei using a magnetic resonance imaging ‐based brain template

Parkinson disease (PD) is a chronic progressive neurodegenerative disorder characterized pathologically by early loss of neuromelanin (NM) in the substantia nigra pars compacta (SNpc) and increased iron deposition in the substantia nigra (SN). Degeneration of the SN presents as a 50 to 70% loss of pigmented neurons in the ventral lateral tier of the SNpc at the onset of symptoms. Also, using magnetic resonance imaging (MRI), iron deposition and volume changes of the red nucleus (RN), and subthalamic nucleus (STN) have been reported to be associated with disease status and rate of progression. Further, the STN serves as an important target for deep brain stimulation treatment in advanced PD patients. Therefore, an accurate in‐vivo delineation of the SN, its subregions and other midbrain structures such as the RN and STN could be useful to better study iron and NM changes in PD. Our goal was to use an MRI template to create an automatic midbrain deep gray matter nuclei segmentation approach based on iron and NM contrast derived from a single, multiecho magnetization transfer contrast gradient echo (MTC‐GRE) imaging sequence. The short echo TE = 7.5 ms data from a 3D MTC‐GRE sequence was used to find the NM‐rich region, while the second echo TE = 15 ms was used to calculate the quantitative susceptibility map for 87 healthy subjects (mean age ± SD: 63.4 ± 6.2 years old, range: 45–81 years). From these data, we created both NM and iron templates and calculated the boundaries of each midbrain nucleus in template space, mapped these boundaries back to the original space and then fine‐tuned the boundaries in the original space using a dynamic programming algorithm to match the details of each individual's NM and iron features. A dual mapping approach was used to improve the performance of the morphological mapping of the midbrain of any given individual to the template space. A threshold approach was used in the NM‐rich region and susceptibility maps to optimize the DICE similarity coefficients and the volume ratios. The results for the NM of the SN as well as the iron containing SN, STN, and RN all indicate a strong agreement with manually drawn structures. The DICE similarity coefficients and volume ratios for these structures were 0.85, 0.87, 0.75, and 0.92 and 0.93, 0.95, 0.89, 1.05, respectively, before applying any threshold on the data. Using this fully automatic template‐based deep gray matter mapping approach, it is possible to accurately measure the tissue properties such as volumes, iron content, and NM content of the midbrain nuclei.

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

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

MRI of nigrosome-1: A potential triage tool for patients with suspected parkinsonism

BACKGROUND AND PURPOSE

Susceptibility-weighted imaging (SWI) of nigrosome-1 is an emerging and clinically applicable imaging marker for parkinsonism, which can be derived from routinely performed brain MRI. The purpose of the study was to assess whether SWI can be used as a triage tool for more efficient selection of subsequent Dopamine Transporter Scan (DaTSCAN) single-photon emission computed tomography (SPECT).

METHODS

We examined 72 consecutive patients with suspected parkinsonism with both DaTSCAN SPECT and SWI (48 in Philips Ingenia, 24 in GE Signa). Additionally, we examined 24 healthy controls with SWI (14 in Philips Ingenia, 10 in GE Signa). Diagnostic performance of SWI and DaTSCAN SPECT was assessed on the basis of clinical diagnosis, in terms of sensitivity, specificity, and diagnostic accuracy.

RESULTS

A total of 54 parkinsonism patients (69 years ± 9, 32 men), 18 nonparkinsonism patients (69.4 years ± 9, 10 men), and 24 healthy controls (62 years ± 8, 10 men) were recruited. SWI had a specificity of 92% and a sensitivity of 74%, whereas DaTSCAN SPECT had 83% and 94%, respectively. By preselecting patients with abnormal or inconclusive SWI, the diagnostic performance of DaTSCAN SPECT improved (specificity 100%, sensitivity 95%). Scans from Philips were associated with significantly lower image quality compared to GE (p < .001). The experienced rater outperformed the less experienced one in diagnostic accuracy (82% vs. 68%).

CONCLUSIONS

SWI can be used as triage tool because normal SWI can in most cases rule out parkinsonism. However, the performance of SWI depends on acquisition parameters and rater's experience.

Manual delineation approaches for direct imaging of the subcortex

The growing interest in the human subcortex is accompanied by an increasing number of parcellation procedures to identify deep brain structures in magnetic resonance imaging (MRI) contrasts. Manual procedures continue to form the gold standard for parcellating brain structures and is used for the validation of automated approaches. Performing manual parcellations is a tedious process which requires a systematic and reproducible approach. For this purpose, we created a series of protocols for the anatomical delineation of 21 individual subcortical structures. The intelligibility of the protocols was assessed by calculating Dice similarity coefficients for ten healthy volunteers. In addition, dilated Dice coefficients showed that manual parcellations created using these protocols can provide high-quality training data for automated algorithms. Here, we share the protocols, together with three example MRI datasets and the created manual delineations. The protocols can be applied to create high-quality training data for automated parcellation procedures, as well as for further validation of existing procedures and are shared without restrictions with the research community.

Iron as the concert master in the pathogenic orchestra playing in sporadic Parkinson's disease

About 60 years ago, the discovery of a deficiency of dopamine in the nigro-striatal system led to a variety of symptomatic therapeutic strategies to supplement dopamine and to substantially improve the quality of life of patients with Parkinson's disease (PD). Since these seminal developments, neuropathological, neurochemical, molecular biological and genetic discoveries contributed to elucidate the pathology of PD. Oxidative stress, the consequences of reactive oxidative species, reduced antioxidative capacity including loss of glutathione, excitotoxicity, mitochondrial dysfunction, proteasomal dysfunction, apoptosis, lysosomal dysfunction, autophagy, suggested to be causal for ɑ-synuclein fibril formation and aggregation and contributing to neuroinflammation and neural cell death underlying this devastating disorder. However, there are no final conclusions about the triggered pathological mechanism(s) and the follow-up of pathological dysfunctions. Nevertheless, it is a fact, that iron, a major component of oxidative reactions, as well as neuromelanin, the major intraneuronal chelator of iron, undergo an age-dependent increase. And ageing is a major risk factor for PD. Iron is significantly increased in the substantia nigra pars compacta (SNpc) of PD. Reasons for this finding include disturbances in iron-related import and export mechanisms across the blood-brain barrier (BBB), localized opening of the BBB at the nigro-striatal tract including brain vessel pathology. Whether this pathology is of primary or secondary importance is not known. We assume that there is a better fit to the top-down hypotheses and pathogens entering the brain via the olfactory system, then to the bottom-up (gut-brain) hypothesis of PD pathology. Triggers for the bottom-up, the dual-hit and the top-down pathologies include chemicals, viruses and bacteria. If so, hepcidin, a regulator of iron absorption and its distribution into tissues, is suggested to play a major role in the pathogenesis of iron dyshomeostasis and risk for initiating and progressing ɑ-synuclein pathology. The role of glial components to the pathology of PD is still unknown. However, the dramatic loss of glutathione (GSH), which is mainly synthesized in glia, suggests dysfunction of this process, or GSH uptake into neurons. Loss of GSH and increase in SNpc iron concentration have been suggested to be early, may be even pre-symptomatic processes in the pathology of PD, despite the fact that they are progression factors. The role of glial ferritin isoforms has not been studied so far in detail in human post-mortem brain tissue and a close insight into their role in PD is called upon. In conclusion, "iron" is a major player in the pathology of PD. Selective chelation of excess iron at the site of the substantia nigra, where a dysfunction of the BBB is suggested, with peripherally acting iron chelators is suggested to contribute to the portfolio and therapeutic armamentarium of anti-Parkinson medications.

High-resolution Structural Magnetic Resonance Imaging and Quantitative Susceptibility Mapping

High-resolution 7-T imaging and quantitative susceptibility mapping produce greater anatomic detail compared with conventional strengths because of improvements in signal/noise ratio and contrast. The exquisite anatomic details of deep structures, including delineation of microscopic architecture using advanced techniques such as quantitative susceptibility mapping, allows improved detection of abnormal findings thought to be imperceptible on clinical strengths. This article reviews caveats and techniques for translating sequences commonly used on 1.5 or 3 T to high-resolution 7-T imaging. It discusses for several broad disease categories how high-resolution 7-T imaging can advance the understanding of various diseases, improve diagnosis, and guide management.

Studying Alzheimer disease, Parkinson disease, and amyotrophic lateral sclerosis with 7-T magnetic resonance

Ultra-high-field (UHF) magnetic resonance (MR) scanners, that is, equipment operating at static magnetic field of 7 tesla (7 T) and above, enable the acquisition of data with greatly improved signal-to-noise ratio with respect to conventional MR systems (e.g., scanners operating at 1.5 T and 3 T). The change in tissue relaxation times at UHF offers the opportunity to improve tissue contrast and depict features that were previously inaccessible. These potential advantages come, however, at a cost: in the majority of UHF-MR clinical protocols, potential drawbacks may include signal inhomogeneity, geometrical distortions, artifacts introduced by patient respiration, cardiac cycle, and motion. This article reviews the 7 T MR literature reporting the recent studies on the most widespread neurodegenerative diseases: Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis.

Role of the nigrosome 1 absence as a biomarker in amyotrophic lateral sclerosis

INTRODUCTION

The absence of nigrosome 1 on brain MRI and the hyperechogenicity of substantia nigra (SNh) by transcranial sonography are two useful biomarkers in the diagnosis of parkinsonisms. We aimed to evaluate the absence of nigrosome 1 in amyotrophic lateral sclerosis (ALS) and to address its meaning.

METHODS

136 ALS patients were recruited, including 16 progressive muscular atrophy (PMA) and 22 primary lateral sclerosis (PLS) patients. The SNh area was measured planimetrically by standard protocols. The nigrosome 1 status was qualitatively assessed by two blind evaluators in susceptibility weight images of 3T MRI. Demographic and clinical data were collected and the C9ORF72 expansion was tested in all patients.

RESULTS

Nigrosome 1 was absent in 30% of ALS patients (36% of PLS, 29% of classical ALS and 19% of PMA patients). There was no relationship between radiological and clinical laterality, nor between nigrosome 1 and SNh area. Male sex (OR = 3.63 [1.51, 9.38], p = 0.005) and a higher upper motor neuron (UMN) score (OR = 1.10 [1.02, 1.2], p = 0.022) were independently associated to nigrosome 1 absence, which also was an independent marker of poor survival (HR = 1.79 [1.3, 2.8], p = 0.013).

CONCLUSION

In ALS patients, the absence of nigrosome 1 is associated with male sex, UMN impairment and shorter survival. This suggests that constitutional factors and the degree of pyramidal involvement are related to the substantia nigra involvement in ALS. Thus, nigrosome 1 could be a marker of a multisystem degeneration, which in turn associates to poor prognosis.