Differentiation of idiopathic Parkinson's disease, multiple system atrophy, progressive supranuclear palsy, and healthy controls using magnetization transfer imaging

Only-train-once MR fingerprinting for B0 and B1 inhomogeneity correction in quantitative magnetization-transfer contrast

PURPOSE

To develop a fast, deep-learning approach for quantitative magnetization-transfer contrast (MTC)-MR fingerprinting (MRF) that simultaneously estimates multiple tissue parameters and corrects the effects of B0 and B1 variations.

METHODS

An only-train-once recurrent neural network was designed to perform the fast tissue-parameter quantification for a large range of different MRF acquisition schedules. It enabled a dynamic scan-wise linear calibration of the scan parameters using the measured B0 and B1 maps, which allowed accurate, multiple-tissue parameter mapping. MRF images were acquired from 8 healthy volunteers at 3 T. Estimated parameter maps from the MRF images were used to synthesize the MTC reference signal (Zref ) through Bloch equations at multiple saturation power levels.

RESULTS

The B0 and B1 errors in MR fingerprints, if not corrected, would impair the tissue quantification and subsequently corrupt the synthesized MTC reference images. Bloch equation-based numerical phantom studies and synthetic MRI analysis demonstrated that the proposed approach could correctly estimate water and semisolid macromolecule parameters, even with severe B0 and B1 inhomogeneities.

CONCLUSION

The only-train-once deep-learning framework can improve the reconstruction accuracy of brain-tissue parameter maps and be further combined with any conventional MRF or CEST-MRF method.

Multimodality imaging of neurodegenerative disorders with a focus on multiparametric magnetic resonance and molecular imaging

Neurodegenerative diseases afflict a large number of persons worldwide, with the prevalence and incidence of dementia rapidly increasing. Despite their prevalence, clinical diagnosis of dementia syndromes remains imperfect with limited specificity. Conventional structural-based imaging techniques also lack the accuracy necessary for confident diagnosis. Multiparametric magnetic resonance imaging and molecular imaging provide the promise of improving specificity and sensitivity in the diagnosis of neurodegenerative disease as well as therapeutic monitoring of monoclonal antibody therapy. This educational review will briefly focus on the epidemiology, clinical presentation, and pathologic findings of common and uncommon neurodegenerative diseases. Imaging features of each disease spanning from conventional magnetic resonance sequences to advanced multiparametric methods such as resting-state functional magnetic resonance imaging and arterial spin labeling imaging will be described in detail. Additionally, the review will explore the findings of each diagnosis on molecular imaging including single-photon emission computed tomography and positron emission tomography with a variety of clinically used and experimental radiotracers. The literature and clinical cases provided demonstrate the power of advanced magnetic resonance imaging and molecular techniques in the diagnosis of neurodegenerative diseases and areas of future and ongoing research. With the advent of combined positron emission tomography/magnetic resonance imaging scanners, hybrid protocols utilizing both techniques are an attractive option for improving the evaluation of neurodegenerative diseases.

A Critical Analysis of Quercetin as the Attractive Target for the Treatment of Parkinson's Disease

Parkinson's Disease (PD) is a multifaceted disorder with various factors suggested to play a synergistic pathophysiological role, such as oxidative stress, autophagy, pro-inflammatory events, and neurotransmitter abnormalities. While it is crucial to discover new treatments in addition to preventing PD, recent studies have focused on determining whether nutraceuticals will exert neuroprotective actions and pharmacological functions in PD. Quercetin, a flavonol-type flavonoid, is found in many fruits and vegetables and is recognised as a complementary therapy for PD. The neuroprotective effect of quercetin is directly associated with its antioxidant activity, in addition to stimulating cellular defence against oxidative stress. Other related mechanisms are activating Sirtuins (SIRT1) and inducing autophagy, in addition to induction of Nrf2-ARE and Paraoxonase 2 (PON2). Quercetin, whose neuroprotective activity has been demonstrated in many studies, unfortunately, has a disadvantage because of its poor water solubility, chemical instability, and low oral bioavailability. It has been reported that the disadvantages of quercetin have been eliminated with nanocarriers loaded with quercetin. The role of nanotechnology and nanodelivery systems in reducing oxidative stress during PD provides an indisputable advantage. Accordingly, the present review aims to shed light on quercetin's beneficial effects and underlying mechanisms in neuroprotection. In addition, the contribution of nanodelivery systems to the neuroprotective effect of quercetin is also discussed.

The “Black Straight-Line Sign” in the Putamen in Diffusion-Weighted Imaging: A Potential Diagnostic MRI Marker for Multiple System Atrophy

Background and Purpose

The diagnosis of multiple system atrophy (MSA) remains challenging in clinical practice. This study investigated the value of hypointense signals in the putamen (“black straight-line sign”) in diffusion-weighted imaging (DWI) of brain MRI for distinguishing (MSA) from Parkinson's disease (PD).

Methods

We retrospectively enrolled 30 MSA patients, 30 PD patients, and 30 healthy controls who had undergone brain MRI between 2016 and 2020. Two readers independently assessed the signal intensity of the bilateral putamen on DWI. The putaminal hypointensity was scored using 4-point visual scales. Putaminal hypointensity and the presence of a “black straight-line sign” were statistically compared between MSA and PD or healthy controls.

Results

The mean scores of putaminal hypointensity in DWI in the MSA group were significantly higher than in both the PD (U = 315.5, P = 0.034) and healthy control groups (U = 304.0, P = 0.022). Uni- or bilateral putaminal hypointensity in DWI with a score ≥2 was identified in 53.3% (16/30), 16.7% (5/30), and 13.3% (4/30) of MSA, PD, and healthy controls, respectively, with significant differences between MSA and PD (X² = 8.864, P = 0.003) or healthy controls (X² = 10.800, P = 0.001). Notably, the “black straight-line sign” of the putamen was observed in 16/30 (sensitivity 53.3%) patients with MSA, while it was absent in PD and healthy controls (specificity 100%). There were no significant differences for the presence of “black straight-line sign” in the MSA-P and MSA-C groups (X² = 0.433, P = 0.510).

Conclusion

The “black straight-line sign” of the putamen in DWI of head MRIs has the potential to serve as a diagnostic marker for distinguishing MSA from PD.

Imaging modalities in differential diagnosis of Parkinson’s disease: opportunities and challenges

Background

Parkinson’s disease (PD) diagnosis is yet largely based on the related clinical aspects. However, genetics, biomarkers, and neuroimaging studies have demonstrated a confirming role in the diagnosis, and future developments might be used in a pre-symptomatic phase of the disease.

Main text

This review provides an update on the current applications of neuroimaging modalities for PD diagnosis. A literature search was performed to find published studies that were involved on the application of different imaging modalities for PD diagnosis. An organized search of PubMed/MEDLINE, Embase, ProQuest, Scopus, Cochrane, and Google Scholar was performed based on MeSH keywords and suitable synonyms. Two researchers (TM and JPI) independently and separately performed the literature search. Our search strategy in each database was done by the following terms: ((Parkinson [Title/Abstract]) AND ((“Parkinsonian syndromes ”[Mesh]) OR Parkinsonism [Title/Abstract])) AND ((PET [Title/Abstract]) OR “SPECT”[Mesh]) OR ((Functional imaging, Transcranial sonography [Title/Abstract]) OR “Magnetic resonance spectroscopy ”[Mesh]). Database search had no limitation in time, and our last update of search was in February 2021. To have a comprehensive search and to find possible relevant articles, a manual search was conducted on the reference list of the articles and limited to those published in English.

Conclusion

Early diagnosis of PD could be vital for early management and adequate neuroprotection. Recent neuroimaging modalities such as SPECT and PET imaging using radiolabeled tracers, MRI, and CT are used to discover the disease. By the modalities, it is possible to early diagnose dopaminergic degeneration and also to differentiate PD from others parkinsonian syndromes, to monitor the natural progression of the disease and the effect of neuroprotective treatments on the progression. In this regard, functional imaging techniques have provided critical insights and roles on PD.

White matter and nigral alterations in multiple system atrophy-parkinsonian type

Multiple system atrophy (MSA) is classified into two main types: parkinsonian and cerebellar ataxia with oligodendrogliopathy. We examined microstructural alterations in the white matter and the substantia nigra pars compacta (SNc) of patients with MSA of parkinsonian type (MSA-P) using multishell diffusion magnetic resonance imaging (dMRI) and myelin sensitive imaging techniques. Age- and sex-matched patients with MSA-P (n = 21, n = 10 first and second cohorts, respectively), Parkinson’s disease patients (n = 19, 17), and healthy controls (n = 20, 24) were enrolled. Magnetization transfer saturation imaging (MT-sat) and dMRI were obtained using 3-T MRI. Measurements obtained from diffusion tensor imaging (DTI), free-water elimination DTI, neurite orientation dispersion and density imaging (NODDI), and MT-sat were compared between groups. Tract-based spatial statistics analysis revealed differences in diffuse white matter alterations in the free-water fractional volume, myelin volume fraction, and intracellular volume fraction between the patients with MSA-P and healthy controls, whereas free-water and MT-sat differences were limited to the middle cerebellar peduncle in comparison with those with Parkinson’s disease. Region-of-interest analysis of white matter and SNc revealed significant differences in the middle and inferior cerebellar peduncle, pontine crossing tract, corticospinal tract, and SNc between the MSA-P and healthy controls and/or Parkinson’s disease patients. Our results shed light on alterations to brain microstructure in MSA.

Multiparametric MRI for Characterization of the Basal Ganglia and the Midbrain

Objectives To characterize subcortical nuclei by multi-parametric quantitative magnetic resonance imaging.

Materials and Methods: The following quantitative multiparametric MR data of five healthy volunteers were acquired on a 7T MRI system: 3D gradient echo (GRE) data for the calculation of quantitative susceptibility maps (QSM), GRE sequences with and without off-resonant magnetic transfer pulse for magnetization transfer ratio (MTR) calculation, a magnetization−prepared 2 rapid acquisition gradient echo sequence for T₁ mapping, and (after a coil change) a density-adapted 3D radial pulse sequence for ²³Na imaging. First, all data were co-registered to the GRE data, volumes of interest (VOIs) for 21 subcortical structures were drawn manually for each volunteer, and a combined voxel-wise analysis of the four MR contrasts (QSM, MTR, T₁, ²³Na) in each structure was conducted to assess the quantitative, MR value-based differentiability of structures. Second, a machine learning algorithm based on random forests was trained to automatically classify the groups of multi-parametric voxel values from each VOI according to their association to one of the 21 subcortical structures.

Results The analysis of the integrated multimodal visualization of quantitative MR values in each structure yielded a successful classification among nuclei of the ascending reticular activation system (ARAS), the limbic system and the extrapyramidal system, while classification among (epi-)thalamic nuclei was less successful. The machine learning-based approach facilitated quantitative MR value-based structure classification especially in the group of extrapyramidal nuclei and reached an overall accuracy of 85% regarding all selected nuclei.

Conclusion Multimodal quantitative MR enabled excellent differentiation of a wide spectrum of subcortical nuclei with reasonable accuracy and may thus enable sensitive detection of disease and nucleus-specific MR-based contrast alterations in the future.

Utility of Multi-Modal MRI for Differentiating of Parkinson's Disease and Progressive Supranuclear Palsy Using Machine Learning

Background: Patients with Parkinson's disease (PD) and progressive supranuclear palsy Richardson's syndrome (PSP-RS) often show overlapping clinical features, leading to misdiagnoses. The objective of this study was to investigate the feasibility and utility of using multi-modal MRI datasets for an automatic differentiation of PD patients, PSP-RS patients, and healthy control (HC) subjects. Material and Methods: T1-weighted, T2-weighted, and diffusion-tensor (DTI) MRI datasets from 45 PD patients, 20 PSP-RS patients, and 38 HC subjects were available for this study. Using an atlas-based approach, regional values of brain morphology (T1-weighted), brain iron metabolism (T2-weighted), and microstructural integrity (DTI) were measured and employed for feature selection and subsequent classification using combinations of various established machine learning methods. Results: The optimal machine learning model using regional morphology features only achieved a classification accuracy of 65% (67/103 correct classifications) differentiating PD patients, PSP-RS patients, and HC subjects. The optimal machine learning model using only quantitative T2 values performed slightly better and achieved an accuracy of 75.7% (78/103). The optimal classifier using DTI features alone performed considerably better with 95.1% accuracy (98/103). The optimal multi-modal classifier using all features also achieved an accuracy of 95.1% but required more features and achieved a slightly lower F1-score compared to the optimal model using DTI features alone. Conclusion: Machine learning models using multi-modal MRI perform significantly better than uni-modal machine learning models using morphological parameters based on T1-weighted MRI datasets alone or brain iron metabolism markers based on T2-weighted MRI datasets alone. However, machine learnig models using regional brain microstructural integrity metrics computed from DTI datasets perform similar to the optimal multi-modal machine learning model. Thus, given the results from this study cohort, it appears that morphology and brain iron metabolism markers may not provide additional value for classification compared to using DTI metrics alone.

Can Autonomic Testing and Imaging Contribute to the Early Diagnosis of Multiple System Atrophy? A Systematic Review and Recommendations by the Movement Disorder Society Multiple System Atrophy Study Group

Background

In the current consensus diagnostic criteria, the diagnosis of probable multiple system atrophy (MSA) is based solely on clinical findings, whereas neuroimaging findings are listed as aid for the diagnosis of possible MSA. There are overlapping phenotypes between MSA-parkinsonian type and Parkinson's disease, progressive supranuclear palsy, and dementia with Lewy bodies, and between MSA-cerebellar type and sporadic adult-onset ataxia resulting in a significant diagnostic delay and misdiagnosis of MSA during life.

Objectives

In light of an ongoing effort to revise the current consensus criteria for MSA, the Movement Disorders Society Multiple System Atrophy Study Group performed a systematic review of original articles published before August 2019.

Methods

We included articles that studied at least 10 patients with MSA as well as participants with another disorder or control group for comparison purposes. MSA was defined by neuropathological confirmation, or as clinically probable, or clinically probable plus possible according to consensus diagnostic criteria.

Results

We discuss the pitfalls and benefits of each diagnostic test and provide specific recommendations on how to evaluate patients in whom MSA is suspected.

Conclusions

This systematic review of relevant studies indicates that imaging and autonomic function tests significantly contribute to increasing the accuracy of a diagnosis of MSA.

The Role of Magnetic Resonance Imaging for the Diagnosis of Atypical Parkinsonism

The diagnosis of Parkinson's disease and atypical Parkinsonism remains clinically difficult, especially at the early stage of the disease, since there is a significant overlap of symptoms. Multimodal MRI has significantly improved diagnostic accuracy and understanding of the pathophysiology of Parkinsonian disorders. Structural and quantitative MRI sequences provide biomarkers sensitive to different tissue properties that detect abnormalities specific to each disease and contribute to the diagnosis. Machine learning techniques using these MRI biomarkers can effectively differentiate atypical Parkinsonian syndromes. Such approaches could be implemented in a clinical environment and improve the management of Parkinsonian patients. This review presents different structural and quantitative MRI techniques, their contribution to the differential diagnosis of atypical Parkinsonian disorders and their interest for individual-level diagnosis.

An update on advances in magnetic resonance imaging of multiple system atrophy

In this review, we describe how different neuroimaging tools have been used to identify novel MSA biomarkers, highlighting their advantages and limitations. First, we describe the main structural MRI changes frequently associated with MSA including the 'hot cross-bun' and 'putaminal rim' signs as well as putaminal, pontine, and middle cerebellar peduncle (MCP) atrophy. We discuss the sensitivity and specificity of different supra- and infratentorial changes in differentiating MSA from other disorders, highlighting those that can improve diagnostic accuracy, including the MCP width and MCP/superior cerebellar peduncle (SCP) ratio on T1-weighted imaging, raised putaminal diffusivity on diffusion-weighted imaging, and increased T2* signal in the putamen, striatum, and substantia nigra on susceptibility-weighted imaging. Second, we focus on recent advances in structural and functional MRI techniques including diffusion tensor imaging (DTI), resting-state functional MRI (fMRI), and arterial spin labelling (ASL) imaging. Finally, we discuss new approaches for MSA research such as multimodal neuroimaging strategies and how such markers may be applied in clinical trials to provide crucial data for accurately selecting patients and to act as secondary outcome measures.

Structural Imaging in Atypical Parkinsonism

Qualitative and quantitative structural magnetic resonance imaging offer objective measures of the underlying neurodegeneration in atypical parkinsonism. Regional changes in tissue volume, signal changes and increased deposition of iron as assessed with different structural MRI techniques are surrogate markers of underlying neurodegeneration and may reflect cell loss, microglial proliferation and astroglial activation. Structural MRI has been explored as a tool to enhance diagnostic accuracy in differentiating atypical parkinsonian disorders (APDs). Moreover, the longitudinal assessment of serial structural MRI-derived parameters offers the opportunity for robust inferences regarding the progression of APDs. This review summarizes recent research findings as (1) a diagnostic tool for APDs as well as (2) as a tool to assess longitudinal changes of serial MRI-derived parameters in the different APDs.

Improved Automatic Morphology-Based Classification of Parkinson's Disease and Progressive Supranuclear Palsy

OBJECTIVES

The overlapping symptoms of Parkinson's disease (PD) and progressive supranuclear palsy-Richardson's syndrome (PSP-RS) often make a correct clinical diagnosis difficult. The volume of subcortical brain structures derived from high-resolution T1-weighted magnetic resonance imaging (MRI) datasets is frequently used for individual level classification of PD and PSP-RS patients. The aim of this study was to evaluate the benefit of including additional morphological features beyond the simple regional volume, as well as clinical features, and morphological features of cortical structures for an automatic classification of PD and PSP-RS patients.

MATERIAL AND METHODS

A total of 98 high-resolution T1-weighted MRI datasets from 76 PD patients, and 22 PSP-RS patients were available for this study. Using an atlas-based approach, the volume, surface area, and surface-area-to-volume ratio (SA:V) of 21 subcortical and 48 cortical brain regions were calculated and used as features for a support vector machine classification after application of a RELIEF feature selection method.

RESULTS

The comparison of the classification results suggests that including all three morphological parameters (volume, surface area and SA:V) can considerably improve classification accuracy compared to using volume or surface area alone. Likewise, including clinical patient features in addition to morphological parameters also considerably increases the classification accuracy. In contrast to this, integrating morphological features of other cortical structures did not lead to improved classification accuracy. Using this optimal set-up, an accuracy of 98% was achieved with only one falsely classified PD and one falsely classified PSP-RS patient.

CONCLUSION

The results of this study suggest that clinical features as well as more advanced morphological features should be used for future computer-aided diagnosis systems to differentiate PD and PSP-RS patients based on morphological parameters.

Advancing imaging technologies for patients with spinal pain: with a focus on whiplash injury

BACKGROUND CONTEXT

Radiological observations of soft-tissue changes that may relate to clinical symptoms in patients with traumatic and non-traumatic spinal disorders are highly controversial. Studies are often of poor quality and findings are inconsistent. A plethora of evidence suggests some pathoanatomical findings from traditional imaging applications are common in asymptomatic participants across the life span, which further questions the diagnostic, prognostic, and theranostic value of traditional imaging. Although we do not dispute the limited evidence for the clinical importance of most imaging findings, we contend that the disparate findings across studies may in part be due to limitations in the approaches used in assessment and analysis of imaging findings.

PURPOSE

This clinical commentary aimed to (1) briefly detail available imaging guidelines, (2) detail research-based evidence around the clinical use of findings from advanced, but available, imaging applications (eg, fat and water magnetic resonance imaging and magnetization transfer imaging), and (3) introduce how evolving imaging technologies may improve our mechanistic understanding of pain and disability, leading to improved treatments and outcomes.

STUDY DESIGN/SETTING

A non-systematic review of the literature is carried out.

METHODS

A narrative summary (including studies from the authors' own work in whiplash injuries) of the available literature is provided.

RESULTS

An emerging body of evidence suggests that the combination of existing imaging sequences or the use of developing imaging technologies in tandem with a good clinical assessment of modifiable risk factors may provide important diagnostic information toward the exploration and development of more informed and effective treatment options for some patients with traumatic neck pain.

CONCLUSIONS

Advancing imaging technologies may help to explain the seemingly disconnected spectrum of biopsychosocial signs and symptoms of traumatic neck pain.

Olfactory Impairment in Parkinson's Disease Studied with Diffusion Tensor and Magnetization Transfer Imaging

Background: Olfactory impairment is an early manifestation of Parkinson’s disease (PD). Diffusion Tensor Imaging (DTI) and Magnetization Transfer (MT) are two imaging techniques that allow noninvasive detection of microstructural changes in the cerebral white matter.

Objective: To assess white matter alterations associated with olfactory impairment in PD, using a binary imaging approach with DTI and MT.

Methods: 22 PD patients and 13 healthy controls were examined with DTI, MT and an odor discrimination test. DTI data were first analyzed with tract-based spatial statistics (TBSS) in order to detect differences in fractional anisotropy, mean, radial and axial diffusivity between PD patients and controls. Voxelwise randomized permutation was employed for the MT analysis, after spatial and intensity normalization. Additionally, ROI analysis was performed on both the DTI and MT data, focused on the white matter adjacent to olfactory brain regions.

Results: Whole brain voxelwise analysis revealed decreased axial diffusivity in the left uncinate fasciculus and the white matter adjacent to the left olfactory sulcus of PD patients. ROI analysis demonstrated decreased axial diffusivity in the right orbitofrontal cortex, as well as decreased mean diffusivity and axial diffusivity in the white matter of the left entorhinal cortex of PD patients. There were no significant differences regarding fractional anisotropy, radial diffusivity or MT between patients and controls.

Conclusions: ROI analysis of DTI could detect microstructural changes in the white matter adjacent to olfactory areas in PD patients, whereas MT imaging could not.

Pool size ratio of the substantia nigra in Parkinson's disease derived from two different quantitative magnetization transfer approaches

PURPOSE

We sought to measure quantitative magnetization transfer (qMT) properties of the substantia nigra pars compacta (SNc) in patients with Parkinson's disease (PD) and healthy controls (HCs) using a full qMT analysis and determine whether a rapid single-point measurement yields equivalent results for pool size ratio (PSR).

METHODS

Sixteen different MT-prepared MRI scans were obtained at 3 T from 16 PD patients and eight HCs, along with B1, B0, and relaxation time maps. Maps of PSR, free and macromolecular pool transverse relaxation times ([Formula: see text], [Formula: see text]) and rate of MT exchange between pools (k _mf ) were generated using a full qMT model. PSR maps were also generated using a single-point qMT model requiring just two MT-prepared images. qMT parameter values of the SNc, red nucleus, cerebral crus, and gray matter were compared between groups and methods.

RESULTS

PSR of the SNc was the only qMT parameter to differ significantly between groups (p < 0.05). PSR measured via single-point analysis was less variable than with the full MT model, provided slightly better differentiation of PD patients from HCs (area under curve 0.77 vs. 0.75) with sensitivity of 0.75 and specificity of 0.87, and was better than transverse relaxation time in distinguishing PD patients from HCs (area under curve 0.71, sensitivity 0.87, and specificity 0.50).

CONCLUSION

The increased PSR observed in the SNc of PD patients may provide a novel biomarker of PD, possibly associated with an increased macromolecular content. Single-point PSR mapping with reduced variability and shorter scan times relative to the full qMT model appears clinically feasible.

Magnetic resonance imaging for the diagnosis of Parkinson's disease

The differential diagnosis of parkinsonian syndromes is considered one of the most challenging in neurology and error rates in the clinical diagnosis can be high even at specialized centres. Despite several limitations, magnetic resonance imaging (MRI) has undoubtedly enhanced the diagnostic accuracy in the differential diagnosis of neurodegenerative parkinsonism over the last three decades. This review aims to summarize research findings regarding the value of the different MRI techniques, including advanced sequences at high- and ultra-high-field MRI and modern image analysis algorithms, in the diagnostic work-up of Parkinson's disease. This includes not only the exclusion of alternative diagnoses for Parkinson's disease such as symptomatic parkinsonism and atypical parkinsonism, but also the diagnosis of early, new onset, and even prodromal Parkinson's disease.

Disrupted topological organization of structural networks revealed by probabilistic diffusion tractography in Tourette syndrome children

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. Although previous TS studies revealed structural abnormalities in distinct corticobasal ganglia circuits, the topological alterations of the whole-brain white matter (WM) structural networks remain poorly understood. Here, we used diffusion MRI probabilistic tractography and graph theoretical analysis to investigate the topological organization of WM networks in 44 drug-naive TS children and 41 age- and gender-matched healthy children. The WM networks were constructed by estimating inter-regional connectivity probability and the topological properties were characterized using graph theory. We found that both TS and control groups showed an efficient small-world organization in WM networks. However, compared to controls, TS children exhibited decreased global and local efficiency, increased shortest path length and small worldness, indicating a disrupted balance between local specialization and global integration in structural networks. Although both TS and control groups showed highly similar hub distributions, TS children exhibited significant decreased nodal efficiency, mainly distributed in the default mode, language, visual, and sensorimotor systems. Furthermore, two separate networks showing significantly decreased connectivity in TS group were identified using network-based statistical (NBS) analysis, primarily composed of the parieto-occipital cortex, precuneus, and paracentral lobule. Importantly, we combined support vector machine and multiple kernel learning frameworks to fuse multiple levels of network topological features for classification of individuals, achieving high accuracy of 86.47%. Together, our study revealed the disrupted topological organization of structural networks related to pathophysiology of TS, and the discriminative topological features for classification are potential quantitative neuroimaging biomarkers for clinical TS diagnosis. Hum Brain Mapp 38:3988-4008, 2017. © 2017 Wiley Periodicals, Inc.

Radiological biomarkers for diagnosis in PSP: Where are we and where do we need to be?

PSP is a pathologically defined neurodegenerative tauopathy with a variety of clinical presentations including typical Richardson's syndrome and other variant PSP syndromes. A large body of neuroimaging research has been conducted over the past two decades, with many studies proposing different structural MRI and molecular PET/SPECT biomarkers for PSP. These include measures of brainstem, cortical and striatal atrophy, diffusion weighted and diffusion tensor imaging abnormalities, [18F] fluorodeoxyglucose PET hypometabolism, reductions in striatal dopamine imaging and, most recently, PET imaging with ligands that bind to tau. Our aim was to critically evaluate the degree to which structural and molecular neuroimaging metrics fulfill criteria for diagnostic biomarkers of PSP. We queried the PubMed, Cochrane, Medline, and PSYCInfo databases for original research articles published in English over the past 20 years using postmortem diagnosis or the NINDS-SPSP criteria as the diagnostic standard from 1996 to 2016. We define a five-level theoretical construct for the utility of neuroimaging biomarkers in PSP, with level 1 representing group-level findings, level 2 representing biomarkers with demonstrable individual-level diagnostic utility, level 3 representing biomarkers for early disease, level 4 representing surrogate biomarkers of PSP pathology, and level 5 representing definitive PSP biomarkers of PSP pathology. We discuss the degree to which each of the currently available biomarkers fit into this theoretical construct, consider the role of biomarkers in the diagnosis of Richardson's syndrome, variant PSP syndromes and autopsy confirmed PSP, and emphasize current shortfalls in the field. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Brain MR Contribution to the Differential Diagnosis of Parkinsonian Syndromes: An Update

Brain magnetic resonance (MR) represents a useful and feasible tool for the differential diagnosis of Parkinson's disease. Conventional MR may reveal secondary forms of parkinsonism and may show peculiar brain alterations of atypical parkinsonian syndromes. Furthermore, advanced MR techniques, such as morphometric-volumetric analyses, diffusion-weighted imaging, diffusion tensor imaging, tractography, proton MR spectroscopy, and iron-content sensitive imaging, have been used to obtain quantitative parameters useful to increase the diagnostic accuracy. Currently, many MR studies have provided both qualitative and quantitative findings, reflecting the underlying neuropathological pattern of the different degenerative parkinsonian syndromes. Although the variability in the methods and results across the studies limits the conclusion about which technique is the best, specific radiologic phenotypes may be identified. Qualitative/quantitative MR changes in the substantia nigra do not discriminate between different parkinsonisms. In the absence of extranigral abnormalities, the diagnosis of PD is more probable, whereas basal ganglia changes (mainly in the putamen) suggest the diagnosis of an atypical parkinsonian syndrome. In this context, changes in pons, middle cerebellar peduncles, and cerebellum suggest the diagnosis of MSA, in midbrain and superior cerebellar peduncles the diagnosis of PSP, and in whole cerebral hemispheres (mainly in frontoparietal cortex with asymmetric distribution) the diagnosis of Corticobasal Syndrome.

Magnetic resonance imaging as a potential biomarker for Parkinson's disease

Although a magnetic resonance imaging (MRI) biomarker for Parkinson's disease (PD) remains an unfulfilled objective, there have been numerous developments in MRI methodology and some of these have shown promise for PD. With funding from the National Institutes of Health and the Michael J Fox Foundation there will be further validation of structural, diffusion-based, and iron-focused MRI methods as possible biomarkers for PD. In this review, these methods and other strategies such as neurochemical and metabolic MRI have been covered. One of the challenges in establishing a biomarker is in the selection of individuals as PD is a heterogeneous disease with varying clinical features, different etiologies, and a range of pathologic changes. Additionally, longitudinal studies are needed of individuals with clinically diagnosed PD and cohorts of individuals who are at great risk for developing PD to validate methods. Ultimately an MRI biomarker will be useful in the diagnosis of PD, predicting the course of PD, providing a means to track its course, and provide an approach to select and monitor treatments.

Role of Magnetic Resonance Imaging in the Diagnosis of Multiple System Atrophy

Background

Multiple system atrophy (MSA) is a rapidly progressing neurodegenerative disorder without effective disease-modifying therapies. Because of a lack of reliable diagnostic biomarkers, there has been increasing interest in using magnetic resonance imaging (MRI) to improve the diagnostic accuracy of MSA.

Methods

This review summarizes recent literatures on the role of MRI in the diagnosis of MSA.

Results

Several MRI abnormalities on conventional MRI already are included in the current diagnostic criteria for MSA. Other features on conventional MRI are also used to make a diagnosis of MSA or to rule out alternative diagnoses. On the other hand, some of the MRI findings that were previously considered suggestive of a diagnosis of MSA are now being challenged, because it turned out that they were not as specific to MSA as previously thought. More advanced MRI modalities, including susceptibility-weighted imaging, diffusion-weighted imaging, diffusion tensor imaging, voxel-based morphometry, and cortical thickness analysis, are now used to study the changes in the brains of patients with MSA. Furthermore, studies have produced promising results demonstrating the use of MRI as a tool for monitoring and assessing disease progression in MSA.

Conclusions

MRI is useful and indispensable in the diagnosis of MSA and also possibly for monitoring disease progression. In this regard, well-designed, long-term, prospective studies on large numbers of patients are needed.

On-resonance variable delay multipulse scheme for imaging of fast-exchanging protons and semisolid macromolecules

PURPOSE

To develop an on-resonance variable delay multipulse (VDMP) scheme to image magnetization transfer contrast (MTC) and the chemical exchange saturation transfer (CEST) contrast of total fast-exchanging protons (TFP) with exchange rate above approximately 1 kHz.

METHODS

A train of high power binomial pulses was applied at the water resonance. The interpulse delay, called mixing time, was varied to observe its effect on the water signal reduction, allowing separation and quantification of MTC and CEST contributions as a result of their different proton transfer rates. The fast-exchanging protons in CEST and MTC are labeled together with the short T₂ components in MTC and separated out using a variable mixing time.

RESULTS

Phantom studies of selected metabolite solutions (glucose, glutamate, creatine, myo-inositol), bovine serum albumin (BSA), and hair conditioner show the capability of on-resonance VDMP to separate out exchangeable protons with exchange rates above 1 kHz. Quantitative MTC and TFP maps were acquired on healthy mouse brains using this method, showing strong gray/white matter contrast for the slowly transferring MTC protons, whereas the TFP map was more uniform across the brain but somewhat higher in gray matter.

CONCLUSIONS

The new method provides a simple way of imaging fast-exchanging protons and MTC components with a slow transfer rate. Magn Reson Med 77:730-739, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Imaging synucleinopathies

In this review the structural and functional imaging changes associated with the synucleinopathies PD, MSA, and dementias associated with Lewy bodies are reviewed. The role of imaging for supporting differential diagnosis, detecting subclinical disease, and following disease progression is discussed and its potential use for monitoring disease progression is debated. © 2016 International Parkinson and Movement Disorder Society.

Distinguishing Parkinson's disease from atypical parkinsonian syndromes using PET data and a computer system based on support vector machines and Bayesian networks

Differentiating between Parkinson's disease (PD) and atypical parkinsonian syndromes (APS) is still a challenge, specially at early stages when the patients show similar symptoms. During last years, several computer systems have been proposed in order to improve the diagnosis of PD, but their accuracy is still limited. In this work we demonstrate a full automatic computer system to assist the diagnosis of PD using ¹⁸F-DMFP PET data. First, a few regions of interest are selected by means of a two-sample t-test. The accuracy of the selected regions to separate PD from APS patients is then computed using a support vector machine classifier. The accuracy values are finally used to train a Bayesian network that can be used to predict the class of new unseen data. This methodology was evaluated using a database with 87 neuroimages, achieving accuracy rates over 78%. A fair comparison with other similar approaches is also provided.

Obsessive-compulsive disorder is a heterogeneous disorder: evidence from diffusion tensor imaging and magnetization transfer imaging

BACKGROUND

Current models of obsessive compulsive disorder (OCD) propose abnormalities of cortico-striatal circuits that involve the orbitofrontal cortex, anterior cingulate cortex, thalamus and the striatum. Nevertheless, during the last years, results of morphometric studies were contradictory. Since fully automated whole-brain voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are used to assess structural changes in OCD patients, increased consistent evidence has been reported that brain abnormalities are not limited exclusively to the "affective" orbitofronto-striatal circuit. Moreover, several studies conducted using a symptom dimensional approach demonstrated that different symptoms are mediated by distinct neural systems.

METHOD

We investigated structural brain abnormalities in 14 carefully selected adult (≥18 years), male and unmedicated patients with OCD - separately for obsession and compulsion scores (Y-BOCS) - compared to 20 healthy controls as reflected according to white matter changes by fractional anisotropy and apparent diffusion coefficient. Moreover, this is the first study in OCD patients, using magnetization transfer imaging (MTI). This method is said to be more sensitive to subtle structural brain changes than conventional volumetric imaging.

RESULTS

In our study, we show a positive correlation between MTR and Y-BOCS obsession scores with an increased integrity of tissue structure in the parietal cortex, including myelination and axonal density reflected by the magnetization transfer ratio (MTR) which was used for the first time in our study. Furthermore, Y-BOCS scores for compulsions correlated negatively with ADC-maps in the left nucleus lentiformis and the cingulum.

CONCLUSION

The results support the hypothesis that OCD is a heterogeneous disorder with distinct neural correlates across symptom dimensions and call for a substantial revision of such a model that takes into account the heterogeneity of the disorder.

Magnetization transfer MRI in dementia disorders, Huntington's disease and parkinsonism

Magnetic resonance imaging is the most used technique of neuroimaging. Using recent advances in magnetic resonance application it is possible to investigate several changes in neurodegenerative disease. Among different techniques, magnetization-transfer imaging (MTI), a magnetic resonance acquisition protocol assessing the magnetization exchange between protons bound to water and those bound to macromolecules, is able to identify microstructural brain tissue changes peculiar of neurodegenerative diseases. This review provides a report on the MTI technique and its use in the dementia disorders, Huntington's disease and parkinsonisms, comprehensive of the predictive values of MTI in the identification of early-phase disease.

Differentiating multiple-system atrophy from Parkinson's disease

The purpose of this review is to illustrate the differentiating features of multiple-system atrophy from Parkinson's disease at MRI. The various MRI sequences helpful in the differentiation will be discussed, including newer methods, such as diffusion tensor imaging, MR spectroscopy, and nuclear imaging.

Shape abnormalities of the caudate nucleus correlate with poorer gait and balance: results from a subset of the LADIS study

OBJECTIVE

Functional deficits seen in several neurodegenerative disorders have been linked with dysfunction in frontostriatal circuits and with associated shape alterations in striatal structures. The severity of visible white matter hyperintensities (WMHs) on magnetic resonance imaging has been found to correlate with poorer performance on measures of gait and balance. This study aimed to determine whether striatal volume and shape changes were correlated with gait dysfunction.

METHODS

Magnetic resonance imaging scans and clinical gait/balance data (scores from the Short Physical Performance Battery [SPPB]) were sourced from 66 subjects in the previously published LADIS trial, performed in nondisabled individuals older than age 65 years with WMHs at study entry. Data were obtained at study entry and at 3-year follow-up. Caudate nuclei and putamina were manually traced using a previously published method and volumes calculated. The relationships between volume and physical performance on the SPPB were investigated with shape analysis using the spherical harmonic shape description toolkit.

RESULTS

There was no correlation between the severity of WMHs and striatal volumes. Caudate nuclei volume correlated with performance on the SPPB at baseline but not at follow-up, with subsequent shape analysis showing left caudate changes occurred in areas corresponding to inputs of the dorsolateral prefrontal, premotor, and motor cortex. There was no correlation between putamen volumes and performance on the SPPB.

CONCLUSION

Disruption in frontostriatal circuits may play a role in mediating poorer physical performance in individuals with WMHs. Striatal volume and shape changes may be suitable biomarkers for functional changes in this population.

Levodopa administration modulates striatal processing of punishment-associated items in healthy participants

RATIONALE

Appetitive and aversive processes share a number of features such as their relevance for action and learning. On a neural level, reward and its predictors are associated with increased firing of dopaminergic neurons, whereas punishment processing has been linked to the serotonergic system and to decreases in dopamine transmission. Recent data indicate, however, that the dopaminergic system also responds to aversive stimuli and associated actions.

OBJECTIVES

In this pharmacological functional magnetic resonance imaging study, we investigated the contribution of the dopaminergic system to reward and punishment processing in humans.

METHODS

Two groups of participants received either placebo or the dopamine precursor levodopa and were scanned during alternating reward and punishment anticipation blocks.

RESULTS

Levodopa administration increased striatal activations for cues presented in punishment blocks. In an interaction with individual personality scores, levodopa also enhanced striatal activation for punishment-predictive compared with neutral cues in participants scoring higher on the novelty-seeking dimension.

CONCLUSIONS

These data support recent indications that dopamine contributes to punishment processing and suggest that the novelty-seeking trait is a measure of susceptibility to drug effects on motivation. These findings are also consistent with the possibility of an inverted U-shaped response function of dopamine in the striatum, suggesting an optimal level of dopamine release for motivational processing.

High-resolution quantitative imaging of the substantia nigra

There is a growing interest in identifying neuroimaging-based biomarkers for Parkinson's disease (PD), a progressive neurodegenerative disorder in which the major pathologic substrate is the loss of pigmented dopaminergic neurons in the substantia nigra (SN). Recently, an MRI technique dubbed "neuromelanin-sensitive MRI" (NM-MRI), has been found to provide notable contrast between the SN and surrounding brain tissues with potential applications as biomarker of PD. The contrast in NM-MRI has been associated with magnetization transfer (MT) effects, and thus the goal of this study was to characterize the impact of MT on NM-MRI, and to demonstrate the feasibility of performing quantitative MT (qMT) imaging in human SN. The results of this study demonstrate that high-resolution rapid qMT imaging of the SN can be reliably obtained within reasonable scan times, thereby can be translatable into clinical practice.

Mechanisms underlying chronic whiplash: contributions from an incomplete spinal cord injury?

OBJECTIVE

To explore the association between findings on advanced, but available, magnetic resonance imaging (MRI) sequences of the cervical spinal cord and muscular system, in tandem with biomechanical measures of maximum volitional plantar flexion torques as a proxy for a mild incomplete spinal cord injury.

DESIGN

Observational case series.

SETTING

University research laboratory.

SUBJECTS

Three patients with chronic whiplash and one patient with history of whiplash injury but no current symptoms.

METHODS

We measured lower extremity muscle fat, morphological changes in descending spinal cord pathways with advanced MRI applications and maximal activation of the plantar flexors.

RESULTS

Larger magnitudes of lower extremity muscle fat corresponded to altered spinal cord anatomy and reductions in the ability to maximally activate plantar flexor torques in the three subjects with chronic whiplash. Such findings were not present in the recovered participant.

CONCLUSIONS

The potential value of MRI to quantify neuromuscular degeneration in chronic whiplash is recognized. Larger scaled prospective studies are warranted before stronger conclusions can be drawn.

Structural and functional hallmarks of amyotrophic lateral sclerosis progression in motor- and memory-related brain regions

Previous studies have shown that in amyotrophic lateral sclerosis (ALS) multiple motor and extra-motor regions display structural and functional alterations. However, their temporal dynamics during disease-progression are unknown. To address this question we employed a longitudinal design assessing motor- and novelty-related brain activity in two fMRI sessions separated by a 3-month interval. In each session, patients and controls executed a Go/NoGo-task, in which additional presentation of novel stimuli served to elicit hippocampal activity. We observed a decline in the patients' movement-related activity during the 3-month interval. Importantly, in comparison to controls, the patients' motor activations were higher during the initial measurement. Thus, the relative decrease seems to reflect a breakdown of compensatory mechanisms due to progressive neural loss within the motor-system. In contrast, the patients' novelty-evoked hippocampal activity increased across 3 months, most likely reflecting the build-up of compensatory processes typically observed at the beginning of lesions. Consistent with a stage-dependent emergence of hippocampal and motor-system lesions, we observed a positive correlation between the ALSFRS-R or MRC-Megascores and the decline in motor activity, but a negative one with the hippocampal activation-increase. Finally, to determine whether the observed functional changes co-occur with structural alterations, we performed voxel-based volumetric analyses on magnetization transfer images in a separate patient cohort studied cross-sectionally at another scanning site. Therein, we observed a close overlap between the structural changes in this cohort, and the functional alterations in the other. Thus, our results provide important insights into the temporal dynamics of functional alterations during disease-progression, and provide support for an anatomical relationship between functional and structural cerebral changes in ALS.

A review of the use of magnetic resonance imaging in Parkinson's disease

To date, the most frequently used Parkinson's disease (PD) biomarkers are the brain imaging measures of dopaminergic dysfunction using positron emission tomography and single photon emission computed tomography. However, major advances have occurred in the development of magnetic resonance imaging (MRI) biomarkers for PD in the past decade. Although conventional structural imaging remains normal in PD, advanced techniques have shown changes in the substantia nigra and the cortex. The most well-developed MRI markers in PD include diffusion imaging and iron load using T2/T2* relaxometry techniques. Other quantitative biomarkers such as susceptibility-weighted imaging for iron load, magnetization transfer and ultra-high-field MRI have shown great potential. More sophisticated techniques such as tractography and resting state functional connectivity give access to anatomical and functional connectivity changes in the brain, respectively. Brain perfusion can be assessed using non-contrast-agent techniques such as arterial spin labelling and spectroscopy gives access to metabolites concentrations. However, to date these techniques are not yet fully validated and standardized quantitative metrics for PD are still lacking. This review presents an overview of new structural, perfusion, metabolic and anatomo-functional connectivity biomarkers, their use in PD and their potential applications to improve the clinical diagnosis of Parkinsonian syndromes and the quality of clinical trials.

The utility of neuroimaging in the differential diagnosis of parkinsonian syndromes

The differential diagnosis of parkinsonian syndromes can be challenging, particularly in early disease stages. However, prognosis and therapeutic regimes are not alike in Parkinson disease and atypical parkinsonism, and thus a correct diagnosis at the earliest possible stage is desirable. Over the past two decades, magnetic resonance imaging and radiotracer-based imaging techniques have proven to be helpful tools to enhance the accuracy of clinical diagnosis in these disorders. Here, we review recent advances in neuroimaging for the differential diagnosis of parkinsonian syndromes.

Pain anticipation recruits the mesolimbic system and differentially modulates subsequent recognition memory

The ability to encode information into long-term memory is not a passive process but can be influenced by motivational factors. While the mesolimbic system has long been associated with reward-driven memory enhancement, the precise neurobiology of processing aversive events and their effects on declarative learning remain unclear. To address this issue, human subjects encoded a series of scene images, which was combined with cues predicting an aversive electric shock with different probabilities (0.2, 0.5, 0.8). Subsequently, recognition memory for the scenes was tested using a remember/know procedure. In a behavioral experiment, shock probability had linear effects on familiarity and inverted u-shaped effects on recollection. While the behavioral effect was absent in experiment 2 (fMRI), at the neural level encoding-related activity in the hippocampus mimicked the recollection specific quadratic effect, whereas activity in the anterior parahippocampal gyrus mirrored the familiarity specific linear relationship that was evident in experiment 1. Importantly, the probability of upcoming shocks was linearly coded in the substantia nigra / ventral tegmental area, and pain associated brain regions, such as the insula, responded to shock delivery. Our results demonstrate that anticipating primary aversive events recruits the human mesolimbic system and differentially modulates declarative memory functions via medial temporal lobe structures.

Prior fear conditioning and reward learning interact in fear and reward networks

The ability to flexibly adapt responses to changes in the environment is important for survival. Previous research in humans separately examined the mechanisms underlying acquisition and extinction of aversive and appetitive conditioned responses. It is yet unclear how aversive and appetitive learning interact on a neural level during counterconditioning in humans. This functional magnetic resonance imaging (fMRI) study investigated the interaction of fear conditioning and subsequent reward learning. In the first phase (fear acquisition), images predicted aversive electric shocks or no aversive outcome. In the second phase (counterconditioning), half of the CS+ and CS− were associated with monetary reward in the absence of electric stimulation. The third phase initiated reinstatement of fear through presentation of electric shocks, followed by CS presentation in the absence of shock or reward. Results indicate that participants were impaired at learning the reward contingencies for stimuli previously associated with shock. In the counterconditioning phase, prior fear association interacted with reward representation in the amygdala, where activation was decreased for rewarded compared to unrewarded CS− trials, while there was no reward-related difference in CS+ trials. In the reinstatement phase, an interaction of previous fear association and previous reward status was observed in a reward network consisting of substantia nigra/ventral tegmental area (SN/VTA), striatum and orbitofrontal cortex (OFC), where activation was increased by previous reward association only for CS− but not for CS+ trials. These findings suggest that during counterconditioning, prior fear conditioning interferes with reward learning, subsequently leading to lower activation of the reward network.

MR imaging of the substantia nigra at 7 T enables diagnosis of Parkinson disease

PURPOSE

To evaluate the anatomy of the substantia nigra (SN) in healthy subjects by performing 7-T magnetic resonance (MR) imaging of the SN, and to prospectively define the accuracy of 7-T MR imaging in distinguishing Parkinson disease (PD) patients from healthy subjects on an individual basis.

MATERIALS AND METHODS

The 7-T MR imaging protocol was approved by the Italian Ministry of Health and by the local competent ethics committee. SN anatomy was described ex vivo on a gross brain specimen by using highly resolved proton-density (spin-echo proton density) and gradient-recalled-echo (GRE) images, and in vivo in eight healthy subjects (mean age, 40.1 years) by using GRE three-dimensional multiecho susceptibility-weighted images. After training on appearance of SN in eight healthy subjects, the SN anatomy was evaluated twice by two blinded observers in 13 healthy subjects (mean age, 54.7 years) and in 17 PD patients (mean age, 56.9 years). Deviations from normal SN appearance were described and indicated as abnormal, and both diagnostic accuracy and intra- and interobserver agreement for diagnosis of PD with 7-T MR imaging were calculated.

RESULTS

Three-dimensional multiecho susceptibility-weighted 7-T MR imaging reveals a three-layered organization of the SN allowing readers to distinguish pars compacta ventralis and dorsalis from pars reticulata. The abnormal architecture of the SN allowed a discrimination between PD patients and healthy subjects with sensitivity and specificity of 100% and 96.2% (range, 92.3%-100%), respectively. Intraobserver agreement (κ = 1) and interobserver agreement (κ = 0.932) were excellent.

CONCLUSION

MR imaging at 7-T allows a precise characterization of the SN and visualization of its inner organization. Three-dimensional multiecho susceptibility-weighted images can be used to accurately differentiate healthy subjects from PD patients, which provides a novel diagnostic opportunity.

White noise improves learning by modulating activity in dopaminergic midbrain regions and right superior temporal sulcus

In neural systems, information processing can be facilitated by adding an optimal level of white noise. Although this phenomenon, the so-called stochastic resonance, has traditionally been linked with perception, recent evidence indicates that white noise may also exert positive effects on cognitive functions, such as learning and memory. The underlying neural mechanisms, however, remain unclear. Here, on the basis of recent theories, we tested the hypothesis that auditory white noise, when presented during the encoding of scene images, enhances subsequent recognition memory performance and modulates activity within the dopaminergic midbrain (i.e., substantia nigra/ventral tegmental area, SN/VTA). Indeed, in a behavioral experiment, we can show in healthy humans that auditory white noise-but not control sounds, such as a sinus tone-slightly improves recognition memory. In an fMRI experiment, white noise selectively enhances stimulus-driven phasic activity in the SN/VTA and auditory cortex. Moreover, it induces stronger connectivity between SN/VTA and right STS, which, in addition, exhibited a positive correlation with subsequent memory improvement by white noise. Our results suggest that the beneficial effects of auditory white noise on learning depend on dopaminergic neuromodulation and enhanced connectivity between midbrain regions and the STS-a key player in attention modulation. Moreover, they indicate that white noise could be particularly useful to facilitate learning in conditions where changes of the mesolimbic system are causally related to memory deficits including healthy and pathological aging.

Reprint of: DAT genotype modulates striatal processing and long-term memory for items associated with reward and punishment

Previous studies have shown that appetitive motivation enhances episodic memory formation via a network including the substantia nigra/ventral tegmental area (SN/VTA), striatum and hippocampus. This functional magnetic resonance imaging (fMRI) study now contrasted the impact of aversive and appetitive motivation on episodic long-term memory. Cue pictures predicted monetary reward or punishment in alternating experimental blocks. One day later, episodic memory for the cue pictures was tested. We also investigated how the neural processing of appetitive and aversive motivation and episodic memory were modulated by dopaminergic mechanisms. To that end, participants were selected on the basis of their genotype for a variable number of tandem repeat polymorphism of the dopamine transporter (DAT) gene. The resulting groups were carefully matched for the 5-HTTLPR polymorphism of the serotonin transporter gene. Recognition memory for cues from both motivational categories was enhanced in participants homozygous for the 10-repeat allele of the DAT, the functional effects of which are not known yet, but not in heterozygous subjects. In comparison with heterozygous participants, 10-repeat homozygous participants also showed increased striatal activity for anticipation of motivational outcomes compared to neutral outcomes. In a subsequent memory analysis, encoding activity in striatum and hippocampus was found to be higher for later recognized items in 10-repeat homozygotes compared to 9/10-repeat heterozygotes. These findings suggest that processing of appetitive and aversive motivation in the human striatum involve the dopaminergic system and that dopamine plays a role in memory for both types of motivational information. In accordance with animal studies, these data support the idea that encoding of motivational events depends on dopaminergic processes in the hippocampus.

Structural brain abnormalities in cervical dystonia

Background

Idiopathic cervical dystonia is characterized by involuntary spasms, tremors or jerks. It is not restricted to a disturbance in the basal ganglia system because non-conventional voxel-based MRI morphometry (VBM) and diffusion tensor imaging (DTI) have detected numerous regional changes in the brains of patients.

In this study scans of 24 patients with cervical dystonia and 24 age-and sex-matched controls were analysed using VBM, DTI and magnetization transfer imaging (MTI) using a voxel-based approach and a region-of-interest analysis. Results were correlated with UDRS, TWSTRS and disease duration.

Results

We found structural alterations in the basal ganglia; thalamus; motor cortex; premotor cortex; frontal, temporal and parietal cortices; visual system; cerebellum and brainstem of the patients with dystonia.

Conclusions

Cervical dystonia is a multisystem disease involving several networks such as the motor, sensory and visual systems.

DAT genotype modulates striatal processing and long-term memory for items associated with reward and punishment

Previous studies have shown that appetitive motivation enhances episodic memory formation via a network including the substantia nigra/ventral tegmental area (SN/VTA), striatum and hippocampus. This functional magnetic resonance imaging (fMRI) study now contrasted the impact of aversive and appetitive motivation on episodic long-term memory. Cue pictures predicted monetary reward or punishment in alternating experimental blocks. One day later, episodic memory for the cue pictures was tested. We also investigated how the neural processing of appetitive and aversive motivation and episodic memory were modulated by dopaminergic mechanisms. To that end, participants were selected on the basis of their genotype for a variable number of tandem repeat polymorphism of the dopamine transporter (DAT) gene. The resulting groups were carefully matched for the 5-HTTLPR polymorphism of the serotonin transporter gene. Recognition memory for cues from both motivational categories was enhanced in participants homozygous for the 10-repeat allele of the DAT, the functional effects of which are not known yet, but not in heterozygous subjects. In comparison with heterozygous participants, 10-repeat homozygous participants also showed increased striatal activity for anticipation of motivational outcomes compared to neutral outcomes. In a subsequent memory analysis, encoding activity in striatum and hippocampus was found to be higher for later recognized items in 10-repeat homozygotes compared to 9/10-repeat heterozygotes. These findings suggest that processing of appetitive and aversive motivation in the human striatum involve the dopaminergic system and that dopamine plays a role in memory for both types of motivational information. In accordance with animal studies, these data support the idea that encoding of motivational events depends on dopaminergic processes in the hippocampus.

Motor phenotype and magnetic resonance measures of basal ganglia iron levels in Parkinson's disease

Background

In Parkinson's disease the degree of motor impairment can be classified with respect to tremor dominant and akinetic rigid features. While tremor dominance and akinetic rigidity might represent two ends of a continuum rather than discrete entities, it would be important to have non-invasive markers of any biological differences between them in vivo, to assess disease trajectories and response to treatment, as well as providing insights into the underlying mechanisms contributing to heterogeneity within the Parkinson's disease population.

Methods

Here, we used magnetic resonance imaging to examine whether Parkinson's disease patients exhibit structural changes within the basal ganglia that might relate to motor phenotype. Specifically, we examined volumes of basal ganglia regions, as well as transverse relaxation rate (a putative marker of iron load) and magnetization transfer saturation (considered to index structural integrity) within these regions in 40 individuals.

Results

We found decreased volume and reduced magnetization transfer within the substantia nigra in Parkinson's disease patients compared to healthy controls. Importantly, there was a positive correlation between tremulous motor phenotype and transverse relaxation rate (reflecting iron load) within the putamen, caudate and thalamus.

Conclusions

Our findings suggest that akinetic rigid and tremor dominant symptoms of Parkinson's disease might be differentiated on the basis of the transverse relaxation rate within specific basal ganglia structures. Moreover, they suggest that iron load within the basal ganglia makes an important contribution to motor phenotype, a key prognostic indicator of disease progression in Parkinson's disease.