1
|
Bange M, Herz DM, Ciolac D, Gonzalez-Escamilla G, Groppa S. Modifying the progression of Parkinson's disease through movement interventions: multimodal quantification of underlying mechanisms. Neural Regen Res 2024; 19:1651-1652. [PMID: 38103225 PMCID: PMC10960283 DOI: 10.4103/1673-5374.389633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 10/09/2023] [Accepted: 10/30/2023] [Indexed: 12/18/2023] Open
Affiliation(s)
- Manuel Bange
- Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Damian Marc Herz
- Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Dumitru Ciolac
- Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| |
Collapse
|
2
|
Kawabata K, Krismer F, Heim B, Hussl A, Mueller C, Scherfler C, Gizewski ER, Seppi K, Poewe W. A Blinded Evaluation of Brain Morphometry for Differential Diagnosis of Atypical Parkinsonism. Mov Disord Clin Pract 2024; 11:381-390. [PMID: 38314609 PMCID: PMC10982602 DOI: 10.1002/mdc3.13987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 01/14/2024] [Indexed: 02/06/2024] Open
Abstract
BACKGROUND Advanced imaging techniques have been studied for differential diagnosis between PD, MSA, and PSP. OBJECTIVES This study aims to validate the utility of individual voxel-based morphometry techniques for atypical parkinsonism in a blinded fashion. METHODS Forty-eight healthy controls (HC) T1-WI were used to develop a referential dataset and fit a general linear model after segmentation into gray matter (GM) and white matter (WM) compartments. Segmented GM and WM with PD (n = 96), MSA (n = 18), and PSP (n = 20) were transformed into z-scores using the statistics of referential HC and individual voxel-based z-score maps were generated. An imaging diagnosis was assigned by two independent raters (trained and untrained) blinded to clinical information and final diagnosis. Furthermore, we developed an observer-independent index for ROI-based automated differentiation. RESULTS The diagnostic performance using voxel-based z-score maps by rater 1 and rater 2 for MSA yielded sensitivities: 0.89, 0.94 (95% CI: 0.74-1.00, 0.84-1.00), specificities: 0.94, 0.80 (0.90-0.98, 0.73-0.87); for PSP, sensitivities: 0.85, 0.90 (0.69-1.00, 0.77-1.00), specificities: 0.98, 0.94 (0.96-1.00, 0.90-0.98). Interrater agreement was good for MSA (Cohen's kappa: 0.61), and excellent for PSP (0.84). Receiver operating characteristic analysis using the ROI-based new index showed an area under the curve (AUC): 0.89 (0.77-1.00) for MSA, and 0.99 (0.98-1.00) for PSP. CONCLUSIONS These evaluations provide support for the utility of this imaging technique in the differential diagnosis of atypical parkinsonism demonstrating a remarkably high differentiation accuracy for PSP, suggesting potential use in clinical settings in the future.
Collapse
Affiliation(s)
- Kazuya Kawabata
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Department of NeurologyNagoya University Graduate School of MedicineNagoyaJapan
| | - Florian Krismer
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
| | - Beatrice Heim
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
| | - Anna Hussl
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
| | | | - Christoph Scherfler
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
| | - Elke R. Gizewski
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
- Department of NeuroradiologyMedical University InnsbruckInnsbruckAustria
| | - Klaus Seppi
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
| | - Werner Poewe
- Department of NeurologyMedical University InnsbruckInnsbruckAustria
- Neuroimaging Research Core FacilityMedical University InnsbruckInnsbruckAustria
| |
Collapse
|
3
|
Samanci B, Tan S, Michielse S, Kuijf ML, Temel Y. The habenula in Parkinson's disease: Anatomy, function, and implications for mood disorders - A narrative review. J Chem Neuroanat 2024; 136:102392. [PMID: 38237746 DOI: 10.1016/j.jchemneu.2024.102392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/07/2024] [Accepted: 01/12/2024] [Indexed: 01/31/2024]
Abstract
Parkinson's disease (PD), a widespread neurodegenerative disorder, often coexists with mood disorders. Degeneration of serotonergic neurons in brainstem raphe nuclei have been linked to depression and anxiety. Additionally, the locus coeruleus and its noradrenergic neurons are among the first areas to degenerate in PD and contribute to stress, emotional memory, motor, sensory, and autonomic symptoms. Another brain region of interest is habenula, which is especially related to anti-reward processing, and its function has recently been linked to PD and to mood-related symptoms. There are several neuroimaging studies that investigated role of the habenula in mood disorders. Differences in habenular size and hemispheric symmetry were found in healthy controls compared to individuals with mood disorders. The lateral habenula, as a link between the dopaminergic and serotonergic systems, is thought to contribute to depressive symptoms in PD. However, there is only one imaging study about role of habenula in mood disorders in PD, although the relationship between PD and mood disorders is known. There is little known about habenula pathology in PD but given these observations, the question arises whether habenular dysfunction could play a role in PD and the development of PD-related mood disorders. In this review, we evaluate neuroimaging techniques and studies that investigated the habenula in the context of PD and mood disorders. Future studies are important to understand habenula's role in PD patients with mood disorders. Thus, new potential diagnostic and treatment opportunities would be found for mood disorders in PD.
Collapse
Affiliation(s)
- Bedia Samanci
- School for Mental Health and Neurosciences, Maastricht University, Maastricht, the Netherlands; Behavioral Neurology and Movement Disorders Unit, Department of Neurology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey.
| | - Sonny Tan
- School for Mental Health and Neurosciences, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Antwerp University Hospital, Edegem, Belgium
| | - Stijn Michielse
- School for Mental Health and Neurosciences, Maastricht University, Maastricht, the Netherlands
| | - Mark L Kuijf
- School for Mental Health and Neurosciences, Maastricht University, Maastricht, the Netherlands; Department of Neurology, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Yasin Temel
- School for Mental Health and Neurosciences, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, the Netherlands
| |
Collapse
|
4
|
Alushaj E, Handfield-Jones N, Kuurstra A, Morava A, Menon RS, Owen AM, Sharma M, Khan AR, MacDonald PA. Increased iron in the substantia nigra pars compacta identifies patients with early Parkinson'sdisease: A 3T and 7T MRI study. Neuroimage Clin 2024; 41:103577. [PMID: 38377722 PMCID: PMC10944193 DOI: 10.1016/j.nicl.2024.103577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 12/19/2023] [Accepted: 02/07/2024] [Indexed: 02/22/2024]
Abstract
Degeneration in the substantia nigra (SN) pars compacta (SNc) underlies motor symptoms in Parkinson's disease (PD). Currently, there are no neuroimaging biomarkers that are sufficiently sensitive, specific, reproducible, and accessible for routine diagnosis or staging of PD. Although iron is essential for cellular processes, it also mediates neurodegeneration. MRI can localize and quantify brain iron using magnetic susceptibility, which could potentially provide biomarkers of PD. We measured iron in the SNc, SN pars reticulata (SNr), total SN, and ventral tegmental area (VTA), using quantitative susceptibility mapping (QSM) and R2* relaxometry, in PD patients and age-matched healthy controls (HCs). PD patients, diagnosed within five years of participation and HCs were scanned at 3T (22 PD and 23 HCs) and 7T (17 PD and 21 HCs) MRI. Midbrain nuclei were segmented using a probabilistic subcortical atlas. QSM and R2* values were measured in midbrain subregions. For each measure, groups were contrasted, with Age and Sex as covariates, and receiver operating characteristic (ROC) curve analyses were performed with repeated k-fold cross-validation to test the potential of our measures to classify PD patients and HCs. Statistical differences of area under the curves (AUCs) were compared using the Hanley-MacNeil method (QSM versus R2*; 3T versus 7T MRI). PD patients had higher QSM values in the SNc at both 3T (padj = 0.001) and 7T (padj = 0.01), but not in SNr, total SN, or VTA, at either field strength. No significant group differences were revealed using R2* in any midbrain region at 3T, though increased R2* values in SNc at 7T MRI were marginally significant in PDs compared to HCs (padj = 0.052). ROC curve analyses showed that SNc iron measured with QSM, distinguished early PD patients from HCs at the single-subject level with good diagnostic accuracy, using 3T (mean AUC = 0.83, 95 % CI = 0.82-0.84) and 7T (mean AUC = 0.80, 95 % CI = 0.79-0.81) MRI. Mean AUCs reported here are from averages of tests in the hold-out fold of cross-validated samples. The Hanley-MacNeil method demonstrated that QSM outperforms R2* in discriminating PD patients from HCs at 3T, but not 7T. There were no significant differences between 3T and 7T in diagnostic accuracy of QSM values in SNc. This study highlights the importance of segmenting midbrain subregions, performed here using a standardized atlas, and demonstrates high accuracy of SNc iron measured with QSM at 3T MRI in identifying early PD patients. QSM measures of SNc show potential for inclusion in neuroimaging diagnostic biomarkers of early PD. An MRI diagnostic biomarker of PD would represent a significant clinical advance.
Collapse
Affiliation(s)
- Erind Alushaj
- Department of Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 3K7, Canada; Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada
| | - Nicholas Handfield-Jones
- Department of Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A 3K7, Canada; Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada
| | - Alan Kuurstra
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada; Department of Medical Biophysics, Western University, London, Ontario N6A 3K7, Canada
| | - Anisa Morava
- School of Kinesiology, Faculty of Health Sciences, Western University, London, Ontario N6A 3K7, Canada
| | - Ravi S Menon
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada; Department of Medical Biophysics, Western University, London, Ontario N6A 3K7, Canada
| | - Adrian M Owen
- Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada; Department of Physiology and Pharmacology, Western University, London, Ontario N6A 3K7, Canada
| | - Manas Sharma
- Department of Radiology, Western University, London, Ontario N6A 3K7, Canada; Department of Clinical Neurological Sciences, Western University, London, Ontario N6A 3K7, Canada
| | - Ali R Khan
- Robarts Research Institute, Western University, London, Ontario N6A 3K7, Canada; Department of Medical Biophysics, Western University, London, Ontario N6A 3K7, Canada
| | - Penny A MacDonald
- Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada; Department of Clinical Neurological Sciences, Western University, London, Ontario N6A 3K7, Canada.
| |
Collapse
|
5
|
Savoie FA, Arpin DJ, Vaillancourt DE. Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here? Curr Neuropharmacol 2024; 22:1583-1605. [PMID: 37533246 DOI: 10.2174/1570159x21666230801140648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 01/11/2023] [Accepted: 01/13/2023] [Indexed: 08/04/2023] Open
Abstract
Parkinsonian disorders are a heterogeneous group of incurable neurodegenerative diseases that significantly reduce quality of life and constitute a substantial economic burden. Nuclear imaging (NI) and magnetic resonance imaging (MRI) have played and continue to play a key role in research aimed at understanding and monitoring these disorders. MRI is cheaper, more accessible, nonirradiating, and better at measuring biological structures and hemodynamics than NI. NI, on the other hand, can track molecular processes, which may be crucial for the development of efficient diseasemodifying therapies. Given the strengths and weaknesses of NI and MRI, how can they best be applied to Parkinsonism research going forward? This review aims to examine the effectiveness of NI and MRI in three areas of Parkinsonism research (differential diagnosis, prodromal disease identification, and disease monitoring) to highlight where they can be most impactful. Based on the available literature, MRI can assist with differential diagnosis, prodromal disease identification, and disease monitoring as well as NI. However, more work is needed, to confirm the value of MRI for monitoring prodromal disease and predicting phenoconversion. Although NI can complement or be a substitute for MRI in all the areas covered in this review, we believe that its most meaningful impact will emerge once reliable Parkinsonian proteinopathy tracers become available. Future work in tracer development and high-field imaging will continue to influence the landscape for NI and MRI.
Collapse
Affiliation(s)
- Félix-Antoine Savoie
- Department of Applied Physiology and Kinesiology, Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
| | - David J Arpin
- Department of Applied Physiology and Kinesiology, Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
| | - David E Vaillancourt
- Department of Applied Physiology and Kinesiology, Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| |
Collapse
|
6
|
Vijiaratnam N, Foltynie T. How should we be using biomarkers in trials of disease modification in Parkinson's disease? Brain 2023; 146:4845-4869. [PMID: 37536279 PMCID: PMC10690028 DOI: 10.1093/brain/awad265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 07/18/2023] [Accepted: 07/22/2023] [Indexed: 08/05/2023] Open
Abstract
The recent validation of the α-synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson's disease has formed the backbone for a proposed staging system for incorporation in Parkinson's disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson's disease patients into trials (as distinct from patients with non-Parkinson's disease parkinsonism or non-Parkinson's disease tremors). There remain, however, further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson's disease, namely: optimizing the distinction between different α-synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; a sensitive means of confirming target engagement; and the early prediction of longer-term clinical benefit. For example, levels of CSF proteins such as the lysosomal enzyme β-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer's disease-like pathology (detectable through CSF levels of amyloid-β42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline in Parkinson's disease even in its later stages. The exploitation of additional biomarkers to the α-synuclein seed amplification assay will, therefore, greatly add to our ability to plan trials and assess the disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson's disease. However, correlation with clinical progression does not necessarily equate to causation, and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson's disease.
Collapse
Affiliation(s)
- Nirosen Vijiaratnam
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Thomas Foltynie
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| |
Collapse
|
7
|
Kas A, Rozenblum L, Pyatigorskaya N. Clinical Value of Hybrid PET/MR Imaging: Brain Imaging Using PET/MR Imaging. Magn Reson Imaging Clin N Am 2023; 31:591-604. [PMID: 37741643 DOI: 10.1016/j.mric.2023.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/25/2023]
Abstract
Hybrid PET/MR imaging offers a unique opportunity to acquire MR imaging and PET information during a single imaging session. PET/MR imaging has numerous advantages, including enhanced diagnostic accuracy, improved disease characterization, and better treatment planning and monitoring. It enables the immediate integration of anatomic, functional, and metabolic imaging information, allowing for personalized characterization and monitoring of neurologic diseases. This review presents recent advances in PET/MR imaging and highlights advantages in clinical practice for neuro-oncology, epilepsy, and neurodegenerative disorders. PET/MR imaging provides valuable information about brain tumor metabolism, perfusion, and anatomic features, aiding in accurate delineation, treatment response assessment, and prognostication.
Collapse
Affiliation(s)
- Aurélie Kas
- Department of Nuclear Medicine, Pitié-Salpêtrière Hospital, APHP Sorbonne Université, Paris, France; Sorbonne Université, INSERM, CNRS, Laboratoire d'Imagerie Biomédicale, LIB, Paris F-75006, France.
| | - Laura Rozenblum
- Department of Nuclear Medicine, Pitié-Salpêtrière Hospital, APHP Sorbonne Université, Paris, France; Sorbonne Université, INSERM, CNRS, Laboratoire d'Imagerie Biomédicale, LIB, Paris F-75006, France
| | - Nadya Pyatigorskaya
- Neuroradiology Department, Pitié-Salpêtrière Hospital, APHP Sorbonne Université, Paris, France; Sorbonne Université, UMR S 1127, CNRS UMR 722, Institut du Cerveau, Paris, France
| |
Collapse
|
8
|
Bower AE, Crisomia SJ, Chung JW, Martello JP, Burciu RG. Free water imaging unravels unique patterns of longitudinal structural brain changes in Parkinson's disease subtypes. Front Neurol 2023; 14:1278065. [PMID: 37965163 PMCID: PMC10642764 DOI: 10.3389/fneur.2023.1278065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 10/12/2023] [Indexed: 11/16/2023] Open
Abstract
Background Research shows that individuals with Parkinson's disease (PD) who have a postural instability and gait difficulties (PIGD) subtype have a faster disease progression compared to those with a tremor dominant (TD) subtype. Nevertheless, our understanding of the structural brain changes contributing to these clinical differences remains limited, primarily because many brain imaging techniques are only capable of detecting changes in the later stages of the disease. Objective Free water (FW) has emerged as a robust progression marker in several studies, showing increased values in the posterior substantia nigra that predict symptom worsening. Here, we examined longitudinal FW changes in TD and PIGD across multiple brain regions. Methods Participants were TD and PIGD enrolled in the Parkinson's Progression Marker Initiative (PPMI) study who underwent diffusion MRI at baseline and 2 years later. FW changes were quantified for regions of interest (ROI) within the basal ganglia, thalamus, brainstem, and cerebellum. Results Baseline FW in all ROIs did not differ between groups. Over 2 years, PIGD had a greater percentage increase in FW in the putamen, globus pallidus, and cerebellar lobule V. A logistic regression model incorporating percent change in motor scores and FW in these brain regions achieved 91.4% accuracy in discriminating TD and PIGD, surpassing models based solely on clinical measures (74.3%) or imaging (76.1%). Conclusion The results further suggest the use of FW to study disease progression in PD and provide insight into the differential course of brain changes in early-stage PD subtypes.
Collapse
Affiliation(s)
- Abigail E. Bower
- Department of Kinesiology and Applied Physiology, University of Delaware, Newark, DE, United States
| | - Sophia J. Crisomia
- Department of Kinesiology and Applied Physiology, University of Delaware, Newark, DE, United States
| | - Jae Woo Chung
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Justin P. Martello
- Department of Neurosciences, Christiana Care Health System, Newark, DE, United States
| | - Roxana G. Burciu
- Department of Kinesiology and Applied Physiology, University of Delaware, Newark, DE, United States
| |
Collapse
|
9
|
Alushaj E, Hemachandra D, Kuurstra A, Menon RS, Ganjavi H, Sharma M, Kashgari A, Barr J, Reisman W, Khan AR, MacDonald PA. Subregional analysis of striatum iron in Parkinson's disease and rapid eye movement sleep behaviour disorder. Neuroimage Clin 2023; 40:103519. [PMID: 37797434 PMCID: PMC10568416 DOI: 10.1016/j.nicl.2023.103519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/24/2023] [Accepted: 09/26/2023] [Indexed: 10/07/2023]
Abstract
The loss of dopamine in the striatum underlies motor symptoms of Parkinson's disease (PD). Rapid eye movement sleep behaviour disorder (RBD) is considered prodromal PD and has shown similar neural changes in the striatum. Alterations in brain iron suggest neurodegeneration; however, the literature on striatal iron has been inconsistent in PD and scant in RBD. Toward clarifying pathophysiological changes in PD and RBD, and uncovering possible biomarkers, we imaged 26 early-stage PD patients, 16 RBD patients, and 39 age-matched healthy controls with 3 T MRI. We compared mean susceptibility using quantitative susceptibility mapping (QSM) in the standard striatum (caudate, putamen, and nucleus accumbens) and tractography-parcellated striatum. Diffusion MRI permitted parcellation of the striatum into seven subregions based on the cortical areas of maximal connectivity from the Tziortzi atlas. No significant differences in mean susceptibility were found in the standard striatum anatomy. For the parcellated striatum, the caudal motor subregion, the most affected region in PD, showed lower iron levels compared to healthy controls. Receiver operating characteristic curves using mean susceptibility in the caudal motor striatum showed a good diagnostic accuracy of 0.80 when classifying early-stage PD from healthy controls. This study highlights that tractography-based parcellation of the striatum could enhance sensitivity to changes in iron levels, which have not been consistent in the PD literature. The decreased caudal motor striatum iron was sufficiently sensitive to PD, but not RBD. QSM in the striatum could contribute to development of a multivariate or multimodal biomarker of early-stage PD, but further work in larger datasets is needed to confirm its utility in prodromal groups.
Collapse
Affiliation(s)
- Erind Alushaj
- Department of Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; Western Institute for Neuroscience, Western University, London, Ontario, Canada
| | - Dimuthu Hemachandra
- Robarts Research Institute, Western University, London, Ontario, Canada; School of Biomedical Engineering, Western University, London, Ontario, Canada
| | - Alan Kuurstra
- Robarts Research Institute, Western University, London, Ontario, Canada; Department of Medical Biophysics, Western University, London, Ontario, Canada
| | - Ravi S Menon
- Robarts Research Institute, Western University, London, Ontario, Canada; Department of Medical Biophysics, Western University, London, Ontario, Canada
| | - Hooman Ganjavi
- Department of Psychiatry, Western University, London, Ontario, Canada
| | - Manas Sharma
- Department of Radiology, Western University, London, Ontario, Canada; Department of Clinical Neurological Sciences, Western University, London, Ontario, Canada
| | - Alia Kashgari
- Department of Medicine, Respirology Division, Western University, London, Ontario, Canada
| | - Jennifer Barr
- Department of Psychiatry, Western University, London, Ontario, Canada
| | - William Reisman
- Department of Medicine, Respirology Division, Western University, London, Ontario, Canada
| | - Ali R Khan
- Robarts Research Institute, Western University, London, Ontario, Canada; Department of Medical Biophysics, Western University, London, Ontario, Canada
| | - Penny A MacDonald
- Western Institute for Neuroscience, Western University, London, Ontario, Canada; Department of Clinical Neurological Sciences, Western University, London, Ontario, Canada.
| |
Collapse
|
10
|
Seada SA, van der Eerden AW, Boon AJW, Hernandez-Tamames JA. Quantitative MRI protocol and decision model for a 'one stop shop' early-stage Parkinsonism diagnosis: Study design. Neuroimage Clin 2023; 39:103506. [PMID: 37696098 PMCID: PMC10500558 DOI: 10.1016/j.nicl.2023.103506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 06/21/2023] [Accepted: 09/04/2023] [Indexed: 09/13/2023]
Abstract
Differentiating among early-stage parkinsonisms is a challenge in clinical practice. Quantitative MRI can aid the diagnostic process, but studies with singular MRI techniques have had limited success thus far. Our objective is to develop a multi-modal MRI method for this purpose. In this review we describe existing methods and present a dedicated quantitative MRI protocol, a decision model and a study design to validate our approach ahead of a pilot study. We present example imaging data from patients and a healthy control, which resemble related literature.
Collapse
Affiliation(s)
- Samy Abo Seada
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Anke W van der Eerden
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Agnita J W Boon
- Department of Neurology, Erasmus MC, Rotterdam, The Netherlands
| | - Juan A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands; Department of Imaging Physics, TU Delft, The Netherlands.
| |
Collapse
|
11
|
Droby A, Thaler A, Mirelman A. Imaging Markers in Genetic Forms of Parkinson's Disease. Brain Sci 2023; 13:1212. [PMID: 37626568 PMCID: PMC10452191 DOI: 10.3390/brainsci13081212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/13/2023] [Accepted: 08/14/2023] [Indexed: 08/27/2023] Open
Abstract
Parkinson's disease (PD) is a complex neurodegenerative disorder characterized by motor symptoms such as bradykinesia, rigidity, and resting tremor. While the majority of PD cases are sporadic, approximately 15-20% of cases have a genetic component. Advances in neuroimaging techniques have provided valuable insights into the pathophysiology of PD, including the different genetic forms of the disease. This literature review aims to summarize the current state of knowledge regarding neuroimaging findings in genetic PD, focusing on the most prevalent known genetic forms: mutations in the GBA1, LRRK2, and Parkin genes. In this review, we will highlight the contributions of various neuroimaging modalities, including positron emission tomography (PET), single-photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI), in elucidating the underlying pathophysiological mechanisms and potentially identifying candidate biomarkers for genetic forms of PD.
Collapse
Affiliation(s)
- Amgad Droby
- Laboratory for Early Markers of Neurodegeneration (LEMON), Neurological Institute, Tel Aviv Medical Center, Tel Aviv 6801298, Israel; (A.T.); (A.M.)
- Movement Disorders Unit, Neurological Institute, Tel Aviv Medical Center, Tel Aviv 6423906, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv 39040, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 39040, Israel
| | - Avner Thaler
- Laboratory for Early Markers of Neurodegeneration (LEMON), Neurological Institute, Tel Aviv Medical Center, Tel Aviv 6801298, Israel; (A.T.); (A.M.)
- Movement Disorders Unit, Neurological Institute, Tel Aviv Medical Center, Tel Aviv 6423906, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv 39040, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 39040, Israel
| | - Anat Mirelman
- Laboratory for Early Markers of Neurodegeneration (LEMON), Neurological Institute, Tel Aviv Medical Center, Tel Aviv 6801298, Israel; (A.T.); (A.M.)
- Movement Disorders Unit, Neurological Institute, Tel Aviv Medical Center, Tel Aviv 6423906, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv 39040, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 39040, Israel
| |
Collapse
|
12
|
Wolters AF, Heijmans M, Priovoulos N, Jacobs HIL, Postma AA, Temel Y, Kuijf ML, Michielse S. Neuromelanin related ultra-high field signal intensity of the locus coeruleus differs between Parkinson's disease and controls. Neuroimage Clin 2023; 39:103479. [PMID: 37494758 PMCID: PMC10394012 DOI: 10.1016/j.nicl.2023.103479] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 07/05/2023] [Accepted: 07/18/2023] [Indexed: 07/28/2023]
Abstract
INTRODUCTION Neuromelanin related signal changes in catecholaminergic nuclei are considered as a promising MRI biomarker in Parkinson's disease (PD). Until now, most studies have investigated the substantia nigra (SN), while signal changes might be more prominent in the locus coeruleus (LC). Ultra-high field MRI improves the visualisation of these small brainstem regions and might support the development of imaging biomarkers in PD. OBJECTIVES To compare signal intensity of the SN and LC on Magnetization Transfer MRI between PD patients and healthy controls (HC) and to explore its association with cognitive performance in PD. METHODS This study was conducted using data from the TRACK-PD study, a longitudinal 7T MRI study. A total of 78 early-stage PD patients and 36 HC were included. A mask for the SN and LC was automatically segmented and manually corrected. Neuromelanin related signal intensity of the SN and LC was compared between PD and HC. RESULTS PD participants showed a lower contrast-to-noise ratio (CNR) in the right SN (p = 0.029) and left LC (p = 0.027). After adding age as a confounder, the CNR of the right SN did not significantly differ anymore between PD and HC (p = 0.055). Additionally, a significant positive correlation was found between the SN CNR and memory function. DISCUSSION This study confirms that neuromelanin related signal intensity of the LC differs between early-stage PD patients and HC. No significant difference was found in the SN. This supports the theory of bottom-up disease progression in PD. Furthermore, loss of SN integrity might influence working memory or learning capabilities in PD patients.
Collapse
Affiliation(s)
- Amée F Wolters
- Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands; School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands.
| | - Margot Heijmans
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Nikos Priovoulos
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands; Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Heidi I L Jacobs
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands; Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - Alida A Postma
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre, The Netherlands
| | - Yasin Temel
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands; Department of Neurosurgery, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Mark L Kuijf
- Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands; School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Stijn Michielse
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| |
Collapse
|
13
|
Bae YJ, Choi BS, Kim JM, Ai WA, Yun I, Song YS, Nam Y, Cho SJ, Kim JH. Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake. Neuroradiology 2023:10.1007/s00234-023-03168-z. [PMID: 37209181 DOI: 10.1007/s00234-023-03168-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 05/15/2023] [Indexed: 05/22/2023]
Abstract
PURPOSE Nigrosome imaging using susceptibility-weighted imaging (SWI) and dopamine transporter imaging using 123I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (123I-FP-CIT) single-photon emission computerized tomography (SPECT) can evaluate Parkinsonism. Nigral hyperintensity from nigrosome-1 and striatal dopamine transporter uptake are reduced in Parkinsonism; however, quantification is only possible with SPECT. Here, we aimed to develop a deep-learning-based regressor model that can predict striatal 123I-FP-CIT uptake on nigrosome magnetic resonance imaging (MRI) as a biomarker for Parkinsonism. METHODS Between February 2017 and December 2018, participants who underwent 3 T brain MRI including SWI and 123I-FP-CIT SPECT based on suspected Parkinsonism were included. Two neuroradiologists evaluated the nigral hyperintensity and annotated the centroids of nigrosome-1 structures. We used a convolutional neural network-based regression model to predict striatal specific binding ratios (SBRs) measured via SPECT using the cropped nigrosome images. The correlation between measured and predicted SBRs was evaluated. RESULTS We included 367 participants (203 women (55.3%); age, 69.0 ± 9.2 [range, 39-88] years). Random data from 293 participants (80%) were used for training. In the test set (74 participants [20%]), the measured and predicted 123I-FP-CIT SBRs were significantly lower with the loss of nigral hyperintensity (2.31 ± 0.85 vs. 2.44 ± 0.90) than with intact nigral hyperintensity (4.16 ± 1.24 vs. 4.21 ± 1.35, P < 0.01). The sorted measured 123I-FP-CIT SBRs and the corresponding predicted values were significantly and positively correlated (ρc = 0.7443; 95% confidence interval, 0.6216-0.8314; P < 0.01). CONCLUSION A deep learning-based regressor model effectively predicted striatal 123I-FP-CIT SBRs based on nigrosome MRI with high correlation using manually-measured values, enabling nigrosome MRI as a biomarker for nigrostriatal dopaminergic degeneration in Parkinsonism.
Collapse
Affiliation(s)
- Yun Jung Bae
- Departments of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Byung Se Choi
- Departments of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Jong-Min Kim
- Departments of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173beon-gil, Bundang-gu, 13620, Seongnam, Republic of Korea.
| | - Walid Abdullah Ai
- Division of Computer Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea
| | - Ildong Yun
- Division of Computer Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea
| | - Yoo Sung Song
- Departments of Nuclear Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Yoonho Nam
- Division of Computer Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea
| | - Se Jin Cho
- Departments of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | - Jae Hyoung Kim
- Departments of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| |
Collapse
|
14
|
Outeiro TF, Alcalay RN, Antonini A, Attems J, Bonifati V, Cardoso F, Chesselet MF, Hardy J, Madeo G, McKeith I, Mollenhauer B, Moore DJ, Rascol O, Schlossmacher MG, Soreq H, Stefanis L, Ferreira JJ. Defining the Riddle in Order to Solve It: There Is More Than One "Parkinson's Disease". Mov Disord 2023. [PMID: 37156737 DOI: 10.1002/mds.29419] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 03/30/2023] [Accepted: 04/05/2023] [Indexed: 05/10/2023] Open
Abstract
BACKGROUND More than 200 years after James Parkinsondescribed a clinical syndrome based on his astute observations, Parkinson's disease (PD) has evolved into a complex entity, akin to the heterogeneity of other complex human syndromes of the central nervous system such as dementia, motor neuron disease, multiple sclerosis, and epilepsy. Clinicians, pathologists, and basic science researchers evolved arrange of concepts andcriteria for the clinical, genetic, mechanistic, and neuropathological characterization of what, in their best judgment, constitutes PD. However, these specialists have generated and used criteria that are not necessarily aligned between their different operational definitions, which may hinder progress in solving the riddle of the distinct forms of PD and ultimately how to treat them. OBJECTIVE This task force has identified current in consistencies between the definitions of PD and its diverse variants in different domains: clinical criteria, neuropathological classification, genetic subtyping, biomarker signatures, and mechanisms of disease. This initial effort for "defining the riddle" will lay the foundation for future attempts to better define the range of PD and its variants, as has been done and implemented for other heterogeneous neurological syndromes, such as stroke and peripheral neuropathy. We strongly advocate for a more systematic and evidence-based integration of our diverse disciplines by looking at well-defined variants of the syndrome of PD. CONCLUSION Accuracy in defining endophenotypes of "typical PD" across these different but interrelated disciplines will enable better definition of variants and their stratification in therapeutic trials, a prerequisite for breakthroughs in the era of precision medicine. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Collapse
Affiliation(s)
- Tiago F Outeiro
- Department of Experimental Neurodegeneration, Center for Biostructural Imaging of Neurodegeneration, University Medical Center Goettingen, Goettingen, Germany
- Max Planck Institute for Multidisciplinary Sciences, Goettingen, Germany
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, United Kingdom
| | - Roy N Alcalay
- Neurological Institute, Tel-Aviv Sourasky Medical Center, Tel Aviv, Israel
- Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - Angelo Antonini
- Department of Neurosciences (DNS), Padova University, Padova, Italy
| | - Johannes Attems
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, United Kingdom
| | - Vincenzo Bonifati
- Department of Clinical Genetics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Francisco Cardoso
- Movement Disorders Unit, Neurology Service, Internal Medicine Department, The Federal University of Minas Gerais, Belo Horizonte, Brazil
| | | | - John Hardy
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom
- UK Dementia Research Institute at UCL and Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, United Kingdom
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
- UCL Movement Disorders Centre, University College London, London, United Kingdom
- Institute for Advanced Study, The Hong Kong University of Science and Technology, Hong Kong, China
| | | | - Ian McKeith
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, United Kingdom
| | - Brit Mollenhauer
- Department of Neurology, University Medical Center, Göttingen, Germany
- Paracelsus-Elena-Klinik, Kassel, Germany
| | - Darren J Moore
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, Michigan, USA
| | - Olivier Rascol
- Department of Neurosciences, Clinical Investigation Center CIC 1436, Parkinson Toulouse Expert Centre, NS-Park/FCRIN Network and Neuro Toul COEN Centre, Toulouse University Hospital, INSERM, University of Toulouse 3, Toulouse, France
| | - Michael G Schlossmacher
- Program in Neuroscience and Division of Neurology, The Ottawa Hospital, Ottawa, Ontario, Canada
- University of Ottawa Brain and Mind Research Institute, Ottawa, Ontario, Canada
| | - Hermona Soreq
- The Institute of Life Sciences and The Edmond and Lily Safra Center of Brain Science, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Leonidas Stefanis
- First Department of Neurology, National and Kapodistrian University of Athens Medical School, Athens, Greece
- Biomedical Research Foundation of the Academy of Athens, Athens, Greece
- Laboratory of Clinical Pharmacology and Therapeutics, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
| | - Joaquim J Ferreira
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
- CNS-Campus Neurológico, Torres Vedras, Portugal
| |
Collapse
|
15
|
Bates S, Dumoulin SO, Folkers PJM, Formisano E, Goebel R, Haghnejad A, Helmich RC, Klomp D, van der Kolk AG, Li Y, Nederveen A, Norris DG, Petridou N, Roell S, Scheenen TWJ, Schoonheim MM, Voogt I, Webb A. A vision of 14 T MR for fundamental and clinical science. MAGMA (NEW YORK, N.Y.) 2023; 36:211-225. [PMID: 37036574 PMCID: PMC10088620 DOI: 10.1007/s10334-023-01081-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 03/20/2023] [Accepted: 03/21/2023] [Indexed: 04/11/2023]
Abstract
OBJECTIVE We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set. RESEARCH FIELDS The 14 Tesla system can be considered a 'mesocope': a device capable of measuring on biologically relevant scales. In neuroscience the increased spatial resolution will anatomically resolve all layers of the cortex, cerebellum, subcortical structures, and inner nuclei. Spectroscopic imaging will simultaneously measure excitatory and inhibitory activity, characterizing the excitation/inhibition balance of neural circuits. In medical research (including brain disorders) we will visualize fine-grained patterns of structural abnormalities and relate these changes to functional and molecular changes. The significantly increased spectral resolution will make it possible to detect (dynamic changes in) individual metabolites associated with pathological pathways including molecular interactions and dynamic disease processes. CONCLUSIONS The 14 Tesla system will offer new perspectives in neuroscience and fundamental research. We anticipate that this initiative will usher in a new era of ultra-high-field MR.
Collapse
Affiliation(s)
- Steve Bates
- Tesla Engineering Ltd., Water Lane, Storrington, West Sussex, RH20 3EA, UK
| | - Serge O Dumoulin
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
- Experimental and Applied Psychology, Vrije University Amsterdam, Amsterdam, The Netherlands
- Experimental Psychology, Utrecht University, Utrecht, The Netherlands
| | | | - Elia Formisano
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | | | - Rick C Helmich
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands
- Department of Neurology, Center of Expertise for Parkinson and Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Dennis Klomp
- Radiology Department, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anja G van der Kolk
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yi Li
- Independent Researcher, Magdeburg, Germany
| | - Aart Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - David G Norris
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands.
- Erwin L. Hahn Institute for Magnetic Resonance Imaging UNESCO World Cultural Heritage Zollverein, Kokereiallee 7, Building C84, 45141, Essen, Germany.
- Department of Clinical Neurophysiology (CNPH), Faculty Science and Technology, University of Twente, Enschede, The Netherlands.
| | - Natalia Petridou
- Radiology Department, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Stefan Roell
- Neoscan Solutions GmbH, Joseph-von-Fraunhofer-Str. 6, 39106, Magdeburg, Germany
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Ingmar Voogt
- Wavetronica, Padualaan 8, 3584 CH, Utrecht, The Netherlands
| | - Andrew Webb
- Department of Radiology, C.J. Gorter MRI Centre, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands
| |
Collapse
|
16
|
Sasikumar S, Strafella AP. Structural and Molecular Imaging for Clinically Uncertain Parkinsonism. Semin Neurol 2023; 43:95-105. [PMID: 36878467 DOI: 10.1055/s-0043-1764228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
Abstract
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.
Collapse
Affiliation(s)
- Sanskriti Sasikumar
- Morton and Gloria Shulman Movement Disorder Unit and Edmond J. Safra Parkinson Disease Program, Neurology Division, Department of Medicine, University of Toronto, Toronto Western Hospital, UHN, Ontario, Canada
| | - Antonio P Strafella
- Morton and Gloria Shulman Movement Disorder Unit and Edmond J. Safra Parkinson Disease Program, Neurology Division, Department of Medicine, University of Toronto, Toronto Western Hospital, UHN, Ontario, Canada.,Krembil Brain Institute, University Health Network and Brain Health Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
17
|
Sarasso E, Filippi M, Agosta F. Clinical and MRI features of gait and balance disorders in neurodegenerative diseases. J Neurol 2023; 270:1798-1807. [PMID: 36577818 DOI: 10.1007/s00415-022-11544-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 12/20/2022] [Accepted: 12/21/2022] [Indexed: 12/29/2022]
Abstract
Gait and balance disorders are common signs in several neurodegenerative diseases such as Parkinson's disease, atypical parkinsonism, idiopathic normal pressure hydrocephalus, cerebrovascular disease, dementing disorders and multiple sclerosis. According to each condition, patients present with different gait and balance alterations depending on the structural and functional brain changes through the disease course. In this review, we will summarize the main clinical characteristics of gait and balance disorders in the major neurodegenerative conditions, providing an overview of the significant structural and functional MRI brain alterations underlying these deficits. We also will discuss the role of neurorehabilitation strategies in promoting brain plasticity and gait/balance improvements in these patients.
Collapse
Affiliation(s)
- Elisabetta Sarasso
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal Child Health, University of Genoa, Genoa, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
| |
Collapse
|
18
|
Marxreiter F, Lambrecht V, Mennecke A, Hanspach J, Jukic J, Regensburger M, Herrler J, German A, Kassubek J, Grön G, Müller HP, Laun FB, Dörfler A, Winkler J, Schmidt MA. Parkinson's disease or multiple system atrophy: potential separation by quantitative susceptibility mapping. Ther Adv Neurol Disord 2023; 16:17562864221143834. [PMID: 36846471 PMCID: PMC9950607 DOI: 10.1177/17562864221143834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 11/08/2022] [Indexed: 02/24/2023] Open
Abstract
Background Due to the absence of robust biomarkers, and the low sensitivity and specificity of routine imaging techniques, the differential diagnosis between Parkinson's disease (PD) and multiple system atrophy (MSA) is challenging. High-field magnetic resonance imaging (MRI) opened up new possibilities regarding the analysis of pathological alterations associated with neurodegenerative processes. Recently, we have shown that quantitative susceptibility mapping (QSM) enables visualization and quantification of two major histopathologic hallmarks observed in MSA: reduced myelin density and iron accumulation in the basal ganglia of a transgenic murine model of MSA. It is therefore emerging as a promising imaging modality on the differential diagnosis of Parkinsonian syndromes. Objectives To assess QSM on high-field MRI for the differential diagnosis of PD and MSA. Methods We assessed 23 patients (nine PDs and 14 MSAs) and nine controls using QSM on 3T and 7T MRI scanners at two academic centers. Results We observed increased susceptibility in MSA at 3T in prototypical subcortical and brainstem regions. Susceptibility measures of putamen, pallidum, and substantia nigra reached excellent diagnostic accuracy to separate both synucleinopathies. Increase toward 100% sensitivity and specificity was achieved using 7T MRI in a subset of patients. Magnetic susceptibility correlated with age in all groups, but not with disease duration in MSA. Sensitivity and specificity were particularly high for possible MSA, and reached 100% in the putamen. Conclusion Putaminal susceptibility measures, in particular on ultra-high-field MRI, may distinguish MSA patients from both, PD and controls, allowing an early and sensitive diagnosis of MSA.
Collapse
Affiliation(s)
| | | | - Angelika Mennecke
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany
| | - Jannis Hanspach
- Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Jelena Jukic
- Department of Molecular Neurology, University
Hospital Erlangen, Erlangen, Germany
| | - Martin Regensburger
- Department of Molecular Neurology, University
Hospital Erlangen, Erlangen, Germany,Center for Rare Diseases, University Hospital
Erlangen, Erlangen, Germany
| | - Juergen Herrler
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany,Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Alexander German
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany,Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Jan Kassubek
- Department of Neurology, Ulm University, Ulm,
Germany
| | - Georg Grön
- Department of Psychiatry and Psychotherapy
III, Ulm University, Ulm, Germany
| | | | - Frederik B. Laun
- Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Arnd Dörfler
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany
| | - Juergen Winkler
- Department of Molecular Neurology, University
Hospital Erlangen, Erlangen, Germany,Center for Rare Diseases, University Hospital
Erlangen, Erlangen, Germany
| | - Manuel A. Schmidt
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany
| |
Collapse
|
19
|
Zhang D, Shi Y, Yao J, Zhou L, Wei H, Liu J, Tong Q, Ma L, He H, Wu T. Free-Water Imaging of the Substantia Nigra in GBA Pathogenic Variant Carriers. Mov Disord 2023. [PMID: 36797645 DOI: 10.1002/mds.29356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/30/2023] [Accepted: 02/01/2023] [Indexed: 02/18/2023] Open
Abstract
BACKGROUND Pathogenic variants in the glucocerebrosidase gene (GBA) have been identified as the most common genetic risk factor for Parkinson's disease (PD). However, the features of substantia nigra damage in GBA pathogenic variant carriers remain unclear. OBJECTIVE We aimed to evaluate the microstructural changes in the substantia nigra in non-manifesting GBA pathogenic variant carriers (GBA-NMC) and PD patients with GBA pathogenic variant (GBA-PD) with free-water imaging. METHODS First, we compared free water values in the posterior substantia nigra between non-manifesting non-carriers (NMNC, n = 29), GBA-NMC (n = 26), and GBA-PD (n = 16). Then, free water values in the posterior substantia nigra were compared between GBA-PD and early- (n = 19) and late-onset (n = 40) idiopathic PD (iPD) patients. Furthermore, we examined whether the baseline free water values could predict the progressions of clinical symptoms. RESULTS The free water values in the posterior substantia nigra were significantly higher in the GBA-NMC and GBA-PD groups compared to NMNC, and were significantly increased in the GBA-PD group than both early- and late-onset iPD. Free water values in the posterior substantia nigra could predict the progression of anxiety and cognitive decline in GBA-NMC and GBA-PD groups. CONCLUSIONS We demonstrate that free water values are elevated in the substantia nigra and predict the development of non-motor symptoms in GBA-NMC and GBA-PD. Our findings demonstrate that a significant nigral impairment already exists in GBA-NMC, and nigral injury may be more severe in GBA-PD than in iPD. These results support that free-water imaging can as a potential early marker of substantia nigra damage. © 2023 International Parkinson and Movement Disorder Society.
Collapse
Affiliation(s)
- Dongling Zhang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Yuting Shi
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Junye Yao
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Liche Zhou
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jun Liu
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiqi Tong
- Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, China
| | - Lingyan Ma
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.,School of Physics, Zhejiang University, Hangzhou, China
| | - Tao Wu
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| |
Collapse
|
20
|
Resting-state network connectivity changes in drug-naive Parkinson's disease patients with probable REM sleep behavior disorder. J Neural Transm (Vienna) 2023; 130:43-51. [PMID: 36474090 DOI: 10.1007/s00702-022-02565-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 11/01/2022] [Indexed: 12/12/2022]
Abstract
Epidemiological studies have shown that Parkinson's disease (PD) patients with probable REM sleep behavior disorder (pRBD) present an increased risk of worse cognitive progression over the disease course. The aim of this study was to investigate, using resting-state functional MRI (RS-fMRI), the functional connectivity (FC) changes associated with the presence of pRBD in a cohort of newly diagnosed, drug-naive and cognitively unimpaired PD patients compared to healthy controls (HC). Fifty-six drug-naïve patients (25 PD-pRBD+ and 31 PD-pRBD-) and 23 HC underwent both RS-fMRI and clinical assessment. Single-subject and group-level independent component analysis was used to analyze intra- and inter-network FC differences within the major large-scale neurocognitive networks, namely the default mode (DMN), frontoparietal (FPN), salience (SN) and executive-control (ECN) networks. Widespread FC changes were found within the most relevant neurocognitive networks in PD patients compared to HC. Moreover, PD-pRBD+ patients showed abnormal intrinsic FC within the DMN, ECN and SN compared to PD-pRBD-. Finally, PD-pRBD+ patients showed functional decoupling between left and right FPN. In the present study, we revealed that FC changes within the most relevant neurocognitive networks are already detectable in early drug-naïve PD patients, even in the absence of clinical overt cognitive impairment. These changes are even more evident in PD patients with RBD, potentially leading to profound impairment in cognitive processing and cognitive/behavioral integration, as well as to fronto-striatal maladaptive compensatory mechanisms.
Collapse
|
21
|
Zhang D, Yao J, Sun J, Tong Q, Zhu S, Wang J, Chen L, Ma J, He H, Wu T. Quantitative Susceptibility Mapping and Free Water Imaging of Substantia Nigra in Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2022; 12:2469-2478. [PMID: 36404557 DOI: 10.3233/jpd-223499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND The utility of imaging methods to detect iron content in the substantia nigra pars compacta (SNc) and free water imaging in the posterior substantia nigra (pSN) has the potential to be imaging markers for the detection of Parkinson's disease (PD). OBJECTIVE This study aimed to compare the discriminative power of above methods, and whether the combination can improve the diagnostic potential of PD. METHODS Quantitative susceptibility mapping (QSM) and diffusion-weighted data were obtained from 41 healthy controls (HC), 37 patients with idiopathic REM sleep behavior disorder (RBD), and 65 patients with PD. Mean QSM values of bilateral SNc and mean isotropic volume fraction (Viso) values of bilateral pSN (mean QSM|Viso values of bilateral SNc|pSN) were separately calculated and compared among the groups. RESULTS Mean QSM|Viso values of bilateral SNc|pSN were significantly higher for RBD and PD patients compared to HC and were significantly higher in PD patients than in RBD patients. The power of the mean QSM|Viso values of bilateral SNc|pSN and combined mean QSM and Viso values was 0.873, 0.870, and 0.961 in discriminating PD and HC, 0.779, 0.719, and 0.864 in discriminating RBD from HC, 0.634, 0.636, and 0.689 in discriminating PD and RBD patients. CONCLUSION QSM and free water imaging have similar discriminative power in the detection of prodromal and clinical PD, while combination of these two methods increases discriminative power. Our findings suggest that the combination of QSM and free water imaging has the potential to become an imaging marker for the diagnosis of PD.
Collapse
Affiliation(s)
- Dongling Zhang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Junye Yao
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Junyan Sun
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Qiqi Tong
- Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, Zhejiang, China
| | - Silei Zhu
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Junling Wang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Lili Chen
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jinghong Ma
- Department of Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.,School of Physics, Zhejiang University, Hangzhou, Zhejiang, China
| | - Tao Wu
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| |
Collapse
|
22
|
Du H, Wang Q, Liang Z, Li Q, Li F, Ling D. Fabrication of magnetic nanoprobes for ultrahigh-field magnetic resonance imaging. NANOSCALE 2022; 14:17483-17499. [PMID: 36413075 DOI: 10.1039/d2nr04979a] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Ultrahigh-field magnetic resonance imaging (UHF-MRI) has been attracting tremendous attention in biomedical imaging owing to its high signal-to-noise ratio, superior spatial resolution, and fast imaging speed. However, at UHF-MRI, there is a lack of proper imaging probes that can impart superior imaging sensitivity of disease lesions because conventional contrast agents generally produce pronounced susceptibility artifacts and induce very strong T2 decay effects, thus hindering satisfactory imaging performance. This review focused on the recent development of high-performance nanoprobes that can improve the sensitivity and specificity of UHF-MRI. Firstly, the contrast enhancement mechanism of nanoprobes at UHF-MRI has been elucidated. In particular, the strategies for modulating nanoprobe performance, including size effects, metal alloying and magnetic-dopant effects, surface effects, and stimuli-response regulation, have been comprehensively discussed. Furthermore, we illustrate the remarkable advances in the design of UHF-MRI nanoprobes for medical diagnosis, such as early-stage primary tumor and metastasis imaging, angiography, and dynamic monitoring of biosignaling factors in vivo. Finally, we provide a summary and outlook on the development of cutting-edge UHF-MRI nanoprobes for advanced biomedical imaging.
Collapse
Affiliation(s)
- Hui Du
- Frontiers Science Center for Transformative Molecules, School of Chemistry and Chemical Engineering, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, PR China.
| | - Qiyue Wang
- Frontiers Science Center for Transformative Molecules, School of Chemistry and Chemical Engineering, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, PR China.
- World Laureates Association (WLA) Laboratories, Shanghai 201203, PR China
| | - Zeyu Liang
- Frontiers Science Center for Transformative Molecules, School of Chemistry and Chemical Engineering, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, PR China.
- World Laureates Association (WLA) Laboratories, Shanghai 201203, PR China
| | - Qilong Li
- Frontiers Science Center for Transformative Molecules, School of Chemistry and Chemical Engineering, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, PR China.
- World Laureates Association (WLA) Laboratories, Shanghai 201203, PR China
| | - Fangyuan Li
- Institute of Pharmaceutics, College of Pharmaceutical Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, PR China.
- Hangzhou Institute of Innovative Medicine, Zhejiang University, Hangzhou 310058, PR China
| | - Daishun Ling
- Frontiers Science Center for Transformative Molecules, School of Chemistry and Chemical Engineering, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, PR China.
- Institute of Pharmaceutics, College of Pharmaceutical Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, PR China.
- Hangzhou Institute of Innovative Medicine, Zhejiang University, Hangzhou 310058, PR China
- World Laureates Association (WLA) Laboratories, Shanghai 201203, PR China
| |
Collapse
|
23
|
Valli M, Uribe C, Mihaescu A, Strafella AP. Neuroimaging of rapid eye movement sleep behavior disorder and its relation to Parkinson's disease. J Neurosci Res 2022; 100:1815-1833. [DOI: 10.1002/jnr.25099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 05/10/2022] [Accepted: 06/08/2022] [Indexed: 11/12/2022]
Affiliation(s)
- Mikaeel Valli
- Brain Health Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health University of Toronto Toronto Ontario Canada
- Division of Brain, Imaging and Behaviour – Systems Neuroscience, Krembil Brain Institute, UHN University of Toronto Toronto Ontario Canada
- Institute of Medical Science University of Toronto Toronto Ontario Canada
| | - Carme Uribe
- Brain Health Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health University of Toronto Toronto Ontario Canada
- Medical Psychology Unit, Department of Medicine, Institute of Neuroscience University of Barcelona Barcelona Spain
| | - Alexander Mihaescu
- Brain Health Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health University of Toronto Toronto Ontario Canada
- Division of Brain, Imaging and Behaviour – Systems Neuroscience, Krembil Brain Institute, UHN University of Toronto Toronto Ontario Canada
- Institute of Medical Science University of Toronto Toronto Ontario Canada
| | - Antonio P. Strafella
- Brain Health Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health University of Toronto Toronto Ontario Canada
- Division of Brain, Imaging and Behaviour – Systems Neuroscience, Krembil Brain Institute, UHN University of Toronto Toronto Ontario Canada
- Institute of Medical Science University of Toronto Toronto Ontario Canada
- Edmond J. Safra Parkinson Disease Program & Morton and Gloria Shulman Movement Disorder Unit, Neurology Division, Department of Medicine, Toronto Western Hospital, UHN University of Toronto Toronto Ontario Canada
| |
Collapse
|
24
|
Okada T, Fujimoto K, Fushimi Y, Akasaka T, Thuy DHD, Shima A, Sawamoto N, Oishi N, Zhang Z, Funaki T, Nakamoto Y, Murai T, Miyamoto S, Takahashi R, Isa T. Neuroimaging at 7 Tesla: a pictorial narrative review. Quant Imaging Med Surg 2022; 12:3406-3435. [PMID: 35655840 PMCID: PMC9131333 DOI: 10.21037/qims-21-969] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 02/05/2022] [Indexed: 01/26/2024]
Abstract
Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.
Collapse
Affiliation(s)
- Tomohisa Okada
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Koji Fujimoto
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Thai Akasaka
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Dinh H. D. Thuy
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Atsushi Shima
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Nobukatsu Sawamoto
- Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Oishi
- Medial Innovation Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Zhilin Zhang
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takeshi Funaki
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tadashi Isa
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| |
Collapse
|
25
|
Peralta C, Strafella AP, van Eimeren T, Ceravolo R, Seppi K, Kaasinen V, Arena JE, Lehericy S. Pragmatic Approach on Neuroimaging Techniques for the Differential Diagnosis of Parkinsonisms. Mov Disord Clin Pract 2022; 9:6-19. [PMID: 35005060 DOI: 10.1002/mdc3.13354] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 08/26/2021] [Accepted: 09/16/2021] [Indexed: 12/17/2022] Open
Abstract
Background Rapid advances in neuroimaging technologies in the exploration of the living human brain also apply to movement disorders. However, the accurate diagnosis of Parkinson's disease (PD) and atypical parkinsonian disorders (APDs) still remains a challenge in daily practice. Methods We review the literature and our own experience as the Movement Disorder Society-Neuroimaging Study Group in Movement Disorders with the aim of providing a practical approach to the use of imaging technologies in the clinical setting. Results The enormous amount of articles published so far and our increasing recognition of imaging technologies contrast with a lack of imaging protocols and updated algorithms for differential diagnosis. The distinctive pathological involvement in different brain structures and the correlation with imaging findings obtained with magnetic resonance, positron emission tomography, or single-photon emission computed tomography illustrate what qualitative and quantitative measures may be useful in the clinical setting. Conclusion We delineate a pragmatic approach to discuss imaging technologies, updated imaging algorithms, and their implications for differential diagnoses in PD and APDs.
Collapse
Affiliation(s)
- Cecilia Peralta
- Movement Disorders Clinic, Neuroscience Department Hospital Universitario CEMIC, Centro de Educación Médica e Investigaciones Clínicas "Norberto Quirno" Buenos Aires Argentina
| | - Antonio P Strafella
- Morton and Gloria Shulman Movement Disorder Unit & E.J. Safra Parkinson Disease Program, Division of Neurology/Department of Medicine, Toronto Western Hospital University Health Network Toronto Ontario Canada.,Krembil Brain Institute, University Health Network Toronto Ontario Canada.,Brain Health Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health University of Toronto Toronto Ontario Canada
| | - Thilo van Eimeren
- Department of Nuclear Medicine University of Cologne Cologne Germany.,Department of Neurology University of Cologne Cologne Germany
| | - Roberto Ceravolo
- Department of Clinical and Experimental Medicine University of Pisa Pisa Italy
| | - Klaus Seppi
- Department of Neurology Medical University Innsbruck Innsbruck Austria
| | - Valtteri Kaasinen
- Clinical Neurosciences University of Turku and Turku University Hospital Turku Finland
| | - Julieta E Arena
- Movement Disorders Section, Department of Neurology, Fleni Buenos Aires Argentina
| | - Stephane Lehericy
- Institut du Cerveau-ICM, Team "Movement Investigations and Therapeutics," Centre de NeuroImagerie de Recherche-CENIR, Neuroradiology Department Paris France.,Sorbonne Université, INSERM U, Institut national de la santé et de la recherche médicale 1127, National Centre for Scientific Research, Unité mixte de recherche 7225 Paris France.,Department of Neuroradiology Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris Paris France
| | | |
Collapse
|
26
|
Heijmans M, Wolters AF, Temel Y, Kuijf ML, Michielse S. Comparison of Olfactory Tract Diffusion Measures Between Early Stage Parkinson's Disease Patients and Healthy Controls Using Ultra-High Field MRI. JOURNAL OF PARKINSON'S DISEASE 2022; 12:2161-2170. [PMID: 36093714 PMCID: PMC9661345 DOI: 10.3233/jpd-223349] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 08/16/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND MRI is a valuable method to assist in the diagnostic work-up of Parkinson's disease (PD). The olfactory tract (OT) has been proposed as a potential MRI biomarker for distinguishing PD patients from healthy controls. OBJECTIVE This study aims to further investigate whether diffusion measures of the OT differ between early stage PD patients and healthy controls. METHODS Twenty hyposmic/anosmic PD patients, 65 normosmic PD patients, and 36 normosmic healthy controls were evaluated and a 7T diffusion weighted image scan was acquired. Manual seed regions of interest were drawn in the OT region. Tractography of the OT was performed using a deterministic streamlines algorithm. Diffusion measures (fractional anisotropy and mean- radial- and axial diffusivity) of the generated streamlines were compared between groups. RESULTS Diffusion measures did not differ between PD patients compared to healthy controls and between hyposmic/anosmic PD patients, normosmic PD patients, and normosmic healthy controls. A positive correlation was found between age and mean- and axial diffusivity within the hyposmic/anosmic PD subgroup, but not in the normosmic groups. A positive correlation was found between MDS-UPDRSIII scores and fractional anisotropy. CONCLUSION This study showed that fiber tracking of the OT was feasible in both early stage PD and healthy controls using 7T diffusion weighted imaging data. However, 7T MRI diffusion measures of the OT are not useful as an early clinical biomarker for PD. Future work is needed to clarify the role of other OT measurements as a biomarker for PD and its different subgroups.
Collapse
Affiliation(s)
- Margot Heijmans
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Amée F. Wolters
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Yasin Temel
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Department of Neurosurgery, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Mark L. Kuijf
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Stijn Michielse
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| |
Collapse
|
27
|
Ma B, Zhang F, Ma B. Self-Attention-Guided Recurrent Neural Network and Motion Perception for Intelligent Prediction of Chronic Diseases. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:6382619. [PMID: 34745506 PMCID: PMC8566041 DOI: 10.1155/2021/6382619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 09/14/2021] [Accepted: 09/16/2021] [Indexed: 11/18/2022]
Abstract
Parkinson's disease is a common chronic disease that affects a large number of people. In the real world, however, Parkinson's disease can result in a loss of physical performance, which is classified as a movement disorder by clinicians. Parkinson's disease is currently diagnosed primarily through clinical symptoms, which are highly dependent on clinician experience. As a result, there is a need for effective early detection methods. Traditional machine learning algorithms filter out many inherently relevant features in the process of dimensionality reduction and feature classification, lowering the classification model's performance. To solve this problem and ensure high correlation between features while reducing dimensionality to achieve the goal of improving classification performance, this paper proposes a recurrent neural network classification model based on self attention and motion perception. Using a combination of self-attention mechanism and recurrent neural network, as well as wearable inertial sensors, the model classifies and trains the five brain area features extracted from MRI and DTI images (cerebral gray matter, white matter, cerebrospinal fluid density, and so on). Clinical and exercise data can be combined to produce characteristic parameters that can be used to describe movement sluggishness. The experimental results show that the model proposed in this paper improves the recognition performance of Parkinson's disease, which is better than the compared methods by 2.45% to 12.07%.
Collapse
Affiliation(s)
- Baojuan Ma
- Physical Education Department, Shijiazhuang Information Engineering Vocational College, Shijiazhuang 05000, Hebei, China
| | - Fengyan Zhang
- Physical Education Department, Shijiazhuang Information Engineering Vocational College, Shijiazhuang 05000, Hebei, China
| | - Baoling Ma
- Physical Education and Health College, Hebei Normal University of Science and Technology, Qinhuangdao 066004, Hebei, China
| |
Collapse
|
28
|
Mitchell T, Lehéricy S, Chiu SY, Strafella AP, Stoessl AJ, Vaillancourt DE. Emerging Neuroimaging Biomarkers Across Disease Stage in Parkinson Disease: A Review. JAMA Neurol 2021; 78:1262-1272. [PMID: 34459865 PMCID: PMC9017381 DOI: 10.1001/jamaneurol.2021.1312] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Importance Imaging biomarkers in Parkinson disease (PD) are increasingly important for monitoring progression in clinical trials and also have the potential to improve clinical care and management. This Review addresses a critical need to make clear the temporal relevance for diagnostic and progression imaging biomarkers to be used by clinicians and researchers over the clinical course of PD. Magnetic resonance imaging (diffusion imaging, neuromelanin-sensitive imaging, iron-sensitive imaging, T1-weighted imaging), positron emission tomography/single-photon emission computed tomography dopaminergic, serotonergic, and cholinergic imaging as well as metabolic and cerebral blood flow network neuroimaging biomarkers in the preclinical, prodromal, early, and moderate to late stages are characterized. Observations If a clinical trial is being carried out in the preclinical and prodromal stages, potentially useful disease-state biomarkers include dopaminergic imaging of the striatum; metabolic imaging; free-water, neuromelanin-sensitive, and iron-sensitive imaging in the substantia nigra; and T1-weighted structural magnetic resonance imaging. Disease-state biomarkers that can distinguish atypical parkinsonisms are metabolic imaging, free-water imaging, and T1-weighted imaging; dopaminergic imaging and other molecular imaging track progression in prodromal patients, whereas other established progression biomarkers need to be evaluated in prodromal cohorts. Progression in early-stage PD can be monitored using dopaminergic imaging in the striatum, metabolic imaging, and free-water and neuromelanin-sensitive imaging in the posterior substantia nigra. Progression in patients with moderate to late-stage PD can be monitored using free-water imaging in the anterior substantia nigra, R2* of substantia nigra, and metabolic imaging. Cortical thickness and gyrification might also be useful markers or predictors of progression. Dopaminergic imaging and free-water imaging detect progression over 1 year, whereas other modalities detect progression over 18 months or longer. The reliability of progression biomarkers varies with disease stage, whereas disease-state biomarkers are relatively consistent in individuals with preclinical, prodromal, early, and moderate to late-stage PD. Conclusions and Relevance Imaging biomarkers for various stages of PD are readily available to be used as outcome measures in clinical trials and are potentially useful in multimodal combination with routine clinical assessment. This Review provides a critically important template for considering disease stage when implementing diagnostic and progression biomarkers in both clinical trials and clinical care settings.
Collapse
Affiliation(s)
- Trina Mitchell
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville
| | - Stéphane Lehéricy
- Paris Brain Institute, Centre de NeuroImagerie de Recherche, INSERM 1127, CNRS 7225, Sorbonne Université, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | - Shannon Y Chiu
- Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville
| | - Antonio P Strafella
- Division of Brain, Imaging and Behaviour-Systems Neuroscience, Krembil Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada
- Research Imaging Centre, Campbell Family Mental Health, Toronto, Ontario, Canada
- Morton and Gloria Shulman Movement Disorder Unit and E.J. Safra Parkinson Disease Program, Neurology Division, Department of Medicine, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - A Jon Stoessl
- Pacific Parkinson's Research Centre and Parkinson's Foundation Centre of Excellence, Division of Neurology and Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - David E Vaillancourt
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville
- Fixel Institute for Neurological Diseases, Department of Neurology, University of Florida, Gainesville
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville
| |
Collapse
|
29
|
Hallett M, DelRosso LM, Elble R, Ferri R, Horak FB, Lehericy S, Mancini M, Matsuhashi M, Matsumoto R, Muthuraman M, Raethjen J, Shibasaki H. Evaluation of movement and brain activity. Clin Neurophysiol 2021; 132:2608-2638. [PMID: 34488012 PMCID: PMC8478902 DOI: 10.1016/j.clinph.2021.04.023] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 04/07/2021] [Accepted: 04/25/2021] [Indexed: 11/25/2022]
Abstract
Clinical neurophysiology studies can contribute important information about the physiology of human movement and the pathophysiology and diagnosis of different movement disorders. Some techniques can be accomplished in a routine clinical neurophysiology laboratory and others require some special equipment. This review, initiating a series of articles on this topic, focuses on the methods and techniques. The methods reviewed include EMG, EEG, MEG, evoked potentials, coherence, accelerometry, posturography (balance), gait, and sleep studies. Functional MRI (fMRI) is also reviewed as a physiological method that can be used independently or together with other methods. A few applications to patients with movement disorders are discussed as examples, but the detailed applications will be the subject of other articles.
Collapse
Affiliation(s)
- Mark Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA.
| | | | - Rodger Elble
- Department of Neurology, Southern Illinois University School of Medicine, Springfield, IL, USA
| | | | - Fay B Horak
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
| | - Stephan Lehericy
- Paris Brain Institute (ICM), Centre de NeuroImagerie de Recherche (CENIR), Team "Movement, Investigations and Therapeutics" (MOV'IT), INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
| | - Martina Mancini
- Department of Neurology, Oregon Health & Science University, Portland, OR, USA
| | - Masao Matsuhashi
- Department of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate, School of Medicine, Japan
| | - Riki Matsumoto
- Division of Neurology, Kobe University Graduate School of Medicine, Japan
| | - Muthuraman Muthuraman
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Jan Raethjen
- Neurology Outpatient Clinic, Preusserstr. 1-9, 24105 Kiel, Germany
| | | |
Collapse
|
30
|
Düzel E, Costagli M, Donatelli G, Speck O, Cosottini M. Studying Alzheimer disease, Parkinson disease, and amyotrophic lateral sclerosis with 7-T magnetic resonance. Eur Radiol Exp 2021; 5:36. [PMID: 34435242 PMCID: PMC8387546 DOI: 10.1186/s41747-021-00221-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 04/07/2021] [Indexed: 12/18/2022] Open
Abstract
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.
Collapse
Affiliation(s)
- Emrah Düzel
- Otto-von-Guericke University Magdeburg, Magdeburg, Germany. .,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany. .,University College London, London, UK.
| | - Mauro Costagli
- IRCCS Stella Maris, Pisa, Italy.,University of Genoa, Genova, Italy
| | - Graziella Donatelli
- Fondazione Imago 7, Pisa, Italy.,Azienda Ospedaliero Universitaria Pisana, Pisa, Italy
| | - Oliver Speck
- Otto-von-Guericke University Magdeburg, Magdeburg, Germany.,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Mirco Cosottini
- Azienda Ospedaliero Universitaria Pisana, Pisa, Italy.,University of Pisa, Pisa, Italy
| |
Collapse
|
31
|
Modulation of Working Memory and Resting-State fMRI by tDCS of the Right Frontoparietal Network. Neural Plast 2021; 2021:5594305. [PMID: 34349797 PMCID: PMC8328716 DOI: 10.1155/2021/5594305] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 06/25/2021] [Accepted: 07/09/2021] [Indexed: 11/20/2022] Open
Abstract
Many cognitive functions, including working memory, are processed within large-scale brain networks. We targeted the right frontoparietal network (FPN) with one session of transcranial direct current stimulation (tDCS) in an attempt to modulate the cognitive speed of a visual working memory task (WMT) in 27 young healthy subjects using a double-blind crossover design. We further explored the neural underpinnings of induced changes by performing resting-state fMRI prior to and immediately after each stimulation session with the main focus on the interaction between a task-positive FPN and a task-negative default mode network (DMN). Twenty minutes of 2 mA anodal tDCS was superior to sham stimulation in terms of cognitive speed manipulation of a subtask with processing of objects and tools in unconventional views (i.e., the higher cognitive load subtask of the offline WMT). This result was linked to the magnitude of resting-state functional connectivity decreases between the stimulated FPN seed and DMN seeds. We provide the first evidence for the action reappraisal mechanism of object and tool processing. Modulation of cognitive speed of the task by tDCS was reflected by FPN-DMN cross-talk changes.
Collapse
|
32
|
Bae YJ, Kim JM, Sohn CH, Choi JH, Choi BS, Song YS, Nam Y, Cho SJ, Jeon B, Kim JH. Imaging the Substantia Nigra in Parkinson Disease and Other Parkinsonian Syndromes. Radiology 2021; 300:260-278. [PMID: 34100679 DOI: 10.1148/radiol.2021203341] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Parkinson disease is characterized by dopaminergic cell loss in the substantia nigra of the midbrain. There are various imaging markers for Parkinson disease. Recent advances in MRI have enabled elucidation of the underlying pathophysiologic changes in the nigral structure. This has contributed to accurate and early diagnosis and has improved disease progression monitoring. This article aims to review recent developments in nigral imaging for Parkinson disease and other parkinsonian syndromes, including nigrosome imaging, neuromelanin imaging, quantitative iron mapping, and diffusion-tensor imaging. In particular, this article examines nigrosome imaging using 7-T MRI and 3-T susceptibility-weighted imaging. Finally, this article discusses volumetry and its clinical importance related to symptom manifestation. This review will improve understanding of recent advancements in nigral imaging of Parkinson disease. Published under a CC BY 4.0 license.
Collapse
Affiliation(s)
- Yun Jung Bae
- From the Departments of Radiology (Y.J.B., B.S.C., S.J.C., J.H.K.), Neurology (J.M.K., J.H.C.), and Nuclear Medicine (Y.S.S.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 173-82 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea; Departments of Radiology (C.H.S.) and Neurology (B.J.), Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea; and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.)
| | - Jong-Min Kim
- From the Departments of Radiology (Y.J.B., B.S.C., S.J.C., J.H.K.), Neurology (J.M.K., J.H.C.), and Nuclear Medicine (Y.S.S.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 173-82 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea; Departments of Radiology (C.H.S.) and Neurology (B.J.), Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea; and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.)
| | - Chul-Ho Sohn
- From the Departments of Radiology (Y.J.B., B.S.C., S.J.C., J.H.K.), Neurology (J.M.K., J.H.C.), and Nuclear Medicine (Y.S.S.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 173-82 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea; Departments of Radiology (C.H.S.) and Neurology (B.J.), Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea; and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.)
| | - Ji-Hyun Choi
- From the Departments of Radiology (Y.J.B., B.S.C., S.J.C., J.H.K.), Neurology (J.M.K., J.H.C.), and Nuclear Medicine (Y.S.S.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 173-82 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea; Departments of Radiology (C.H.S.) and Neurology (B.J.), Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea; and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.)
| | - Byung Se Choi
- From the Departments of Radiology (Y.J.B., B.S.C., S.J.C., J.H.K.), Neurology (J.M.K., J.H.C.), and Nuclear Medicine (Y.S.S.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 173-82 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea; Departments of Radiology (C.H.S.) and Neurology (B.J.), Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea; and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.)
| | - Yoo Sung Song
- From the Departments of Radiology (Y.J.B., B.S.C., S.J.C., J.H.K.), Neurology (J.M.K., J.H.C.), and Nuclear Medicine (Y.S.S.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 173-82 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea; Departments of Radiology (C.H.S.) and Neurology (B.J.), Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea; and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.)
| | - Yoonho Nam
- From the Departments of Radiology (Y.J.B., B.S.C., S.J.C., J.H.K.), Neurology (J.M.K., J.H.C.), and Nuclear Medicine (Y.S.S.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 173-82 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea; Departments of Radiology (C.H.S.) and Neurology (B.J.), Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea; and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.)
| | - Se Jin Cho
- From the Departments of Radiology (Y.J.B., B.S.C., S.J.C., J.H.K.), Neurology (J.M.K., J.H.C.), and Nuclear Medicine (Y.S.S.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 173-82 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea; Departments of Radiology (C.H.S.) and Neurology (B.J.), Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea; and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.)
| | - Beomseok Jeon
- From the Departments of Radiology (Y.J.B., B.S.C., S.J.C., J.H.K.), Neurology (J.M.K., J.H.C.), and Nuclear Medicine (Y.S.S.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 173-82 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea; Departments of Radiology (C.H.S.) and Neurology (B.J.), Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea; and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.)
| | - Jae Hyoung Kim
- From the Departments of Radiology (Y.J.B., B.S.C., S.J.C., J.H.K.), Neurology (J.M.K., J.H.C.), and Nuclear Medicine (Y.S.S.), Seoul National University Bundang Hospital, Seoul National University College of Medicine, 173-82 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, Republic of Korea; Departments of Radiology (C.H.S.) and Neurology (B.J.), Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea; and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (Y.N.)
| |
Collapse
|
33
|
Østergaard FG, Skoven CS, Wade AR, Siebner HR, Laursen B, Christensen KV, Dyrby TB. No Detectable Effect on Visual Responses Using Functional MRI in a Rodent Model of α-Synuclein Expression. eNeuro 2021; 8:ENEURO.0516-20.2021. [PMID: 33958374 PMCID: PMC8143025 DOI: 10.1523/eneuro.0516-20.2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 04/23/2021] [Accepted: 04/30/2021] [Indexed: 12/03/2022] Open
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disease that is typically diagnosed late in its progression. There is a need for biomarkers suitable for monitoring the disease progression at earlier stages to guide the development of novel neuroprotective therapies. One potential biomarker, α-synuclein, has been found in both the familial cases of PD, as well as the sporadic cases and is considered a key feature of PD. α-synuclein is naturally present in the retina, and it has been suggested that early symptoms of the visual system may be used as a biomarker for PD. Here, we use a viral vector to induce a unilateral expression of human wild-type α-synuclein in rats as a mechanistic model of protein aggregation in PD. We employed functional magnetic resonance imaging (fMRI) to investigate whether adeno-associated virus (AAV) mediated expression of human wild-type α-synuclein alter functional activity in the visual system. A total of 16 rats were injected with either AAV-α-synuclein (n = 7) or AAV-null (n = 9) in the substantia nigra pars compacta (SNc) of the left hemisphere. The expression of α-synuclein was validated by a motor assay and postmortem immunohistochemistry. Five months after the introduction of the AAV-vector, fMRI showed robust blood oxygen level-dependent (BOLD) responses to light stimulation in the visual systems of both control and AAV-α-synuclein animals. However, our results demonstrate that the expression of AAV-α-synuclein does not affect functional activation of the visual system. This negative finding suggests that fMRI-based read-outs of visual responses may not be a sensitive biomarker for PD.
Collapse
Affiliation(s)
| | - Christian Stald Skoven
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen 2650, Denmark
| | - Alex R Wade
- Department of Psychology, The University of York, Heslington, York YO10 5DD, United Kingdom
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen 2650, Denmark
| | | | | | - Tim B Dyrby
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen 2650, Denmark
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby 2800, Denmark
| |
Collapse
|
34
|
De Micco R, Agosta F, Basaia S, Siciliano M, Cividini C, Tedeschi G, Filippi M, Tessitore A. Functional Connectomics and Disease Progression in Drug-Naïve Parkinson's Disease Patients. Mov Disord 2021; 36:1603-1616. [PMID: 33639029 DOI: 10.1002/mds.28541] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 01/06/2021] [Accepted: 01/11/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Functional brain connectivity alterations may be detectable even before the occurrence of brain atrophy, indicating their potential as early markers of pathological processes. OBJECTIVE We aimed to determine the whole-brain network topologic organization of the functional connectome in a large cohort of drug-naïve Parkinson's disease (PD) patients using resting-state functional magnetic resonance imaging and to explore whether baseline connectivity changes may predict clinical progression. METHODS One hundred and forty-seven drug-naïve, cognitively unimpaired PD patients were enrolled in the study at baseline and compared to 38 age- and gender-matched controls. Non-hierarchical cluster analysis using motor and non-motor data was applied to stratify PD patients into two subtypes: 77 early/mild and 70 early/severe. Graph theory analysis and connectomics were used to assess global and local topological network properties and regional functional connectivity at baseline. Stepwise multivariate regression analysis investigated whether baseline functional imaging data were predictors of clinical progression over 2 years. RESULTS At baseline, widespread functional connectivity abnormalities were detected in the basal ganglia, sensorimotor, frontal, and occipital networks in PD patients compared to controls. Decreased regional functional connectivity involving mostly striato-frontal, temporal, occipital, and limbic connections differentiated early/mild from early/severe PD patients. Connectivity changes were found to be independent predictors of cognitive progression at 2-year follow-up. CONCLUSIONS Our findings revealed that functional reorganization of the brain connectome occurs early in PD and underlies crucial involvement of striatal projections. Connectomic measures may be helpful to identify a specific PD patient subtype, characterized by severe motor and non-motor clinical burden as well as widespread functional connectivity abnormalities. © 2021 International Parkinson and Movement Disorder Society.
Collapse
Affiliation(s)
- Rosa De Micco
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.,MRI Research Center, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Mattia Siciliano
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.,Department of Psychology, University of Campania "Luigi Vanvitelli", Caserta, Italy
| | - Camilla Cividini
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Gioacchino Tedeschi
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.,MRI Research Center, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Neurorehabilitation Unit and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandro Tessitore
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.,MRI Research Center, University of Campania "Luigi Vanvitelli", Naples, Italy
| |
Collapse
|
35
|
Chougar L, Faouzi J, Pyatigorskaya N, Yahia‐Cherif L, Gaurav R, Biondetti E, Villotte M, Valabrègue R, Corvol J, Brice A, Mariani L, Cormier F, Vidailhet M, Dupont G, Piot I, Grabli D, Payan C, Colliot O, Degos B, Lehéricy S. Automated Categorization of Parkinsonian Syndromes Using
Magnetic Resonance Imaging
in a Clinical Setting. Mov Disord 2020; 36:460-470. [DOI: 10.1002/mds.28348] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 09/15/2020] [Indexed: 02/06/2023] Open
Affiliation(s)
- Lydia Chougar
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- ICM, “Movement Investigations and Therapeutics” Team (MOV'IT) Paris France
- ICM, Centre de NeuroImagerie de Recherche–CENIR Paris France
- Department of Neuroradiology Pitié‐Salpêtrière University Hospital, APHP Paris France
| | - Johann Faouzi
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- INRIA, Aramis Team Paris France
| | - Nadya Pyatigorskaya
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- ICM, “Movement Investigations and Therapeutics” Team (MOV'IT) Paris France
- ICM, Centre de NeuroImagerie de Recherche–CENIR Paris France
- Department of Neuroradiology Pitié‐Salpêtrière University Hospital, APHP Paris France
| | - Lydia Yahia‐Cherif
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- ICM, Centre de NeuroImagerie de Recherche–CENIR Paris France
| | - Rahul Gaurav
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- ICM, “Movement Investigations and Therapeutics” Team (MOV'IT) Paris France
- ICM, Centre de NeuroImagerie de Recherche–CENIR Paris France
| | - Emma Biondetti
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- ICM, “Movement Investigations and Therapeutics” Team (MOV'IT) Paris France
- ICM, Centre de NeuroImagerie de Recherche–CENIR Paris France
| | - Marie Villotte
- Faculté de Médecine Université Denis Diderot Paris France
| | - Romain Valabrègue
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- ICM, Centre de NeuroImagerie de Recherche–CENIR Paris France
| | - Jean‐Christophe Corvol
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- ICM, Centre d'Investigation Clinique Neurosciences Paris France
| | - Alexis Brice
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- ICM, Team Neurogénétique Fondamentale et Translationnelle Paris France
| | - Louise‐Laure Mariani
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- ICM, Centre d'Investigation Clinique Neurosciences Paris France
- Clinique des Mouvements Anormaux, Département des Maladies du Système Nerveux, Hôpital Pitié‐Salpêtrière, APHP Paris France
| | - Florence Cormier
- Clinique des Mouvements Anormaux, Département des Maladies du Système Nerveux, Hôpital Pitié‐Salpêtrière, APHP Paris France
| | - Marie Vidailhet
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- ICM, “Movement Investigations and Therapeutics” Team (MOV'IT) Paris France
- Clinique des Mouvements Anormaux, Département des Maladies du Système Nerveux, Hôpital Pitié‐Salpêtrière, APHP Paris France
| | - Gwendoline Dupont
- Université de Bourgogne Dijon France
- Centre Hospitalier Universitaire François Mitterrand, Département de Neurologie Dijon France
| | - Ines Piot
- Department of Neuroradiology Pitié‐Salpêtrière University Hospital, APHP Paris France
| | - David Grabli
- Clinique des Mouvements Anormaux, Département des Maladies du Système Nerveux, Hôpital Pitié‐Salpêtrière, APHP Paris France
| | - Christine Payan
- BESPIM, Hôpital Universitaire de Nîmes Nîmes France
- Service de Pharmacologie Clinique, Hôpital Pitié‐Salpêtrière, APHP Paris France
| | - Olivier Colliot
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- INRIA, Aramis Team Paris France
| | - Bertrand Degos
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology Collège de France, CNRS UMR7241/INSERM U1050, MemoLife Labex Paris France
- Department of Neurology, Avicenne University Hospital Sorbonne Paris Nord University Bobigny France
| | - Stéphane Lehéricy
- Paris Brain Institute–ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UMR S 1127, CNRS UMR 7225 Paris France
- ICM, “Movement Investigations and Therapeutics” Team (MOV'IT) Paris France
- ICM, Centre de NeuroImagerie de Recherche–CENIR Paris France
- Department of Neuroradiology Pitié‐Salpêtrière University Hospital, APHP Paris France
| |
Collapse
|
36
|
Krismer F, Beliveau V, Seppi K, Mueller C, Goebel G, Gizewski ER, Wenning GK, Poewe W, Scherfler C. Automated Analysis of Diffusion-Weighted Magnetic Resonance Imaging for the Differential Diagnosis of Multiple System Atrophy from Parkinson's Disease. Mov Disord 2020; 36:241-245. [PMID: 32935402 PMCID: PMC7891649 DOI: 10.1002/mds.28281] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/14/2020] [Accepted: 08/17/2020] [Indexed: 12/14/2022] Open
Abstract
Background Manual region‐of‐interest analysis of putaminal and middle cerebellar peduncle diffusivity distinguishes patients with multiple system atrophy (MSA) and Parkinson's disease (PD) with high diagnostic accuracy. However, a recent meta‐analysis found substantial between‐study heterogeneity of diagnostic accuracy due to the lack of harmonized imaging protocols and standardized analyses pipelines. Objective Evaluation of diagnostic accuracy of observer‐independent analysis of microstructural integrity as measured by diffusion‐tensor imaging in patients with MSA and PD. Methods A total of 29 patients with MSA and 19 patients with PD (matched for age, gender, and disease duration) with 3 years of follow‐up were investigated with diffusion‐tensor imaging and T1‐weighted magnetic resonance imaging. Automated localization of relevant brain regions was obtained, and mean diffusivity and fractional anisotropy values were averaged within the regions of interest. The classification was performed using a C5.0 hierachical decision tree algorithm. Results Mean diffusivity of the middle cerebellar peduncle and cerebellar gray and white matter compartment as well as the putamen were significantly increased in patients with MSA and showed superior effect sizes compared to the volumetric analysis of these regions. A classifier model identified mean diffusivity of the middle cerebellar peduncle and putamen as the most predictive parameters. Cross‐validation of the classification model yields a Cohen's κ and overall diagnostic accuracy of 0.823 and 0.914, respectively. Conclusion Analysis of microstructural integrity within the middle cerebellar peduncle and putamen yielded a superior effect size compared to the volumetric measures, resulting in excellent diagnostic accuracy to discriminate patients with MSA from PD in the early to moderate disease stages. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
Collapse
Affiliation(s)
- Florian Krismer
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.,Neuroimaging Research Core Facility, Medical University of Innsbruck, Innsbruck, Austria
| | - Vincent Beliveau
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.,Neuroimaging Research Core Facility, Medical University of Innsbruck, Innsbruck, Austria
| | - Klaus Seppi
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.,Neuroimaging Research Core Facility, Medical University of Innsbruck, Innsbruck, Austria
| | - Christoph Mueller
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.,Neuroimaging Research Core Facility, Medical University of Innsbruck, Innsbruck, Austria
| | - Georg Goebel
- Department of Medical Statistics, Informatics and Health Economics, Medical University of Innsbruck, Innsbruck, Austria
| | - Elke R Gizewski
- Neuroimaging Research Core Facility, Medical University of Innsbruck, Innsbruck, Austria.,Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Gregor K Wenning
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Werner Poewe
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.,Neuroimaging Research Core Facility, Medical University of Innsbruck, Innsbruck, Austria
| | - Christoph Scherfler
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.,Neuroimaging Research Core Facility, Medical University of Innsbruck, Innsbruck, Austria
| |
Collapse
|
37
|
Mu L, Zhou Q, Sun D, Wang M, Chai X, Wang M. The Application of Resting Magnetic Resonance Imaging in the Cognitive Judgment of Parkinson. World Neurosurg 2020; 138:672-679. [PMID: 32545020 DOI: 10.1016/j.wneu.2020.02.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 01/31/2020] [Accepted: 02/01/2020] [Indexed: 10/24/2022]
Abstract
OBJECTIVE In this study, we considered the treatment of cognitive characteristics of Parkinson's subtypes under resting magnetic resonance imaging scans, and used magnetic resonance imaging to analyze brain activity characteristics of patients with Parkinson's subtypes at rest. METHODS In this study, patients with neurological Parkinson's disease subtypes were selected: 27 patients in the tremor group, 33 patients in the orthostatic gastric instability group, and 3 patients with mild cognitive impairment and neuropathic Parkinson's disease. Scientific treatment was adopted. RESULTS Nineteen patients had mild cognitive dysfunction tremor and unstable posture, and 23 of them had mild cognitive dysfunction. Fifteen healthy controls were subjected to resting state functional magnetic resonance imaging by plane echo imaging sequence scanning. Neurological diseases-Regional consistency analysis of brain regions in patients with Parkinson's disease increased, including the right lower lobe, while regional consistency analysis of brain regions decreased, including the right frontal gyrus, right middle anterior gyrus, and lateral cerebellum. CONCLUSIONS The experimental results show that the local consistency analysis method based on resting magnetic resonance imaging scan can effectively detect the differences in early neural activity in patients with Parkinson's disease subtype cognitive impairment, and can effectively reflect the brain characteristics of Parkinson's disease.
Collapse
Affiliation(s)
- Lin Mu
- Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Qiang Zhou
- Cadre's Ward, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Dawei Sun
- Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Min Wang
- Department of Pathology, Jilin Provincial Cancer Hospital, Changchun, China
| | - Xin Chai
- Department of Breast Surgery, Jilin Cancer Hospital, Changchun, China
| | - Meng Wang
- Center of Reproductive Medicine, Center of Prenatal Diagnosis, The First Hospital of Jilin University, Changchun, Jilin, China.
| |
Collapse
|
38
|
Wolters AF, Heijmans M, Michielse S, Leentjens AFG, Postma AA, Jansen JFA, Ivanov D, Duits AA, Temel Y, Kuijf ML. The TRACK-PD study: protocol of a longitudinal ultra-high field imaging study in Parkinson's disease. BMC Neurol 2020; 20:292. [PMID: 32758176 PMCID: PMC7409458 DOI: 10.1186/s12883-020-01874-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 07/29/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The diagnosis of Parkinson's Disease (PD) remains a challenge and is currently based on the assessment of clinical symptoms. PD is also a heterogeneous disease with great variability in symptoms, disease course, and response to therapy. There is a general need for a better understanding of this heterogeneity and the interlinked long-term changes in brain function and structure in PD. Over the past years there is increasing interest in the value of new paradigms in Magnetic Resonance Imaging (MRI) and the potential of ultra-high field strength imaging in the diagnostic work-up of PD. With this multimodal 7 T MRI study, our objectives are: 1) To identify distinctive MRI characteristics in PD patients and to create a diagnostic tool based on these differences. 2) To correlate MRI characteristics to clinical phenotype, genetics and progression of symptoms. 3) To detect future imaging biomarkers for disease progression that could be valuable for the evaluation of new therapies. METHODS The TRACK-PD study is a longitudinal observational study in a cohort of 130 recently diagnosed (≤ 3 years after diagnosis) PD patients and 60 age-matched healthy controls (HC). A 7 T MRI of the brain will be performed at baseline and repeated after 2 and 4 years. Complete assessment of motor, cognitive, neuropsychiatric and autonomic symptoms will be performed at baseline and follow-up visits with wearable sensors, validated questionnaires and rating scales. At baseline a blood DNA sample will also be collected. DISCUSSION This is the first longitudinal, observational, 7 T MRI study in PD patients. With this study, an important contribution can be made to the improvement of the current diagnostic process in PD. Moreover, this study will be able to provide valuable information related to the different clinical phenotypes of PD and their correlating MRI characteristics. The long-term aim of this study is to better understand PD and develop new biomarkers for disease progression which may help new therapy development. Eventually, this may lead to predictive models for individual PD patients and towards personalized medicine in the future. TRIAL REGISTRATION Dutch Trial Register, NL7558 . Registered March 11, 2019.
Collapse
Affiliation(s)
- A F Wolters
- Department of Neurology, Maastricht University Medical Centre, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands.
- School for Mental Health and Neuroscience, EURON, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.
| | - M Heijmans
- School for Mental Health and Neuroscience, EURON, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
| | - S Michielse
- School for Mental Health and Neuroscience, EURON, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
| | - A F G Leentjens
- School for Mental Health and Neuroscience, EURON, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Psychiatry, Maastricht University Medical Centre, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - A A Postma
- School for Mental Health and Neuroscience, EURON, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - J F A Jansen
- School for Mental Health and Neuroscience, EURON, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - D Ivanov
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
| | - A A Duits
- School for Mental Health and Neuroscience, EURON, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Medical Psychology, Maastricht University Medical Centre, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - Y Temel
- School for Mental Health and Neuroscience, EURON, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Neurosurgery, Maastricht University Medical Centre, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - M L Kuijf
- Department of Neurology, Maastricht University Medical Centre, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
- School for Mental Health and Neuroscience, EURON, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
| |
Collapse
|
39
|
Chougar L, Pyatigorskaya N, Degos B, Grabli D, Lehéricy S. The Role of Magnetic Resonance Imaging for the Diagnosis of Atypical Parkinsonism. Front Neurol 2020; 11:665. [PMID: 32765399 PMCID: PMC7380089 DOI: 10.3389/fneur.2020.00665] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Accepted: 06/03/2020] [Indexed: 12/14/2022] Open
Abstract
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.
Collapse
Affiliation(s)
- Lydia Chougar
- Institut du Cerveau et de la Moelle épinière-ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS UMR 7225, Paris, France.,ICM, "Movement Investigations and Therapeutics" Team (MOV'IT), Paris, France.,ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France.,Service de Neuroradiologie, Hôpital Pitié-Salpêtrière, APHP, Paris, France
| | - Nadya Pyatigorskaya
- Institut du Cerveau et de la Moelle épinière-ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS UMR 7225, Paris, France.,ICM, "Movement Investigations and Therapeutics" Team (MOV'IT), Paris, France.,ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France.,Service de Neuroradiologie, Hôpital Pitié-Salpêtrière, APHP, Paris, France
| | - Bertrand Degos
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology, Collège de France, CNRS UMR7241/INSERM U1050, MemoLife Labex, Paris, France.,Department of Neurology, Avicenne University Hospital, Sorbonne Paris Nord University, Bobigny, France
| | - David Grabli
- Département des Maladies du Système Nerveux, Hôpital Pitié-Salpêtrière, APHP, Paris, France
| | - Stéphane Lehéricy
- Institut du Cerveau et de la Moelle épinière-ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS UMR 7225, Paris, France.,ICM, "Movement Investigations and Therapeutics" Team (MOV'IT), Paris, France.,ICM, Centre de NeuroImagerie de Recherche-CENIR, Paris, France.,Service de Neuroradiologie, Hôpital Pitié-Salpêtrière, APHP, Paris, France
| |
Collapse
|
40
|
Abstract
PURPOSE OF REVIEW Hybrid PET- MRI is a technique that has the ability to improve diagnostic accuracy in many applications, whereas PET and MRI performed separately often fail to provide accurate responses to clinical questions. Here, we review recent studies and current developments in PET-MRI, focusing on clinical applications. RECENT FINDINGS The combination of PET and MRI imaging methods aims at increasing the potential of each individual modality. Combined methods of image reconstruction and correction of PET-MRI attenuation are being developed, and a number of applications are being introduced into clinical practice. To date, the value of PET-MRI has been demonstrated for the evaluation of brain tumours in epilepsy and neurodegenerative diseases. Continued advances in data analysis regularly improve the efficiency and the potential application of multimodal biomarkers. SUMMARY PET-MRI provides simultaneous of anatomical, functional, biochemical and metabolic information for the personalized characterization and monitoring of neurological diseases. In this review, we show the advantage of the complementarity of different biomarkers obtained using PET-MRI data. We also present the recent advances made in this hybrid imaging modality and its advantages in clinical practice compared with MRI and PET separately.
Collapse
|
41
|
Klobušiaková P, Mareček R, Fousek J, Výtvarová E, Rektorová I. Connectivity Between Brain Networks Dynamically Reflects Cognitive Status of Parkinson's Disease: A Longitudinal Study. J Alzheimers Dis 2020; 67:971-984. [PMID: 30776007 PMCID: PMC6398554 DOI: 10.3233/jad-180834] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
BACKGROUND Cognitive impairment in Parkinson's disease (PD) is associated with altered connectivity of the resting state networks (RSNs). Longitudinal studies in well cognitively characterized PD subgroups are missing. OBJECTIVES To assess changes of the whole-brain connectivity and between-network connectivity (BNC) of large-scale functional networks related to cognition in well characterized PD patients using a longitudinal study design and various analytical methods. METHODS We explored the whole-brain connectivity and BNC of the frontoparietal control network (FPCN) and the default mode, dorsal attention, and visual networks in PD with normal cognition (PD-NC, n = 17) and mild cognitive impairment (PD-MCI, n = 22) as compared to 51 healthy controls (HC). We applied regions of interest-based, partial least squares, and graph theory based network analyses. The differences among groups were analyzed at baseline and at the one-year follow-up visit (37 HC, 23 PD all). RESULTS The BNC of the FPCN and other RSNs was reduced, and the whole-brain analysis revealed increased characteristic path length and decreased average node strength, clustering coefficient, and global efficiency in PD-NC compared to HC. Values of all measures in PD-MCI were between that of HC and PD-NC. After one year, the BNC was further increased in the PD-all group; no changes were detected in HC. No cognitive domain z-scores deteriorated in either group. CONCLUSION As compared to HC, PD-NC patients display a less efficient transfer of information globally and reduced BNC of the visual and frontoparietal control network. The BNC increases with time and MCI status, reflecting compensatory efforts.
Collapse
Affiliation(s)
- Patrícia Klobušiaková
- Applied Neuroscience Research Group, Central European Institute of Technology, Masaryk University (CEITEC MU), Brno, Czech Republic.,Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Radek Mareček
- Applied Neuroscience Research Group, Central European Institute of Technology, Masaryk University (CEITEC MU), Brno, Czech Republic.,First Department of Neurology, St. Anne's University Hospital and School of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, Central European Institute of Technology, Masaryk University (CEITEC MU), Brno, Czech Republic
| | - Jan Fousek
- Multimodal and Functional Neuroimaging Research Group, Central European Institute of Technology, Masaryk University (CEITEC MU), Brno, Czech Republic.,Institute of Computer Science, Masaryk University (MU), Brno, Czech Republic
| | - Eva Výtvarová
- Applied Neuroscience Research Group, Central European Institute of Technology, Masaryk University (CEITEC MU), Brno, Czech Republic.,Faculty of Informatics, Masaryk University (MU), Brno, Czech Republic
| | - Irena Rektorová
- Applied Neuroscience Research Group, Central European Institute of Technology, Masaryk University (CEITEC MU), Brno, Czech Republic.,First Department of Neurology, St. Anne's University Hospital and School of Medicine, Masaryk University, Brno, Czech Republic
| |
Collapse
|
42
|
Hu H. Recent Advances of Bioresponsive Nano-Sized Contrast Agents for Ultra-High-Field Magnetic Resonance Imaging. Front Chem 2020; 8:203. [PMID: 32266217 PMCID: PMC7100386 DOI: 10.3389/fchem.2020.00203] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Accepted: 03/04/2020] [Indexed: 12/11/2022] Open
Abstract
The ultra-high-field magnetic resonance imaging (MRI) nowadays has been receiving enormous attention in both biomaterial research and clinical diagnosis. MRI contrast agents are generally comprising of T1-weighted and T2-weighted contrast agent types, where T1-weighted contrast agents show positive contrast enhancement with brighter images by decreasing the proton's longitudinal relaxation times and T2-weighted contrast agents show negative contrast enhancement with darker images by decreasing the proton's transverse relaxation times. To meet the incredible demand of MRI, ultra-high-field T2 MRI is gradually attracting the attention of research and medical needs owing to its high resolution and high accuracy for detection. It is anticipated that high field MRI contrast agents can achieve high performance in MRI imaging, where parameters of chemical composition, molecular structure and size of varied contrast agents show contrasted influence in each specific diagnostic test. This review firstly presents the recent advances of nanoparticle contrast agents for MRI. Moreover, multimodal molecular imaging with MRI for better monitoring is discussed during biological process. To fasten the process of developing better contrast agents, deep learning of artificial intelligent (AI) can be well-integrated into optimizing the crucial parameters of nanoparticle contrast agents and achieving high resolution MRI prior to the clinical applications. Finally, prospects and challenges are summarized.
Collapse
Affiliation(s)
- Hailong Hu
- School of Aeronautics and Astronautics, Central South University, Changsha, China
- Research Center in Intelligent Thermal Structures for Aerospace, Central South University, Changsha, China
| |
Collapse
|
43
|
Sasikumar S, Strafella AP. Imaging Mild Cognitive Impairment and Dementia in Parkinson's Disease. Front Neurol 2020; 11:47. [PMID: 32082250 PMCID: PMC7005138 DOI: 10.3389/fneur.2020.00047] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 01/14/2020] [Indexed: 12/11/2022] Open
Abstract
Cognitive dysfunction is a significant non-motor feature of Parkinson's disease, with the risk of dementia increasing with prolonged disease duration. Multiple cognitive domains are affected, and the pathophysiology cannot be explained by dopaminergic loss alone. Sophisticated neuroimaging techniques can detect the nature and extent of extra-nigral involvement by targeting neurotransmitters, abnormal protein aggregates and tissue metabolism. This review identifies the functional and anatomical imaging characteristics that predict cognitive impairment in PD, the limitations that challenge this process, and the avenues of potential research.
Collapse
Affiliation(s)
| | - Antonio P Strafella
- Division of Neurology, University of Toronto, Toronto, ON, Canada.,Morton and Gloria Shulman Movement Disorder Unit & E. J. Safra Parkinson Disease Program, Neurology Division, Department of Medicine, Toronto Western Hospital, UHN, University of Toronto, Toronto, ON, Canada.,Research Imaging Centre, Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, University of Toronto, Toronto, ON, Canada.,Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, UHN, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
44
|
Brain activity during lower limb movements in Parkinson’s disease patients with and without freezing of gait. J Neurol 2020; 267:1116-1126. [DOI: 10.1007/s00415-019-09687-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 12/19/2019] [Accepted: 12/23/2019] [Indexed: 01/26/2023]
|
45
|
Langley J, Hussain S, Flores JJ, Bennett IJ, Hu X. Characterization of age-related microstructural changes in locus coeruleus and substantia nigra pars compacta. Neurobiol Aging 2019; 87:89-97. [PMID: 31870645 DOI: 10.1016/j.neurobiolaging.2019.11.016] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2019] [Revised: 11/19/2019] [Accepted: 11/22/2019] [Indexed: 12/15/2022]
Abstract
Locus coeruleus (LC) and substantia nigra pars compacta (SNpc) degrade with normal aging, but not much is known regarding how these changes manifest in MRI images, or whether these markers predict aspects of cognition. Here, we use high-resolution diffusion-weighted MRI to investigate microstructural and compositional changes in LC and SNpc in young and older adult cohorts, as well as their relationship with cognition. In LC, the older cohort exhibited a significant reduction in mean and radial diffusivity, but a significant increase in fractional anisotropy compared with the young cohort. We observed a significant correlation between the decrease in LC mean, axial, and radial diffusivities and measures examining cognition (Rey Auditory Verbal Learning Test delayed recall) in the older adult cohort. This observation suggests that LC is involved in retaining cognitive abilities. In addition, we observed that iron deposition in SNpc occurs early in life and continues during normal aging.
Collapse
Affiliation(s)
- Jason Langley
- Center for Advanced Neuroimaging, University of California Riverside, Riverside, CA, USA
| | - Sana Hussain
- Department of Bioengineering, University of California Riverside, Riverside, CA, USA
| | - Justino J Flores
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Ilana J Bennett
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Xiaoping Hu
- Center for Advanced Neuroimaging, University of California Riverside, Riverside, CA, USA; Department of Bioengineering, University of California Riverside, Riverside, CA, USA.
| |
Collapse
|
46
|
Helmich RC, Vaillancourt DE, Brooks DJ. The Future of Brain Imaging in Parkinson's Disease. JOURNAL OF PARKINSONS DISEASE 2019; 8:S47-S51. [PMID: 30584163 PMCID: PMC6311365 DOI: 10.3233/jpd-181482] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Parkinson’s disease (PD) is a progressive neurodegenerative disorder that is associated with distinct abnormalities in brain function and structure. Here we discuss how future developments in functional, structural and nuclear brain imaging may help us to better understand, diagnose, and potentially even treat PD. These new horizons may be reached by developing tracers that specifically bind to alpha synuclein, by looking into different places in the body (such as the gut) or in smaller cerebral nuclei (with improved spatial resolution), and by developing new approaches for quantifying and interpreting altered dynamics in large-scale brain networks.
Collapse
Affiliation(s)
- Rick C Helmich
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
| | - David E Vaillancourt
- University of Florida, Applied Physiology and Kinesiology, Neurology, and Biomedical Engineering, Gainesville, FL, USA
| | - David J Brooks
- Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Aarhus, Denmark, Division of Neuroscience, Newcastle University, Newcastle, UK
| |
Collapse
|
47
|
Molecular Imaging of the Dopamine Transporter. Cells 2019; 8:cells8080872. [PMID: 31405186 PMCID: PMC6721747 DOI: 10.3390/cells8080872] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Revised: 08/07/2019] [Accepted: 08/09/2019] [Indexed: 02/06/2023] Open
Abstract
Dopamine transporter (DAT) single-photon emission tomography (SPECT) with (123)Ioflupane is a widely used diagnostic tool for patients with suspected parkinsonian syndromes, as it assists with differentiating between Parkinson’s disease (PD) or atypical parkinsonisms and conditions without a presynaptic dopaminergic deficit such as essential tremor, vascular and drug-induced parkinsonisms. Recent evidence supports its utility as in vivo proof of degenerative parkinsonisms, and DAT imaging has been proposed as a potential surrogate marker for dopaminergic nigrostriatal neurons. However, the interpretation of DAT-SPECT imaging may be challenged by several factors including the loss of DAT receptor density with age and the effect of certain drugs on dopamine uptake. Furthermore, a clear, direct relationship between nigral loss and DAT decrease has been controversial so far. Striatal DAT uptake could reflect nigral neuronal loss once the loss exceeds 50%. Indeed, reduction of DAT binding seems to be already present in the prodromal stage of PD, suggesting both an early synaptic dysfunction and the activation of compensatory changes to delay the onset of symptoms. Despite a weak correlation with PD severity and progression, quantitative measurements of DAT binding at baseline could be used to predict the emergence of late-disease motor fluctuations and dyskinesias. This review addresses the possibilities and limitations of DAT-SPECT in PD and, focusing specifically on regulatory changes of DAT in surviving DA neurons, we investigate its role in diagnosis and its prognostic value for motor complications as disease progresses.
Collapse
|
48
|
Prange S, Metereau E, Thobois S. Structural Imaging in Parkinson’s Disease: New Developments. Curr Neurol Neurosci Rep 2019; 19:50. [DOI: 10.1007/s11910-019-0964-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
|
49
|
|
50
|
Mishra VR, Sreenivasan KR, Zhuang X, Yang Z, Cordes D, Walsh RR. Influence of analytic techniques on comparing DTI-derived measurements in early stage Parkinson's disease. Heliyon 2019; 5:e01481. [PMID: 31008407 PMCID: PMC6458486 DOI: 10.1016/j.heliyon.2019.e01481] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 03/08/2019] [Accepted: 04/02/2019] [Indexed: 11/16/2022] Open
Abstract
Diffusion tensor imaging (DTI) studies in early Parkinson's disease (PD) to understand pathologic changes in white matter (WM) organization are variable in their findings. Evaluation of different analytic techniques frequently employed to understand the DTI-derived change in WM organization in a multisite, well-characterized, early stage PD cohort should aid the identification of the most robust analytic techniques to be used to investigate WM pathology in this disease, an important unmet need in the field. Thus, region of interest (ROI)-based analysis, voxel-based morphometry (VBM) analysis with varying spatial smoothing, and the two most widely used skeletonwise approaches (tract-based spatial statistics, TBSS, and tensor-based registration, DTI-TK) were evaluated in a DTI dataset of early PD and Healthy Controls (HC) from the Parkinson's Progression Markers Initiative (PPMI) cohort. Statistical tests on the DTI-derived metrics were conducted using a nonparametric approach from this cohort of early PD, after rigorously controlling for motion and signal artifacts during DTI scan which are frequent confounds in this disease population. Both TBSS and DTI-TK revealed a significantly negative correlation of fractional anisotropy (FA) with disease duration. However, only DTI-TK revealed radial diffusivity (RD) to be driving this FA correlation with disease duration. HC had a significantly positive correlation of MD with cumulative DaT score in the right middle-frontal cortex after a minimum smoothing level (at least 13mm) was attained. The present study found that scalar DTI-derived measures such as FA, MD, and RD should be used as imaging biomarkers with caution in early PD as the conclusions derived from them are heavily dependent on the choice of the analysis used. This study further demonstrated DTI-TK may be used to understand changes in DTI-derived measures with disease progression as it was found to be more accurate than TBSS. In addition, no singular region was identified that could explain both disease duration and severity in early PD. The results of this study should help standardize the utilization of DTI-derived measures in PD in an effort to improve comparability across studies and time, and to minimize variability in reported results due to variation in techniques.
Collapse
Affiliation(s)
- Virendra R Mishra
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Karthik R Sreenivasan
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Xiaowei Zhuang
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Zhengshi Yang
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Dietmar Cordes
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States.,Departments of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, Colorado, United States
| | - Ryan R Walsh
- Muhammad Ali Parkinson Center, Barrow Neurological Institute, Phoenix, Arizona, United States
| |
Collapse
|