1
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Strobel J, Müller HP, Ludolph AC, Beer AJ, Sollmann N, Kassubek J. New Perspectives in Radiological and Radiopharmaceutical Hybrid Imaging in Progressive Supranuclear Palsy: A Systematic Review. Cells 2023; 12:2776. [PMID: 38132096 PMCID: PMC10742083 DOI: 10.3390/cells12242776] [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: 10/30/2023] [Revised: 11/28/2023] [Accepted: 12/04/2023] [Indexed: 12/23/2023] Open
Abstract
Progressive supranuclear palsy (PSP) is a neurodegenerative disease characterized by four-repeat tau deposition in various cell types and anatomical regions, and can manifest as several clinical phenotypes, including the most common phenotype, Richardson's syndrome. The limited availability of biomarkers for PSP relates to the overlap of clinical features with other neurodegenerative disorders, but identification of a growing number of biomarkers from imaging is underway. One way to increase the reliability of imaging biomarkers is to combine different modalities for multimodal imaging. This review aimed to provide an overview of the current state of PSP hybrid imaging by combinations of positron emission tomography (PET) and magnetic resonance imaging (MRI). Specifically, combined PET and MRI studies in PSP highlight the potential of [18F]AV-1451 to detect tau, but also the challenge in differentiating PSP from other neurodegenerative diseases. Studies over the last years showed a reduced synaptic density in [11C]UCB-J PET, linked [11C]PK11195 and [18F]AV-1451 markers to disease progression, and suggested the potential role of [18F]RO948 PET for identifying tau pathology in subcortical regions. The integration of quantitative global and regional gray matter analysis by MRI may further guide the assessment of reduced cortical thickness or volume alterations, and diffusion MRI could provide insight into microstructural changes and structural connectivity in PSP. Challenges in radiopharmaceutical biomarkers and hybrid imaging require further research targeting markers for comprehensive PSP diagnosis.
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Affiliation(s)
- Joachim Strobel
- Department of Nuclear Medicine, University Hospital Ulm, 89081 Ulm, Germany;
| | - Hans-Peter Müller
- Department of Neurology, University Hospital Ulm, 89081 Ulm, Germany; (H.-P.M.); (A.C.L.); (J.K.)
| | - Albert C. Ludolph
- Department of Neurology, University Hospital Ulm, 89081 Ulm, Germany; (H.-P.M.); (A.C.L.); (J.K.)
- German Center for Neurodegenerative Diseases (DZNE), Ulm University, 89081 Ulm, Germany
| | - Ambros J. Beer
- Department of Nuclear Medicine, University Hospital Ulm, 89081 Ulm, Germany;
| | - Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, 89081 Ulm, Germany;
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Jan Kassubek
- Department of Neurology, University Hospital Ulm, 89081 Ulm, Germany; (H.-P.M.); (A.C.L.); (J.K.)
- German Center for Neurodegenerative Diseases (DZNE), Ulm University, 89081 Ulm, Germany
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2
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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.
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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
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3
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Siafaka PI, Okur ME, Erim PD, Çağlar EŞ, Özgenç E, Gündoğdu E, Köprülü REP, Karantas ID, Üstündağ Okur N. Protein and Gene Delivery Systems for Neurodegenerative Disorders: Where Do We Stand Today? Pharmaceutics 2022; 14:2425. [PMID: 36365243 PMCID: PMC9698227 DOI: 10.3390/pharmaceutics14112425] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 10/28/2022] [Accepted: 11/05/2022] [Indexed: 12/24/2023] Open
Abstract
It has been estimated that every year, millions of people are affected by neurodegenerative disorders, which complicate their lives and their caregivers' lives. To date, there has not been an approved pharmacological approach to provide the complete treatment of neurodegenerative disorders. The only available drugs may only relieve the symptoms or slow down the progression of the disease. The absence of any treatment is quite rational given that neurodegeneration occurs by the progressive loss of the function or structure of the nerve cells of the brain or the peripheral nervous system, which eventually leads to their death either by apoptosis or necrotic cell death. According to a recent study, even though adult brain cells are injured, they can revert to an embryonic state, which may help to restore their function. These interesting findings might open a new path for the development of more efficient therapeutic strategies to combat devastating neurodegenerative disorders. Gene and protein therapies have emerged as a rapidly growing field for various disorders, especially neurodegenerative diseases. Despite these promising therapies, the complete treatment of neurodegenerative disorders has not yet been achieved. Therefore, the aim of this review is to address the most up-to-date data for neurodegenerative diseases, but most importantly, to summarize the available delivery systems incorporating proteins, peptides, and genes that can potentially target such diseases and pass into the blood-brain barrier. The authors highlight the advancements, at present, on delivery based on the carrier, i.e., lipid, polymeric, and inorganic, as well as the recent studies on radiopharmaceutical theranostics.
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Affiliation(s)
| | - Mehmet Evren Okur
- Department of Pharmacology, Faculty of Pharmacy, University of Health Sciences, Istanbul 34668, Turkey
| | - Pelin Dilsiz Erim
- Department of Physiology, School of Medicine, Regenerative and Restorative Medical Research Center (REMER), Istanbul Medipol University, Istanbul 34810, Turkey
- Faculty of Pharmacy, Altınbaş University, Istanbul 34217, Turkey
| | - Emre Şefik Çağlar
- Department of Pharmaceutical Biotechnology, Faculty of Pharmacy, University of Health Sciences, Istanbul 34668, Turkey
| | - Emre Özgenç
- Department of Radiopharmacy, Faculty of Pharmacy, Ege University, Izmir 35040, Turkey
| | - Evren Gündoğdu
- Department of Radiopharmacy, Faculty of Pharmacy, Ege University, Izmir 35040, Turkey
| | - Rabia Edibe Parlar Köprülü
- Department of Medical Pharmacology, Institute of Health Sciences, İstanbul Medipol University, Istanbul 34810, Turkey
| | | | - Neslihan Üstündağ Okur
- Department of Pharmaceutical Technology, Faculty of Pharmacy, University of Health Sciences, Istanbul 34668, Turkey
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4
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Bârlescu LA, Müller HP, Uttner I, Ludolph AC, Pinkhardt EH, Huppertz HJ, Kassubek J. Segmental Alterations of the Corpus Callosum in Progressive Supranuclear Palsy: A Multiparametric Magnetic Resonance Imaging Study. Front Aging Neurosci 2021; 13:720634. [PMID: 34867268 PMCID: PMC8640496 DOI: 10.3389/fnagi.2021.720634] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 10/22/2021] [Indexed: 01/18/2023] Open
Abstract
Background: The regional distribution of the widespread cerebral morphological alterations in progressive supranuclear palsy (PSP) is considered to include segmental parts of the corpus callosum (CC). Objective: The study was designed to investigate the regional white matter (WM) of the CC by T1 weighted magnetic resonance imaging (T1w MRI) data combined with diffusion tensor imaging (DTI) data in PSP patients, differentiated in the variants Richardson syndrome and PSP-parkinsonism, and to compare them with Parkinson’s Disease (PD) patients and healthy controls, in order to identify macro- and micro-structural alterations in vivo. Methods: MRI-based WM mapping was used to perform an operator-independent segmentation for the different CC segments in 66 PSP patients vs. 66 PD patients vs. 44 matched healthy controls. The segmentation was followed by both planimetric and texture analysis of the separated CC areas for the comparison of the three groups. Results were complemented by a DTI-based tract-of-interest analysis of the associated callosal tracts. Results: Significant alterations of the parameters entropy and homogeneity compared to controls were observed for PSP as well as for PD for the CC areas I, II, and III. The inhomogeneity in area II in the PSP cohort was the highest and differed significantly from PD. A combined score was defined as a potential marker for the different types of neurodegenerative parkinsonism; receiver operating characteristics (ROC) curves were calculated with areas under the curve values of 0.86 for PSP vs. controls, 0.72 for PD vs. controls, and 0.69 for PSP vs. PD, respectively. Conclusion: The multiparametric MRI texture and DTI analysis demonstrated extensive alterations of the frontal CC in neurodegenerative parkinsonism, whereas regional CC atrophy cannot be regarded as a constant neuroimaging feature of PSP. Specifically, the comparison PSP vs. PD revealed significant alterations in callosal area II. The combination of the texture and the DTI parameters might contribute as a neuroimaging marker for the assessment of the CC in PSP, including the differentiation vs. PD.
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Affiliation(s)
| | | | - Ingo Uttner
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Albert C Ludolph
- Department of Neurology, University of Ulm, Ulm, Germany.,German Center for Neurodegenerative Diseases (DZNE), Ulm, Germany
| | | | | | - Jan Kassubek
- Department of Neurology, University of Ulm, Ulm, Germany.,German Center for Neurodegenerative Diseases (DZNE), Ulm, Germany
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5
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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
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6
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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.
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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
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7
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Bocchetta M, Iglesias JE, Chelban V, Jabbari E, Lamb R, Russell LL, Greaves CV, Neason M, Cash DM, Thomas DL, Warren JD, Woodside J, Houlden H, Morris HR, Rohrer JD. Automated Brainstem Segmentation Detects Differential Involvement in Atypical Parkinsonian Syndromes. J Mov Disord 2019; 13:39-46. [PMID: 31552724 PMCID: PMC6987532 DOI: 10.14802/jmd.19030] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Accepted: 07/09/2019] [Indexed: 12/25/2022] Open
Abstract
Objective Brainstem segmentation has been useful in identifying potential imaging biomarkers for diagnosis and progression in atypical parkinsonian syndromes (APS). However, the majority of work has been performed using manual segmentation, which is time consuming for large cohorts. Methods We investigated brainstem involvement in APS using an automated method. We measured the volume of the medulla, pons, superior cerebellar peduncle (SCP) and midbrain from T1-weighted MRIs in 67 patients and 42 controls. Diagnoses were corticobasal syndrome (CBS, n = 14), multiple system atrophy (MSA, n = 16: 8 with parkinsonian syndrome, MSA-P; 8 with cerebellar syndrome, MSA-C), progressive supranuclear palsy with a Richardson’s syndrome (PSP-RS, n = 12), variant PSP (n = 18), and APS not otherwise specified (APS-NOS, n = 7). Results All brainstem regions were smaller in MSA-C (19–42% volume difference, p < 0.0005) and in both PSP groups (18–33%, p < 0.0005) than in controls. MSA-P showed lower volumes in all regions except the SCP (15–26%, p < 0.0005). The most affected region in MSA-C and MSA-P was the pons (42% and 26%, respectively), while the most affected regions in both the PSP-RS and variant PSP groups were the SCP (33% and 23%, respectively) and midbrain (26% and 24%, respectively). The brainstem was less affected in CBS, but nonetheless, the pons (14%, p < 0.0005), midbrain (14%, p < 0.0005) and medulla (10%, p = 0.001) were significantly smaller in CBS than in controls. The brainstem was unaffected in APS-NOS. Conclusion Automated methods can accurately quantify the involvement of brainstem structures in APS. This will be important in future trials with large patient numbers where manual segmentation is unfeasible.
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Affiliation(s)
- Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Juan Eugenio Iglesias
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Viorica Chelban
- Department of Movement Disorders, UCL Queen Square Institute of Neurology, University College London, London, UK.,Department of Neurology and Neurosurgery, Institute of Emergency Medicine, Chisinau, Republic of Moldova
| | - Edwin Jabbari
- Department of Movement Disorders, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ruth Lamb
- Department of Movement Disorders, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Lucy L Russell
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Caroline V Greaves
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Mollie Neason
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David M Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK.,Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - David L Thomas
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Leonard Wolfson Experimental Neurology Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jason D Warren
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - John Woodside
- Department of Movement Disorders, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Henry Houlden
- Department of Movement Disorders, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Huw R Morris
- Department of Movement Disorders, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
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8
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Zuo C, Zhuang X, Heckemann RA, Peng F. Editorial: Radiopharmaceuticals, Imaging Techniques and Clinical Applications in Neurodegenerative Diseases. Front Neurol 2019; 10:962. [PMID: 31551918 PMCID: PMC6737996 DOI: 10.3389/fneur.2019.00962] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 08/22/2019] [Indexed: 12/14/2022] Open
Affiliation(s)
- Chuantao Zuo
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
- *Correspondence: Chuantao Zuo
| | - Xiahai Zhuang
- School of Data Science, Fudan University, Shanghai, China
| | - Rolf A. Heckemann
- Department of Radiation Physics, University of Gothenburg, Gothenburg, Sweden
| | - Fangyu Peng
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX, United States
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9
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Müller HP, Kassubek J. Editorial: Computerized Magnetic Resonance Imaging-Based Neuroimaging of Neurodegenerative Diseases. Front Neurol 2019; 10:237. [PMID: 30930844 PMCID: PMC6428730 DOI: 10.3389/fneur.2019.00237] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Accepted: 02/22/2019] [Indexed: 12/13/2022] Open
Affiliation(s)
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Ulm, Germany
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10
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Jin L, Wang J, Wang C, Lian D, Zhou Y, Zhang Y, Lv M, Li Y, Huang Z, Cheng X, Fei G, Liu K, Zeng M, Zhong C. Combined Visualization of Nigrosome-1 and Neuromelanin in the Substantia Nigra Using 3T MRI for the Differential Diagnosis of Essential Tremor and de novo Parkinson's Disease. Front Neurol 2019; 10:100. [PMID: 30809189 PMCID: PMC6379476 DOI: 10.3389/fneur.2019.00100] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2018] [Accepted: 01/25/2019] [Indexed: 01/12/2023] Open
Abstract
Differentiating early-stage Parkinson's disease (PD) from essential tremor (ET) remains challenging. In the current study, we aimed to evaluate whether visual analyses of neuromelanin-sensitive magnetic resonance imaging (NM-MRI) combined with nigrosome-1 (N1) imaging using quantitative susceptibility mapping (QSM) in the substantia nigra (SN) are of diagnostic value in the differentiation of de novo PD from untreated ET. Sixty-eight patients with de novo PD, 25 patients with untreated ET, and 34 control participants underwent NM-MRI and QSM. NM and N1 signals in the SN on MR images were visually evaluated using a 3-point ordinal scale. Receiver operating characteristic (ROC) analyses were performed to determine the diagnostic values of the visual ratings of NM and N1. The diagnostic values of the predicted probabilities were calculated via logistic regression analysis using the combination of NM and N1 visual ratings, as well as their quadratic items. The proportions of invisible NM and invisible N1 were significantly higher in the PD group than those in the ET and control groups (p < 0.001). The sensitivity/specificity for differentiating PD from ET was 0.882/0.800 for NM and 0.794/0.920 for N1, respectively. Combining the two biomarkers, the area under the curve (AUC) of the predicted probabilities was 0.935, and the sensitivity/specificity was 0.853/0.920 when the cutoff value was set to 0.704. Our findings demonstrate that visual analyses combing NM and N1 imaging in the SN may aid in differential diagnosis of PD and ET. Furthermore, our results suggest that patients with PD exhibit larger iron deposits in the SN than those with ET.
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Affiliation(s)
- Lirong Jin
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jian Wang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Medical Imaging Institute, Shanghai, China
| | - Changpeng Wang
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Danlan Lian
- Department of Radiology, Xiamen Branch, Zhongshan Hospital, Fudan University, Xiamen, China
| | - Ying Zhou
- Department of Neurology, Xiamen Branch, Zhongshan Hospital, Fudan University, Xiamen, China
| | - Yong Zhang
- MR Research, GE Healthcare, Shanghai, China
| | - Minzhi Lv
- Department of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yuanfang Li
- Department of Neurology, Xiamen Branch, Zhongshan Hospital, Fudan University, Xiamen, China
| | - Zhen Huang
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xiaoqin Cheng
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Guoqiang Fei
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Kai Liu
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Medical Imaging Institute, Shanghai, China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Medical Imaging Institute, Shanghai, China
| | - Chunjiu Zhong
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
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11
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Lee JH, Lee MS. Brain Iron Accumulation in Atypical Parkinsonian Syndromes: in vivo MRI Evidences for Distinctive Patterns. Front Neurol 2019; 10:74. [PMID: 30809185 PMCID: PMC6379317 DOI: 10.3389/fneur.2019.00074] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 01/21/2019] [Indexed: 12/13/2022] Open
Abstract
Recent data suggest mechanistic links among perturbed iron homeostasis, oxidative stress, and misfolded protein aggregation in neurodegenerative diseases. Iron overload and toxicity toward dopaminergic neurons have been established as playing a role in the pathogenesis of Parkinson's disease (PD). Brain iron accumulation has also been documented in atypical parkinsonian syndromes (APS), mainly comprising multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). Iron-sensitive magnetic resonance imaging (MRI) has been applied to identify iron-related signal changes for the diagnosis and differentiation of these disorders. Topographic patterns of widespread iron deposition in deep brain nuclei have been described as differing between patients with MSA and PSP and those with PD. A disease-specific increase of iron occurs in the brain regions mainly affected by underlying disease pathologies. However, whether iron changes are a primary pathogenic factor or an epiphenomenon of neuronal degeneration has not been fully elucidated. Moreover, the clinical implications of iron-related pathology in APS remain unclear. In this review study, we collected data from qualitative and quantitative MRI studies on brain iron accumulation in APS to identify disease-related patterns and the potential role of iron-sensitive MRI.
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Affiliation(s)
- Jae-Hyeok Lee
- Department of Neurology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, South Korea
| | - Myung-Sik Lee
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
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