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Carvalho Macruz FBD, Dias ALMP, Andrade CS, Nucci MP, Rimkus CDM, Lucato LT, Rocha AJD, Kitamura FC. The new era of artificial intelligence in neuroradiology: current research and promising tools. ARQUIVOS DE NEURO-PSIQUIATRIA 2024; 82:1-12. [PMID: 38565188 PMCID: PMC10987255 DOI: 10.1055/s-0044-1779486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 12/13/2023] [Indexed: 04/04/2024]
Abstract
Radiology has a number of characteristics that make it an especially suitable medical discipline for early artificial intelligence (AI) adoption. These include having a well-established digital workflow, standardized protocols for image storage, and numerous well-defined interpretive activities. The more than 200 commercial radiologic AI-based products recently approved by the Food and Drug Administration (FDA) to assist radiologists in a number of narrow image-analysis tasks such as image enhancement, workflow triage, and quantification, corroborate this observation. However, in order to leverage AI to boost efficacy and efficiency, and to overcome substantial obstacles to widespread successful clinical use of these products, radiologists should become familiarized with the emerging applications in their particular areas of expertise. In light of this, in this article we survey the existing literature on the application of AI-based techniques in neuroradiology, focusing on conditions such as vascular diseases, epilepsy, and demyelinating and neurodegenerative conditions. We also introduce some of the algorithms behind the applications, briefly discuss a few of the challenges of generalization in the use of AI models in neuroradiology, and skate over the most relevant commercially available solutions adopted in clinical practice. If well designed, AI algorithms have the potential to radically improve radiology, strengthening image analysis, enhancing the value of quantitative imaging techniques, and mitigating diagnostic errors.
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Affiliation(s)
- Fabíola Bezerra de Carvalho Macruz
- Universidade de São Paulo, Hospital das Clínicas, Departamento de Radiologia e Oncologia, Seção de Neurorradiologia, Faculdade de Medicina, São Paulo SP, Brazil.
- Rede D'Or São Luiz, Departamento de Radiologia e Diagnóstico por Imagem, São Paulo SP, Brazil.
- Universidade de São Paulo, Laboratório de Investigação Médica em Ressonância Magnética (LIM 44), São Paulo SP, Brazil.
- Academia Nacional de Medicina, Rio de Janeiro RJ, Brazil.
| | | | | | - Mariana Penteado Nucci
- Universidade de São Paulo, Laboratório de Investigação Médica em Ressonância Magnética (LIM 44), São Paulo SP, Brazil.
| | - Carolina de Medeiros Rimkus
- Universidade de São Paulo, Hospital das Clínicas, Departamento de Radiologia e Oncologia, Seção de Neurorradiologia, Faculdade de Medicina, São Paulo SP, Brazil.
- Rede D'Or São Luiz, Departamento de Radiologia e Diagnóstico por Imagem, São Paulo SP, Brazil.
- Universidade de São Paulo, Laboratório de Investigação Médica em Ressonância Magnética (LIM 44), São Paulo SP, Brazil.
| | - Leandro Tavares Lucato
- Universidade de São Paulo, Hospital das Clínicas, Departamento de Radiologia e Oncologia, Seção de Neurorradiologia, Faculdade de Medicina, São Paulo SP, Brazil.
- Diagnósticos da América SA, São Paulo SP, Brazil.
| | | | - Felipe Campos Kitamura
- Diagnósticos da América SA, São Paulo SP, Brazil.
- Universidade Federal de São Paulo, São Paulo SP, Brazil.
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Prasuhn J, Xu J, Hua J, van Zijl P, Knutsson L. Exploring neurodegenerative disorders using advanced magnetic resonance imaging of the glymphatic system. Front Psychiatry 2024; 15:1368489. [PMID: 38651012 PMCID: PMC11033437 DOI: 10.3389/fpsyt.2024.1368489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 03/22/2024] [Indexed: 04/25/2024] Open
Abstract
The glymphatic system, a macroscopic waste clearance system in the brain, is crucial for maintaining neural health. It facilitates the exchange of cerebrospinal and interstitial fluid, aiding the clearance of soluble proteins and metabolites and distributing essential nutrients and signaling molecules. Emerging evidence suggests a link between glymphatic dysfunction and the pathogenesis of neurodegenerative disorders, including Alzheimer's, Parkinson's, and Huntington's disease. These disorders are characterized by the accumulation and propagation of misfolded or mutant proteins, a process in which the glymphatic system is likely involved. Impaired glymphatic clearance could lead to the buildup of these toxic proteins, contributing to neurodegeneration. Understanding the glymphatic system's role in these disorders could provide insights into their pathophysiology and pave the way for new therapeutic strategies. Pharmacological enhancement of glymphatic clearance could reduce the burden of toxic proteins and slow disease progression. Neuroimaging techniques, particularly MRI-based methods, have emerged as promising tools for studying the glymphatic system in vivo. These techniques allow for the visualization of glymphatic flow, providing insights into its function under healthy and pathological conditions. This narrative review highlights current MRI-based methodologies, such as motion-sensitizing pulsed field gradient (PFG) based methods, as well as dynamic gadolinium-based and glucose-enhanced methodologies currently used in the study of neurodegenerative disorders.
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Affiliation(s)
- Jannik Prasuhn
- Division of Magnetic Resonance (MR) Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, MD, United States
- Department of Neurology, University Medical Center Schleswig-Holstein, Lübeck, Germany
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Center for Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany
| | - Jiadi Xu
- Division of Magnetic Resonance (MR) Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, MD, United States
| | - Jun Hua
- Division of Magnetic Resonance (MR) Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, MD, United States
| | - Peter van Zijl
- Division of Magnetic Resonance (MR) Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, MD, United States
| | - Linda Knutsson
- F. M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, MD, United States
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
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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.
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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
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Stephen CD, Vangel M, Gupta AS, MacMore JP, Schmahmann JD. Rates of change of pons and middle cerebellar peduncle diameters are diagnostic of multiple system atrophy of the cerebellar type. Brain Commun 2024; 6:fcae019. [PMID: 38410617 PMCID: PMC10896291 DOI: 10.1093/braincomms/fcae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 12/01/2023] [Accepted: 02/19/2024] [Indexed: 02/28/2024] Open
Abstract
Definitive diagnosis of multiple system atrophy of the cerebellar type (MSA-C) is challenging. We hypothesized that rates of change of pons and middle cerebellar peduncle diameters on MRI would be unique to MSA-C and serve as diagnostic biomarkers. We defined the normative data for anterior-posterior pons and transverse middle cerebellar peduncle diameters on brain MRI in healthy controls, performed diameter-volume correlations and measured intra- and inter-rater reliability. We studied an Exploratory cohort (2002-2014) of 88 MSA-C and 78 other cerebellar ataxia patients, and a Validation cohort (2015-2021) of 49 MSA-C, 13 multiple system atrophy of the parkinsonian type (MSA-P), 99 other cerebellar ataxia patients and 314 non-ataxia patients. We measured anterior-posterior pons and middle cerebellar peduncle diameters on baseline and subsequent MRIs, and correlated results with Brief Ataxia Rating Scale scores. We assessed midbrain:pons and middle cerebellar peduncle:pons ratios over time. The normative anterior-posterior pons diameter was 23.6 ± 1.6 mm, and middle cerebellar peduncle diameter 16.4 ± 1.4 mm. Pons diameter correlated with volume, r = 0.94, P < 0.0001. The anterior-posterior pons and middle cerebellar peduncle measures were smaller at first scan in MSA-C compared to all other ataxias; anterior-posterior pons diameter: Exploratory, 19.3 ± 2.6 mm versus 20.7 ± 2.6 mm, Validation, 19.9 ± 2.1 mm versus 21.1 ± 2.1 mm; middle cerebellar peduncle transverse diameter, Exploratory, 12.0 ± 2.6 mm versus 14.3 ±2.1 mm, Validation, 13.6 ± 2.1 mm versus 15.1 ± 1.8 mm, all P < 0.001. The anterior-posterior pons and middle cerebellar peduncle rates of change were faster in MSA-C than in all other ataxias; anterior-posterior pons diameter rates of change: Exploratory, -0.87 ± 0.04 mm/year versus -0.09 ± 0.02 mm/year, Validation, -0.89 ± 0.48 mm/year versus -0.10 ± 0.21 mm/year; middle cerebellar peduncle transverse diameter rates of change: Exploratory, -0.84 ± 0.05 mm/year versus -0.08 ± 0.02 mm/year, Validation, -0.94 ± 0.64 mm/year versus -0.11 ± 0.27 mm/year, all values P < 0.0001. Anterior-posterior pons and middle cerebellar peduncle diameters were indistinguishable between Possible, Probable and Definite MSA-C. The rate of anterior-posterior pons atrophy was linear, correlating with ataxia severity. Using a lower threshold anterior-posterior pons diameter decrease of -0.4 mm/year to balance sensitivity and specificity, area under the curve analysis discriminating MSA-C from other ataxias was 0.94, yielding sensitivity 0.92 and specificity 0.87. For the middle cerebellar peduncle, with threshold decline -0.5 mm/year, area under the curve was 0.90 yielding sensitivity 0.85 and specificity 0.79. The midbrain:pons ratio increased progressively in MSA-C, whereas the middle cerebellar peduncle:pons ratio was almost unchanged. Anterior-posterior pons and middle cerebellar peduncle diameters were smaller in MSA-C than in MSA-P, P < 0.001. We conclude from this 20-year longitudinal clinical and imaging study that anterior-posterior pons and middle cerebellar peduncle diameters are phenotypic imaging biomarkers of MSA-C. In the correct clinical context, an anterior-posterior pons and transverse middle cerebellar peduncle diameter decline of ∼0.8 mm/year is sufficient for and diagnostic of MSA-C.
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Affiliation(s)
- Christopher D Stephen
- Ataxia Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Cognitive Behavioral Neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Mark Vangel
- Biostatistics Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02129, USA
| | - Anoopum S Gupta
- Ataxia Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Cognitive Behavioral Neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Jason P MacMore
- Ataxia Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Cognitive Behavioral Neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Jeremy D Schmahmann
- Ataxia Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Cognitive Behavioral Neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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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.
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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.
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Wang J, Xue L, Jiang J, Liu F, Wu P, Lu J, Zhang H, Bao W, Xu Q, Ju Z, Chen L, Jiao F, Lin H, Ge J, Zuo C, Tian M. Diagnostic performance of artificial intelligence-assisted PET imaging for Parkinson's disease: a systematic review and meta-analysis. NPJ Digit Med 2024; 7:17. [PMID: 38253738 PMCID: PMC10803804 DOI: 10.1038/s41746-024-01012-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: 09/14/2023] [Accepted: 01/10/2024] [Indexed: 01/24/2024] Open
Abstract
Artificial intelligence (AI)-assisted PET imaging is emerging as a promising tool for the diagnosis of Parkinson's disease (PD). We aim to systematically review the diagnostic accuracy of AI-assisted PET in detecting PD. The Ovid MEDLINE, Ovid Embase, Web of Science, and IEEE Xplore databases were systematically searched for related studies that developed an AI algorithm in PET imaging for diagnostic performance from PD and were published by August 17, 2023. Binary diagnostic accuracy data were extracted for meta-analysis to derive outcomes of interest: area under the curve (AUC). 23 eligible studies provided sufficient data to construct contingency tables that allowed the calculation of diagnostic accuracy. Specifically, 11 studies were identified that distinguished PD from normal control, with a pooled AUC of 0.96 (95% CI: 0.94-0.97) for presynaptic dopamine (DA) and 0.90 (95% CI: 0.87-0.93) for glucose metabolism (18F-FDG). 13 studies were identified that distinguished PD from the atypical parkinsonism (AP), with a pooled AUC of 0.93 (95% CI: 0.91 - 0.95) for presynaptic DA, 0.79 (95% CI: 0.75-0.82) for postsynaptic DA, and 0.97 (95% CI: 0.96-0.99) for 18F-FDG. Acceptable diagnostic performance of PD with AI algorithms-assisted PET imaging was highlighted across the subgroups. More rigorous reporting standards that take into account the unique challenges of AI research could improve future studies.
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Affiliation(s)
- Jing Wang
- Huashan Hospital & Human Phenome Institute, Fudan University, Shanghai, China
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Le Xue
- Department of Nuclear Medicine, the Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jiehui Jiang
- Institute of Biomedical Engineering, School of Life Science, Shanghai University, Shanghai, China
| | - Fengtao Liu
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine, & National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Ping Wu
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jiaying Lu
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Huiwei Zhang
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Weiqi Bao
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Qian Xu
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Zizhao Ju
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Li Chen
- Department of Ultrasound Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Fangyang Jiao
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Huamei Lin
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jingjie Ge
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
| | - Chuantao Zuo
- Huashan Hospital & Human Phenome Institute, Fudan University, Shanghai, China.
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
- National Clinical Research Center for Aging and Medicine, & National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
| | - Mei Tian
- Huashan Hospital & Human Phenome Institute, Fudan University, Shanghai, China.
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
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Peralta C, Strafella AP, Kim H. Covering Basic Needs on Molecular Imaging. Mov Disord Clin Pract 2024; 11:10-13. [PMID: 38291843 PMCID: PMC10828620 DOI: 10.1002/mdc3.13905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 06/08/2023] [Accepted: 06/18/2023] [Indexed: 02/01/2024] Open
Affiliation(s)
- Cecilia Peralta
- Movement Disorders Clinic, Neuroscience DepartmentHospital Universitario CEMIC, Centro de Educación Médica e Investigaciones Clínicas “Norberto Quirno”Buenos AiresArgentina
| | - Antonio P. Strafella
- Morton and Gloria Shulman Movement Disorder Unit & E.J. Safra Parkinson Disease Program, Division of Neurology/Department of MedicineToronto Western Hospital, University Health NetworkTorontoONCanada
| | - Han‐Joon Kim
- Department of Neurology and Movement Disorder CenterSeoul National University HospitalSeoulKorea
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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.
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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.
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9
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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.
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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.
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10
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Klietz M, Mahmoudi N, Maudsley AA, Sheriff S, Bronzlik P, Almohammad M, Nösel P, Wegner F, Höglinger GU, Lanfermann H, Ding XQ. Whole-Brain Magnetic Resonance Spectroscopy Reveals Distinct Alterations in Neurometabolic Profile in Progressive Supranuclear Palsy. Mov Disord 2023; 38:1503-1514. [PMID: 37289057 DOI: 10.1002/mds.29456] [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: 10/31/2022] [Revised: 03/16/2023] [Accepted: 05/09/2023] [Indexed: 06/09/2023] Open
Abstract
BACKGROUND Progressive supranuclear palsy (PSP) is an atypical Parkinsonian syndrome characterized by supranuclear gaze palsy, early postural instability, and a frontal dysexecutive syndrome. Contrary to normal brain magnetic resonance imaging in Parkinson's disease (PD), PSP shows specific cerebral atrophy patterns and alterations, but these findings are not present in every patient, and it is still unclear if these signs are also detectable in early disease stages. OBJECTIVE The aim of the present study was to analyze the metabolic profile of patients with clinically diagnosed PSP in comparison with matched healthy volunteers and PD patients using whole-brain magnetic resonance spectroscopic imaging (wbMRSI). METHODS Thirty-nine healthy controls (HCs), 29 PD, and 22 PSP patients underwent wbMRSI. PSP and PD patients were matched for age and handedness with HCs. Clinical characterization was performed using the Movement Disorder Society Unified Parkinson's Disease Rating Scale, PSP rating scale, and DemTect (test for cognitive assessment). RESULTS In PSP patients a significant reduction in N-acetyl-aspartate (NAA) was detected in all brain lobes. Fractional volume of the cerebrospinal fluid significantly increased in PSP patients compared to PD and healthy volunteers. CONCLUSIONS In PSP much more neuronal degeneration and cerebral atrophy have been detected compared with PD. The most relevant alteration is the decrease in NAA in all lobes of the brain, which also showed a partial correlation with clinical symptoms. However, more studies are needed to confirm the additional value of wbMRSI in clinical practice. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Martin Klietz
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Nima Mahmoudi
- Department of Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Andrew A Maudsley
- Department of Radiology, University of Miami School of Medicine, Miami, Florida, USA
| | - Sulaiman Sheriff
- Department of Radiology, University of Miami School of Medicine, Miami, Florida, USA
| | - Paul Bronzlik
- Department of Neuroradiology, Hannover Medical School, Hannover, Germany
| | | | - Patrick Nösel
- Department of Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Florian Wegner
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | | | | | - Xiao-Qi Ding
- Department of Neuroradiology, Hannover Medical School, Hannover, Germany
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11
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Lewis MM, Van Scoy LJ, De Jesus S, Hakun JG, Eslinger PJ, Fernandez-Mendoza J, Kong L, Yang Y, Snyder BL, Loktionova N, Duvvuri S, Gray DL, Huang X, Mailman RB. Dopamine D 1 Agonists: First Potential Treatment for Late-Stage Parkinson's Disease. Biomolecules 2023; 13:biom13050829. [PMID: 37238699 DOI: 10.3390/biom13050829] [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: 02/17/2023] [Revised: 03/17/2023] [Accepted: 05/08/2023] [Indexed: 05/28/2023] Open
Abstract
Current pharmacotherapy has limited efficacy and/or intolerable side effects in late-stage Parkinson's disease (LsPD) patients whose daily life depends primarily on caregivers and palliative care. Clinical metrics inadequately gauge efficacy in LsPD patients. We explored if a D1/5 dopamine agonist would have efficacy in LsPD using a double-blind placebo-controlled crossover phase Ia/b study comparing the D1/5 agonist PF-06412562 to levodopa/carbidopa in six LsPD patients. Caregiver assessment was the primary efficacy measure because caregivers were with patients throughout the study, and standard clinical metrics inadequately gauge efficacy in LsPD. Assessments included standard quantitative scales of motor function (MDS-UPDRS-III), alertness (Glasgow Coma and Stanford Sleepiness Scales), and cognition (Severe Impairment and Frontal Assessment Batteries) at baseline (Day 1) and thrice daily during drug testing (Days 2-3). Clinicians and caregivers completed the clinical impression of change questionnaires, and caregivers participated in a qualitative exit interview. Blinded triangulation of quantitative and qualitative data was used to integrate findings. Neither traditional scales nor clinician impression of change detected consistent differences between treatments in the five participants who completed the study. Conversely, the overall caregiver data strongly favored PF-06412562 over levodopa in four of five patients. The most meaningful improvements converged on motor, alertness, and functional engagement. These data suggest for the first time that there can be useful pharmacological intervention in LsPD patients using D1/5 agonists and also that caregiver perspectives with mixed method analyses may overcome limitations using methods common in early-stage patients. The results encourage future clinical studies and understanding of the most efficacious signaling properties of a D1 agonist for this population.
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Affiliation(s)
- Mechelle M Lewis
- Department of Neurology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Department of Pharmacology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Translational Brain Research Center, Penn State Milton S. Hershey Medical Center, Penn State College of Medicine, Hershey, PA 17033, USA
| | - Lauren J Van Scoy
- Translational Brain Research Center, Penn State Milton S. Hershey Medical Center, Penn State College of Medicine, Hershey, PA 17033, USA
- Department of Medicine, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Department of Humanities, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
| | - Sol De Jesus
- Department of Neurology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
| | - Jonathan G Hakun
- Department of Neurology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
| | - Paul J Eslinger
- Department of Neurology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Department of Medicine, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Department of Radiology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
| | - Julio Fernandez-Mendoza
- Department of Neurology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Department of Psychiatry, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
| | - Lan Kong
- Translational Brain Research Center, Penn State Milton S. Hershey Medical Center, Penn State College of Medicine, Hershey, PA 17033, USA
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
| | - Yang Yang
- Department of Neurology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Translational Brain Research Center, Penn State Milton S. Hershey Medical Center, Penn State College of Medicine, Hershey, PA 17033, USA
| | - Bethany L Snyder
- Department of Neurology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Translational Brain Research Center, Penn State Milton S. Hershey Medical Center, Penn State College of Medicine, Hershey, PA 17033, USA
| | - Natalia Loktionova
- Department of Pharmacology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
| | | | - David L Gray
- Cerevel Neurosciences LLC, Cambridge, MA 02141, USA
| | - Xuemei Huang
- Department of Neurology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Department of Pharmacology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Translational Brain Research Center, Penn State Milton S. Hershey Medical Center, Penn State College of Medicine, Hershey, PA 17033, USA
- Department of Radiology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Department of Kinesiology, Pennsylvania State University, University Park, PA 16802, USA
- Department of Neurosurgery, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
| | - Richard B Mailman
- Department of Neurology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Department of Pharmacology, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
- Translational Brain Research Center, Penn State Milton S. Hershey Medical Center, Penn State College of Medicine, Hershey, PA 17033, USA
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12
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Tan AH, Gatto EM. Movement Disorder Rounds: Learning through observation, Building on collective experiences. Parkinsonism Relat Disord 2023; 110:105396. [PMID: 37045676 DOI: 10.1016/j.parkreldis.2023.105396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
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13
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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.
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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
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14
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The challenging quest of neuroimaging: From clinical to molecular-based subtyping of Parkinson disease and atypical parkinsonisms. HANDBOOK OF CLINICAL NEUROLOGY 2023; 192:231-258. [PMID: 36796945 DOI: 10.1016/b978-0-323-85538-9.00004-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
The current framework of Parkinson disease (PD) focuses on phenotypic classification despite its considerable heterogeneity. We argue that this method of classification has restricted therapeutic advances and therefore limited our ability to develop disease-modifying interventions in PD. Advances in neuroimaging have identified several molecular mechanisms relevant to PD, variation within and between clinical phenotypes, and potential compensatory mechanisms with disease progression. Magnetic resonance imaging (MRI) techniques can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging have informed the neurotransmitter, metabolic, and inflammatory dysfunctions that could potentially distinguish disease phenotypes and predict response to therapy and clinical outcomes. However, rapid advancements in imaging techniques make it challenging to assess the significance of newer studies in the context of new theoretical frameworks. As such, there needs to not only be a standardization of practice criteria in molecular imaging but also a rethinking of target approaches. In order to harness precision medicine, a coordinated shift is needed toward divergent rather than convergent diagnostic approaches that account for interindividual differences rather than similarities within an affected population, and focus on predictive patterns rather than already lost neural activity.
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15
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Tinaz S. Magnetic resonance imaging modalities aid in the differential diagnosis of atypical parkinsonian syndromes. Front Neurol 2023; 14:1082060. [PMID: 36816565 PMCID: PMC9932598 DOI: 10.3389/fneur.2023.1082060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 01/16/2023] [Indexed: 02/05/2023] Open
Abstract
Accurate and timely diagnosis of atypical parkinsonian syndromes (APS) remains a challenge. Especially early in the disease course, the clinical manifestations of the APS overlap with each other and with those of idiopathic Parkinson's disease (PD). Recent advances in magnetic resonance imaging (MRI) technology have introduced promising imaging modalities to aid in the diagnosis of APS. Some of these MRI modalities are also included in the updated diagnostic criteria of APS. Importantly, MRI is safe for repeated use and more affordable and accessible compared to nuclear imaging. These advantages make MRI tools more appealing for diagnostic purposes. As the MRI field continues to advance, the diagnostic use of these techniques in APS, alone or in combination, are expected to become commonplace in clinical practice.
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Affiliation(s)
- Sule Tinaz
- Division of Movement Disorders, Department of Neurology, Yale School of Medicine, New Haven, CT, United States
- Department of Neurology, Clinical Neurosciences Imaging Center, Yale School of Medicine, New Haven, CT, United States
- *Correspondence: Sule Tinaz ✉
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16
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Prange S, Theis H, Banwinkler M, van Eimeren T. Molecular Imaging in Parkinsonian Disorders—What’s New and Hot? Brain Sci 2022; 12:brainsci12091146. [PMID: 36138882 PMCID: PMC9496752 DOI: 10.3390/brainsci12091146] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/23/2022] [Accepted: 08/24/2022] [Indexed: 12/02/2022] Open
Abstract
Highlights Abstract Neurodegenerative parkinsonian disorders are characterized by a great diversity of clinical symptoms and underlying neuropathology, yet differential diagnosis during lifetime remains probabilistic. Molecular imaging is a powerful method to detect pathological changes in vivo on a cellular and molecular level with high specificity. Thereby, molecular imaging enables to investigate functional changes and pathological hallmarks in neurodegenerative disorders, thus allowing to better differentiate between different forms of degenerative parkinsonism, improve the accuracy of the clinical diagnosis and disentangle the pathophysiology of disease-related symptoms. The past decade led to significant progress in the field of molecular imaging, including the development of multiple new and promising radioactive tracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) as well as novel analytical methods. Here, we review the most recent advances in molecular imaging for the diagnosis, prognosis, and mechanistic understanding of parkinsonian disorders. First, advances in imaging of neurotransmission abnormalities, metabolism, synaptic density, inflammation, and pathological protein aggregation are reviewed, highlighting our renewed understanding regarding the multiplicity of neurodegenerative processes involved in parkinsonian disorders. Consequently, we review the role of molecular imaging in the context of disease-modifying interventions to follow neurodegeneration, ensure stratification, and target engagement in clinical trials.
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Affiliation(s)
- Stéphane Prange
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Institut des Sciences Cognitives Marc Jeannerod, CNRS, UMR 5229, Université de Lyon, 69675 Bron, France
- Correspondence: (S.P.); (T.v.E.); Tel.: +49-221-47882843 (T.v.E.)
| | - Hendrik Theis
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Department of Neurology, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
| | - Magdalena Banwinkler
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
| | - Thilo van Eimeren
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Department of Neurology, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Correspondence: (S.P.); (T.v.E.); Tel.: +49-221-47882843 (T.v.E.)
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17
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COVID-19 and Parkinsonism: A Critical Appraisal. Biomolecules 2022; 12:biom12070970. [PMID: 35883526 PMCID: PMC9313170 DOI: 10.3390/biom12070970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 07/05/2022] [Accepted: 07/07/2022] [Indexed: 11/16/2022] Open
Abstract
A few cases of parkinsonism linked to COVID-19 infection have been reported so far, raising the possibility of a post-viral parkinsonian syndrome. The objective of this review is to summarize the clinical, biological, and neuroimaging features of published cases describing COVID-19-related parkinsonism and to discuss the possible pathophysiological mechanisms. A comprehensive literature search was performed using NCBI’s PubMed database and standardized search terms. Thirteen cases of COVID-19-related parkinsonism were included (7 males; mean age: 51 years ± 14.51, range 31–73). Patients were classified based on the possible mechanisms of post-COVID-19 parkinsonism: extensive inflammation or hypoxic brain injury within the context of encephalopathy (n = 5); unmasking of underlying still non-symptomatic Parkinson’s Disease (PD) (n = 5), and structural and functional basal ganglia damage (n = 3). The various clinical scenarios show different outcomes and responses to dopaminergic treatment. Different mechanisms may play a role, including vascular damage, neuroinflammation, SARS-CoV-2 neuroinvasive potential, and the impact of SARS-CoV-2 on α-synuclein. Our results confirm that the appearance of parkinsonism during or immediately after COVID-19 infection represents a very rare event. Future long-term observational studies are needed to evaluate the possible role of SARS-CoV-2 infection as a trigger for the development of PD in the long term.
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18
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Mazzucchi S, Del Prete E, Costagli M, Frosini D, Paoli D, Migaleddu G, Cecchi P, Donatelli G, Morganti R, Siciliano G, Cosottini M, Ceravolo R. Morphometric imaging and quantitative susceptibility mapping as complementary tools in the diagnosis of parkinsonisms. Eur J Neurol 2022; 29:2944-2955. [PMID: 35700041 PMCID: PMC9545010 DOI: 10.1111/ene.15447] [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: 03/22/2022] [Revised: 06/02/2022] [Accepted: 06/09/2022] [Indexed: 11/26/2022]
Abstract
Background and purpose In the quest for in vivo diagnostic biomarkers to discriminate Parkinson's disease (PD) from progressive supranuclear palsy (PSP) and multiple system atrophy (MSA, mainly p phenotype), many advanced magnetic resonance imaging (MRI) techniques have been studied. Morphometric indices, such as the Magnetic Resonance Parkinsonism Index (MRPI), demonstrated high diagnostic value in the comparison between PD and PSP. The potential of quantitative susceptibility mapping (QSM) was hypothesized, as increased magnetic susceptibility (Δχ) was reported in the red nucleus (RN) and medial part of the substantia nigra (SNImed) of PSP patients and in the putamen of MSA patients. However, disease‐specific susceptibility values for relevant regions of interest are yet to be identified. The aims of the study were to evaluate the diagnostic potential of a multimodal MRI protocol combining morphometric and QSM imaging in patients with determined parkinsonisms and to explore its value in a population of undetermined cases. Method Patients with suspected degenerative parkinsonism underwent clinical evaluation, 3 T brain MRI and clinical follow‐up. The MRPI was manually calculated on T1‐weighted images. QSM maps were generated from 3D multi‐echo T2*‐weighted sequences. Results In determined cases the morphometric evaluation confirmed optimal diagnostic accuracy in the comparison between PD and PSP but failed to discriminate PD from MSA‐p. Significant nigral and extranigral differences were found with QSM. RN Δχ showed excellent diagnostic accuracy in the comparison between PD and PSP and good accuracy in the comparison of PD and MSA‐p. Optimal susceptibility cut‐off values of RN and SNImed were tested in undetermined cases in addition to MRPI. Conclusions A combined use of morphometric imaging and QSM could improve the diagnostic phase of degenerative parkinsonisms.
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Affiliation(s)
- Sonia Mazzucchi
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Eleonora Del Prete
- Neurology Unit, Department of Medical Specialties, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Mauro Costagli
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy.,Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Daniela Frosini
- Neurology Unit, Department of Medical Specialties, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Davide Paoli
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | | | - Paolo Cecchi
- Neuroradiology Unit, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Graziella Donatelli
- Neuroradiology Unit, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy.,Imago7 Research Foundation, Pisa, Italy
| | | | - Gabriele Siciliano
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Mirco Cosottini
- Imago7 Research Foundation, Pisa, Italy.,Neuroradiology Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Roberto Ceravolo
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.,Centre for Neurodegenerative Diseases, Parkinson's Disease and Movement Disorders, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
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19
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Höllerhage M, Klietz M, Höglinger GU. Disease modification in Parkinsonism: obstacles and ways forward. J Neural Transm (Vienna) 2022; 129:1133-1153. [PMID: 35695938 PMCID: PMC9463344 DOI: 10.1007/s00702-022-02520-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/21/2022] [Indexed: 12/19/2022]
Abstract
To date, the diagnoses of Parkinson syndromes are based on clinical examination. Therefore, these specific diagnoses are made, when the neuropathological process is already advanced. However, disease modification or neuroprotection, is considered to be most effective before marked neurodegeneration has occurred. In recent years, early clinical or prodromal stages of Parkinson syndromes came into focus. Moreover, subtypes of distinct diseases will allow predictions of the individual course of the diseases more precisely. Thereby, patients will be enrolled into clinical trials with more specific disease entities and endpoints. Furthermore, novel fluid and imaging biomarkers that allow biochemical diagnoses are under development. These will lead to earlier diagnoses and earlier therapy in the future as consequence. Furthermore, therapeutic approaches will take the underlying neuropathological process of neurodegenerative Parkinson syndromes more specific into account. Specifically, future therapies will target the aggregation of aggregation-prone proteins such as alpha-synuclein and tau, the degradation of pathological aggregates, and the spreading of pathological protein aggregates throughout the brain. Many of these approaches are already in (pre)clinical development. In addition, anti-inflammatory approaches are in development. Furthermore, drug-repurposing is a feasible approach to shorten the developmental process of new drugs.
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Affiliation(s)
- M Höllerhage
- Department of Neurology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - M Klietz
- Department of Neurology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - G U Höglinger
- Department of Neurology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
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20
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Otani RTV, Yamamoto JYS, Nunes DM, Haddad MS, Parmera JB. Magnetic resonance and dopamine transporter imaging for the diagnosis of Parkinson´s disease: a narrative review. ARQUIVOS DE NEURO-PSIQUIATRIA 2022; 80:116-125. [PMID: 35976320 PMCID: PMC9491424 DOI: 10.1590/0004-282x-anp-2022-s130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 04/29/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND the diagnosis of Parkinson's disease (PD) can be challenging, especially in the early stages, albeit its updated and validated clinical criteria. Recent developments on neuroimaging in PD, altogether with its consolidated role of excluding secondary and other neurodegenerative causes of parkinsonism, provide more confidence in the diagnosis across the different stages of the disease. This review highlights current knowledge and major recent advances in magnetic resonance and dopamine transporter imaging in aiding PD diagnosis. OBJECTIVE This study aims to review current knowledge about the role of magnetic resonance imaging and neuroimaging of the dopamine transporter in diagnosing Parkinson's disease. METHODS We performed a non-systematic literature review through the PubMed database, using the keywords "Parkinson", "magnetic resonance imaging", "diffusion tensor", "diffusion-weighted", "neuromelanin", "nigrosome-1", "single-photon emission computed tomography", "dopamine transporter imaging". The search was restricted to articles written in English, published between January 2010 and February 2022. RESULTS The diagnosis of Parkinson's disease remains a clinical diagnosis. However, new neuroimaging biomarkers hold promise for increased diagnostic accuracy, especially in earlier stages of the disease. CONCLUSION Future validation of new imaging biomarkers bring the expectation of an increased neuroimaging role in the diagnosis of PD in the following years.
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Affiliation(s)
- Rafael Tomio Vicentini Otani
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, São Paulo SP, Brazil
| | - Joyce Yuri Silvestre Yamamoto
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, São Paulo SP, Brazil
| | - Douglas Mendes Nunes
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departmento de Radiologia e Oncologia, Instituto de Radiologia, São Paulo SP, Brazil
| | - Mônica Santoro Haddad
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, São Paulo SP, Brazil
| | - Jacy Bezerra Parmera
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, São Paulo SP, Brazil
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