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Brinia ME, Kapsali I, Giagkou N, Constantinides VC. Planimetric and Volumetric Brainstem MRI Markers in Progressive Supranuclear Palsy, Multiple System Atrophy, and Corticobasal Syndrome. A Systematic Review and Meta-Analysis. Neurol Int 2023; 16:1-19. [PMID: 38392951 PMCID: PMC10892270 DOI: 10.3390/neurolint16010001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 12/13/2023] [Accepted: 12/13/2023] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND Various MRI markers-including midbrain and pons areas (Marea, Parea) and volumes (Mvol, Pvol), ratios (M/Parea, M/Pvol), and composite markers (magnetic resonance imaging Parkinsonism Indices 1,2; MRPI 1,2)-have been proposed as imaging markers of Richardson's syndrome (RS) and multiple system atrophy-Parkinsonism (MSA-P). A systematic review/meta-analysis of relevant studies aiming to compare the diagnostic accuracy of these imaging markers is lacking. METHODS Pubmed and Scopus were searched for studies with >10 patients (RS, MSA-P or CBS) and >10 controls with data on Marea, Parea, Mvol, Pvol, M/Parea, M/Pvol, MRPI 1, and MRPI 2. Cohen's d, as a measure of effect size, was calculated for all markers in RS, MSA-P, and CBS. RESULTS Twenty-five studies on RS, five studies on MSA-P, and four studies on CBS were included. Midbrain area provided the greatest effect size for differentiating RS from controls (Cohen's d = -3.10; p < 0.001), followed by M/Parea and MRPI 1. MSA-P had decreased midbrain and pontine areas. Included studies exhibited high heterogeneity, whereas publication bias was low. CONCLUSIONS Midbrain area is the optimal MRI marker for RS, and pons area is optimal for MSA-P. M/Parea and MRPIs produce smaller effect sizes for differentiating RS from controls.
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Affiliation(s)
| | | | | | - Vasilios C. Constantinides
- First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Eginition Hospital, 11528 Athens, Greece; (M.-E.B.); (I.K.)
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Shetty N, Koteshwar P, Priyanka. Identification of optimal value of magnetic resonance planimetry and the parkinsonism index for the diagnosis of Parkinson's disease and progressive supranuclear palsy. J Taibah Univ Med Sci 2023; 18:1577-1585. [PMID: 37701844 PMCID: PMC10494174 DOI: 10.1016/j.jtumed.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 05/30/2023] [Accepted: 07/10/2023] [Indexed: 09/14/2023] Open
Abstract
Objectives Parkinson's disease (PD) and progressive supranuclear palsy (PSP) are neurodegenerative conditions that have overlapping clinical and imaging features, thus making it difficult to distinguish and diagnose PSP from PD. Therefore, in this study, we aimed to investigate the optimal value of magnetic resonance planimetry and the parkinsonism index to differentiate between PSP and PD. Methods In this retrospective study, we recruited a total of 84 patients (27 patients with PSP, 27 patients with PD and 27 normal controls) who underwent MRI brain examinations. For each subject, we calculated the corpus callosum area, midbrain area, pons area, middle cerebellar peduncle (MCP) width and superior cerebellar peduncle (SCP) width on MRI brain images. We also calculated the pons to midbrain area (P/M) ratio, MCP/SCP ratio and magnetic resonance parkinsonism index (MRPI). Results Receiver operating characteristic curve (ROC) analysis was used to identify the diagnostic value of each biomarker. MRPI had a sensitivity of 70.4%, a specificity of 88.9%, and a diagnostic accuracy of 79.6% with an optimum cut off of 24.3 for differentiating PSP from PD. P/M ratio had a sensitivity of 74.1%, a specificity of 77.8%, and a diagnostic accuracy of 75.9% with an optimal cutoff of 24.3 for differentiating PSP from PD. The MCP/SCP ratio had a sensitivity of 66.7%, a specificity of 77.8%, and an accuracy of 72.2% with an optimal cut off of 4.65 for differentiating PSP from PD. Conclusions The study revealed that MRPI and P/M ratio are accurate markers for differentiating PSP from PD. The optimal cut-off values derived from our study can help in the early diagnosis of PD.
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Affiliation(s)
- Nikhitha Shetty
- Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, India
- Department of Medical Imaging Sciences, College of Health Sciences, Gulf Medical University, Ajman, UAE
| | - Prakashini Koteshwar
- Department of Radiodiagnosis and Imaging, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Priyanka
- Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, India
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Xue J, Li F, Dai P. The Potential of ANK1 to Predict Parkinson's Disease. Genes (Basel) 2023; 14:genes14010226. [PMID: 36672967 PMCID: PMC9859451 DOI: 10.3390/genes14010226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/10/2023] [Accepted: 01/12/2023] [Indexed: 01/18/2023] Open
Abstract
The main cause of Parkinson's disease (PD) remains unknown and the pathologic changes in the brain limit rapid diagnosis. Herein, differentially expressed genes (DEGs) in the Gene Expression Omnibus (GEO) database (GSE8397 and GSE22491) were assessed using linear models for microarray analysis (limma). Ankyrin 1 (ANK1) was the only common gene differentially down-regulated in lateral substantia nigra (LSN), medial substantia nigra (MSN) and blood. Additionally, DEGs between high ANK1 and low ANK1 in GSE99039 were picked out and then uploaded to the Database for Annotation, Visualization and Integrated Discovery (DAVID) for gene ontology (GO) functional annotation analysis. GO analysis displayed that these DEGs were mainly enriched in oxygen transport, myeloid cell development and gas transport (biological process (BP)); hemoglobin complex, haptoglobin-hemoglobin complex and cortical cytoskeleton (cellular component (CC)); and oxygen transporter activity, haptoglobin binding and oxygen binding (molecular function (MF)). Receiver operating characteristic (ROC) curve analysis showed ANK1 had good diagnostic accuracy and increased the area under the curve (AUC) value when combined with other biomarkers. Consistently, intraperitoneal injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropy-ridi-ne (MPTP) in C57BL/6J mice reduced ANK1 mRNA expression in both substantia nigra and blood compared to the control group. Thus, ANK1 may serve as a candidate biomarker for PD diagnosis.
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Magnetic Resonance Planimetry in the Differential Diagnosis between Parkinson’s Disease and Progressive Supranuclear Palsy. Brain Sci 2022; 12:brainsci12070949. [PMID: 35884755 PMCID: PMC9313181 DOI: 10.3390/brainsci12070949] [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: 06/19/2022] [Revised: 07/12/2022] [Accepted: 07/14/2022] [Indexed: 12/10/2022] Open
Abstract
The clinical differential diagnosis between Parkinson’s disease (PD) and progressive supranuclear palsy (PSP) is often challenging. The description of milder PSP phenotypes strongly resembling PD, such as PSP-Parkinsonism, further increased the diagnostic challenge and the need for reliable neuroimaging biomarkers to enhance the diagnostic certainty. This review aims to summarize the contribution of a relatively simple and widely available imaging technique such as MR planimetry in the differential diagnosis between PD and PSP, focusing on the recent advancements in this field. The development of accurate MR planimetric biomarkers, together with the implementation of automated algorithms, led to robust and objective measures for the differential diagnosis of PSP and PD at the individual level. Evidence from longitudinal studies also suggests a role of MR planimetry in predicting the development of the PSP clinical signs, allowing to identify PSP patients before they meet diagnostic criteria when their clinical phenotype can be indistinguishable from PD. Finally, promising evidence exists on the possible association between MR planimetric measures and the underlying pathology, with important implications for trials with new disease-modifying target therapies.
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Diagnostic Performance of the Magnetic Resonance Parkinsonism Index in Differentiating Progressive Supranuclear Palsy from Parkinson's Disease: An Updated Systematic Review and Meta-Analysis. Diagnostics (Basel) 2021; 12:diagnostics12010012. [PMID: 35054178 PMCID: PMC8774886 DOI: 10.3390/diagnostics12010012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 12/13/2021] [Accepted: 12/20/2021] [Indexed: 12/17/2022] Open
Abstract
Progressive supranuclear palsy (PSP) and Parkinson's disease (PD) are difficult to differentiate especially in the early stages. We aimed to investigate the diagnostic performance of the magnetic resonance parkinsonism index (MRPI) in differentiating PSP from PD. A systematic literature search of PubMed-MEDLINE and EMBASE was performed to identify original articles evaluating the diagnostic performance of the MRPI in differentiating PSP from PD published up to 20 February 2021. The pooled sensitivity, specificity, and 95% CI were calculated using the bivariate random-effects model. The area under the curve (AUC) was calculated using a hierarchical summary receiver operating characteristic (HSROC) model. Meta-regression was performed to explain the effects of heterogeneity. A total of 14 original articles involving 484 PSP patients and 1243 PD patients were included. In all studies, T1-weighted images were used to calculate the MRPI. Among the 14 studies, nine studies used 3D T1-weighted images. The pooled sensitivity and specificity for the diagnostic performance of the MRPI in differentiating PSP from PD were 96% (95% CI, 87-99%) and 98% (95% CI, 91-100%), respectively. The area under the HSROC curve was 0.99 (95% CI, 0.98-1.00). Heterogeneity was present (sensitivity: I2 = 97.29%; specificity: I2 = 98.82%). Meta-regression showed the association of the magnet field strength with heterogeneity. Studies using 3 T MRI showed significantly higher sensitivity (100%) and specificity (100%) than those of studies using 1.5 T MRI (sensitivity of 98% and specificity of 97%) (p < 0.01). Thus, the MRPI could accurately differentiate PSP from PD and support the implementation of appropriate management strategies for patients with PSP.
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Zhang K, Liang Z, Wang C, Zhang X, Yu B, Liu X. Diagnostic validity of magnetic resonance parkinsonism index in differentiating patients with progressive supranuclear palsy from patients with Parkinson's disease. Parkinsonism Relat Disord 2019; 66:176-181. [PMID: 31420309 DOI: 10.1016/j.parkreldis.2019.08.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 06/30/2019] [Accepted: 08/09/2019] [Indexed: 01/05/2023]
Abstract
BACKGROUND Progressive supranuclear palsy is a neuropathologically defined disease, and many studies worked on detecting the diagnostic use of Magnetic resonance imaging. This article purposed to detect the diagnostic performance of Magnetic resonance parkinsonism index (MRPI). METHODS We systematically searched electronic database PubMed for articles published since 1996 using the National Institute of Neurological Disorders and Stroke and Society for PSP (NINDS-SPSP) criteria as the diagnostic standard. Methodological quality was assessed by Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and software Review Manager 5.3, software STATA 14.0 and meta-disc were applied in statistics analysis. RESULTS Totally 14 articles were included in this article. MRPI is proved to have pooled sensitivity of 0.98, pooled specificity of 0.99 in differentiating patients with Progressive supranuclear palsy (PSP) from patients with Parkinson's disease (PD) and the area under the Receiver operating characteristic curve value was 1.00. CONCLUSION MRPI shows excellent performance in differentiating patients with PSP from patients with PD, the clinical usage of MRPI in auxiliary diagnosis of PSP is recommended.
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Affiliation(s)
- Kejia Zhang
- School of Clinical Medicine, Jilin University, Changchun, China
| | - Zhenzhen Liang
- NHC Key Lab of Radiobiology (Jilin University), Changchun, Jilin, 130021, China
| | - Chunpeng Wang
- School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, 130000, China
| | - Xueyuan Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Binbin Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China
| | - Xin Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, 130021, China.
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Quattrone A, Morelli M, Vescio B, Nigro S, Le Piane E, Sabatini U, Caracciolo M, Vescio V, Quattrone A, Barbagallo G, Stanà C, Nicoletti G, Arabia G, Nisticò R, Novellino F, Salsone M. Refining initial diagnosis of Parkinson's disease after follow-up: A 4-year prospective clinical and magnetic resonance imaging study. Mov Disord 2019; 34:487-495. [PMID: 30759325 PMCID: PMC6593994 DOI: 10.1002/mds.27621] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 12/27/2018] [Accepted: 01/02/2019] [Indexed: 01/05/2023] Open
Abstract
Background No prospective study of patients with Parkinson's disease (PD) has investigated the appearance of vertical gaze abnormalities, a feature suggestive of progressive supranuclear palsy (PSP). Objective To identify, within a cohort of patients with an initial diagnosis of PD, those who developed vertical gaze abnormalities during a 4‐year follow‐up, and to investigate the performance of new imaging biomarkers in predicting vertical gaze abnormalities. Methods A total of 110 patients initially classified as PD and 74 controls were enrolled. All patients underwent clinical assessment at baseline and every year up to the end of the follow‐up. The pons/midbrain area ratio 2.0 and the Magnetic Resonance Parkinsonism Index 2.0 were calculated. Results After 4‐year follow‐up, 100 of 110 patients maintained the diagnosis of PD, whereas 10 PD patients (9.1%) developed vertical gaze abnormalities, suggesting an alternative diagnosis of PSP‐parkinsonism. At baseline, the Magnetic Resonance Parkinsonism Index 2.0 was the most accurate biomarker in differentiating PD patients who developed vertical gaze abnormalities from those who maintained an initial diagnosis of PD. At the end of follow‐up, both of these biomarkers accurately distinguished PSP‐parkinsonism from PD. Conclusions Our results demonstrate that a number of patients with an initial diagnosis of PD developed vertical gaze abnormalities during a 4‐year follow‐up, and the diagnosis was changed from PD to PSP‐parkinsonism. In PD patients, baseline Magnetic Resonance Parkinsonism Index 2.0 showed the best performance in predicting the clinical evolution toward a PSP‐parkinsonism phenotype, enabling PSP‐parkinsonism patients to be identified at the earliest stage of the disease for promising disease‐modifying therapies. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Aldo Quattrone
- Neuroscience Centre, Magna Graecia University, Catanzaro, Italy.,Neuroimaging Research Unit, Institute of Molecular Bioimaging and Physiology, National Research Council, Catanzaro, Italy
| | - Maurizio Morelli
- Neuroimaging Research Unit, Institute of Molecular Bioimaging and Physiology, National Research Council, Catanzaro, Italy.,Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro, Italy
| | | | - Salvatore Nigro
- Neuroimaging Research Unit, Institute of Molecular Bioimaging and Physiology, National Research Council, Catanzaro, Italy
| | - Emilio Le Piane
- Department of Neurology, Pugliese-Ciaccio Hospital, Catanzaro, Italy
| | - Umberto Sabatini
- Institute of Neuroradiology, Magna Graecia University, Catanzaro, Italy
| | - Manuela Caracciolo
- Neuroimaging Research Unit, Institute of Molecular Bioimaging and Physiology, National Research Council, Catanzaro, Italy
| | - Virginia Vescio
- Institute of Neuroradiology, Magna Graecia University, Catanzaro, Italy
| | - Andrea Quattrone
- Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro, Italy
| | - Gaetano Barbagallo
- Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro, Italy
| | - Carlo Stanà
- Institute of Neuroradiology, Magna Graecia University, Catanzaro, Italy
| | - Giuseppe Nicoletti
- Neuroimaging Research Unit, Institute of Molecular Bioimaging and Physiology, National Research Council, Catanzaro, Italy
| | - Gennarina Arabia
- Neuroimaging Research Unit, Institute of Molecular Bioimaging and Physiology, National Research Council, Catanzaro, Italy.,Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro, Italy
| | - Rita Nisticò
- Neuroimaging Research Unit, Institute of Molecular Bioimaging and Physiology, National Research Council, Catanzaro, Italy
| | - Fabiana Novellino
- Neuroimaging Research Unit, Institute of Molecular Bioimaging and Physiology, National Research Council, Catanzaro, Italy
| | - Maria Salsone
- Neuroimaging Research Unit, Institute of Molecular Bioimaging and Physiology, National Research Council, Catanzaro, Italy
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