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Mohammadi S, Ghaderi S, Mohammadi H, Fatehi F. Simultaneous Increase of Mean Susceptibility and Mean Kurtosis in the Substantia Nigra as an MRI Neuroimaging Biomarker for Early-Stage Parkinson's Disease: A Systematic Review and Meta-Analysis. J Magn Reson Imaging 2024. [PMID: 39210501 DOI: 10.1002/jmri.29569] [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: 06/13/2024] [Revised: 08/01/2024] [Accepted: 08/01/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Parkinson's disease (PD) is the second most common neurodegenerative disorder. Early detection is crucial for treatment and slowing disease progression. HYPOTHESIS Simultaneous alterations in mean susceptibility (MS) from quantitative susceptibility mapping (QSM) and mean kurtosis (MK) from diffusion kurtosis imaging (DKI) can serve as reliable neuroimaging biomarkers for early-stage PD (ESPD) in the basal ganglia nuclei, including the substantia nigra (SN), putamen (PUT), globus pallidus (GP), and caudate nucleus (CN). STUDY TYPE Systematic review and meta-analysis. POPULATION One hundred eleven patients diagnosed with ESPD and 81 healthy controls (HCs) were included from four studies that utilized both QSM and DKI in both subject groups. FIELD STRENGTH/SEQUENCE Three-dimensional multi-echo gradient echo sequence for QSM and spin echo planar imaging sequence for DKI at 3 Tesla. ASSESSMENT A systematic review and meta-analysis using PRISMA guidelines searched PubMed, Web of Science, and Scopus. STATISTICAL TESTS Random-effects model, standardized mean difference (SMD) to compare MS and MK between ESPD patients and HCs, I2 statistic for heterogeneity, Newcastle-Ottawa Scale (NOS) for risk of bias, and Egger's test for publication bias. A P-value <0.05 was considered significant. RESULTS MS values were significantly higher in SN (SMD 0.72, 95% CI 0.31 to 1.12), PUT (SMD 0.68, 95% CI 0.29 to 1.07), and GP (SMD 0.53, 95% CI 0.19 to 0.87) in ESPD patients compared to HCs. CN did not show a significant difference in MS values (P = 0.15). MK values were significantly higher only in SN (SMD = 0.72, 95% CI 0.16 to 1.27). MK values were not significantly different in PUT (P = 1.00), GP (P = 0.97), and CN (P = 0.59). Studies had high quality (NOS 7-8) and no publication bias (P = 0.967). DATA CONCLUSION Simultaneous use of MS and MK may be useful as an early neuroimaging biomarker for ESPD detection and its differentiation from HCs, with significant differences observed in the SN. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Sana Mohammadi
- Neuromuscular Research Center, Department of Neurology, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Sadegh Ghaderi
- Neuromuscular Research Center, Department of Neurology, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Hossein Mohammadi
- Department of Bioimaging, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences (IUMS), Isfahan, Iran
| | - Farzad Fatehi
- Neuromuscular Research Center, Department of Neurology, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Neurology Department, University Hospitals of Leicester NHS Trust, Leicester, UK
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Kobak Tur E, Ari BC. Mild cognitive impairment in patients with Parkinson´s disease and the analysis of associated factors. Neurol Res 2023; 45:1161-1168. [PMID: 37743634 DOI: 10.1080/01616412.2023.2258038] [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: 05/20/2023] [Accepted: 09/04/2023] [Indexed: 09/26/2023]
Abstract
OBJECTIVES This research targeted to understand the impact of clinical findings, non-motor symptoms, white matter hyperintensities (WMHs), and metabolic features on cognition in Parkinson's disease patients with mild cognitive impairment (PD-MCI). METHODS Sixty-one PD patients sundered into two groups: PD-MCI and normal cognition (PD-NC). We assessed cognition using Montreal Cognitive Assessment-TR (MoCA-TR) and Frontal Assessment Battery (FAB). We used the modified Hoehn&Yahr staging scale (mH&Y), Unified Parkinson's Disease Rating Scale (UPDRS), Freezing of Gait questionnaire, Beck Depression Inventory, Parkinson's disease sleep scale-2, Pittsburgh sleep quality index, Epworth sleepiness scale, and Non-motor symptoms questionnaire to evaluate all patients. We used the Fazekas scale to evaluate the WMHs and also investigated all laboratory parameters affecting cognitive functions. RESULTS Duration of disease, UPDRS-Motor part, age, disease stage, and daytime sleepiness were dramatically higher in the PD-MCI group than in PD-NC (p < 0.05). WMHs and homocysteine were higher in the PD-MCI group than in the controls (p = 0.016 and p < 0.001, respectively). There was a negative correlation between cognition and duration of disease, age, disease stage, UPDRS-Motor scale, daytime drowsiness, WMHs and homocysteine levels. Homocysteine was negatively related to visuospatial/executive functions (r=-0.303, p = 0.021). WMHs were correlated with global cognition (p =.000 r = .-542), language (p = .001, r = -.434), and delayed recall (p = .011, r = -.332). DISCUSSION Mild cognitive impairment is a widespread clinical situation of PD patients and often presents before the motor symptoms. Revealing curable causes that affect cognition before the development of PD-related dementia is crucial in controlling motor findings and reducing the burden of the caretakers.
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Affiliation(s)
- Esma Kobak Tur
- Department of Neurology, University of Health Sciences, Istanbul, Turkey
| | - Buse Cagla Ari
- Department of Neurology, Bahcesehir University Medical Faculty, Istanbul, Turkey
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Kamagata K, Andica C, Kato A, Saito Y, Uchida W, Hatano T, Lukies M, Ogawa T, Takeshige-Amano H, Akashi T, Hagiwara A, Fujita S, Aoki S. Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases. Int J Mol Sci 2021; 22:ijms22105216. [PMID: 34069159 PMCID: PMC8155849 DOI: 10.3390/ijms22105216] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/10/2021] [Accepted: 05/10/2021] [Indexed: 12/27/2022] Open
Abstract
There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.
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Affiliation(s)
- Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
- Correspondence:
| | - Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Ayumi Kato
- Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago 683-8504, Japan;
| | - Yuya Saito
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Taku Hatano
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Matthew Lukies
- Department of Diagnostic and Interventional Radiology, Alfred Health, Melbourne, VIC 3004, Australia;
| | - Takashi Ogawa
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Haruka Takeshige-Amano
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Toshiaki Akashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Shohei Fujita
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
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Bergamino M, Keeling EG, Mishra VR, Stokes AM, Walsh RR. Assessing White Matter Pathology in Early-Stage Parkinson Disease Using Diffusion MRI: A Systematic Review. Front Neurol 2020; 11:314. [PMID: 32477235 PMCID: PMC7240075 DOI: 10.3389/fneur.2020.00314] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Accepted: 03/31/2020] [Indexed: 12/15/2022] Open
Abstract
Structural brain white matter (WM) changes such as axonal caliber, density, myelination, and orientation, along with WM-dependent structural connectivity, may be impacted early in Parkinson disease (PD). Diffusion magnetic resonance imaging (dMRI) has been used extensively to understand such pathological WM changes, and the focus of this systematic review is to understand both the methods utilized and their corresponding results in the context of early-stage PD. Diffusion tensor imaging (DTI) is the most commonly utilized method to probe WM pathological changes. Previous studies have suggested that DTI metrics are sensitive in capturing early disease-associated WM changes in preclinical symptomatic regions such as olfactory regions and the substantia nigra, which is considered to be a hallmark of PD pathology and progression. Postprocessing analytic approaches include region of interest-based analysis, voxel-based analysis, skeletonized approaches, and connectome analysis, each with unique advantages and challenges. While DTI has been used extensively to study WM disorganization in early-stage PD, it has several limitations, including an inability to resolve multiple fiber orientations within each voxel and sensitivity to partial volume effects. Given the subtle changes associated with early-stage PD, these limitations result in inaccuracies that severely impact the reliability of DTI-based metrics as potential biomarkers. To overcome these limitations, advanced dMRI acquisition and analysis methods have been employed, including diffusion kurtosis imaging and q-space diffeomorphic reconstruction. The combination of improved acquisition and analysis in DTI may yield novel and accurate information related to WM-associated changes in early-stage PD. In the current article, we present a systematic and critical review of dMRI studies in early-stage PD, with a focus on recent advances in DTI methodology. Yielding novel metrics, these advanced methods have been shown to detect diffuse WM changes in early-stage PD. These findings support the notion of early axonal damage in PD and suggest that WM pathology may go unrecognized until symptoms appear. Finally, the advantages and disadvantages of different dMRI techniques, analysis methods, and software employed are discussed in the context of PD-related pathology.
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Affiliation(s)
- Maurizio Bergamino
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Elizabeth G. Keeling
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States
- School of Life Sciences, Arizona State University, Tempe, AZ, United States
| | - Virendra R. Mishra
- Imaging Research, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States
| | - Ashley M. Stokes
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Ryan R. Walsh
- Muhammad Ali Parkinson Center, Barrow Neurological Institute, Phoenix, AZ, United States
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Kamagata K, Andica C, Hatano T, Ogawa T, Takeshige-Amano H, Ogaki K, Akashi T, Hagiwara A, Fujita S, Aoki S. Advanced diffusion magnetic resonance imaging in patients with Alzheimer's and Parkinson's diseases. Neural Regen Res 2020; 15:1590-1600. [PMID: 32209758 PMCID: PMC7437577 DOI: 10.4103/1673-5374.276326] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
The prevalence of neurodegenerative diseases is increasing as human longevity increases. The objective biomarkers that enable the staging and early diagnosis of neurodegenerative diseases are eagerly anticipated. It has recently become possible to determine pathological changes in the brain without autopsy with the advancement of diffusion magnetic resonance imaging techniques. Diffusion magnetic resonance imaging is a robust tool used to evaluate brain microstructural complexity and integrity, axonal order, density, and myelination via the micron-scale displacement of water molecules diffusing in tissues. Diffusion tensor imaging, a type of diffusion magnetic resonance imaging technique is widely utilized in clinical and research settings; however, it has several limitations. To overcome these limitations, cutting-edge diffusion magnetic resonance imaging techniques, such as diffusional kurtosis imaging, neurite orientation dispersion and density imaging, and free water imaging, have been recently proposed and applied to evaluate the pathology of neurodegenerative diseases. This review focused on the main applications, findings, and future directions of advanced diffusion magnetic resonance imaging techniques in patients with Alzheimer’s and Parkinson’s diseases, the first and second most common neurodegenerative diseases, respectively.
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Affiliation(s)
- Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Taku Hatano
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan
| | - Takashi Ogawa
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan
| | | | - Kotaro Ogaki
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan
| | - Toshiaki Akashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Shohei Fujita
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
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