ArticleHuman brain mapping2014
Characterization of disease-related covariance topographies with SSMPCA toolbox: effects of spatial normalization and PET scanners.
Article in Human brain mapping, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Abnormal metabolic pattern associated with cognitive impairment in Parkinson's disease: a validation study.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2015Trial
- Network modulation following sham surgery in Parkinson's disease.The Journal of clinical investigation · 2014Trial
- Different brain spatial metabolic patterns characterizing different subtypes of multiple system atrophy.Journal of Parkinson's disease · 2026Article
- Positron Emission Tomography Imaging in Clinical Trials for Parkinson's Disease: Applications of Metabolic Brain Network Approach.Movement disorders : official journal of the Movement Disorder Society · 2025Review
- Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission.European journal of nuclear medicine and molecular imaging · 2024Article
- Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer's disease-related pattern.EJNMMI research · 2023Article
- Classifying migraine using PET compressive big data analytics of brain'sFrontiers in pharmacology · 2023Article
- Nicotinamide Adenine Dinucleotide Supplementation in Parkinson's Disease: A Potential Disease-Modifying Agent Targeting Multiple Pathways.Movement disorders clinical practice · 2022Article
- Identification and validation of Alzheimer's disease-related metabolic brain pattern in biomarker confirmed Alzheimer's dementia patients.Scientific reports · 2022Article
- Neuroimaging evaluation of deep brain stimulation in the treatment of representative neurodegenerative and neuropsychiatric disorders.Bioelectronic medicine · 2021Review
- Validation of the Alzheimer Disease Dementia Conversion-Related Pattern as an ATN Biomarker of Neurodegeneration.Neurology · 2021Article
- Radiomics and supervised machine learning in the diagnosis of parkinsonism with FDG PET: promises and challenges.Annals of translational medicine · 2020Article
- Reproducible metabolic topographies associated with multiple system atrophy: Network and regional analyses in Chinese and American patient cohorts.NeuroImage. Clinical · 2020Article
- Brain Functional and Structural Signatures in Parkinson's Disease.Frontiers in aging neuroscience · 2020Article
- Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.Scientific reports · 2018Article
- Reproducible network and regional topographies of abnormal glucose metabolism associated with progressive supranuclear palsy: Multivariate and univariate analyses in American and Chinese patient cohorts.Human brain mapping · 2018Article
- FDG PET Parkinson's disease-related pattern as a biomarker for clinical trials in early stage disease.NeuroImage. Clinical · 2018Article
- Validation of abnormal glucose metabolism associated with Parkinson's disease in Chinese participants based on 18F-fluorodeoxyglucose positron emission tomography imaging.Neuropsychiatric disease and treatment · 2018Article
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7 authors.
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Abstract
To generate imaging biomarkers from disease-specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [(18) F]fluorodeoxyglucose PET scans from patients with PD and normal controls. Motor-related (PDRP) and cognition-related (PDCP) metabolic patterns were derived from images spatially normalized using four versions of SPM software (spm99, spm2, spm5, and spm8). Differences between these patterns and subject scores were compared across multiple independent groups of patients and control subjects. These patterns and subject scores were highly reproducible with different normalization programs in terms of disease discrimination and cognitive correlation. Subject scores were also comparable in patients with PD imaged across multiple PET scanners. Our findings confirm a very high degree of consistency among brain networks and their clinical correlates in PD using images normalized in four different SPM platforms. SSMPCA toolbox can be used reliably for generating disease-specific imaging biomarkers despite the continued evolution of image preprocessing software in the neuroimaging community. Network expressions can be quantified in individual patients independent of different physical characteristics of PET cameras.
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