Predicting Parkinson's disease trajectory using clinical and neuroimaging baseline measures.
Parkinsonism Relat Disord
; 85: 44-51, 2021 04.
Article
em En
| MEDLINE
| ID: mdl-33730626
ABSTRACT
INTRODUCTION:
Predictive biomarkers of Parkinson's Disease progression are needed to expedite neuroprotective treatment development and facilitate prognoses for patients. This work uses measures derived from resting-state functional magnetic resonance imaging, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF), to predict an individual's current and future severity over up to 4 years and to elucidate the most prognostic brain regions.METHODS:
ReHo and fALFF are measured for 82 Parkinson's Disease subjects and used to train machine learning predictors of baseline clinical and future severity at 1 year, 2 years, and 4 years follow-up as measured by the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Predictive performance is measured with nested cross-validation, validated on an external dataset, and again validated through leave-one-site-out cross-validation. Important predictive features are identified.RESULTS:
The models explain up to 30.4% of the variance in current MDS-UPDRS scores, 55.8% of the variance in year 1 scores, and 47.1% of the variance in year 2 scores (p < 0.0001). For distinguishing high and low-severity individuals at each timepoint (MDS-UPDRS score above or below the median, respectively), the models achieve positive predictive values up to 79% and negative predictive values up to 80%. Higher ReHo and fALFF in several regions, including components of the default motor network, predicted lower severity across current and future timepoints.CONCLUSION:
These results identify an accurate prognostic neuroimaging biomarker which may be used to better inform enrollment in trials of neuroprotective treatments and enable physicians to counsel their patients.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Doença de Parkinson
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Imageamento por Ressonância Magnética
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Cerebelo
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Córtex Cerebral
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Progressão da Doença
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Neuroimagem Funcional
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Aprendizado de Máquina
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Rede de Modo Padrão
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Rede Nervosa
Tipo de estudo:
Observational_studies
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Prognostic_studies
/
Risk_factors_studies
Aspecto:
Patient_preference
Limite:
Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Parkinsonism Relat Disord
Ano de publicação:
2021
Tipo de documento:
Article