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PD and DLB: Brain imaging in Parkinson's disease and dementia with Lewy bodies.

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Parkinson's disease (PD) and Dementia with Lewy Bodies (DLB) are both neurodegenerative diseases characterized by the abnormal intraneuronal accumulation of misfolded α-Synuclein into Lewy bodies and Lewy neurites. They are… Click to show full abstract

Parkinson's disease (PD) and Dementia with Lewy Bodies (DLB) are both neurodegenerative diseases characterized by the abnormal intraneuronal accumulation of misfolded α-Synuclein into Lewy bodies and Lewy neurites. They are distinguished in part by the temporal relationship between the onset of parkinsonism versus cognitive signs, with the former occurring earlier in PD and the latter generally occurring earlier in DLB, along with additional clinical features more prominent in DLB. While clinical criteria help to elucidate diagnosis based on history and exam, definitive diagnosis can only be made at autopsy. More recently, various brain imaging modalities have been utilized to augment diagnostic accuracy made at the bedside and are being studied as possible means to monitor progression or to provide early diagnostic biomarkers. Structural imaging techniques such as structural MRI have some utility in differentiating PD from other causes of parkinsonism, and in differentiating DLB from Alzheimer's disease (AD). In addition, molecular and metabolic brain imaging modalities have shown great promise in elucidating possible diagnostic biomarkers and in providing insight into disease severity and pathogenesis for both PD and DLB. In this review, we summarize the utility of clinically available and research-based brain imaging in diagnosis and monitoring in PD and DLB, which are helping to improve early diagnosis, are providing insight into pathologic mechanisms of disease, and may help to provide biomarker monitoring for disease progression and clinical trials.

Keywords: parkinson disease; lewy bodies; disease; brain imaging; disease dementia

Journal Title: Progress in molecular biology and translational science
Year Published: 2019

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