Dopaminergic imaging in degenerative parkinsonisms, an established clinical diagnostic tool.
Nicolas NicastroUmberto NenchaPierre R BurkhardValentina GaribottoPublished in: Journal of neurochemistry (2021)
Parkinson's disease (PD) and other neurodegenerative parkinsonisms are characterised by loss of striatal dopaminergic neurons. Dopamine functional deficits can be measured in vivo using positron emission tomography (PET) and single-photon emission computed tomography (SPECT) ligands assessing either presynaptic (e.g. dopamine synthesis and storage, transporter density) or postsynaptic terminals (i.e. D2 receptors availability). Nuclear medicine imaging thus helps the clinician to separate degenerative forms of parkinsonism with other neurological conditions, e.g. essential tremor or drug-induced parkinsonism. With the present study, we aimed at summarizing the current evidence about dopaminergic molecular imaging in the diagnostic evaluation of PD, atypical parkinsonian syndromes and dementia with Lewy bodies (DLB), as well as its potential to distinguish these conditions and to estimate disease progression. In fact, PET/SPECT methods are clinically validated and have been increasingly integrated into diagnostic guidelines (e.g. for PD and DLB). In addition, there is novel evidence on the classification properties of extrastriatal signal. Finally, dopamine imaging has an outstanding potential to detect neurodegeneration at the premotor stage, including REM-sleep behavior disorder and olfactory loss. Therefore, inclusion of subjects at an early stage for clinical trials can largely benefit from a validated in vivo biomarker such as presynaptic dopamine pathways PET/SPECT assessment.
Keyphrases
- positron emission tomography
- computed tomography
- pet ct
- drug induced
- parkinson disease
- liver injury
- high resolution
- early stage
- uric acid
- clinical trial
- pet imaging
- magnetic resonance imaging
- deep brain stimulation
- physical activity
- spinal cord
- traumatic brain injury
- sleep quality
- mild cognitive impairment
- machine learning
- radiation therapy
- climate change
- spinal cord injury
- lymph node
- clinical practice
- functional connectivity
- risk assessment
- double blind
- adverse drug