ArticleNeuroImage. Clinical2016
Discriminating among degenerative parkinsonisms using advanced (123)I-ioflupane SPECT analyses.
Article in NeuroImage. Clinical, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.
- IMovement disorders clinical practice · 2024Pooled it
- The Role of DaT-SPECT Imaging in the Evaluation of Progressive Supranuclear Palsy.Life (Basel, Switzerland) · 2026Review
- Correlations between cerebrospinal fluid homovanillic acid and dopamine transporter SPECT in degenerative parkinsonian syndromes.Journal of neural transmission (Vienna, Austria : 1996) · 2023Article
- Multimodality imaging of neurodegenerative disorders with a focus on multiparametric magnetic resonance and molecular imaging.Insights into imaging · 2023Review
- The tauopathies: Neuroimaging characteristics and emerging experimental therapies.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2022Review
- Using Artificial Neural Network to Discriminate Parkinson's Disease from Other Parkinsonisms by Focusing on Putamen of Dopamine Transporter SPECT Images.Biomedicines · 2020Article
- Ioflupane 123I (DAT scan) SPECT identifies dopamine receptor dysfunction early in the disease course in progressive apraxia of speech.Journal of neurology · 2020Article
- Classification of degenerative parkinsonism subtypes by support-vector-machine analysis and striatalJournal of neurology · 2019Article
- Parkinson's Disease Detection Using Isosurfaces-Based Features and Convolutional Neural Networks.Frontiers in neuroinformatics · 2019Article
- Degree of dopaminergic degeneration measured byNeural regeneration research · 2018Article
- Robust Ensemble Classification Methodology for I123-Ioflupane SPECT Images and Multiple Heterogeneous Biomarkers in the Diagnosis of Parkinson's Disease.Frontiers in neuroinformatics · 2018Article
- Comparison of machine learning and semi-quantification algorithms for (I123)FP-CIT classification: the beginning of the end for semi-quantification?EJNMMI physics · 2017Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
(123)I-ioflupane single photon emission computed tomography (SPECT) is a sensitive and well established imaging tool in Parkinson's disease (PD) and atypical parkinsonian syndromes (APS), yet a discrimination between PD and APS has been considered inconsistent at least based on visual inspection or simple region of interest analyses. We here reappraise this issue by applying advanced image analysis techniques to separate PD from the various APS. This study included 392 consecutive patients with degenerative parkinsonism undergoing (123)I-ioflupane SPECT at our institution over the last decade: 306 PD, 24 multiple system atrophy (MSA), 32 progressive supranuclear palsy (PSP) and 30 corticobasal degeneration (CBD) patients. Data analysis included voxel-wise univariate statistical parametric mapping and multivariate pattern recognition using linear discriminant classifiers. MSA and PSP showed less ioflupane uptake in the head of caudate nucleus relative to PD and CBD, yet there was no difference between MSA and PSP. CBD had higher uptake in both putamen relative to PD, MSA and PSP. Classification was significant for PD versus APS (AUC 0.69, p < 0.05) and between APS subtypes (MSA vs CBD AUC 0.80, p < 0.05; MSA vs PSP AUC 0.69 p < 0.05; CBD vs PSP AUC 0.69 p < 0.05). Both striatal and extra-striatal regions contain classification information, yet the combination of both regions does not significantly improve classification accuracy. PD, MSA, PSP and CBD have distinct patterns of dopaminergic depletion on (123)I-ioflupane SPECT. The high specificity of 84-90% for PD versus APS indicates that the classifier is particularly useful for confirming APS cases.
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