Intrastriatal analysis of FDOPA PET scans for differentiation of Parkinsonian Disorders
Bibliographic record
Abstract
Aim: L-3,4-dihydroxy-6-18F-fluorophenylalanine (FDOPA) PET allows quantification of presynaptic dopaminergic functioning in vivo. It assesses the function of nigrostriatal projection neurons, particularly dopamine release in the striatum. Previously, it was postulated that Idiopathic Parkinson’s disease (IPD) preferentially affects the posterior putamen. This study aims to investigate the potential of FDOPA PET scans to differentiate atypical parkinsonian disorders (APD), idiopathic parkinson’s disease (IPD) and healthy controls. Materials & Methods: 58 patients (28 IPD, 13 APD and 17 controls) who underwent FDOPA PET scan as part of the clinical evaluation and who were diagnosed by movement disorder specialists, were retrospectively analyzed. Average age of IPD, APD and controls was 61.0, 69.6 and 65.4 respectively. All were scanned on a Siemens HR+ camera, with injected dose of 200MBq and pretreated with carbidopa, 2.5 mg/kg orally. After spatial normalization of images in standard MNI space (Montreal Neurological Institute), predefined sets of volumes of interest (VOIs) were used to sample values from striatum and the occipital reference region. Outcome values were striatal-to-occipital ratios (SOR), intrastriatal ratios and slope of multiple in-line spherical VOIs through the striatum anterior to posterior (gradient analysis). All values were compared between groups using ANOVA test and ROC curves were calculated. Results: SOR values showed no statistically significant difference between APD and IPD patients. When analyzing intrastriatal ratios, caudate-to-putamen was found to be statistically significant when comparing APD and IPD (p<0.001; anterior putamen: 0.94±0.06 vs. 1.05±0.10; posterior putamen: 1.10±0.12 vs. 1.26±0.19, respectively). Gradient analysis also showed statistically significant differences between APD and IPD (p=0.006, 0.07±0.05 vs. 0.12±0.07). In ROC curve, separating controls from parkinsonian patients, the caudate-to-posterior putamen ratio showed the highest area under the curve (AUC=0.930), while for differentiating APD from IPD the highest AUC was the caudate-to-anterior putamen ratio (0.824). Conclusion: SOR value is currently used in clinical routine to discriminate healthy from parkinsonian patients. However, results from this study have shown that the best value for this differentiation seems to be the caudate-to-posterior putamen ratio. In addition, caudate-to-anterior putamen is capable to discriminate between atypical and idiopathic parkinsonian patients. These results are in agreement with previous publications, and support the implementation of this ratios in clinical routine. Moreover, the positive results of the gradient analysis support further exploration of this approach, and its possibilities of creating a model that combines different image measurements and/or clinical information to improve the accuracy for discriminating APD and IPD
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".