Selection of Reference Regions to Model Neurodegeneration in Huntington Disease by 18F-FDG PET/CT Using Imaging and Clinical Parameters
Bibliographic record
Abstract
OBJECTIVE: Normalization to an appropriate reference region in F-FDG PET imaging may enhance diagnostic performance in Huntington disease (HD). We aimed to identify stable brain areas that could be used to model neurometabolic degeneration in HD correlating imaging (SUVrvalues at the basal ganglia [BBGG]) and clinical parameters (disease burden score [DBS]). MATERIALS AND METHODS: We performed brain F-FDG PET/CT in 38 manifest HD patients (meanage ± SD, 54 ± 14.3 years; CAGrepeats ± SD, 44.2 ± 3.1), 20 premanifest HD patients (meanage ± SD, 42.7 ± 11.7 years; CAGrepeats ± SD, 40 ± 3.8), and 18 healthy controls (NC; meanage ± SD, 45 ± 13.2 years). For quantitative analysis, we selected (a) defined reference regions from the Montreal Neurological Institute space atlas (pons, whole cerebellum, cerebral white matter, thalamus, and a pons-cerebellar vermis region of interest), and (b) reference clusters obtained by voxelwise statistical comparison across groups (P < 0.05 FWE; extent voxel threshold k = 200). Each candidate reference region and reference cluster was quantitatively assessed using imaging and clinical parameters. RESULTS: Comparing HD and NC groups, we obtained a reference cluster in the cerebellum, and in temporal and frontal lobes. Comparing manifest HD and premanifest HD patients, we observed reference clusters in the cerebellum, pons, thalamus, parietal lobe, and cuneus. The set of reference regions showed a significant correlation between SUVrvalues at the BBGG and DBS in all HD patients. In premanifest HD patients, the correlation between SUVrvalues at the BBGG and DBS was significant using the pons-cerebellar vermis region of interest, the thalamus as defined reference regions, and the pons and thalamus as reference clusters. In manifest HD patients, the correlation was significant using the temporal and white matter frontal lobe clusters. Variance between SUVrvalues in the set of reference regions and reference clusters was minimal within NC. CONCLUSIONS: The pons may be a stable and reliable region to calculate SUVrvalues to model the neurometabolic degeneration in quantitative F-FDG PET imaging in HD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".