Correlations between clinical characteristics and neuroimaging in Chinese patients with subtypes of frontotemporal lobe degeneration
Bibliographic record
Abstract
The aim of the study was to obtain an overview of the clinical and neuroimaging features of Chinese patients with subtypes of frontotemporal lobe degeneration (FTLD).We evaluated the demographic features, clinical presentation, and lobe atrophy depicted by magnetic resonance imaging (MRI) in 133 patients with FTLD. Two positron emission tomography (PET) scans were performed at baseline: [C]Pittsburgh compound B PET to assess amyloid-β plaque load and [F]fluorodeoxyglucose (FDG) PET to assess glucose metabolism.The behavioral variant of FTD (bvFTD) was the most common subtype (67.7%) of FTLD. The percentages of progressive nonfluent aphasia (PNFA) and semantic dementia (SD) were similar. Cerebral lobe atrophy was seen in 87.7% of the cases. The Activities of Daily Living scale, Mini-Mental State Examination, and Montreal Cognitive Assessment scores were significantly correlated with the degree of overall atrophy. The severity of abnormal behavior was correlated with right anterior and right posterior temporal atrophy scores. The overall atrophy scores and atrophy score in the left temporal region were related to cognitive outcomes and Activities of Daily Living scores. Most of the bvFTD patients presented symmetric/asymmetric hypometabolism in the bilateral temporal cortex, frontal cortex, anterior cingulate cortex, insula, and caudate nucleus. All the PNFA patients presented left dominant hypometabolism in the frontal cortex. All the SD patients presented left dominant hypometabolism in the anterior temporal cortex.FTLD is not rare in cognitive clinics, and the ratios of subtypes in Chinese patients are similar to other ethnic groups. Overall atrophy scores, determined by MRI, were related to the severity of cognitive dysfunction and deficits in Activities of Daily Living. Patterns of hypometabolism, determined by [F]FDG PET, were more specific to subtypes of FTLD and may help provide differential diagnoses of variants of FTLD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".