Assessing neuroinflammatory differences in FTLD‐Tau vs FTLD‐TDP using free water diffusion
Bibliographic record
Abstract
Abstract Background Frontotemporal lobar degeneration (FTLD) is associated with two pathological substrates: Tau and TAR‐DNA‐binding protein 43 (TDP‐43). In‐vivo detection of the pathological substrate is still not possible in FTLD‐related syndromes but progressive supranuclear palsy (PSP) is consistently associated with FTLD‐Tau while semantic‐variant primary progressive aphasia (svPPA) and FTD‐MND (FTD‐ALS) are associated with FTLD‐TDP. In the absence of disease‐specific markers in FTLD, it is necessary to identify biomarkers that can help distinguish FTLD‐Tau and FTLD‐TDP. Recent research has implicated neuroinflammation as a common feature across FTLD subtypes (Bright et al., 2019), however further research is required to investigate neuroinflammatory differences between FTLD‐Tau and FTLD‐TDP, given that microglial burden and activation may differ in FTLD subtypes (Woollacott et al., 2020). The free water fraction (FW), a metric generated from diffusion MRI (dMRI) (Pasternak et al., 2009), is a non‐specific marker of neuroinflammation (Bergamino, Walsh and Stokes, 2021). We will investigate differences in FW diffusion between patients with presumed FTLD‐Tau versus FTLD‐TDP. We hypothesize that differences in neuroinflammation between FTLD‐Tau and FTLD‐TDP can be identified using the free water measure, which may infer neuroinflammatory differences. Method Free‐water maps were generated from dMRI datasets obtained from 43 subjects: 19 with presumed FTLD‐Tau (PSP, mean age = 70), 6 with presumed FTLD‐TDP (mean age = 67, 4 svPPA, 2 FTD‐ALS), and 19 healthy controls (mean age 63). Grey matter (GM) was segmented from T1‐weighted MRIs using FSL’s ‘fast’, projected onto the diffusion MRI space, where free‐water maps were averaged across the GM. The average free water estimates from FTLD‐Tau, FTLD‐TDP and control datasets were tested for group differences using student’s t‐tests and analysis of covariance (ANCOVA), with age as a covariate. Results ANCOVA revealed significant differences between the groups (F = 6.47, p < 0.01). Post‐hoc tests showed significantly higher free‐water in FTLD‐Tau (p<0.01) and FTLD‐TDP (p<0.01) compared to controls. There was also higher free water in FTLD‐TDP in comparison to FTLD‐Tau, approaching significance (p = 0.0503) Conclusion Our preliminary data shows significant differences between healthy controls and patients with FTLD‐Tau and FTLD‐TDP and a trend for increased free water in FTLD‐TDP patients vs FTLD‐Tau, which may be indicative of neuroinflammatory differences.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".