DTI Analysis of Presbycusis Using Voxel-Based Analysis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Presbycusis is the most common sensory deficit in the aging population. A recent study reported using a DTI-based tractography technique to identify a lack of integrity in a portion of the auditory pathway in patients with presbycusis. The aim of our study was to investigate the white matter pathology of patients with presbycusis by using a voxel-based analysis that is highly sensitive to local intensity changes in DTI data. MATERIALS AND METHODS: Fifteen patients with presbycusis and 14 age- and sex-matched healthy controls were scanned on a 3T scanner. Fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were obtained from the DTI data. Intergroup statistics were implemented on these measurements, which were transformed to Montreal Neurological Institute coordinates by using a nonrigid image registration method called large deformation diffeomorphic metric mapping. RESULTS: Increased axial diffusivity, radial diffusivity, and mean diffusivity and decreased fractional anisotropy were found near the right-side hearing-related areas in patients with presbycusis. Increased radial diffusivity and mean diffusivity were also found near a language-related area (Broca area) in patients with presbycusis. CONCLUSIONS: Our findings could be important for exploring reliable imaging evidence of presbycusis and could complement an ROI-based approach.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.000 | 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".