Regional impact of field strength on voxel‐based morphometry results
Bibliographic record
Abstract
The objective of this study was to characterize the sensitivity of voxel-based morphometry (VBM) results to choice field strength. We chose to investigate the two most widespread acquisition sequences for VBM, FLASH and MP-RAGE, at 1.5 and 3 T. We first evaluated image quality of the four acquisition protocols in terms of SNR and image uniformity. We then performed a VBM study on eight subjects scanned twice using the four protocols to evaluate differences in grey matter (GM) density and corresponding scan-rescan variability, and a power analysis for each protocol in the context a longitudinal and cross-sectional VBM study. As expected, the SNR increased significantly at 3 T for both FLASH and MP-RAGE. Image non-uniformity increased as well, in particular for MP-RAGE. The differences in CNR and contrast non-uniformity cause regional biases between protocols in the VBM results, in particular between sequences at 3 T. The power analysis results show an overall decrease in the number of subjects required in a longitudinal study to detect a difference in GM density at 3 T for MP-RAGE, but an increase for FLASH. The number of subjects required in a cross-sectional VBM study is higher at 3 T for both sequences. Our results show that each protocol has a distinct regional sensitivity pattern to morphometric change, which goes against the classical view of VBM as an unbiased whole brain analysis technique, complicates the combination of data within a VBM study and the direct comparison of VBM studies based on different protocols.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".