Repeatability and reproducibility of rapid T1 mapping of brain tissues at 64 mT: A multicentre study
Bibliographic record
Abstract
Abstract Very-low-field MRI (<100 mT) holds promise for Point-of-Care brain imaging applications, including stroke and multiple sclerosis, with T1 mapping emerging as a key biomarker for brain development and pathology. However, current low-field T1 mapping protocols suffer from long acquisition times and limited multi-site repeatability. This study aimed to improve T1 mapping at 64 mT using a clinically feasible 10-minute protocol and assess repeatability and reproducibility across sites. We present an analysis of the repeatability and reproducibility of rapid T1 measurements in a commercially available phantom and in 60 volunteers, scanned with a portable 64 mT MRI systems at six sites. T1 mapping was performed using an undersampled 3D inversion-recovery turbo spin-echo sequence with a 10.8-minute scan time, and reconstructed with a locally low-rank approach. Our results in phantom demonstrated high reproducibility in T1 measurements (below 3% differences from the average), with non-significant differences between sites. Longitudinal measurements demonstrated high repeatability over time both in vivo and in phantom settings in one site, with minimal variability (average Coefficient of Variation of 0.6%). Average in vivo T1 values for white matter and cortex were 290 ± 6 ms and 332 ± 8 ms, respectively and the values demonstrated high reproducibility, with differences of less than 4% from the average across sites. Our results demonstrate the feasibility of multi-site in vivo T1 mapping at 64 mT, providing normative T1 values at this field strength and supporting its use as a quantitative biomarker in clinical applications.
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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 | 0.002 |
| 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".