Multisite reliability and repeatability of an advanced brain MRI protocol
Bibliographic record
Abstract
Background MRI is the imaging modality of choice for diagnosis and intervention assessment in neurological disease. Its full potential has not been realized due in part to challenges in harmonizing advanced techniques across multiple sites. Purpose To develop a method for the assessment of reliability and repeatability of advanced multisite‐multisession neuroimaging studies and specifically to assess the reliability of an advanced MRI protocol, including multiband fMRI and diffusion tensor MRI, in a multisite setting. Study Type Prospective. Population Twice repeated measurement of a single subject with stable relapsing‐remitting multiple sclerosis (MS) at seven institutions. Field Strength/Sequence A 3 T MRI protocol included higher spatial resolution anatomical scans, a variable flip‐angle longitudinal relaxation rate constant (R 1 ≡ 1/T 1 ) measurement, quantitative magnetization transfer imaging, diffusion tensor imaging, and a resting‐state fMRI (rsFMRI) series. Assessment Multiple methods of assessing intrasite repeatability and intersite reliability were evaluated for imaging metrics derived from each sequence. Statistical Tests Student's t ‐test, Pearson's r , and intraclass correlation coefficient (ICC) (2,1) were employed to assess repeatability and reliability. Two new statistical metrics are introduced that frame reliability and repeatability in the respective units of the measurements themselves. Results Intrasite repeatability was excellent for quantitative R 1 , magnetization transfer ratio (MTR), and diffusion‐weighted imaging (DWI) based metrics ( r > 0.95). rsFMRI metrics were less repeatable ( r = 0.8). Intersite reliability was excellent for R 1 , MTR, and DWI (ICC >0.9), and moderate for rsFMRI metrics (ICC∼0.4). Data Conclusion From most reliable to least, using a new reliability metric introduced here, MTR > R 1 > DWI > rsFMRI; for repeatability, MTR > DWI > R 1 > rsFMRI. A graphical method for at‐a‐glance assessment of reliability and repeatability, effect sizes, and outlier identification in multisite‐multisession neuroimaging studies is introduced. Level of Evidence: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:878–888.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".