Reference Values for Water‐Specific <scp>T1</scp>, Intermuscular and Intramuscular Fat Content in Skeletal Muscle at 2.<scp>89 T</scp>
Bibliographic record
Abstract
Background MRI offers quantification of proton density fat fraction (PDFF) and tissue characteristics with T1 mapping. The influence of age, sex, and the potential confounding effects of fat on T1 values in skeletal muscle in healthy adults are insufficiently known. Purpose To determine the accuracy and repeatability of a saturation‐recovery chemical‐shift encoded multiparametric approach (SR‐CSE) for quantification of T1Water and muscle fat content, and establish normative values (age, sex) from a healthy cohort. Study Type Prospective observational; phantoms (NiCL2‐agarose T1 phantoms with no fat content; gadolinium T1 phantoms with mixed fat‐water content). Populations A total of 130 healthy community‐dwelling adults (63 male, 18–76 years) free of chronic health conditions that require regular prescription medication, and with no contraindications to MRI. Field Strength/Sequence 2.89 T; gradient echo sequences including saturation‐recovery chemical‐shift encoded T1 mapping (SR‐CSE); MOLLI; SASHA; CSE; and single voxel spectroscopy. Assessment SR‐CSE provided T1Water and PDFF maps for assessment of intramuscular (MFIntra), intermuscular (MFInter), and subcutaneous fat and muscle volumes (thigh, paraspinal muscles). Comparison with MOLLI/SASHA T1 mapping. Statistical Tests Univariable and multivariable linear regression, general linear models, Bland and Altman, coefficient of variation (CV). P‐value <0.05 was considered statistically significant. Results Phantom and in vivo validation studies showed excellent accuracy of SR‐CSE T1Water and PDFF vs. values from reference standards and repeatability CVs between 0.2% and 2.6% for T1Water, R2*, MFInter, MFIntra, subcutaneous fat and muscle volumes. Mean T1Water was 36 msec significantly higher in females (1445 ± 23 msec vs. 1409 ± 22 msec), with no age‐effect (P = 0.35). Females had significantly higher values for MFInter (10.4% ± 4.8% vs. 7.1% ± 2.9%) and MFIntra (2.6% ± 1.0% vs. 2.3% ± 0.8%), both of which increased with age, secondary to lower muscle volume. MOLLI and SASHA T1 values had a fat‐related bias of 21.7/35.0 msec per 1% increase in fat fraction (MFFIntra), in vivo, and a constant bias of −319.8/+35.6 msec, respectively. Data Conclusion SR‐CSE provides accurate (vs. phantoms) and repeatable assessment of water‐specific T1 values and muscle and fat volumes. Conventional methods (SASHA, MOLLI) have a significant fat‐modulated T1‐bias. T1Water values are higher in females with no significant age dependence. Plain Language Summary We developed and tested the accuracy of a new MRI approach to measure tissue damage in skeletal muscle using a method called T1 mapping. The approach also provided matching images of fat within the muscle. We measured T1 values and muscle fat volumes in the thighs of 130 healthy adults to define normal values in healthy people and to understand if these values are influenced by age, sex, or weight. We found that our MRI technique accurately measured T1 values and fat volumes within muscle and we defined normal ranges of values, which were different in healthy males and females. Level of Evidence 2 Technical Efficacy Stage 1
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".