Comparison of methods to assess quadriceps muscle volume using magnetic resonance imaging
Bibliographic record
Abstract
PURPOSE: To compare the precision of four methods to estimate the volume of quadriceps muscles using axial MRI. MATERIALS AND METHODS: Entire legs of 10 healthy young subjects were scanned using a 1.5 Tesla magnetic resonance imaging scanner and 4-mm-thick sections without any gaps. Quadriceps muscles were outlined on all of the slices to obtain the MRI reference standard measure of quadriceps muscle volume. This MRI reference standard was compared with the volume estimated using (i) the truncated cone formula, (ii) the Cavalieri method, (iii) a cubic spline interpolation of missing cross sectional areas, and, (iv) the deformation of a parametric specific object. For each method, 3 to 21 slices were used. RESULTS: The average volume error was significantly (P < 0.001) different in comparing the four methods (4.4%, 2.3%, 1.1%, and 1.2%, respectively). In addition, the number of slices required to reach a given volume error was significantly (P < 0.001) different across all methods (respectively, 12, 9, 5, and 7 slices required to reach a volume error of 1.1%). CONCLUSION: While methods based on interpolation and deformation of a parametric specific object have not been used in literature, these two methods are the most precise approaches to reach a given level of precision.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".