Skeletal muscle attenuation determined by computed tomography is associated with skeletal muscle lipid content
Bibliographic record
Abstract
The purpose of this investigation was to validate that in vivo measurement of skeletal muscle attenuation (MA) with computed tomography (CT) is associated with muscle lipid content. Single-slice CT scans performed on phantoms of varying lipid concentrations revealed good concordance between attenuation and lipid concentration (r(2) = 0.995); increasing the phantom's lipid concentration by 1 g/100 ml decreased its attenuation by approximately 1 Hounsfield unit (HU). The test-retest coefficient of variation for two CT scans performed in six volunteers was 0.51% for the midthigh and 0.85% for the midcalf, indicating that the methodological variability is low. Lean subjects had significantly higher (P < 0.01) MA values (49.2 +/- 2.8 HU) than did obese nondiabetic (39.3 +/- 7.5 HU) and obese Type 2 diabetic (33.9 +/- 4. 1 HU) subjects, whereas obese Type 2 diabetic subjects had lower MA values that were not different from obese nondiabetic subjects. There was also good concordance between MA in midthigh and midcalf (r = 0.60, P < 0.01), psoas (r = 0.65, P < 0.01), and erector spinae (r = 0.77, P < 0.01) in subsets of volunteers. In 45 men and women who ranged from lean to obese (body mass index = 18.5 to 35.9 kg/m(2)), including 10 patients with Type 2 diabetes mellitus, reduced MA was associated with increased muscle fiber lipid content determined with histological oil red O staining (P = -0.43, P < 0. 01). In a subset of these volunteers (n = 19), triglyceride content in percutaneous biopsy specimens from vastus lateralis was also associated with MA (r = -0.58, P = 0.019). We conclude that the attenuation of skeletal muscle in vivo determined by CT is related to its lipid content and that this noninvasive method may provide additional information regarding the association between muscle composition and muscle function.
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 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 | 0.001 | 0.004 |
| 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) | 0.001 | 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 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".