Computed tomography-based psoas skeletal muscle area and radiodensity are poor sentinels for whole L3 skeletal muscle values
Bibliographic record
Abstract
BACKGROUND AND AIMS: Computed tomography (CT)-based measurement of skeletal muscle cross-sectional area (CSA) and Hounsfield unit (HU) radiodensity are used to assess the presence of sarcopenia and myosteatosis, respectively. The validated CT-based technique involves analysis of skeletal muscle at the third lumbar vertebral (L3) level. Recently there has been increasing interest in the use of psoas muscle alone as a sentinel. However, this technique has not been extensively investigated or compared with the previous validated standard approach. METHODS: Portovenous phase CT images at the L3 level were identified retrospectively from a single institution in 150 patients who had non-emergency scans and were analysed by a single assessor using SliceOmatic software v5.0 (TomoVision, Canada). Manual segmentation based upon validated HU thresholds for skeletal muscle density was performed for all skeletal muscle, as well as the individual muscle groups. The muscle CSA and mean radiodensity of each group were compared against the whole L3 slice values. RESULTS: When compared with whole L3 slice CSA, anterior abdominal wall CSA had the strongest correlation (r = 0.9315, p < 0.0001) followed by paravertebral (r = 0.8948, p < 0.0001), then psoas muscle (r = 0.7041, p < 0.0001). The mean ± SD density of the psoas muscle (42 ± 8.4 HU) was significantly higher than the whole slice radiodensity (32.3 ± 9.5 HU, p < 0.0001), with paravertebral radiodensity being a more accurate estimation (34.5 ± 10.8 HU). There was a significant difference in the prevalence of myosteatosis when the density measured from the psoas was compared with that of the whole L3 skeletal muscle (27.7% vs. 66.0%, p < 0.0001). CONCLUSION: Whole L3 slice CSA correlated positively with psoas muscle CSA but was subject to wide variability in results. Psoas muscle radiodensity was significantly greater than whole L3 slice density and resulted in underestimation of the prevalence of myosteatosis. Given the lack of equivalence from individual muscle groups, we recommend that further work be undertaken to investigate which muscle group, or indeed whether the gold standard of whole L3 skeletal muscle, provides the best correlation with clinical outcomes.
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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 | 0.000 | 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".