Quantitative Paraspinal Muscle Measurements: Inter-Software Reliability and Agreement Using OsiriX and ImageJ
Bibliographic record
Abstract
BACKGROUND: Variations in paraspinal muscle cross-sectional area (CSA) and composition, particularly of the multifidus muscle, have been of interest with respect to risk of, and recovery from, low back pain problems. Several investigators have reported on the reliability of such muscle measurements using various protocols and image analysis programs. However, there is no standard protocol for tissue segmentation, nor has there been an investigation of reliability or agreement of measurements using different software. OBJECTIVE: The purpose of this study was to provide a detailed muscle measurement protocol and determine the reliability and agreement of associated paraspinal muscle composition measurements obtained with 2 commonly used image analysis programs: OsiriX and ImageJ. DESIGN: This was a measurement reliability study. METHODS: Lumbar magnetic resonance images of 30 individuals were randomly selected from a cohort of patients with various low back conditions. Muscle CSA and composition measurements were acquired from axial T2-weighted magnetic resonance images of the multifidus muscle, the erector spinae muscle, and the 2 muscles combined at L4-L5 and S1 for each participant. All measurements were repeated twice using each software program, at least 5 days apart. The assessor was blinded to all earlier measurements. RESULTS: The intrarater reliability and standard error of measurement (SEM) were comparable for most measurements obtained using OsiriX or ImageJ, with reliability coefficients (intraclass correlation coefficients [ICCs]) varying between .77 and .99 for OsiriX and .78 and .99 for ImageJ. There was similarly excellent agreement between muscle composition measurements using the 2 software applications (inter-software ICCs = .81-.99). LIMITATIONS: The high degree of inter-software measurement reliability may not generalize to protocols using other commercial or custom-made software. CONCLUSION: The proposed method to investigate paraspinal muscle CSA, composition, and side-to-side asymmetry was highly reliable, with excellent agreement between the 2 software programs.
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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 | 0.051 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".