Comparing the Accuracy and Reliability of Detecting the Intensity of Spinal Inflammation on STIR Sequence with Apparent Diffusion Coefficient Values in Axial Spondyloarthritis
Bibliographic record
Abstract
Objective: To compare the accuracy and reliability of detecting the intensity of spinal inflammation on short tau inversion recovery (STIR) with the apparent diffusion coefficient (ADC) values of the active magnetic resonance imaging (MRI) lesions in axial spondyloarthritis (axSpA). Materials and methods: Fifty active lesions in the STIR sequence of spinal MRI were identified. With reference to sites of active lesions in STIR, the corresponding region of interest (ROI) on the ADC map was drawn to determine the maximum ADC (ADC[Formula: see text]), mean ADC (ADC[Formula: see text]), normalized maximum (nADC[Formula: see text]), and mean (nADC[Formula: see text]). Four independent readers scored the identified active lesions as “intense” or “non-intense” according to the Spondyloarthritis Research Consortium of Canada (SPARCC) MRI index. They were compared to various ADC parameters for assessment of accuracy and reliability. Regression analyses were used to adjust potential factors that could affect ADC. Results: Significant differences were found in ADC [Formula: see text] between “intense” and “non-intense” lesions scored by three of the four readers (1,405.7 ± 271.4 vs. 1,165.8 ± 223.8, [Formula: see text] = 0.01; 1,420.7 ± 272.1 vs. 1,209.0 ± 248.5, [Formula: see text] = 0.01; 1,438.0 ± 307.2 vs. 1,213.6 ± 231.0, [Formula: see text] = 0.01). Only one reader could differentiate a difference in “intense” and “non-intense” lesions with respect to ADC[Formula: see text] (899.2 ± 248.3 vs. 711.0 ± 222.6, [Formula: see text] = 0.01) and nADC[Formula: see text] (4.4 ± 2.1 vs. 3.4 ± 1.4, [Formula: see text] = 0.05). Inter-reader agreements were slight to moderate (kappa = 0.07–0.45). Reliability substantially improved when only the lowest and highest 25th percentiles of ADC values were included (kappa = 0.17–0.75). Regression analyses showed that the “intense” lesions were associated with higher ADC values after adjustment for confounders. Conclusion: Reading of STIR MRI is limited by the lack of ability in differentiating subtle differences of spinal inflammation. ADC could be an alternative method.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".