Performance of 18F-sodium fluoride positron emission tomography with computed tomography to assess inflammatory and structural sacroiliitis on magnetic resonance imaging and computed tomography, respectively, in axial spondyloarthritis
Bibliographic record
Abstract
To assess increased sacroiliac joint (SIJ) uptake on 18 F-NaF PET/CT and to compare with MRI for inflammation and with CT scan for structural damages in a population of 23 patients with spondyloarthritis (SpA). Twenty-three patients with active SpA according to the Assessment of SpondyloArthritis international Society (ASAS) and/or modified NY criteria were included. All patients had a pelvic radiograph, MRI, and CT scan of the SIJ and 18 F-NaF PET/CT examinations within a month, analyzed by three blinded readers. MRIs were assessed according to the ASAS criteria and SPARCC method. On CT scans, erosion and ankylosis were quantified using the same methodology. On the 18 F-NaF PET, abnormal uptake was assessed using a qualitative method inspired by the ASAS criteria and two quantitative approaches (the PET-activity score according to the SPARCC method and Maximum Standardized Uptake Value (SUVmax)). Structural sacroiliitis was observed on 7 radiographs and 10 CT scans; 10 MRIs showed inflammatory sacroiliitis, and 20 patients had a positive PET. The inter-reader reliability was good for the PET activity score and good to excellent for the SUVmax. A positive PET was not correlated with a positive MRI or with a structural sacroiliitis on CT scan. The PET-activity score and SUVmax were correlated with the SPARCC inflammation score but not with erosion or ankylosis scores on CT scan. Abnormal uptake by the SIJ on 18 F-NaF PET is more frequent than inflammatory and structural sacroiliitis in a population of SpA patients. The PET activity score and SUVmax had good correlations with inflammatory sacroiliitis but not with structural lesions on CT scan.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".