Validation of whole‐body against conventional magnetic resonance imaging for scoring acute inflammatory lesions in the sacroiliac joints of patients with spondylarthritis
Bibliographic record
Abstract
OBJECTIVE: To compare the performance of whole-body magnetic resonance imaging (MRI) versus conventional MRI in assessing acute inflammatory lesions of the sacroiliac (SI) joints in patients with established and active spondylarthritis (SpA) using the Spondyloarthritis Research Consortium of Canada (SPARCC) MRI index. This study is validating whole-body MRI against the current MRI standard for assessing active inflammatory lesions of the SI joints in patients with SpA. METHODS: Thirty-two SpA patients with clinically active disease (Bath Ankylosing Spondylitis Disease Activity Index score >/=4) fulfilling the modified New York criteria were scanned by whole-body and conventional MRI of the SI joints. The MRIs were scored independently in random order by 3 readers blinded to patient identity. Active inflammatory lesions of the SI joints were recorded on a Web-based SPARCC index. Pearson's correlation coefficients were used to compare scores for whole-body and conventional MRI for each reader, whereas intraclass correlation coefficients (ICCs) were used to compare interobserver reliability. RESULTS: The Pearson's correlation coefficients between whole-body and conventional MRI per rater were 0.94, 0.87, and 0.93. The mean sum scores for conventional versus whole-body MRI were statistically significantly higher for all 3 readers, although all patients showing inflammatory lesions on conventional MRI also demonstrated them on whole-body MRI. The ICCs(2,1) were 0.69, 0.78, and 0.95 for conventional MRI, and 0.79, 0.85, and 0.96 for whole-body MRI for the 3 possible reader pairs. CONCLUSION: Whole-body and conventional MRI scores show a strong correlation and comparable reliability for the detection of inflammatory lesions of the SI joints.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".