Low-dose computed tomography for axial spondyloarthritis: update on use and limitations
Bibliographic record
Abstract
PURPOSE OF REVIEW: Recent developments in low-dose computed tomography (ldCT) have greatly reduced radiation exposure levels. This article reviews what a ldCT is and its use and limitations for imaging axial spondyloarthritis. RECENT FINDINGS: Detection of structural damage in bone with CT is far superior to radiography and ldCT of the sacroiliac joints (SIJ) can now be done at radiation exposure levels equivalent to, or even less than, conventional radiography. ldCT should be considered a 'first-choice' test for arthritis imaging, and wherever available, SIJ ldCT may completely replace conventional radiography. Radiation exposure in the spine with ldCT is lower than conventional CT. However, it is unclear whether the additional information regarding structural damage changes in the spine provided by ldCT will alter patient management sufficiently often to merit switching from spinal radiography to ldCT in routine clinical practice. In addition, ldCT cannot assess osteitis disease activity for which MRI remains the best test. SUMMARY: ldCT of the sacroiliac joints (SIJ) can be done at radiation exposure levels equivalent to, or less than, radiography and ldCT may completely replace SIJ radiography. However, the role of spinal ldCT for spondyloarthritis is not clear and MRI is far superior for detecting disease activity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".