Future of Low-Dose Computed Tomography and Dual-Energy Computed Tomography in Axial Spondyloarthritis
Bibliographic record
Abstract
PURPOSE OF REVIEW: Recent technical advances in computed tomography (CT) such as low-dose CT and dual-energy techniques open new applications for this imaging modality in clinical practice and for research purposes. This article will discuss the latest innovations and give a perspective on future developments. RECENT FINDINGS: Low-dose CT has increasingly been used for assessing structural changes at the sacroiliac joints and the spine. It has developed into a method with similar or even lower radiation exposure than radiography while outperforming radiography for lesion detection. Despite being incompatible with low-dose scanning, some studies have shown that dual-energy CT can provide additional information that is otherwise only assessable with magnetic resonance imaging (MRI). However, it is unclear whether this additional information is reliable enough and if it would justify the additional radiation exposure, i.e. whether the performance of dual-energy CT is close enough to MRI to replace it in clinical practice. While the role of dual-energy CT in patients with axial spondyloarthritis remains to be established, low-dose CT has developed to an appropriate modality that should replace radiography in many circumstances and might supplement MRI.
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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 | 0.001 | 0.002 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".