Quantification of Disease Activity in Chronic Nonbacterial Osteomyelitis by Whole-body Magnetic Resonance Imaging
Bibliographic record
Abstract
Chronic nonbacterial osteitis (CNO), also termed chronic recurrent multifocal disease (CRMO), is a rare autoinflammatory disease characterized by recurrent flares of inflammatory bone pain related to aseptic osteomyelitis1,2,3. It usually affects children and adolescents and the clinical presentations range from mild and limited unifocal disease to severe chronic inflammation in multiple bones4,5,6. The long tubular bones of the lower extremities are most commonly involved, followed by the spine and the clavicles2,3; there may be extraskeletal skin and bowel manifestations such as palmoplantar pustulosis, psoriasis, and Crohn disease7. Diagnostic imaging in CNO relies on a multimodality approach usually consisting of radiography followed by magnetic resonance imaging (MRI)2. Because bone marrow edema (BME) is characteristic for active lesions, fat-saturated fluid sensitive MRI sequences such as short-tau inversion recovery (STIR) and T2-weighted fat-saturated sequence are ideal for detecting active lesions, whereas T1-weighted sequences are preferable for detecting chronic structural lesions2. The findings by MRI may, however, be nonspecific and the diagnosis is usually a diagnosis of exclusion after ruling out other diseases, such as infectious osteomyelitis and tumors or tumor-like lesions, based on clinical presentation, imaging, and if needed, culture-negative biopsy1,7,8. The combination of characteristic imaging findings are usually diagnostic2,7, such as multiple bone lesions or characteristic metaphyseal lesions in the lower extremities, and clavicular or spinal osteitis with concomitant dermal changes. To diagnose and monitor the extent of CNO in children/adolescents, a whole-body (WB)-MRI approach is advantageous because radiological disease activity may be underestimated clinically1,5,9. WB-MRI gives a simultaneous evaluation of the entire body without exposure to ionizing radiation, and in small children the … Address correspondence to Dr. A.G. Jurik, Department of Radiology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 35, Entrance C, location C118/reference point C109, 8200 Aarhus N, Denmark. E-mail: annejuri{at}rm.dk
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".