Detection of Inflammatory Lesions by F-18 Fluorodeoxyglucose Positron Emission Tomography in Patients with Polymyositis and Dermatomyositis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the usefulness of F-18 fluorodeoxyglucose positron emission tomography (FDG-PET) imaging in the management of patients with inflammatory myopathy. We examined whether FDG-PET scanning detects myositis or extramuscular lesions in patients with polymyositis (PM) and dermatomyositis (DM). METHODS: FDG-PET imaging was performed in 24 patients with active inflammatory myopathy (PM, 11; DM, 13). The images were read by radiologists in a blinded manner. FDG uptake into muscles was judged positive when the intensity of muscles was higher than or equal to that of the liver. As controls, FDG imaging findings of patients with a lung mass and without muscle diseases were used. To investigate associations between FDG-PET findings and clinical/laboratory findings, the patients' medical records were reviewed retrospectively. RESULTS: Increased FDG uptake in muscles was found in 8 of 24 (33%) patients. In 67 of 69 (97%) controls without muscle diseases, no muscle FDG uptake was detected. The sensitivity of FDG-PET to detect myositis was lower than that of electromyogram (EMG), magnetic resonance imaging, and muscle biopsy. There were no significant differences in clinical manifestations between patients with and without increased FDG uptake in muscles, although patients with FDG muscle uptake had a tendency to have extended myositis with endomysial cell infiltration. FDG-PET detected neoplasms in patients with associated malignancy. FDG uptake in lungs was found in 7 of 18 patients with interstitial lung disease. CONCLUSION: FDG-PET imaging has limited usefulness for the evaluation of myositis in patients with PM/DM because of its low sensitivity, although it might be useful for detection of malignancy in these patients.
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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 | 0.000 | 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 | 0.000 |
| 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".