Neuroimaging in encephalitis: analysis of imaging findings and interobserver agreement
Bibliographic record
Abstract
AIM: To assess the role of imaging in the early management of encephalitis and the agreement on findings in a well-defined cohort of suspected encephalitis cases enrolled in the Prospective Aetiological Study of Encephalitis conducted by the Health Protection Agency (now incorporated into Public Health England). MATERIALS AND METHODS: Eighty-five CT examinations from 68 patients and 101 MRI examinations from 80 patients with suspected encephalitis were independently rated by three neuroradiologists blinded to patient and clinical details. The level of agreement on the interpretation of images was measured using the kappa statistic. The sensitivity, specificity, and negative and positive predictive values of CT and MRI for herpes simplex virus (HSV) encephalitis and acute disseminated encephalomyelitis (ADEM) were estimated. RESULTS: The kappa value for interobserver agreement on rating the scans as normal or abnormal was good (0.65) for CT and moderate (0.59) for MRI. Agreement for HSV encephalitis was very good for CT (0.87) and MRI (0.82), but only fair for ADEM (0.32 CT; 0.31 MRI). Similarly, the overall sensitivity of imaging for HSV encephalitis was ∼80% for both CT and MRI, whereas for ADEM it was 0% for CT and 20% for MRI. MRI specificity for HSV encephalitis between 3-10 days after symptom onset was 100%. CONCLUSION: There is a subjective component to scan interpretation that can have important implications for the clinical management of encephalitis cases. Neuroradiologists were good at diagnosing HSV encephalitis; however, agreement was worse for ADEM and other alternative aetiologies. Findings highlight the importance of a comprehensive and multidisciplinary approach to diagnosing the cause of encephalitis that takes into account individual clinical, microbiological, and radiological features of each patient.
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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 | 0.037 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".