Can MRI differentiate between ring‐enhancing gliomas and intra‐axial abscesses?
Bibliographic record
Abstract
Gliomas of the brain may appear as expansile ring-enhancing masses in MRI studies, mimicking the appearance of intra-axial abscesses. The aims of this study were to compare the MRI features of ring-enhancing gliomas and intra-axial brain abscesses in dogs and cats and to identify the characteristics that might help differentiate them. For this multicenter, retrospective, and observational study, the inclusion criteria were as follows: (a) a definitive diagnosis of glioma or abscess based on cytological or histopathological examination following CSF collection or surgical biopsy/necropsy, respectively; (b) MRI study performed with a high- or low-field MRI scanner, including a same plane T1W pre- and postcontrast, a T2W and a T2 FLAIR sequence in at least one plane. If available, delayed T1W postcontrast, T2*W GE, DWI/ADC, and SWI sequences were also evaluated. Sixteen patients were diagnosed with ring-enhancing gliomas, and 15 were diagnosed with intra-axial abscesses. A homogenous signal on T1W (P = 0.049) and T2W (P = 0.042) sequences, a T2W (P = 0.005) or T2*W GE (P = 0.046) peripheral hypointense halo, and an even enhancing capsule (P = 0.002) were significantly associated with brain abscesses. A progressive central enhancement on delayed T1W postcontrast sequences was correlated with ring-enhancing gliomas (P = 0.009). The combination of the following features was suggestive of brain abscess: homogeneous T1W or T2W signal intensity, a T2W or T2*W GE peripheral hypointense halo and an evenly enhancing capsule. Central progression of enhancement on delayed T1W postcontrast sequences was suggestive of glioma.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".