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 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 | 0.001 |
| 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 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".