Radiological features of infantile glioblastoma and desmoplastic infantile tumors: British Columbia’s Children’s Hospital experience
Bibliographic record
Abstract
OBJECT Two of the more common infantile brain tumors, glioblastoma multiforme (GBM) and desmoplastic infantile tumors (DITs), can be difficult to distinguish on MRI. Both tumors occur in the supratentorial compartment and both have solid and cystic components. Differentiating between the 2 on MRI studies could assist the surgeon in discussions with family and child management. The authors report on their institutional experience with both tumors, focusing on radio-graphic features, especially the diffusion studies, which might be useful in distinguishing between infantile GBM and DIT. METHODS A retrospective review was undertaken of all infantile brain tumors treated at British Columbia's Children's Hospital between 1982 and 2012, and cases of GBM and DIT were recorded. Only cases that had imaging were included in the study. A literature review was completed to identify reported cases of infantile GBM and DIT. Only reports that described or included radiological studies (particularly MRI) of the tumors were included. Certain radiographic features of the tumors were reviewed, including location, size, consistency, pattern of enhancement, and features on MR diffusion studies. RESULTS Of 70 cases of infantile brain tumors, 2 GBM cases and 3 DIT cases (all 3 of which were desmoplastic infantile gangliogliomas [DIGs]) met the inclusion criteria. The radiological studies obtained in all 5 cases were reviewed by a neuroradiologist. All 5 patients had supratentorial tumors with cystic-solid consistency. Diffusion MRI studies showed restricted diffusion in the 2 GBM cases, but no evidence of restricted diffusion in the DIG tumors. The GBM tumors were heterogeneously enhancing, and the DIG tumors showed avid and homogeneous enhancement. The literature review revealed 29 cases of infantile GBM and 32 cases of DIG/DIT that met the inclusion criteria. The tumors were large in both groups. The tumors were cystic-solid in consistency in 10 of 30 (33%) of GBM cases and 28 of 32 (87.5%) of DIT cases. The contrast enhancement was heterogeneous in 9 of 30 (30%) GBM cases, and it was homogeneous and avid in 27 of 32 (84%) of DIT cases. Diffusion studies were recorded in 2 published infantile GBM cases, and in both of them diffusion was restricted. The authors only found 1 report that discussed DIG tumor features on MR diffusion studies, but the interpretation was difficult and unclear. CONCLUSIONS Magnetic resonance imaging, especially diffusion-weighted imaging, may be a useful aid in distinguishing between infantile GBM and DIT tumors, with infantile GBM demonstrating restricted diffusion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".