Cine Phase-Contrast MR Images Failed to Predict Clinical Outcome Following ETV
Bibliographic record
Abstract
BACKGROUND: To predict success of endoscopic third ventriculostomy (ETV) in patients with obstructive hydrocephalus, we evaluated pre- and post- operative phase-contrast cine magnetic resonance images (PC MRI) on cerebrospinal fluid (CSF), cine flow in basal cisterns around the brain stem, and cervical medullar junction (CMJ) retrospectively. METHODS: The study involved 102 patients with mean age of 36.74+/-23.25, and F/M = 1.55. All patients had PC MRI taken both pre- and post-operatively. A dynamic MRI video of PC MRI was reviewed at sagittal, axial, and coronal sections to determine cistern flows around the brain stem and CMJ. For quantitative analysis, quadrants were divided around midbrain axially to evaluate interpeduncular, quadrageminal, and ambient cisterns of both sides using scores of 0 to 60. Pre- and post- pontine and CMJ flows were shown in sagittal view and scored 0 to 20, and lateral cerebellopontine cisterns of both sides were measured on coronal image and scored 0 to 20. RESULTS: No significant difference in CSF flow was seen from three individual views and total cine score, or between ETV success and failure groups by multivariate analysis of variance. Kaplan-Meier Analysis and Spearman's Correlation Test produced no relationship between MRI cine flow scores and interval period after surgery to ETV failure. CONCLUSION: PC MRI cine flow failed to demonstrate significant differences between successful and failed ETV groups. This indicates in addition to achieving an adequate fenestration, CSF pathways beyond the basal cisterns around the brain stem and CMJ may play an essential role in achieving ETV success.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".