Delineation of lateral tentorial sinus with contrast-enhanced MR imaging and its surgical implications.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The lateral tentorial sinus (LTS) has not been well described in the imaging literature. The aim of this study was to investigate the value of MR imaging in assessing the LTS, which may provide guidance for preoperative planning. METHODS: Fifty-five adult patients underwent MR imaging of the brain. Four neuroradiologists evaluated the studies for delineation of the LTS and its branches. Presence of arachnoid granulation and dominance of the venous drainage also were reported. RESULTS: An LTS was detected in 104 of 110 lobes. The LTS in each lobe was classified as type I (candelabra) in 30 (28.8%), type II (independent veins) in 22 (21.1%), and type III (venous lakes) in 37 (35.5%); in 15 (14.4%) of the lobes, the LTS was indeterminate. LTS branches were inconsistently detected, with the exception of the vein of Labbé (VL). Five of eight branches were seen in approximately half of the cases. The VL was identified in 94 (85.4%) lobes. Among these, 53 (56.4%) were draining into the LTS and 22 (23.4%) into the transverse sinus; in 19 (20.2%) cases, the terminal portion was not visualized. The right transverse sinus was dominant in 19 (34.5%) patients and the left in 18 (32.7%); codomination was present in 18 (32.7%) cases. At least one arachnoid granulation was seen in the transverse sinus in 27 (49.1%) patients. CONCLUSION: In many instances, the LTS and VL drainage patterns were well delineated on routine MR images. For selected cases, this information may be crucial during lateral skull base surgery to avoid venous infarct.
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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) | 0.000 | 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 | 0.000 |
| 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".