Imaging of the Intracranial Venous System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Evaluation of the intracranial venous system has historically been performed with conventional catheter-based digital subtraction angiography (DSA). The continued importance of DSA can not be overstated in light of its inherent option of endovascular intervention and thrombolysis for cerebral venous thrombosis. DSA is, however, an invasive procedure with associated risks, including radiation exposure, and adverse effects of iodinated contrast medium. DSA also suffers from the limitations of 2-dimensional planar imaging. For these reasons, noninvasive imaging techniques are playing a greater role in evaluation of the intracranial venous system. REVIEW SUMMARY: This review provides an overview of the current noninvasive methods and their applications and limitations, with examples of their use in a variety of disease processes. Computed tomography venography (CTV) is discussed as well as the various types of cerebral magnetic resonance venography (MRV). CONCLUSION: When available, MR supplemented with the technique of triggered gadolinium-enhanced MRV is the method of choice for the diagnosis of dural sinus thrombosis as well as most other pathologic entities affecting the intracranial venous system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it