Intracranial Venous System: Gadolinium-enhanced Three-dimensional MR Venography with Auto-triggered Elliptic Centric-ordered Sequence—Initial Experience
Bibliographic record
Abstract
PURPOSE: To evaluate gadolinium-enhanced three-dimensional auto-triggered elliptic centric-ordered (ATECO) magnetic resonance (MR) venography for imaging of the intracranial venous system. MATERIALS AND METHODS: ATECO MR venography was performed in 23 patients, eight of whom also underwent two-dimensional time-of-flight (TOF) MR venography for imaging of the intracranial venous system. Seventeen predefined venous structures were evaluated on all venograms by two neuroradiologists. Visualization of venous structures was defined as completely visible (including clearly pathologic), partially visible, or not visible. Readers were also asked to compare the visibility of these predefined structures on ATECO and TOF MR venograms, where available. RESULTS: Of the 23 patients, six had dural venous sinus disease. Of the remaining 17 healthy patients, five underwent both ATECO and TOF MR venography and 12 underwent ATECO MR venography alone. On ATECO MR venograms obtained in the healthy patients, visibility of the 17 predefined venous structures was complete in 92% (531 of 578) of evaluations. For the five normal TOF MR venograms, the rate of complete visibility of the same venous structures was 61% (104 of 170). The rate of complete visibility of the large dural venous sinuses was 99% for ATECO MR venograms and 75% for TOF MR venograms. CONCLUSION: ATECO MR venography provides high-quality images of the intracranial venous anatomy and was superior to TOF MR venography for consistent complete visibility of venous structures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".