E-001 The role of 4D-CTA in the imaging work up of patients with pulsatile tinnitus: a technical note
Bibliographic record
Abstract
Background Pulsatile tinnitus (PT) is a debilitating condition that can be caused by various vascular conditions, including arteriovenous and venous lesions. Most of these lesions can be treated successfully by venous sinus stenting, however, the diagnosis of the venous cases remains a challenge. The purpose of our study was to evaluate the effectiveness of 4D-CTA for diagnosis of venous sinus lesions. Methods Patients referred to our institution with symptoms of pulsatile tinnitus and inconclusive external imaging were included in our study between August 2019 to February 2020 (n=13). Patients underwent a 20s continuous volumetric 4D-CTA scan, with a 50cc bolus of iodinated contrast media injected intravenously. A 0.5s rotation time was used to produce forty 3D volumes demonstrating all phases from arterial to venous. Post-processing was performed to create 4D dynamic reconstructions of all phases. Two neuroradiologists examined the dynamic reconstructions of each patient to exclude arteriovenous disease and evaluate the venous phase. Results A 4D-CTA was successfully performed in all 13 patients. Right sided pulsatile tinnitus was diagnosed in 85% of 4D-CTA scans (n=11/13; 15% left PT= 2/13). Ninety-two percent of cases had a stenosis on the side of PT (n=12/13), which was also the dominant venous drainage of the brain. All stenoses were ranked severe or sub-occlusive (3 or 4 points) on a 4 point Likert-scale. One PT case was caused by jugular occlusion (on the non-dominant side) and rerouting of the venous drainage. Conclusions 4D-CTA is a sensitive imaging modality for detection and characterization of venous stenoses. As 4D-CTA is less invasive and more available in smaller hospitals compared to DSA, it may serve as a better diagnostic sequence for improved detection of venous stenosis underlying pulsatile tinnitus. As we are still enrolling in the study, we plan to present more cases at the time of the conference. Disclosures N. Cancelliere: None. P. Nicholson: None. I. Radovanovic: None. V. Mendes Pereira: None.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".