Systematic Review of the Diagnostic Imaging Evaluation of Pulsatile Tinnitus
Bibliographic record
Abstract
Abstract Objective Aggregate published data on the imaging of pulsatile tinnitus as a step toward building a framework for an evidence-based approach to diagnostic imaging for this symptom. Materials & Methods A systematic review was performed. PUBMED and EMBASE were searched on December 1, 2021 for English-language articles on diagnostic imaging of pulsatile tinnitus. Articles that involved non-standard imaging techniques and those that focused on management of pulsatile tinnitus were excluded. Extracted data included: number of males and females; signs, symptoms, and physical examination findings with associated patient counts; imaging findings; count of patients with imaging-identified cause of pulsatile tinnitus; reported associated interventions and outcomes. Results 41 articles were included with a total of 2,633 reported patients. 10 studies were prospective. MRA appears to be capable of identifying many of the same pathologies traditionally diagnosed with DSA. Few head-to-head comparisons were performed. In head-to-head comparisons of MRI and MRA, MRA was often able to identify more pathology. There was no clear relationship identified between specific symptoms and the imaging modality chosen, indicating that the imaging evaluation of pulsatile tinnitus is likely sensitive to the preferences of the evaluating provider. Conclusion There is limited evidence to inform best practices for the initial imaging evaluation of pulsatile tinnitus and preference-sensitive provider decisions will continue to guide the pulsatile tinnitus workup. We encourage prospective studies with multimodality imaging comparisons to build evidence that would support the development of more effective, efficient, and equitable protocols and pathways for the imaging evaluation of pulsatile tinnitus. Clinical Relevance Statement Evidence is not available in support of any single optimal imaging evaluation of pulsatile tinnitus, but prudent imaging will include evaluation for life-threatening causes such as dural arteriovenous fistula and arteriovenous malformation. Key Points - Many imaging findings associated with pulsatile tinnitus may not be causal. - Current evidence is insufficient to indicate the optimal imaging evaluation. - Local preference-based imaging algorithms are reasonable in the absence of new high-level evidence.
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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 | 0.013 | 0.066 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".