E-113 Understanding the sound production mechanism of pulsatile tinnitus using computational fluid dynamics
Bibliographic record
Abstract
Background and Aim Pulsatile Tinnitus (PT) is a debilitating symptom of a rhythmic ‘whooshing’ sound perceived in the absence of an external stimulus. Vascular PT often stems from underlying pathologies of the blood vessels nearing the cochlea resulting in audible turbulent blood flow. Venous pathologies such as transverse sinus stenosis, high riding jugular bulbs and prominent emissary veins may cause PT. Turbulent blood flow can be observed through vascular imaging as high-pressure gradients and high velocity measurements, and clinically through auscultation and transcanal recordings.Recent work has shown that computational fluid dynamics (CFD) can be used as a noninvasive diagnostic tool to assess the hemodynamics of these vessels and assess the distinct sounds produced. It provides high spatiotemporal resolution where conventional anatomic imaging, such as computed tomography venogram (CTV) and magnetic resonance imaging venogram (MRV), cannot.In 2021, our research group demonstrated a landmark case (which was on the cover of JNIS; August issue, Vol. 13, Issue 8) which the CFD derived PT sound matched the patients self-reported PT, highlighting its potential utility as a non-invasive diagnostic tool. Since then, we have simulated 12 transverse sinus stenosis models with different stenosis morphologies. Methods This study included medical images from patients presenting with unilateral pulsatile tinnitus caused by transverse sinus stenosis who were treated with endovascular stenting. High-fidelity CFD was performed on 3D models digitally segmented from CTV, using patient-calculated flowrates. Spectral power index (SPI) was calculated from the CFD wall shear stress data to visualize areas experiencing flow instabilities. Data-driven sonification of the velocity data was performed from spectrograms at regions of interest. Results In this study, we present the results from those 12 CFD simulations highlighting the distinct and complex flow patterns giving arise to diverse PT sounds in patients. SPI maps revealed localized regions of flow disturbances, particularly in the sigmoid-jugular region, downstream of the stenosis, corresponding with site of sound production of PT. Comparison of spectrograms unveiled distinct acoustic signatures corresponding to the unique PT sounds reported by patients. This auditory analysis further corroborates the link between hemodynamic alterations and subjective PT perception. Conclusion Our results highlight the multifaceted relationship between vascular hemodynamics and PT generation, emphasizing the potential of CFD as a non-invasive diagnostic tool for assessing PT and guiding therapeutic interventions. Disclosures N. Cancelliere: None. G. Sidora: None. A. Haley: None. D. Steinman: 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".