How precise is PreSize Neurovascular? Accuracy evaluation of flow diverter deployed-length prediction.

ABSTRACT

OBJECTIVE: The use of flow-diverting stents has been increasingly important in intracranial aneurysm treatment. However, accurate sizing and landing zone prediction remain challenging. Inaccurate sizing can lead to suboptimal deployment, device waste, and complications. This study presents stent deployment length predictions offered in medical software (PreSize Neurovascular) that provides physicians with real-time planning support, allowing them to preoperatively "test" different devices in the patient's anatomy in a safe virtual environment. This study reports the software evaluation methodology and accuracy results when applied to real-world data from a wide range of cases and sources as a necessary step in demonstrating its reliability, prior to impact assessment in prospective clinical practice. METHODS: Imaging data from 138 consecutive stent cases using the Pipeline embolization device were collected from 5 interventional radiology centers in the United Kingdom and retrospectively analyzed. Prediction accuracy was calculated as the degree of agreement between stent deployed length measured intraoperatively and simulated in the software. RESULTS: The software predicted the deployed stent length with a mean accuracy of 95.61% (95% confidence interval [CI] 94.87%-96.35%), the highest reported accuracy in clinical stent simulations to date. By discounting 4 outlier cases, in which events such as interactions with coils and severe push/pull maneuvers impacted deployed length to an extent the software was not able to simulate or predict, the mean accuracy further increases to 96.13% (95% CI 95.58%-96.69%). A wide discrepancy was observed between labeled and measured deployed stent length, in some cases by more than double, with no demonstrable correlation between device dimensions and deployment elongation. These findings illustrate the complexity of stent behavior and need for simulation-assisted sizing for optimal surgical planning. CONCLUSIONS: The software predicts the deployed stent length with excellent accuracy and could provide physicians with real-time accurate device selection support.