Quantitative magnetic resonance angiography for early identification of in-stent stenosis post-flow diverter aneurysm embolization
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background In-stentstenosis (ISS) is a recognized complication following flow-diverting stent placement for intracranial aneurysms. Although typically asymptomatic and self-resolving, severe cases may result in ischemic complications. Gold-standard detection relies on invasive digital subtraction angiography (DSA). This study sought to determine whether quantitative magnetic resonance angiography with non-invasive optimal vessel analysis (qMRA NOVA) can accurately identify patients with ISS following flowdiverter placement. Methods This retrospective study evaluated 373 patients treated with flow-diverting stents at a single institution between 2017 and 2023. Sixteen patients met the inclusion criteria for DSA-confirmed ISS with matched post-procedure and follow-up NOVA imaging and catheter angiography. Vessel flow, velocity, and diameter were analyzed. Receiver operating characteristic (ROC) analysis was used to determine optimal thresholds for detecting ISS based on flow changes. Results Among ISS patients, 88% demonstrated significant flow reductions in the treated vessel on follow-up NOVA (mean decrease: 76.2 ± 65.0 ml/min, P = .0002). ROC analysis showed that the percent change in ICA flow had high discriminative ability, with optimal thresholds demonstrating sensitivity of 86% and negative predictive value (NPV) of 98%. A dual-threshold model combining ≥40 mL absolute and ≥20% relative ICA flow reduction afforded improved specificity (75%) while maintaining high NPV (97%). Conclusions NOVA is a sensitive non-invasive tool for early ISS detection following flow diversion, potentially detecting subclinical ISS patients that should undergo subsequent angiography, while also reducing the need for early angiography in patients unlikely to have ISS or repeated angiography to follow-up ISS.
Source: Interventional Neuroradiology
Authors: Cassidy Werner, Isabelle Pelcher, Jared Bassett, Rebecca Phillip, Shyle H Mehta, Justin Turpin, Miriam M. Shao, Thomas Link, Athos Patsalides, Timothy G White
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4415380900