Here we seek to identify how hemodynamic factors influence the success or failure of cerebral aneurysm treatment, and measure such factors at the time of treatment in an attempt to improve treatment outcome and prevent brain hemorrhage. This goal is significant due to the prevalence of cerebral aneurysms, which account for over 30,000 life-threatening brain hemorrhages in North America every year, with a dismal prognosis. While aneurysm treatment has advanced rapidly, treatment failure rates (resulting in aneurysm recurrence and risk of either brain hemorrhage or need for retreatment) approach 34%. Hemodynamic forces are thought to influence aneurysm treatment success, but the accurate modeling of such forces has not been incorporated into clinical practice and treatment decision-making. Doing so could improve the efficacy of aneurysm treatment, reducing death and disability as well as health care costs associated with multiple hospitalizations. We will build on our previous NIH-funded, IRB-approved study using a Doppler-tipped guidewire to collect in vivo measurements of patients'blood flow velocity (BFV) and blood pressure in brain blood vessels harboring intracranial aneurysms. We have previously shown that incorporating patient-specific measurements using this technique is safe, feasible and significantly more accurate than traditional methods of hemodynamic modeling. By measuring such characteristics at the time of treatment, we can characterize the treatments'hemodynamic effects. We then observe a cohort of patients over time, classifying those with either treatment success (aneurysm healing) or failure (aneurysm recurrence or persistence). By identifying which hemodynamic changes after treatment are associated with treatment failure, we can then prospectively screen new patients for such factors at the time of initial treatment, predicting which aneurysms might recur. This project has two stages of investigation. First, we will define the immediate hemodynamic effects of endovascular treatments of cerebral aneurysms. We will use computational modeling that incorporates patient- specific, individualized invasive measurements of BFV and blood pressure in precise anatomical locations obtained with the Doppler-tipped guidewire, which improves the accuracy of such calculations. Second, we will obtain follow-up imaging of the cerebral vasculature at least six months after treatment, and identify whether patients'aneurysms were successfully treated. We will then retrospectively compare the initial, immediate post-treatment hemodynamics between those patients whose aneurysms failed treatment and those that healed, and determine the threshold at which important hemodynamic factors correspond to treatment efficacy. Second, we will prospectively screen patients for such factors during aneurysm treatment to identify patients at risk of treatment failure. By prospectively applying the results of stage 1 to a new cohort of patients, we can predict whether aneurysms with particular hemodynamic changes immediately after treatment will either heal or recur at long-term follow-up.
The proposed study will use dual-sensor Doppler guidewire technology to measure blood flow velocity and blood pressure from within cerebral blood vessels harboring intracranial aneurysms during treatment, and apply these measurements to determine causes of treatment success and failure. The results of this study could be used by physicians to alert them to aneurysms at risk for treatment failure, and allow them to provide either additional treatment or more frequent follow-up to prevent aneurysm regrowth and life-threatening brain hemorrhage.
|Levitt, Michael R; Barbour, Michael C; Rolland du Roscoat, Sabine et al. (2017) Computational fluid dynamics of cerebral aneurysm coiling using high-resolution and high-energy synchrotron X-ray microtomography: comparison with the homogeneous porous medium approach. J Neurointerv Surg 9:0|
|Levitt, M R; McGah, P M; Moon, K et al. (2016) Computational Modeling of Venous Sinus Stenosis in Idiopathic Intracranial Hypertension. AJNR Am J Neuroradiol 37:1876-1882|
|McGah, P M; Nerva, J D; Morton, R P et al. (2015) In vitro validation of endovascular Doppler-derived flow rates in models of the cerebral circulation. Physiol Meas 36:2301-17|