Introduction

Method for estimating in real time the probability of success of a thrombectomy surgery, comprising the following steps: creating a database of data generated from thrombectomy models; acquiring clinical images of a patient’s occluded vessels; extracting geometric parameters from these clinical images; generating a three-dimensional model of occluded vessels and occlusion; and finally calculating the probability of success the thrombectomy using predictive algorithm.

Technical features

A method that, starting from a limited set of measurements or points extracted from clinical images such as computed tomography (CT) or magnetic resonance (MRI) and the relative diameters estimated from the same clinical images, automatically or manually constructs an anatomy of the cerebral district of interest suffering from acute ischemic stroke. The method therefore allows to estimate the probability of success of the endovascular procedure of mechanical recanalization of the obstructed vessel by means of stent-retrievers and/or suction catheters based on surrogate models of verified and validated patient-specific numerical simulations of the procedure. It can be used in the optimization phase of the device and/or procedure or as a support to the interventionist in choosing the best device and/or procedure for the patient-specific. The technology has a TRL 3 in fact a working prototype of the framework is available for the evaluation of thrombus removal with two different devices.

Possible Applications

• Manufacturers of mechanical thrombus removal devices can use the method to virtually test the performance of specific prototypes and devices prior to industrial production;
• Clinical operators can use it to evaluate the best treatment for a specific patient in terms of choice of device and procedure;
• Manufacturers of clinical image acquisition machines can implement the method within the software for acquiring and processing clinical images of a single patient.

Advantages

• Faithfully reconstructs the anatomical district and the patient-specific thrombus;
• It is based on finite element numerical simulations verified and validated with clinical data and on the query of a surrogate model that provides an estimate of the outcome of the real-time procedure;
• It allows to evaluate the best device for the considered patient and the best thrombus extraction technique.