Microcatheter tracking in thrombectomy procedures: A finite-element simulation study

Background and objective: Mechanical thrombectomy is a minimally invasive procedure that aims at removing the occluding thrombus from the vasculature of acute ischemic stroke patients. Thrombectomy success and failure can be studied using in-silico thrombectomy models. Such models require realistic modeling steps to be effective. We here present a new approach to model microcatheter tracking during thrombectomy. Methods: For 3 patient-specific vessel geometries, we performed finite-element simulations of the microcatheter tracking (1) following the vessel centerline (centerline method) and (2) as a one-step insertion simulation, where the microcatheter tip was advanced along the vessel centerline while its body was free to interact with the vessel wall (tip-dragging method). Qualitative validation of the two tracking methods was performed with the patient's digital subtraction angiography (DSA) images. In addition, we compared simulated thrombectomy outcomes (successful vs unsuccessful thrombus retrieval) and maximum principal stresses on the thrombus between the centerline and tip-dragging method. Results: Qualitative comparison with the DSA images showed that the tip-dragging method more realistically resembles the patient-specific microcatheter-tracking scenario, where the microcatheter approaches the vessel walls. Although the simulated thrombectomy outcomes were similar in terms of thrombus retrieval, the thrombus stress fields (and the associated fragmentation of the thrombus) were strongly different between the two methods, with local differences in the maximum principal stress curves up to 84%. Conclusions: Microcatheter positioning with respect to the vessel affects the stress fields of the thrombus during retrieval, and therefore, may influence thrombus fragmentation and retrieval in-silico thrombectomy

Metodo per stimare in tempo reale la probabilità di successo di un intervento di trombectomia

Metodo per stimare in tempo reale la probabilità di successo di un intervento di trombectomia, comprendente le seguenti fasi: creare un database di dati generati da modelli di trombectomia e allenare un algoritmo predittivo con tali dati mediante un’unità di elaborazione associata al database; acquisire immagini cliniche relative a vasi occlusi di un paziente ed estrarre da tali immagini cliniche parametri geometrici dei vasi occlusi e parametri di composizione dell’occlusione; generare un modello tridimensionale dei vasi occlusi e dell’occlusione elaborando, mediante l’unità di elaborazione, i parametri geometrici dei vasi occlusi e i parametri di composizione dell’occlusione; selezionare parametri indicatori relativi all’intervento di trombectomia mediante elaborazione del modello tridimensionale dei vasi occlusi e dell’occlusione; calcolare la probabilità di successo dell’intervento di trombectomia con rimozione dell’occlusione elaborando i parametri indicatori mediante l’algoritmo predittivo

Reliable Numerical Models of Nickel-Titanium Stents: How to Deduce the Specific Material Properties from Testing Real Devices

The current interest of those dealing with medical research is the preparation of digital twins. In this frame, the first step to accomplish is the preparation of reliable numerical models. This is a challenging task since it is not common to know the exact device geometry and material properties unless in studies performed in collaboration with the manufacturer. The particular case of modeling Ni–Ti stents can be highlighted as a worst-case scenario due to both the complex geometrical features and non-linear material response. Indeed, if the limitations in the description of the geometry can be overcome, many difficulties still exist in the assessment of the material, which can vary according to the manufacturing process and requires many parameters for its description. The purpose of this work is to propose a coupled experimental and computational workflow to identify the set of material properties in the case of commercially-resembling Ni–Ti stents. This has been achieved from non-destructive tensile tests on the devices compared with results from Finite Element Analysis (FEA). A surrogate modeling approach is proposed for the identification of the material parameters, based on a minimization problem on the database of responses of Ni–Ti materials obtained with FEA with a series of different parameters. The reliability of the final result was validated through the comparison with the output of additional experiments

Microcatheter tracking in thrombectomy procedures: A finite-element simulation study

Background and objective: Mechanical thrombectomy is a minimally invasive procedure that aims at removing the occluding thrombus from the vasculature of acute ischemic stroke patients. Thrombectomy success and failure can be studied using in-silico thrombectomy models. Such models require realistic modeling steps to be effective. We here present a new approach to model microcatheter tracking during thrombectomy. Methods: For 3 patient-specific vessel geometries, we performed finite-element simulations of the microcatheter tracking (1) following the vessel centerline (centerline method) and (2) as a one-step insertion simulation, where the microcatheter tip was advanced along the vessel centerline while its body was free to interact with the vessel wall (tip-dragging method). Qualitative validation of the two tracking methods was performed with the patient's digital subtraction angiography (DSA) images. In addition, we compared simulated thrombectomy outcomes (successful vs unsuccessful thrombus retrieval) and maximum principal stresses on the thrombus between the centerline and tip-dragging method. Results: Qualitative comparison with the DSA images showed that the tip-dragging method more realistically resembles the patient-specific microcatheter-tracking scenario, where the microcatheter approaches the vessel walls. Although the simulated thrombectomy outcomes were similar in terms of thrombus retrieval, the thrombus stress fields (and the associated fragmentation of the thrombus) were strongly different between the two methods, with local differences in the maximum principal stress curves up to 84%. Conclusions: Microcatheter positioning with respect to the vessel affects the stress fields of the thrombus during retrieval, and therefore, may influence thrombus fragmentation and retrieval in-silico thrombectomy