Cascaded U-net for segmentation of endovascular path in mechanical thrombectomy

Endovascular interventions have experienced a very important development in recent years. In the particular context of cerebral stroke, mechanical thrombectomy has become a therapeutic of reference. Nevertheless, catheterization involves a technical gesture that can be very difficult or impossible in complex anatomical configurations. Preoperative images can help physicians in planning via visualization of structures of interest and during the intervention via augmented reality navigation. To guide the intervention, segmented navigation structures from pre-operative images are projected onto 2D intraoperative X-ray images. To this aim, common and internal carotids and aortic arch, that correspond to endovascular path, must be quickly and properly segmented. In this this work we propose a method for segmentation of vascular structures corresponding to endovascular path in mechanical thrombectomy from pre-operative images. Cascaded U-net are used to segment the common and internal arteries: a first U-net is used to mask the original MRA and a second U-net is used to segment the arteries. Another U-net is used to segment the aortic arch. The proposed method better highlights vascular structures related to endovascular navigation than a simple 2D U-net. Also, Dice coefficient of segmented vascular structures is equal to 0.851 with a sensitivity equal to 0.922.