Validation of 3D multimodality roadmapping in interventional neuroradiology

Abstract

Three-dimensional multimodality roadmapping is entering clinical routine utilization for neuro-vascular treatment. Its purpose is to navigate intra-arterial and intra-venous endovascular devices through complex vascular anatomy by fusing pre-operative computed tomography (CT) or magnetic resonance (MR) with the live fluoroscopy image. The fused image presents the real-time position of the intra-vascular devices together with the patient's 3D vascular morphology and its soft-tissue context. This paper investigates the effectiveness, accuracy, robustness and computation times of the described methods in order to assess their suitability for the intended clinical purpose: accurate interventional navigation. The mutual information-based 3D–3D registration proved to be of sub-voxel accuracy and yielded an average registration error of 0.515 mm and the live machine-based 2D–3D registration delivered an average error of less than 0.2 mm. The capture range of the image-based 3D–3D registration was investigated to characterize its robustness, and yielded an extent of 35 mm and 25° for >80% of the datasets for registration of 3D rotational angiography (3DRA) with CT, and 15 mm and 20° for >80% of the datasets for registration of 3DRA with MR data. The image-based 3D–3D registration could be computed within 8 s, while applying the machine-based 2D–3D registration only took 1.5 µs, which makes them very suitable for interventional use.