Three-dimensional DSA is valuable for evaluating the potential for EVT, finding a working view, and performing accurate measurements.

No abstract

Abstract. Today, 3-D angiography volumes are routinely generated from rotational angiography sequences. In previous work [7], we have studied the precision reached by registering such volumes with classical 2-D angiography images, inferring this matching only from the sensors of the angiography machine. The error led by such a registration can be described as a 3-D rigid motion composed of a large translation and a small rotation. This paper describes the strategy we followed to correct this error. The angiography image is compared in a two-step process to the Maximum Intensity Projection (MIP) of the angiography volume. The first step provides most of the translation by maximizing the cross-correlation. The second step recovers the residual rigid-body motion, thanks to a modified optical flow technique. A fine analysis of the equations encountered in both steps allows for a speed-up of the calculations. This algorithm was validated on 17 images of a phantom, and 5 patients. The residual error was determined by manually indicating points of interest and was found to be around 1 mm.

During an interventional neuroradiology exam, knowing the exact location of the catheter tip with respect to the patient can dramatically help the physician. An image registration between digital subtracted angiography ( DSA) images and a volumic pre-operative image (magnetic resonance or computed tomography volumes) is a way to infer this important information. This mono-patient multimodality matching can be reduced to finding the projection matrix that transforms any voxel of the volume onto the DSA image plane. This modelization is unfortunately not valid in the case of distorted images, which is the case for DSA images.A classical angiography room can now generate 3D X-ray angiography volumes (3DXA). Since the DSA images are obtained with the same machine, it should be possible to deduce the projection matrix from the sensor data indicating the current machine position.We propose an interpolation scheme, associated to a pre-operative calibration of the machine that allows us to correct the distortions in the image at any position used during the exam with a precision of one pixel. Thereafter, we describe some calibration procedures and an associated model of the machine that can provide us with a projection matrix at any position of the machine.Thus, we obtain a machine-based 2D DSA/3DXA registration. The misregistration error can be limited to 2.5 mm if the patient is well centered within the system. This error is confirmed by a validation on a phantom of the vascular tree. This validation also yields that the residual error is a translation in the 3D space.As a consequence, the registration method presented in this paper can be used as an initial guess to an iterative refining algorithm.

In Digital Subtraction Angiography, the use of an Image Intensifier as a detector introduces geometrical distortions in the images. For stereotactic applications, such as the irradiation of cerebral arteriovenous malformations, these distortions have necessarily to be corrected, and the accuracy of this correction has to be examined. As the distortions depend on many parameters that vary during an examination (such as magnetic field and spatial position of the acquisition chain), the correction accuracy must be defined as a function of the acquisition protocol. We have developed a correction method based on the calibration of geometrical distortions using an image of a grid phantom. An experimental study of the influence of acquisition parameters over the distortion has been performed. A protocol has been defined which ensures a correction accuracy of 0. 1 millimeter. Finally, we have studied the accuracy obtained in the 3D location of a target as a function of the accuracy of the distortion correction. The final precision allows the use of our method for digital X-Ray stereotactic applications.