Recent C-arm systems used for endovascular image-guided interventions enable the acquisition of three-dimensional
(3D) and dynamic two-dimensional (2D+t) images in the same interventional suite. The 3D images are used to observe
the vascular morphology while the 2D+t images show the current state of the intervention. By spatial alignment of 3D
and 2D+t images one can facilitate the endovascular interventions, e.g. by displaying the intra-interventional tools and
contrast-agent flow in the augmented 3D+t images. To achieve the spatial alignment several 3D-2D registration methods
were proposed that are concerned with finding the rigid-body parameters of the 3D image. Meanwhile, the pose of the C-arm
system is usually obtained through a dedicated C-arm calibration. In practice, the calibrated C-arm pose parameters
are typically valid only if the imaged object is positioned in the C-arm’s isocenter. To compensate this, the 3D-2D
registration should search simultaneously for the rigid-body as well as the C-arm pose parameters. For verification, we
tested three 3D-2D registration methods on real, clinical 3D and 2D+t angiographic images of twenty patients, ten of
which were imaged with attached fiducial markers to obtain a “gold standard” registration. The results indicate that,
compared to searching solely the rigid-body parameters, by searching simultaneously for rigid-body and the C-arm pose
parameters significantly improves the accuracy and success rate of 3D-2D registration methods. Among the three tested
methods the intensity-based method using mutual information was the most robust, as it successfully registered all
clinical datasets, and highly accurate, as the maximal fiducial registration error was less or equal than 0.34 mm.
Endovascular treatment of cerebral aneurysms and arteriovenous malformations (AVM) involves navigation of a catheter
through the femoral artery and vascular system to the site of pathology. Intra-interventional navigation is done under the
guidance of one or at most two two-dimensional (2D) X-ray fluoroscopic images or 2D digital subtracted angiograms
(DSA). Due to the projective nature of 2D images, the interventionist needs to mentally reconstruct the position of the
catheter in respect to the three-dimensional (3D) patient vasculature, which is not a trivial task. By 3D-2D registration of
pre-interventional 3D images like CTA, MRA or 3D-DSA and intra-interventional 2D images, intra-interventional tools
such as catheters can be visualized on the 3D model of patient vasculature, allowing easier and faster navigation. Such a
navigation may consequently lead to the reduction of total ionizing dose and delivered contrast medium. In the past,
development and evaluation of 3D-2D registration methods for endovascular treatments received considerable attention.
The main drawback of these methods is that they have to be initialized rather close to the correct position as they mostly
have a rather small capture range. In this paper, a novel registration method that has a higher capture range and success
rate is proposed. The proposed method and a state-of-the-art method were tested and evaluated on synthetic and clinical
3D-2D image-pairs. The results on both databases indicate that although the proposed method was slightly less accurate,
it significantly outperformed the state-of-the-art 3D-2D registration method in terms of robustness measured by capture
range and success rate.
Endovascular treatment of cerebral aneurysms and arteriovenous malformations (AVM) involves navigation of a catheter
through the femoral artery and vascular system into the brain and into the aneurysm or AVM. Intra-interventional
navigation utilizes digital subtraction angiography (DSA) to visualize vascular structures and X-ray fluoroscopy to
localize the endovascular components. Due to the two-dimensional (2D) nature of the intra-interventional images,
navigation through a complex three-dimensional (3D) structure is a demanding task. Registration of pre-interventional
MRA, CTA, or 3D-DSA images and intra-interventional 2D DSA images can greatly enhance visualization and
navigation. As a consequence of better navigation in 3D, the amount of required contrast medium and absorbed dose
could be significantly reduced. In the past, development and evaluation of 3D-2D registration methods received
considerable attention. Several validation image databases and evaluation criteria were created and made publicly
available in the past. However, applications of 3D-2D registration methods to cerebral angiograms and their validation
are rather scarce. In this paper, the 3D-2D robust gradient reconstruction-based (RGRB) registration algorithm is applied
to CTA and DSA images and analyzed. For the evaluation purposes five image datasets, each comprised of a 3D CTA
and several 2D DSA-like digitally reconstructed radiographs (DRRs) generated from the CTA, with accurate gold
standard registrations were created. A total of 4000 registrations on these five datasets resulted in mean mTRE values
between 0.07 and 0.59 mm, capture ranges between 6 and 11 mm and success rates between 61 and 88% using a failure
threshold of 2 mm.
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