Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries

Robust and accurate identification of intervertebral discs from low resolution, sparse MRI scans is essential for the automated scan planning of the MRI spine scan. This paper presents a graphical model based solution for the detection of both the positions and orientations of intervertebral discs from low resolution, sparse MRI scans. Compared with the existing graphical model based methods, the proposed method does not need a training process using training data and it also has the capability to automatically determine the number of vertebrae visible in the image. Experiments on 25 low resolution, sparse spine MRI data sets verified its performance.

Automated detection of fiducial screws from CT/DVT volume data for image-guided ENT surgery

This paper presents an automated solution for precise detection of fiducial screws from three-dimensional (3D) Computerized Tomography (CT)/Digital Volume Tomography (DVT) data for image-guided ENT surgery. Unlike previously published solutions, we regard the detection of the fiducial screws from the CT/DVT volume data as a pose estimation problem. We thus developed a model-based solution. Starting from a user-supplied initialization, our solution detects the fiducial screws by iteratively matching a computer aided design (CAD) model of the fiducial screw to features extracted from the CT/DVT data. We validated our solution on one conventional CT dataset and on five DVT volume datasets, resulting in a total detection of 24 fiducial screws. Our experimental results indicate that the proposed solution achieves much higher reproducibility and precision than the manual detection. Further comparison shows that the proposed solution produces better results on the DVT dataset than on the conventional CT dataset.

Loss of pace capture on the ablation line: a new marker for complete radiofrequency lesions to achieve pulmonary vein isolation

Catheter ablation procedures for atrial fibrillation (AF) often involve circumferential antral isolation of pulmonary veins (PV). Inability to reliably identify conduction gaps on the ablation line necessitates placing additional lesions within the intended lesion set.

Automated cement segmentation in vertebroplasty

Vertebroplasty is a minimally invasive procedure with many benefits; however, the procedure is not without risks and potential complications, of which leakage of the cement out of the vertebral body and into the surrounding tissues is one of the most serious. Cement can leak into the spinal canal, venous system, soft tissues, lungs and intradiscal space, causing serious neurological complications, tissue necrosis or pulmonary embolism. We present a method for automatic segmentation and tracking of bone cement during vertebroplasty procedures, as a first step towards developing a warning system to avoid cement leakage outside the vertebral body. We show that by using active contours based on level sets the shape of the injected cement can be accurately detected. The model has been improved for segmentation as proposed in our previous work by including a term that restricts the level set function to the vertebral body. The method has been applied to a set of real intra-operative X-ray images and the results show that the algorithm can successfully detect different shapes with blurred and not well-defined boundaries, where the classical active contours segmentation is not applicable. The method has been positively evaluated by physicians.

Automated detection of the osseous acetabular rim using three-dimensional models of the pelvis

An automated algorithm for detection of the acetabular rim was developed. Accuracy of the algorithm was validated in a sawbone study and compared against manually conducted digitization attempts, which were established as the ground truth. The latter proved to be reliable and reproducible, demonstrated by almost perfect intra- and interobserver reliability. Validation of the automated algorithm showed no significant difference compared to the manually acquired data in terms of detected version and inclination. Automated detection of the acetabular rim contour and the spatial orientation of the acetabular opening plane can be accurately achieved with this algorithm.

Evaluation of pulmonary vein stenosis after pulmonary vein isolation using a novel circular mapping and ablation catheter (PVAC)

Background—Pulmonary vein stenosis (PVST) is a well-known complication of pulmonary vein isolation (PVI). Specific anatomically designed ablation catheters for antral PVI have not been evaluated with regard to the incidence of PVST. We investigated the incidence, severity, and characteristics of PVST after PVI with the Pulmonary Vein Ablation Catheter (PVAC) and phased radiofrequency technology. Methods and Results A total of 100 patients (55 men) underwent PVI for atrial fibrillation using the PVAC. PVI was guided by selective angiography of each pulmonary vein (PV) in 70 (70%) patients and by reconstructed 3D atriography (ATG) in 30 (30%) patients. Gadolinium-enhanced MRI or multidetector CT was performed in all patients before treatment and 93±78 days after PVI. PVST was classified as follows: insignificant (<25%), mild (25%–50%), moderate (50%–75%), or severe (>75%). A total of 410 PVs were analyzed. Cardiac imaging demonstrated a detectable narrowing of the PV diameter in 23 (23%) patients and in 28 (7%) PVs. In detail, insignificant PVST was observed in 12 (2.9%) PVs, mild PVST in 15 (3.7%), and moderate PVST in 1 (0.2%). No instances of severe PVST were observed. The use of 3D-ATG was associated with a lower incidence of PVST (0.8% [95% CI, 0.0%–2.2%] versus 5.4% [95% CI, 2.7%–8.1%], P=0.027). Conclusions To our knowledge, this study is the first to report the incidence of PVST using the PVAC. In this regard, the PVAC seems to be safe if used in an experienced center. In addition, the use of 3D-ATG may decrease the risk of PVST.