A novel real-time computational framework for detecting catheters and rigid guidewires in cardiac catheterization procedures

Purpose: Catheters and guidewires are used extensively in cardiac catheterization procedures such as heart arrhythmia treatment (ablation), angioplasty and congenital heart disease treatment. Detecting their positions in fluoroscopic X-ray images is important for several clinical applications, for example, motion compensation, co-registration between 2D and 3D imaging modalities and 3D object reconstruction. Methods: For the generalized framework, a multiscale vessel enhancement filter is first used to enhance the visibility of wire-like structures in the X-ray images. After applying adaptive binarization method, the centerlines of wire-like objects were extracted. Finally, the catheters and guidewires were detected as a smooth path which is reconstructed from centerlines of target wire-like objects. In order to classify electrode catheters which are mainly used in electrophysiology procedures, additional steps were proposed. First, a blob detection method, which is embedded in vessel enhancement filter with no additional computational cost, localizes electrode positions on catheters. Then the type of electrode catheters can be recognized by detecting the number of electrodes and also the shape created by a series of electrodes. Furthermore, for detecting guiding catheters or guidewires, a localized machine learning algorithm is added into the framework to distinguish between target wire objects and other wire-like artifacts. The proposed framework were tested on total 10,624 images which are from 102 image sequences acquired from 63 clinical cases. Results: Detection errors for the coronary sinus (CS) catheter, lasso catheter ring and lasso catheter body are 0.56 ± 0.28 mm, 0.64 ± 0.36 mm and 0.66 ± 0.32 mm, respectively, as well as success rates of 91.4%, 86.3% and 84.8% were achieved. Detection errors for guidewires and guiding catheters are 0.62 ± 0.48 mm and success rates are 83.5%. Conclusion: The proposed computational framework do not require any user interaction or prior models and it can detect multiple catheters or guidewires simultaneously and in real-time. The accuracy of the proposed framework is sub-mm and the methods are robust toward low-dose X-ray fluoroscopic images, which are mainly used during procedures to maintain low radiation dose

Visualization of coronary arteries in paediatric patients using whole-heart coronary magnetic resonance angiography: comparison of image-navigation and the standard approach for respiratory motion compensation

Aims: To investigate the use of respiratory motion compensation using image-based navigation (iNAV) with constant respiratory efficiency using single end-expiratory thresholding (CRUISE) for coronary magnetic resonance angiography (CMRA), and compare it to the conventional diaphragmatic navigator (dNAV) in paediatric patients with congenital or suspected heart disease. Methods: iNAV allowed direct tracking of the respiratory heart motion and was generated using balanced steady state free precession startup echoes. Respiratory gating was achieved using CRUISE with a fixed 50% efficiency. Whole-heart CMRA was acquired with 1.3mm isotropic resolution. For comparison, CMRA with identical imaging parameters were acquired using dNAV. Scan time, visualization of coronary artery origins and mid-course, imaging quality and sharpness was compared between the two sequences. Results: Forty patients (13 females; median weight: 44 kg; median age: 12.6, range: 3 months–17 years) were enrolled. 25 scans were performed in awake patients. A contrast agent was used in 22 patients. The scan time was significantly reduced using iNAV for awake patients (iNAV 7:48 ± 1:26 vs dNAV 9:48 ± 3:11, P = 0.01) but not for patients under general anaesthesia (iNAV = 6:55 ± 1:50 versus dNAV = 6:32 ± 2:16; P = 0.32). In 98% of the cases, iNAV image quality had an equal or higher score than dNAV. The visual score analysis showed a clear difference, favouring iNAV (P = 0.002). The right coronary artery and the left anterior descending vessel sharpness was significantly improved (iNAV: 56.8% ± 10.1% vs dNAV: 53.7% ± 9.9%, P < 0.002 and iNAV: 55.8% ± 8.6% vs dNAV: 53% ± 9.2%, P = 0.001, respectively). Conclusion: iNAV allows for a higher success-rate and clearer depiction of the mid-course of coronary arteries in paediatric patients. Its acquisition time is shorter in awake patients and image quality score is equal or superior to the conventional method in most cases.Medical Engineering at King’s College London WT 088641/Z/09/ZBHF Centre of Excellence RE/08/0