Original new published on DTIC website 06/06/2013.
Ventricular tachycardia (VT) is one of the most common forms of cardiac arrhythmia, severe cardiovascular diseases of electrical origin which can lead to death if are not treated properly in time, as in the cases of sudden death. In many cases, VT is due to injuries (scarring) in cardiac tissue generated after a heart attack.
One of the techniques that have shown a higher rate of successful of treating these arrhythmias is radio frequency ablation (RF) of certain parts of the heart tissue to isolate the electrical circuit causing VT. These RF ablation procedures use invasive acquisition systems (the insertion of intra-venous catheters is required) to guide the intervention. These interventions can become long-term (certain hours) if you do not have any prior information about the state of the patient's heart and it is difficult to find the source of electrical abnormalities.
In a recent study, researchers from the Department of Information Technology (DTIC) at UPF and Hospital Clínic de Barcelona (HCB) have shown how to extract three-dimensional information of the characteristics of cardiac tissue non-invasively from Magnetic resonance images (MRI) of the patient acquired and processed before the operation. This information can guide the ablation procedure more optimal and reduce the time of intervention significantly.
This study, with the participation of Oscar Camara, a Ramon y Cajal researcher from Physense group of the DTIC UPF, was done in collaboration with a group of HCB led by Dr. Antonio Berruezo, and was published on 21 May in the online edition of the prestigious American journal Circulation: Arrhythmia and Electrophysiology of the American Heart Association .
Computational methods for accurate diagnosis
The first step of the developed methodology is to acquire a magnetic resonance image with contrast (Gadolinium) of the patient. These images are high resolution as they are obtained from a 3 Tesla MRI scanner available in the HCB, with advanced acquisition protocols, providing nearly isotropic voxels (same resolution in all dimensions) and enabling the visualization of anatomical structures more accurately than the old MRI 1.5 T scanners.
The next step is to apply computational techniques to the acquired image to extract the most relevant characteristics of the tissue, the left ventricular geometry and scar areas basically.
Then, the extracted geometries are processed to display the tissue characteristics of 3D through the heart wall and thus to identify the slow conduction channels (see the arrows in the figure of the graph), which are the main cause of the electrical anomalies, and therefore ablacionats candidates points to resolve the ventricular tachycardia.
Researchers and developers from PhySense research group, with validation by physicians of HCB have implemented these techniques on a computational platform for open source development created at UPF, GIMIAS, which allows for fast prototyping of applications adapted to clinical needs.
The published study includes the application of the developed methodology in a series of 21 patients with post-myocardial infarction, demonstrating the pyramidal structure of the transmural infarction, with the base of the corresponding pyramid to the inner wall of the heart, the endocardium.
This research was partly funded by various national projects (PI11/02049 and TIN2011-28067) and is part of the close collaboration in recent years between DTIC and the Department of Cardiology HCB, strategic partners in numerous national and international initiatives.
Three-dimensional Architecture of Scar and Conducting Channels Based on High Resolution ce-CMR: Insights for Ventricular Tachycardia ablation . Juan Armenta-Fernandez, Antonio Berruezo, David Andrew, Oscar Camara, Etelvino Silva, Luis Serra, Valeria Barbarito, Luigi Carotenutto, Reinder Evertz, Joseph T. Ortiz-Perez, Maria Teresa De Caralt, Rosary Jesus Perea, Marta Sitges, Lluis Mont, Alejandro Frangi, Josep Brugada. Circulation: Arrhythmia and Electrophysiology, in press.