J Appl Biomed 17:199-208, 2019 | DOI: 10.32725/jab.2019.019

Image-guided left ventricular lead placement in cardiac resynchronization therapy: focused on image fusion methods

Premysl Hajek1,*, Iva Safarikova1,2, Jan Baxa3
1 Ceske Budejovice Hospital, Department of Cardiology, Ceske Budejovice, Czech Republic
2 University of South Bohemia in Ceske Budejovice, Faculty of Health and Social Sciences, Budejovice, Czech Republic
3 Charles University in Prague, University Hospital and Faculty of Medicine in Pilsen, Department of Imaging Methods, Pilsen, Czech Republic

Cardiac resynchronization therapy is an effective and widely accessible treatment for patients with advanced, drug-refractory heart failure. It has been shown to reverse maladaptive ventricular remodeling, increase exercise capacity, and lower hospitalization and mortality rates. However, there still exists a considerable proportion of patients who do not respond favorably to the therapy. Tailored left ventricular (LV) lead positioning instead of empiric implantation is thought to have the greatest potential to increase response rates. In our paper, we focus on the rationale for guided LV lead implantation and provide a review of the non-invasive imaging modalities applicable for navigation during LV lead implantation, with special attention to the latest achievements in the field of multimodality imaging and image fusion techniques. Current limitations and future perspectives of the concept are discussed as well.

Keywords: Cardiac resynchronization; Coronary sinus; Guided implantation; Image fusion; Mechanical activation; Multimodality imaging; Myocardial scar; Non-responder
Conflicts of interest:

The authors have no conflict of interests to declare.

Received: August 18, 2019; Revised: August 18, 2019; Accepted: October 30, 2019; Prepublished online: December 11, 2019; Published: December 13, 2019  Show citation

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Hajek P, Safarikova I, Baxa J. Image-guided left ventricular lead placement in cardiac resynchronization therapy: focused on image fusion methods. J Appl Biomed. 2019;17(4):199-208. doi: 10.32725/jab.2019.019. PubMed PMID: 34907722.
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