Fully Automatic Segmentation of Papillary Muscles in 3D LGE-MRI

Abstract

Cardiac resynchronization therapy is a treatment option for patients suffering from symptomatic heart failure. The problem with this treatment option is, that 30% to 40% of the patients do not respond. One reason might be the inappropriate placement of the left ventricular lead via the coronary sinus. Therefore, endocardial pacing systems have been developed. Nonetheless, the implantation of these devices requires in addition to the knowledge of the anatomy and scar of the left ventricle (LV), the information of the papillary muscles. As pacing in a papillary muscles may lead to severe problems. To overcome this issue, a fully automatic papillary muscle segmentation in 3D LGE-MRI is presented. First, the left ventricle is initialized using a registration basedapproach, afterwards the short axis view of the LV is estimated. In the next step, the blood pool is segmented. Finally, the papillary muscles are extracted using a threshold based approach. The proposed method was evaluated on six 3D LGE-MRI data sets and were compared to gold standard annotations from clinical experts. This comparison resulted in a Dice coefficient of 0.72.