Registration of Real-Time and Prior Imaging Data with Applications to MR Guided Cardiac Interventions

Abstract

Recently, there has been increased interest in using magnetic resonance imaging (MRI) to guide interventional procedures due to its excellent soft tissue contrast and lack of ionizing radiation. One of the applications is the use of MRI to guide radio-frequency (RF) ablations for the treatment of cardiac arrhythmia. However, MRI is challenging as there exists significant tradeoffs between the imaging quality and acquisition time. High quality, pre-operative 3D MR images can be acquired with excellent spatial resolution at the expense of long acquisitions. Alternatively, 2D real-time MR imaging during the intervention sacrifices image quality for the ability to visualize dynamic motion of the heart. Therefore, to improve the MRI guidance capabilities for cardiac interventions, we propose a novel registration method to align the real-time and prior imaging data, which corrects for motion errors between the two datasets. The proposed method uses a hybrid metric within a multi-resolution registration framework to achieve the desired clinical accuracy for cardiac interventions. Registration experiments were performed with in vivo human images, and the mean alignment error between real-time and prior images after registration was 3.91 $\pm$ 1.52 mm.