Automatic identification and reconstruction of the right phrenic nerve on computed tomography

Abstract

In Hartcentrum Hasselt, patients with atrial fibrillation are treated invasively by performing pulmonary vein isolation. One of the techniques used for this procedure, is an endoscopic laser balloon ablation system. During this procedure, there is a slight risk of damaging the right phrenic nerve.

In this master's thesis, a method is developed to visualize the nerve before surgery on CT images. That way, the physician can assess the appropriate ablation areas and reduce the risk of phrenic nerve paralysis. During the previous bachelor's thesis, a 'proof of concept' showed that it is possible to identify the nerve by automatic nerve detection in a single patient. This master's thesis has the objective to improve and enhance the algorithm such that it is useful for a larger patient population.

The algorithm is designed in MATLAB. The processing of the images can be subdivided in four steps. After pre-processing the CT images to reduce the effect of unwanted noise, the various parts of the heart are segmented. By doing this, a small region of interest can be isolated where possible locations of the phrenic nerve can be identified. The last step is the 3D-reconstruction of the right phrenic nerve.

This thesis has led to a more robust algorithm that is able to determine the position of the nerve in 89 percent of the cases with a median error margin of 3.51 mm. However, when the CT slices are of inferior quality or when the contrast fluid is not clearly visible, problems can still arise.