Image fusion of CT and MRI data enables improved target volume definition in 3D-brachytherapy treatment planning

Abstract

Purpose: To integrate MRI into CT-based 3D-brachytherapy treatment planning using a software system for image registration and fusion.

Methods and materials: Sixteen patients with recurrent head-and-neck cancer, vulvar cancer, liposarcoma, and cervical cancer were treated with interstitial (n=12) and endocavitary (n=4) brachytherapy. CT and MRI scans were performed after implantation and prior to treatment planning. Image registration to integrate the CT and MR information into a single geometric framework was performed using a software algorithm based on mutual information. Conventional 3D-brachytherapy planning based on CT-information alone was compared to brachytherapy planning based on fused CT and MRI data. The accuracy of the image fusion was measured using predefined corresponding landmarks in the CT and MRI data.

Results: The presented automated algorithm proved to be robust and reliable (mean registration error 1.8 mm, range 0.8-4.1 mm, SD 0.9 mm). Tumor visualization was difficult using CT alone in all cases. Brachytherapy treatment planning based on fused CT and MRI data enabled better definition of target volume and risk structures as compared to treatment planning based on CT alone.

Conclusions: Image registration and fusion is feasible for afterloading brachytherapy treatment planning. Treatment planning based on fused CT and MRI data resulted in improved target volume and risk structure definition.