Graphics Processing Unit–Accelerated Nonrigid Registration of MR Images to CT Images During CT-Guided Percutaneous Liver Tumor Ablations

Junichi Tokuda,William Plishker,Meysam Torabi,Olutayo I Olubiyi,George Zaki,Servet Tatli,Stuart G Silverman,Raj Shekher,Nobuhiko Hata

doi:10.1016/j.acra.2015.01.007

Abstract

Accuracy and speed are essential for the intraprocedural nonrigid magnetic resonance (MR) to computed tomography (CT) image registration in the assessment of tumor margins during CT-guided liver tumor ablations. Although both accuracy and speed can be improved by limiting the registration to a region of interest (ROI), manual contouring of the ROI prolongs the registration process substantially. To achieve accurate and fast registration without the use of an ROI, we combined a nonrigid registration technique on the basis of volume subdivision with hardware acceleration using a graphics processing unit (GPU). We compared the registration accuracy and processing time of GPU-accelerated volume subdivision-based nonrigid registration technique to the conventional nonrigid B-spline registration technique. Fourteen image data sets of preprocedural MR and intraprocedural CT images for percutaneous CT-guided liver tumor ablations were obtained. Each set of images was registered using the GPU-accelerated volume subdivision technique and the B-spline technique. Manual contouring of ROI was used only for the B-spline technique. Registration accuracies (Dice similarity coefficient [DSC] and 95% Hausdorff distance [HD]) and total processing time including contouring of ROIs and computation were compared using a paired Student t test. Accuracies of the GPU-accelerated registrations and B-spline registrations, respectively, were 88.3 ± 3.7% versus 89.3 ± 4.9% (P = .41) for DSC and 13.1 ± 5.2 versus 11.4 ± 6.3 mm (P = .15) for HD. Total processing time of the GPU-accelerated registration and B-spline registration techniques was 88 ± 14 versus 557 ± 116 seconds (P < .000000002), respectively; there was no significant difference in computation time despite the difference in the complexity of the algorithms (P = .71). The GPU-accelerated volume subdivision technique was as accurate as the B-spline technique and required significantly less processing time. The GPU-accelerated volume subdivision technique may enable the implementation of nonrigid registration into routine clinical practice.

Highlights

Computed tomography (CT) is used commonly to guide percutaneous tumor ablations of liver tumors [1,2,3]
Total processing time of the graphical processing unit (GPU)-accelerated registration and B-spline registration techniques was 88 ± 14 s vs 557 ± 116 s (p < 0.000000002), respectively; there was no significant difference in computation time despite the difference in the complexity of the algorithms (p = 0.71)
The GPU-accelerated volume subdivision technique may enable the implementation of nonrigid registration into routine clinical practice

Summary

Introduction

Computed tomography (CT) is used commonly to guide percutaneous tumor ablations of liver tumors [1,2,3]. CT can provide high-quality three-dimensional (3D) images of the liver intraprocedurally, which help radiologists understand spatial relationship of the tumor with respect to the surrounding structures [4]. Typically only sectional unenhanced CT images are used and tumor margins may not be delineated well [5]; this limitation may contribute to inadequate ablation [6,7,8,9,10]. One way to delineate tumor margins intraprocedurally is to register preprocedural MR images to the intraprocedural CT images; tumor margins depicted by MRI can be directly compared to ablation effects depicted with intraprocedural CT [12]. The same data can be used to depict tumor and ablation volumes [12]

Objectives

Methods

Results

Conclusion