MR ONCO-TREAT: A New Tool for Volumetric and Functional Analysis of Hepatic Tumors Monitored with Multi-Modal MRI

a b Figure 4: Pre(a) and post-treatment (b) arterial enhancement color maps overlaid on arterial phase DCE images. Enhancement increases from blue to red (Green = intermediate) b a Figure 3: ADC analysis. Color map of changes in ADC overlaid on ADC image (a), and scatter plot (b). Red = increased ADC, Blue = decreased ADC (Green = intermediate) Introduction: The RECIST criteria have been the gold standard for determining therapeutic response of a tumor, defining partial response as ≥ 30% decrease in diameter in a single dimension [1]. Recent data strongly suggest that the RECIST criteria are a poor indicator of therapeutic response for hepatic tumors (either primary or metastatic) which have been treated with intra-arterial therapy. In contrast, multi-parametric MRI, including diffusion weighted imaging (DWI) and T1weighted dynamic contrast-enhancement (DCE), has been shown to be a sensitive indicator of tumor response [2]. Typically, measurements of liver tumor size, Apparent Diffusion Coefficient (ADC) characteristics and perfusion are performed manually, and visual comparisons are made across serial examinations. This process is time consuming, is inherently subjective, and may inaccurately assess liver tumor response to intra-arterial therapy. The automation of this task would allow for objective evaluation, decreased inter-observer variability, and increased accuracy of evaluation of liver tumor response to therapy. In this abstract we present our design of MR ONCO-TREAT, a highly flexible, semi-automated software package for three dimensional intraand inter-study image registration, segmentation, volumetric analysis and functional analysis. We present early data showing that this software package can provide objective evaluation of liver tumor response to intra-arterial therapy on either a global or voxel-by-voxel basis. Materials and Methods: The images in preand post-treatment studies are registered in two steps, in order to work in a fixed frame of reference (Fig. 1a-c). In the first step, intra-study registration, images within each study are registered using the venous phase post-contrast DCE volume as the reference image set. Motion is corrected in the dynamic contrast-enhanced images and diffusion weighted images are registered to the reference DCE volume by a deformable registration technique [3]. In the second step, inter-study registration, venous phase DCE images from both studies are co-registered, and the resulting deformation field is applied to all images in the post-treatment study. The deformable registration technique first aligns the images with a rigid method to improve the capture range and accuracy, and then works with a multi-resolution strategy focusing on global and local image features at different resolution levels.