Analyzing DCE-MRI data

I. Overview Dynamic Contrast Enhanced MRI (DCE-MRI) is a rapidly evolving imaging technique. It is the current standard for breast MR imaging; also many research studies have been conducted to evaluate its application for various clinical problems. The development of gadolinium-based contrast agents in early 1980 opened a new era for imaging of tumors and vascular systems. Tumors require a higher supply of nutrients to support the rapid growth; as such it is necessary to induce formation of new blood vessels, termed “angiogenesis”. One of the earliest applications of Gd-based contrast agents is for enhancement of viable tumors on post-contrast T1-weighted images. The typical scan protocol includes precontrast images and post-contrast images, and the enhanced tumors can be detected by visual inspection of post-contrast images referencing to pre-contrast images. Further research has found that if multiple sets of post-contrast images at different times after injection were acquired, the enhancement time course (or, enhancement kinetics) could be measured, and that provided additional information to aid in distinguishing malignant lesions from benign lesions and normal breast tissues. This technique was termed “dynamic contrast enhanced MRI” or “DCE-MRI”. In conjunction with the development of pulse sequences by scanner manufactures, DCE-MRI can now be easily prescribed with preferred spatial and temporal resolution, and the total imaging period, by pushing buttons. This tutorial is focused on the analysis of DCE-MRI data. I will begin by discussing the technical aspects of DCEMRI. A simple approach of heuristic parameters from the time intensity curves will be contrasted with quantitative approach based on curve fitting using pharmacokinetic models and yielding parameters Ktrans and kep. Since DCE-MRI is most established for breast imaging, I will describe how the analysis is commonly applied to imaging of breast lesions. The ROI-based and pixel-by-pixel based analyses are the two main methods. For diagnosis, the hot spot ROI approach to characterize tissues with the most aggressive pathology should be taken; but for therapy response monitoring, the whole tumor should be analyzed. Following the application in the breast, I will briefly describe DCE-MRI applications to other organs. Lastly the available tools for analysis of DCE-MRI provided by major scanner manufactures and the two mostwidely used commercial software (CADstream and DynaCAD) will be described. The objective of this tutorial is to provide an overview for analysis of DCE-MRI data, first using the application in breast imaging to give in-depth examples, then extending to other organs; and lastly to illustrate the available tools provided by major manufactures.