ABSTRACT

Multiparametric image analysis has become increasingly relevant within oncology research. Despite the exquisite spatial detail o›ered by the traditional T1-and T2-weighted images and even with the use of contrast agents, it is well known that these images are not uniquely speciœc for any malignancy. However, as evidenced by the prior chapters, magnetic resonance (MR) imaging (MRI) now o›ers a multitude of new parameters (Table 19.1), with each o›ering a portion of the physiological and anatomical picture. še goal of this chapter is to describe three of the more common approaches and techniques used to synthesize multiparameter data sets, identify areas of uncertainty, and present examples where these methods have been applied to cancer, and to discuss future directions for multiparameter analyses.