Differentiation of normal and pathologic brain structures in MRI using exact T1 and T2 values followed by a multidimensional cluster analysis.

A new method to differentiate and classify normal and pathologic brain tissue in Magnetic Resonance Imaging (MRI) is introduced. With a special pulse sequence, exact T1 and T2 values are simultaneously acquired, where the T2 values may show a biexponential decay behavior. The automatic segmentation of the tissue is based on a histogram analysis of the multidimensional parameters. The tissue-characterizing parameters are stored in a database, which serves as an objective classification of different tissues. A pilot study with 15 healthy volunteers and 100 patients showed a good differentiation between normal tissue like white and gray matter, cerebrospinal fluid, muscle, and fat, thereby revealing a biexponential decay behavior of fat. Pathologic tissue-like edema and meningioma could be classified with high accuracy, while glioblastoma or astrocytoma were difficult to classify because of their non-homogeneous structures.