Multispectral analysis of uterine corpus tumors in magnetic resonance imaging.

The goal of this prospective study was to evaluate multispectral analysis techniques for automatic recognition of uterine cancer in magnetic resonance (MR) imaging. The first part of this study was an open training phase in which the statistical parameters of the various normal and pathological tissue types were estimated. This was followed by a test phase that was done as a blind experiment. Results from an extensive pathological examination of the surgically removed organs served as the reference for the diagnosis and various geometric measurements of the lesions. A radiological examination of the MR images was also performed. All malignant test tumors were correctly or close to correctly classified. However, parts of normal endometrium and other mucosal linings were also classified as adenocarcinomas. In addition, parts of some of the malignant tumors were classified as normal endometrium. The geometrical extension of the tumor and its relationship to the surroundings were slightly better predicted than those obtained by the radiologist. The results indicate that it is possible to differentiate and determine the local extension of some types of uterine malignancies based on the information present in MR images.