The purpose of this study was to evaluate 18 F-FDG PET studies of primary and recurrent sarcomas for diagnosis and correlation with grading. Methods: The evaluation included 56 patients, 43 with histologically proven malignancies and 13 with benign lesions. Seventeen patients were referred with suspicion on a primary tumor, and the remaining 39 were referred with suspicion on a recurrent tumor. The FDG studies were accomplished as a dynamic series for 60 min. The evaluation of the FDG kinetics was performed using the following parameters: standardized uptake value (SUV), global influx, computation of the transport constants K1–k4 with consideration of the distribution volume (VB) according to a two-tissue-compartment model, and fractal dimension based on the box-counting procedure (parameter for the inhomogeneity of the tumors). Results: Visual evaluation revealed a sensitivity of 76.2%, a specificity of

EvIdent^TM (EVent IDENTification) is a user-friendly, algorithm-rich, graphical environment for detecting, investigating, and visualizing novelty in a set of images. Novelty is identified for a region of interest and its associated characteristics. For functional magnetic resonance imaging, for instance, a characteristic of the region of interest is a time course, which represents the intensity value of voxels over several discrete instances in time. Originally developed for a platform-specific environment using proprietary technology, a new incarnation of EvIdent has been designed using an application programming interface called VIStA^TM (VISualization Through Analysis). VIStA is written in Java^TM and offers a sophisticated generalized data model, an extensible algorithm framework, and a suite of graphical user interface constructs. This paper describes EvIdent and some of its features, the rationale behind the design of VIStA, and the motivations and challenges of scientific programming using Java.