S. van Marwick, A. Beer, S. Metz, A. Martinez-Möller, M. Schwaiger, S. Nekolla M3P-Anima: A Visualization and Quantification Concept for Multimodal, Multiparametric Imaging. Radiological Society of North America (RSNA 2011) Chicago, IL, USA, November 2011 (bib)
	Background In contrast to the increasing availability of multimodal data (e.g. PET/CT and MRI) as well as serial examinations of patients in various techniques, only a limited number of flexible visualization and evaluation applications exist, that can process this plethora of data. This work presents an implementaion which allows powerful combinations in multiparametric imaging. Evaluation: M3P–Anima (MultiModal?, MultiParametric? Analysis & Imaging) is a platform-independent (Win, Mac, Linux) software package for visualization and quantification of an arbitrary number of data sets (static/dynamic/gated; PET/SPECT/CT/MRI). Those can be aligned to each other using manual or mutal information based registration. ROIs and VOIs can be defined using semi-automatic region growing, thresholding, manual definition, or derived from a scatterplot analysis of two fused data sets. Moreover, as all data is processed in the same coordinate space, ROIs and VOIs can be copied freely in space and time. Transfer functions (e.g. pharmacokinetic models) allow derivations of three-dimensional data sets out of four-dimensional data. User-specific plug-ins are supported. All derived data can then be further processed. Discussion: An example for multimodal, multiparametric evaluation is the classification of tumor tissue in MRI and PET data: F-18-Galacto-RGD and F-18-FDG data are fused and the tumor is segmented manually in one slice. A scatterplot and one threshold per data set divides the data into four segments. The resulting visualization of four tumor regions in PET data is then transferred onto a dynamic MRT and manually moved to the tumor. This yields intensity curves for all four clusters and the entire tumor, which are converted into quantitative T1 values. Lastly, regional tissue parameters are found using an average input function and a one compartment model. Conclusion: M3P-Anima is a flexible research tool that enables extraction and visualization of complex, quantitative parameters from nearly limitless combinations of tomographic data.
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