Analysis of pairwise correlations in multi-parametric PET/MR data for biological tumor characterization and treatment individualization strategies

Abstract

Purpose The aim of this pilot study was to explore simultaneous functional PET/MR for biological characterization of tumors and potential future treatment adaptations. To investigate the extent of complementarity between different PET/MR-based functional datasets, a pairwise correlation analysis was performed. Methods Functional datasets of N=15 head and neck (HN) cancer patients were evaluated. For patients of group A (N=7), combined PET/MR datasets including FDG-PET and ADC maps were available. Patients of group B (N=8) had FMISO-PET, DCE-MRI and ADC maps from combined PET/MRI, an additional dynamic FMISO-PET/CT acquired directly after FMISO tracer injection as well as an FDG-PET/CT acquired a few days earlier. From DCE-MR, Electronic supplementary material The online version of this article (doi:10.1007/s00259-016-3307-7) contains supplementary material, which is available to authorized users. Sara Leibfarth sara.leibfarth@med.uni-tuebingen.de 1 Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany 2 Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany 3 Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Tübingen, Germany 4 Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia 5 Jozef Stefan Institute, Ljubljana, Slovenia parameter maps K trans, ve and vp were obtained with the extended Tofts model. Moreover, parameter maps of mean DCE enhancement, SDCE, and mean FMISO signal 0-4 min p.i., AFMISO, were derived. Pairwise correlations were quantified using the Spearman correlation coefficient (r) on both a voxel and a regional level within the gross tumor

DOI: 10.1007/s00259-016-3307-7

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@inproceedings{Leibfarth2016AnalysisOP, title={Analysis of pairwise correlations in multi-parametric PET/MR data for biological tumor characterization and treatment individualization strategies}, author={Sara Leibfarth and Urban Simon{\vc}i{\vc} and David M{\"{o}nnich and Stefan Welz and Holger Schmidt and N. Schwenzer and Daniel Zips and Daniela Thorwarth}, booktitle={European Journal of Nuclear Medicine and Molecular Imaging}, year={2016} }