RT Journal Article SR Electronic T1 18F-FDG PET/MRI for therapy response assessment of isolated limb perfusion in patients with soft-tissue sarcomas JF Journal of Nuclear Medicine JO J Nucl Med FD Society of Nuclear Medicine SP jnumed.119.226761 DO 10.2967/jnumed.119.226761 A1 Grueneisen, Johannes A1 Schaarschmidt, Benedikt Michael A1 Demircioglu, Aydin A1 Chodyla, Michal A1 Martin, Ole A1 Bertram, Stefanie A1 Wetter, Axel A1 Bauer, Sebastian A1 Fendler, Wolfgang Peter A1 Podleska, Lars A1 Forsting, Michael A1 Herrmann, Ken A1 Umutlu, Lale YR 2019 UL http://jnm.snmjournals.org/content/early/2019/04/18/jnumed.119.226761.abstract AB Purpose: To assess the diagnostic potential of simultaneously acquired 18F-FDG PET- and MR datasets for therapy response assessment of isolated limb perfusion (ILP) in patients with soft-tissue sarcomas (STS). Methods: A total of 45 patients with histopathologically verified STS were prospectively enrolled for an integrated 18F-FDG PET/MR examination before and after ILP. Therapy response was assessed based on different MR- and PET-derived morphological (RECIST, MR-adapted Choi criteria) and metabolic (PERCIST) criteria. In addition, a regression model was used combining relative changes of quantitative variables to predict treatment response under ILP. Histopathological results after subsequent tumor resection served as reference standard and patients were categorized as responders/non-responders based on the six-stage regression scale by Salzer-Kuntschik. Results: Histopathological analysis categorized 27 patients as therapy responders (Grade I-III) and 18 patients as non-responders (Grade IV-VI). Calculated sensitivities, specificities, positive and negative predictive values and diagnostic accuracies were 22%, 89%, 75%, 43% and 49% for RECIST, 70%, 44%, 66%, 50% and 60% for MRadapted Choi and 85%, 78%, 85%, 78% and 82% for the PERCIST criteria. ROC analysis revealed AUC values of 0.56 (RECIST), 0.57 (MR-adapted CHOI) and 0.82 (PERCIST), respectively. The combined regression model revealed higher values (AUC: 0.90) than for the stand-alone analysis, however, differences to metabolic parameters did not reached significance (p-value: 0.067). Conclusion: Our study demonstrates the superiority of 18F-FDG PET over MR-datasets for response assessment of STS under neoadjuvant ILP. In a clinical setting, MRI delivers valuable information for presurgical assessment. Therefore, combining 18FFDG PET and MRI data may enable a more reliable treatment planning and therapy monitoring of STS.