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 1537 OP 1542 DO 10.2967/jnumed.119.226761 VO 60 IS 11 A1 Johannes Grueneisen A1 Benedikt Schaarschmidt A1 Aydin Demircioglu A1 Michal Chodyla A1 Ole Martin A1 Stefanie Bertram A1 Axel Wetter A1 Sebastian Bauer A1 Wolfgang Peter Fendler A1 Lars Podleska A1 Michael Forsting A1 Ken Herrmann A1 Lale Umutlu YR 2019 UL http://jnm.snmjournals.org/content/60/11/1537.abstract AB Our purpose was to assess the diagnostic potential of simultaneously acquired 18F-FDG PET and MRI data sets for therapy response assessment of isolated limb perfusion (ILP) in patients with soft-tissue sarcomas (STS). Methods: In total, 45 patients with histopathologically verified STS were prospectively enrolled for an integrated 18F-FDG PET/MRI examination before and after ILP. Therapy response was assessed based on different MRI- and PET-derived morphologic (RECIST and the MR-adapted Choi criteria) and metabolic (PERCIST) criteria. In addition, a regression model was used combining relative changes in quantitative variables to predict treatment response under ILP. Histopathologic results after subsequent tumor resection served as the reference standard, and patients were categorized as responders or nonresponders on the basis of the 6-stage regression scale by Salzer-Kuntschik. Results: Histopathologic analysis categorized 27 patients as responders (grades I–III) and 18 patients as nonresponders (grades IV–VI). Calculated sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy were 22%, 89%, 75%, 43%, and 49% for RECIST; 70%, 44%, 66%, 50%, and 60% for the Choi criteria; and 85%, 78%, 85%, 78%, and 82% for PERCIST. Receiver-operating-characteristic analysis revealed an area under the curve (AUC) of 0.56 for RECIST, 0.57 for the Choi criteria, and 0.82 for PERCIST. The combined regression model revealed higher values (AUC, 0.90) than for the stand-alone analysis, however, differences to metabolic parameters did not reach significance (P value: 0.067). Conclusion: Our study demonstrates the superiority of 18F-FDG PET over MRI data sets for response assessment of STS under neoadjuvant ILP. In a clinical setting, MRI delivers valuable information for presurgical assessment. Therefore, combining 18F-FDG PET and MRI data may enable more reliable treatment planning and therapy monitoring of STS.