• Waleed Shady, Sirish Kishore, Somali Gavane, Richard K Do, Joseph R Osborne, Gary A Ulaner, Mithat Gonen, Etay Ziv, Franz E Boas, and Constantinos T Sofocleous.
• Section of Interventional Radiology, Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States.
• Eur J Radiol. 2016 Jun 1; 85 (6): 1224-31.

PurposeTo compare the performance of 4 metrics of metabolic response on FDG-PET/CT against RECIST 1.0 for determining response and predicting overall survival (OS) following (90)Y resin microspheres radioembolization of colorectal liver metastases (CLM).MethodsWe conducted an IRB-waived retrospective review of our radioembolization database to identify patients with unresectable CLM treated between December 2009 and December 2013. We included patients who had both PET/CT and contrast enhanced CT (CECT) available at baseline and on the first follow-up post-radioembolization. On baseline CECT up to five target tumors were chosen per patient according to RECIST 1.0. Four metrics of FDG-avidity (SUVmax, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG)) on PET/CT were measured for the same target tumors. Using RECIST 1.0, patients were classified as no progression (partial response or stable disease) and progression. For each PET metric, a cut-off point of ≥30% decrease was chosen to define response. OS was calculated from the time of radioembolization using Kaplan-Meier methodology. The log-rank test was used for univariate analysis to identify predictors of OS.ResultsThe study enrolled 49 patients with 119 target tumors; a median of 2 (range: 1-5) tumors were selected per patient. Median OS was 12.7 months (95%CI: 7.2-16.7). Response by MTV (P=0.035) and TLG (P=0.044) reached statistical significance in predicting OS. Response by SUVmax (P=0.21), SUVpeak (P=0.20) or no progression by RECIST 1.0 (P=0.44) did not predict OS.ConclusionMetabolic response based on changes in MTV and TLG can predict OS post-radioembolization of CLM.Copyright © 2016. Published by Elsevier Ireland Ltd.

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