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Prediction Model of Chemotherapy Response in Osteosarcoma by ¹⁸F-FDG PET and MRI

¹ Department of Nuclear Medicine, Korea Cancer Center Hospital, Seoul, Korea; ² Department of Molecular Imaging Center, Korea Institute of Radiological and Medical Sciences, Seoul, Korea; ³ Department of Pathology, Korea Cancer Center Hospital, Seoul, Korea; ⁴ Department of Pediatrics, Korea Cancer Center Hospital, Seoul, Korea; ⁵ Department of Orthopedic Surgery, Korea Cancer Center Hospital, Seoul, Korea; ⁶ Department of Radiology, Korea Cancer Center Hospital, Seoul, Korea; and ⁷ Department of Orthopedic Surgery, Yeungnam University College of Medicine, Daegu, Korea

View larger version (11K): [in this window] [in a new window]   FIGURE 1.  ROC curve analysis of response prediction. ROC curves of SUV1 (A), SUV2 (B), SCR (C), VCR (D), and MVCR (E) were plotted to predict histologic response. On basis of AUC, all parameters—except SUV1—predicted histologic response.

View larger version (6K): [in this window] [in a new window]   FIGURE 2.  Decision tree for response prediction. Decision tree was devised to predict histologic response based on SUV2 and MVCR values. Predictive values of our model for good responders and poor responders were 97% (31/32) and 95% (36/38), respectively.