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Combined Assessment of Metabolic and Volumetric Changes for Assessment of Tumor Response in Patients with Soft-Tissue Sarcomas

¹ Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California; ² Division of Surgical Oncology, University of California Los Angeles, Los Angeles, California; ³ Department of Radiology, University of California Los Angeles, Los Angeles, California; ⁴ Department of Pathology, University of California Los Angeles, Los Angeles, California; and ⁵ Abteilung Nuklearmedizin, University of Freiburg, Freiburg, Germany

Correspondence: For correspondence or reprints contact: Wolfgang Weber, Abteilung Nuklearmedizin University of Freiburg, Hugstetterstrasse 55, 79106 Freiburg, Germany. E-mail: wolfgang.weber{at}uniklinik-freiburg.de

By allowing simultaneous measurements of tumor volume and metabolic activity, integrated PET/CT opens up new approaches for assessing tumor response to therapy. The aim of this study was to determine whether combined assessment of tumor volume and metabolic activity improves the accuracy of ¹⁸F-FDG PET for predicting histopathologic tumor response in patients with soft-tissue sarcomas. Methods: Twenty patients with locally advanced high-grade soft-tissue sarcoma (10 men and 10 women; mean age, 49 ± 17 y) were studied by ¹⁸F-FDG PET/CT before and after preoperative therapy. CT tumor volume (CTvol) was measured by delineating tumor borders on consecutive slices of the CT scan. Mean and maximum ¹⁸F-FDG standardized uptake value within this volume (SUVmean and SUVmax, respectively) were determined. Two indices of total lesion glycolysis (TLG) were calculated by multiplying tumor volume by SUVmean (TLGmean) and SUVmax (TLGmax). Changes in CTvol, SUVmean, SUVmax, TLGmean, and TLGmax after chemotherapy were correlated with histopathologic tumor response (95% treatment-induced tumor necrosis). Accuracy for predicting histopathologic response was compared by receiver-operating-characteristic (ROC) curve analysis. Results: Baseline SUVmax, SUVmean, CTvol, TLGmean, and TLGmax were 11.22 g/mL, 2.84 g/mL, 544.1 mL, 1,619.8 g, and 8852.9 g, respectively. After neoadjuvant therapy, all parameters except CTvol showed a significant decline (SUVmax = –51%, P < 0.001; SUVmean = –40%, P < 0.001; CTvol = –14%, P = 0.37; TLGmean = –44%, P = 0.006; and TLGmax = –54%, P = 0.001). SUV changes in histopathologic responders (n = 6) were significantly more pronounced than those in nonresponders (n = 14) (P = 0.001). Histopathologic response was well predicted by changes in SUVmean and SUVmax (area under ROC curve [AUC] = 1.0 and 0.98, respectively) followed by TLGmean (AUC = 0.77) and TLGmax (AUC = 0.74). In contrast, changes in CTvol did not allow prediction of treatment response (AUC = 0.48). Conclusion: In this population of patients with sarcoma, TLG was less accurate in predicting tumor response than were measurements of the intratumoral ¹⁸F-FDG concentration (SUVmax, SUVmean). Further evaluation of TLG in larger patient populations and other tumor types is necessary to determine the value of this conceptually attractive parameter for assessing tumor response.

Key Words: sarcoma • PET/CT • ¹⁸F-FDG • treatment monitoring • multimodality imaging

Guest Editor: Barry Siegel, Mallinckrodt Institute of Radiology

COPYRIGHT © 2008 by the Society of Nuclear Medicine, Inc.

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