Combined assessment of metabolic and volumetric changes for assessment of tumor response in patients with soft-tissue sarcomas

Abstract

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 (18)F-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 (18)F-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 (18)F-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 (> or =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 (DeltaSUVmax = -51%, P < 0.001; DeltaSUVmean = -40%, P < 0.001; DeltaCTvol = -14%, P = 0.37; DeltaTLGmean = -44%, P = 0.006; and DeltaTLGmax = -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 (18)F-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.

FIGURE 1

Contrast-enhanced CT images acquired before and after treatment are shown (axial cuts at level of proximal thigh [top] and coronal images [bottom]). (A) Patient with soft-tissue sarcoma located in right proximal thigh (arrow). (B) Regions of interest were placed manually around all axial cuts that included tumor on baseline and follow-up scans. (C) This volume of interest was then used to determine SUVmax (1) and SUVmean (2) within tumor volume.

FIGURE 2

Changes in CTvol, SUVmean, SUVmax, TLGmean, and TLGmax are stratified into responders and nonresponders as defined by histopathology. Each patient is represented by 1 box.

FIGURE 3

ROC curve for assessment of histopathologic response by changes in SUVmean, SUVmax, TLGmean, TLGmax, and CTvol.

FIGURE 4

Graphs show correlations between SUVmax and SUVmean at baseline (A) and at follow-up (B) (Pearson correlation coefficient = 0.598 and 0.579, respectively). (C) Relative changes in SUVmax and SUVmean from baseline to posttreatment scan were closely correlated (Pearson correlation coefficient = 0.92).