Combined Assessment of Metabolic and Volumetric Changes for Assessment of Tumor Response in Patients with Soft-Tissue Sarcomas
Combined Assessment of Metabolic and Volumetric Changes for Assessment of Tumor Response in Patients with Soft-Tissue Sarcomas
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DOI：
10.2967/jnumed.108.053694
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发表时间：
2008-10-01
影响因子：
9.3
通讯作者：
Weber, Wolfgang A.
中科院分区：
文献类型：
--
作者：
Benz, Matthias R.;Allen-Auerbach, Martin S.;Weber, Wolfgang A.
通过允许同时测量肿瘤体积和代谢活性，集成PET/CT开辟了评估肿瘤对治疗反应的新方法。本研究的目的是确定联合评估肿瘤体积和代谢活性是否能提高F-18-FDG PET预测软组织肉瘤患者组织病理学肿瘤反应的准确性。研究方法：20例局部晚期高级别软组织肉瘤患者（10例男性和10例女性;平均年龄49 ± 17岁）在术前治疗前后进行了F-18-FDG PET/CT研究。通过在连续的CT扫描切片上描绘肿瘤边界来测量CT肿瘤体积（CTvol）。测定该体积内的平均和最大F-18-FDG标准化摄取值（分别为SUV平均值和SUV最大值）。总病变糖酵解（TLG）的两个指数通过将肿瘤体积乘以SUVmean（TLGmean）和SUVmax（TLGmax）计算。化疗后CTvol、SUVmean、SUVmax、TLGmean和TLGmax的变化与组织病理学肿瘤反应相关（>= 95%治疗诱导的肿瘤坏死）。通过受试者工作特征（ROC）曲线分析比较预测组织病理学反应的准确性。结果：基线SUVmax、SUVmean、CTvol、TLGmean和TLGmax分别为11.22 g/mL、2.84 g/mL、544.1 mL、1，619.8 g和8852.9 g。新辅助治疗后，除CTvol外的所有参数均显示出显著下降（Δ SUV最大值=-51%，P <0.001; Δ SUV平均值=-40%，P < 0.001; Δ CTvol =-14%，P = 0.37; Δ TLG平均值=-44%，P = 0.006;和Δ TLG最大值=-54%，P = 0.001）。组织病理学应答者（n = 6）的SUV变化显著高于无应答者（n = 14）（P = 0.001）。通过SUV平均值和SUV最大值（ROC曲线下面积[AUC]分别为1.0和0.98）的变化以及TLG平均值（AUC = 0.77）和TLG最大值（AUC = 0.74）的变化可以很好地预测组织学缓解。相比之下，CTvol的变化无法预测治疗反应（AUC = 0.48）。结论：在这群肉瘤患者中，TLG在预测肿瘤反应方面不如测量肿瘤内F-18-FDG浓度（SUVmax，SUVmean）准确。需要在更大的患者人群和其他肿瘤类型中进一步评价TLG，以确定这一概念上有吸引力的参数用于评估肿瘤缓解的价值。
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 F-18-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 F-18-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 F-18-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 (Delta SUVmax = -51%, P < 0.001; Delta SUVmean = -40%, P < 0.001; Delta CTvol = -14%, P = 0.37; Delta TLGmean = -44%, P = 0.006; and Delta 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 F-18-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.